Control device, method and computer program product

Abstract

The present subject matter relates to a control device, a method and a computer program product for controlling a driving assistance system for a vehicle. The control device is provided with a first measurement device that determines a plurality of first obstacle parameters of the detected obstacle, and is connected to a second measurement device that determines a plurality of second obstacle parameters of the detected obstacle. The control device is further provided with an obstacle parameter calculation unit (104) that receives the plurality of first obstacle parameters and the second obstacle parameters, and calculates a plurality of third obstacle parameters of the detected obstacle on the basis of the plurality of first obstacle parameters and the second obstacle parameters. The control device is further provided with a unit (105) that calculates a first determination parameter on the basis of the plurality of third obstacle parameters, and activates driving assistance when the first determination parameter is less than a prescribed activation threshold value.

Description

Technical Field

[0001] The present invention relates to a control device, a method and a computer program product for controlling a driver assistance system for a vehicle. Background Art

[0002] Current advanced driver assistance systems (ADAS) use on-board sensors installed in vehicles to detect obstacles in the area surrounding the vehicle and intervene when there is a risk of collision. In order to avoid false triggering, the obstacle is observed / detected several times in succession before the intervention is activated. This can, for example, improve the reliability of the calculation results of the position and speed of the detected obstacle. However, repeated detection requires a specific observation time, which may, for example, cause the ADAS to brake strongly, which may cause discomfort to the vehicle driver. This is particularly likely to occur when an obstacle suddenly appears from a blind spot in front of or behind the vehicle. A possibility to alleviate this situation is to use V2X (vehicle to everything) communication to obtain information that is beyond the detection range of the vehicle's on-board sensors.

[0003] Patent Document 1 describes a system and apparatus for detecting moving objects entering the field of view of a vehicle's camera. This system uses positional information acquired from a vehicle-mounted positioning device and periodically received positional information from a mobile terminal carried by the moving object. Based on the positional information from the mobile terminal and the vehicle's own direction of travel, when a moving object enters the camera's field of view, a region for detecting the moving object is defined in the image captured by the camera, and the moving object is detected. Prior art literature Patent Literature

[0004] Patent Document 1: International Publication No. 2015 / 098510 Summary of the Invention Problems to be solved by the invention

[0005] However, it is difficult for external devices to directly control ADAS because it is necessary to avoid erroneous activation of direct control due to delays, transmission instability, and illegal transmission of V2X information. Therefore, it is important to evaluate V2X information (for example, considering the specifications and applicable range of the external device) and use only the preferred parameters of V2X information to initialize ADAS functions.

[0006] The subject matter described in this specification addresses the technical objective of improving driving comfort in vehicles equipped with a driver assistance system while enhancing the reliability of the driver assistance function. This objective is achieved by the subject matter of the independent claims. Further preferred developments are described in the dependent claims. Technical means to solve the problem

[0007] According to the subject matter recited in the accompanying claims, a control device, a method, and a computer program product for controlling a driver assistance system for a vehicle are provided. In particular, the subject matter disclosed in this specification improves the characteristics of the driver assistance system when an obstacle suddenly appears in the area surrounding the vehicle.

[0008] The driver assistance system controlled by the disclosed subject matter may be, for example, automatic emergency braking (AEB), adaptive cruise control (ACC), or lane change assist (LCA). Other types of driver assistance systems may also be combined with the proposed subject matter.

[0009] The control device includes a first obstacle parameter acquisition unit that receives a plurality of first obstacle parameters of obstacles in an area around the vehicle (which may include a range from centimeters to several meters and up to several kilometers) detected by a first measuring device, wherein the plurality of first obstacle parameters include one or more parameters of a first category and one or more parameters of a second category.

[0010] The first measuring device can be a radar (radio detection and ranging) sensor, a camera sensor, a lidar (optical detection and ranging) sensor, a sonar (sound navigation and ranging) sensor, a GNSS (global navigation satellite system) sensor, or any other sensor suitable for detecting obstacles in the area surrounding the vehicle. The first measuring device can be connected to the vehicle, or can be integrated or part of it. The obstacle can be, for example, a pedestrian, a bicycle, another vehicle, or any other object that appears around the vehicle when the vehicle travels along the road. The plurality of first obstacle parameters can include, for example, the obstacle type (bicycle, pedestrian, etc.), position, direction of travel, speed, yaw rate and acceleration of the obstacle detected by the first measuring device, or any other type of parameter that describes the characteristics of the obstacle.

[0011] The first measuring device (also referred to as a sensor, onboard sensor, or onboard device) can be part of the control device or can be external to the control device. For example, the control device, whether a separate control unit or a control unit integrated with another control unit of the vehicle, can receive signals / data from the first measuring device, which can be located at a different location / position on the vehicle. Alternatively, the first measuring device can be integrated with the control device described in this specification, and in further modifications, the first obstacle parameter acquisition unit and the first measuring device can be integrated with each other as a single unit, so that the functions of the two units described in this disclosure can be performed by the aforementioned integrated single unit.

[0012] In this context, a first obstacle parameter is understood to be a parameter of an object detected by the first measuring device. The plurality of first obstacle parameters can be divided into a first group comprising one or more parameters of a first category and a second group comprising one or more parameters of a second category. The categories of parameters can be defined, for example, by features / attributes / characteristics that one parameter may share with another parameter.

[0013] The control device also includes a second obstacle parameter acquisition unit that receives a plurality of second obstacle parameters for obstacles in the area surrounding the vehicle, detected by a second measuring device. The second measuring device (or sensor or external sensor) is located outside the vehicle where the first measuring device resides. The plurality of second obstacle parameters include one or more parameters from a first category and one or more parameters from a second category. The second obstacle parameter acquisition unit is part of the control device described herein. To receive these parameters at least at the control device, the second obstacle parameter acquisition unit preferably receives data / signals from the second measuring device and forwards them to a subsequent unit, preferably the obstacle parameter calculation unit. However, if the second obstacle parameter acquisition unit is omitted in an alternative configuration of the control device described herein, a second measuring device located outside the vehicle equipped with the first measuring device and / or control device described herein may transmit the second obstacle parameters directly to the obstacle parameter calculation unit.

[0014] Second obstacle parameters are understood to be parameters of a detected obstacle determined / detected / measured by a second measurement device or a second obstacle parameter acquisition unit. The plurality of second obstacle parameters may also include, for example, obstacle type, position, orientation (direction of travel), velocity, yaw rate, and acceleration detected by the first measurement device, or any other parameters describing obstacle characteristics. These parameters are further divided into a first group comprising one or more parameters of a first category and a second group comprising one or more parameters of a second category. Specifically, the second measurement device may determine the same parameters of the first and second categories as the first measurement device.

[0015] The second measuring device can also be a radar sensor, a camera sensor, a lidar sensor, a sonar sensor, a GNSS sensor, or any other sensor suitable for detecting obstacles in the area surrounding the vehicle. The second measuring device can be the same or a different sensor type as the first measuring device. In particular, the second measuring device can be located at a different location from the first measuring device, thereby detecting obstacles at a different time than the first measuring device. Preferably, the second measuring device is positioned to detect obstacles earlier than the first measuring device. As described above, the second measuring device is remotely located from the vehicle, that is, not integrated with the vehicle or not located within the vehicle, but located externally.

[0016] Preferably, the one or more parameters in the first category can be parameters that can be determined / measured / detected with higher reliability by the first measurement device (or the first obstacle parameter acquisition unit) than by the second measurement device (or the second obstacle parameter acquisition unit). Conversely, the one or more parameters in the second category can be parameters that can be determined / measured / detected with higher reliability by the second measurement device.

[0017] For example, if the second measurement device detects an obstacle earlier than the first measurement device, the second measurement device (or the second obstacle parameter acquisition unit) may have received multiple obstacle parameters before the first measurement device (or the first obstacle parameter acquisition unit) receives the first obstacle parameter. Due to the longer obstacle observation time resulting from the continuous receipt of obstacle parameters, the second measurement device can determine parameters that remain unchanged during the observation time with higher accuracy.

[0018] Similarly, if two measuring devices have different sensor types, the characteristics of the two measuring devices may be different, which further results in the first measuring device being able to determine parameters of the first category with higher accuracy, and the second measuring device being able to determine parameters of the second category with higher accuracy.

[0019] In addition, the control device includes an obstacle parameter calculation unit that receives multiple first obstacle parameters and second obstacle parameters from the first obstacle parameter and second obstacle parameter acquisition unit, and calculates multiple third obstacle parameters based on the multiple first obstacle parameters and second obstacle parameters. The multiple third obstacle parameters include one or more parameters of the first category and one or more parameters of the second category.

[0020] In other words, the obstacle parameter calculation unit uses the multiple first obstacle parameters and second obstacle parameters determined by the first and second measurement devices (or the obstacle parameter acquisition unit) to calculate a new set of third obstacle parameters. This new set of third obstacle parameters also includes one or more parameters of the first category and one or more parameters of the second category. When calculating the multiple third parameters, the obstacle parameter calculation unit calculates the one or more parameters of the first category based on the multiple first obstacle parameters and calculates the one or more parameters of the second category based on the multiple second obstacle parameters.

[0021] Specifically, in order to calculate a new set of third obstacle parameters, the obstacle parameter calculation unit obtains, from a plurality of first obstacle parameters, parameters of a first category that can be determined with higher reliability by a first measuring device (or a first obstacle parameter acquisition unit), and obtains, from a plurality of second obstacle parameters, parameters of a second category that can be determined with higher reliability by a second measuring device (or a second obstacle parameter acquisition unit).

[0022] By using the most reliable parameters, the obstacle parameter calculation unit can calculate multiple third obstacle parameters with high accuracy. This means that the obstacle parameter calculation unit can provide multiple reliable obstacle parameters earlier than if calculations were performed using only a single measurement device, which would take longer to obtain reliable values ​​for each obstacle parameter.

[0023] As described above, the control device may include a first obstacle parameter acquisition unit and a second obstacle parameter acquisition unit that receive first and second obstacle parameters from the first and second measurement devices. These obstacle parameter acquisition units may, for example, perform processing (e.g., smoothing, filtering, averaging) on ​​the first and second obstacle parameters determined by the first and second measurement devices before transmitting them to the obstacle parameter calculation unit. Furthermore, these obstacle parameter acquisition units may also be configured to detect, determine, and / or select target parameters for obstacles detected by the first or second measurement device. In other words, the first or second measurement device may also be configured to detect obstacles, and the first or second obstacle parameter acquisition unit may be configured to process the detection data from the first or second measurement device to extract or acquire parameters for further processing within the control device as described herein. Additionally or alternatively, the first and second obstacle parameter acquisition units may further (simply) function as receiving and parameter forwarding units within the control device.

[0024] The control device also includes an activation unit (sometimes also referred to as a driving assistance activation determination unit or driving assistance activation unit, etc.) that calculates a first determination parameter based on multiple third obstacle parameters received from the obstacle parameter calculation unit and activates driving assistance if the determination parameter is less than a specified activation threshold. In other words, the obstacle parameter calculation unit transmits the multiple third obstacle parameters to the activation unit, and the activation unit derives comparison data (determination parameter) from the third obstacle parameters to determine whether to activate driving assistance. Driving assistance can include, for example, automatic braking, acceleration, or maneuvering. Alternatively or additionally, driving assistance can also be an audible or visual signal prompting the driver to perform a specific maneuver, such as braking or deceleration.

[0025] The activation unit then compares the determination parameter with a specified activation threshold and activates the driving assistance system if the determination parameter is below the threshold. For example, the activation unit may calculate the time to collision (time to collision) or the difference between the vehicle and the obstacle based on the third obstacle parameter as the determination parameter. In this case, the specified activation threshold may also be a specified time or distance.

[0026] When the activation unit derives the first determination parameter from a plurality of third obstacle parameters based on the most reliable obstacle parameter received from the first and second measurement units, the activation unit can determine the first determination parameter early and with high accuracy. This enables the control device to activate driving assistance before an obstacle appears alongside the vehicle, thereby avoiding abrupt driving maneuvers and improving driving comfort.

[0027] In one example, the control device may further include an activation unit that can activate driving assistance based on an activation signal received from the activation unit. In other words, if a determination parameter falls below a specified threshold, the activation unit can send an activation signal to the activation unit, which then activates actuators / control elements for vehicle driving assistance, such as hydraulic valves for braking or steering operations and / or signal outputs for providing audible and visual information. However, the actuators may also be activated directly by the activation unit.

[0028] According to one example, the obstacle parameter calculation unit can determine whether the first measuring device and the second measuring device detect the same (identical) obstacle based on the comparison result of multiple first obstacle parameters and at least one of the second obstacle parameters, and calculate multiple third obstacle parameters only when the judgment result is positive, that is, only when the obstacles detected by the first measuring device and the second measuring device are the same.

[0029] For example, the obstacle parameter calculation unit may first determine whether the plurality of first obstacle parameters and second obstacle parameters include the same obstacle type, for example, whether both measuring devices have detected a bicycle. If they do, the obstacle parameter calculation unit may calculate the distance between the obstacle position included in the first obstacle parameter and the obstacle position included in the second obstacle parameter. If the calculated distance is less than a specified distance threshold, the obstacle parameter calculation unit may identify the obstacles detected by the two measuring devices as the same object. If the result is positive, i.e., identical, the obstacle parameter calculation unit may use the first and second plurality of obstacle parameters to calculate the plurality of third obstacle parameters as described above. If the result is negative, i.e., different, the obstacle parameter calculation unit may receive more first and / or second obstacle parameters from the first and / or second measuring devices and repeat this process until a positive result is obtained.

[0030] According to one example, the first measurement device can communicate with the obstacle parameter calculation unit (or the first obstacle parameter acquisition unit) at a higher speed than the second measurement device, but can detect obstacles more slowly than the second measurement device. Conversely, the second measurement device can detect obstacles earlier than the first measurement device, but can communicate with the obstacle parameter calculation unit (or the second obstacle parameter acquisition unit) via a slower / longer communication path than the first measurement device.

[0031] Preferably, as described above, the first measurement device may be an onboard measurement device located inside the vehicle, while the second measurement device may be an external measurement device located outside the vehicle. Communication between the onboard measurement device and the control device (or first obstacle parameter acquisition unit) described herein may be performed in real time or with low latency, while communication between the external measurement device and the control device described herein may be performed, for example, via a cellular network with a longer latency.

[0032] The on-board measurement device (preferably the first measurement device) can be a radar sensor, a camera sensor, a lidar sensor, a sonar sensor, a GNSS sensor, or any other sensor that is onboard the vehicle. Specifically, a combination of a radar sensor, a camera sensor, a lidar sensor, a sonar sensor, and a GNSS sensor can be installed on the vehicle. However, each of these sensors can only detect an obstacle when it appears in the field of view, that is, when there is no interference from another obstacle near the vehicle. Therefore, a second external device capable of early obstacle detection can provide effective second obstacle parameters for non-abrupt and early-stage driving assistance.

[0033] The external measuring device (preferably the second measuring device) can be, for example, a roadside unit (RSU), which can detect obstacles using, for example, radar sensors and / or camera sensors. Furthermore, the RSU can be configured to exchange information with other vehicles and pedestrians / cyclists carrying mobile devices, which have their own measuring devices. The latter, i.e., other vehicles with onboard measuring devices and mobile devices (smartphones, tablets, laptops), can also be external measuring devices suitable as the second measuring device. Specifically, another vehicle near the vehicle can be an obstacle that provides information about its own status, such as its current position, speed, and direction of travel, and / or a measuring device that simply provides information about another obstacle near the vehicle detected by its own onboard measuring device.

[0034] In one example, the second measuring device can be an onboard measuring device of another vehicle traveling as a potential obstacle around the vehicle. In this case, the obstacle parameter calculation unit can receive the width and height of the other vehicle as a further second obstacle parameter and consider this further obstacle parameter when calculating the plurality of third obstacle parameters. Specifically, the obstacle parameter calculation unit can use the width and height of the vehicle to determine its spatial position coordinates. By knowing the spatial position coordinates of the obstacle, the activation unit can subsequently determine the collision distance and / or collision margin time with the obstacle with greater accuracy.

[0035] Furthermore, as described above, both the first and second measuring devices can be external devices located outside the vehicle. In this case, the measuring device closer to the vehicle can function as the first measuring device, while the measuring device further away can function as the second measuring device. Therefore, the measuring device closer to the vehicle has a shorter delay period than the measuring device further away. On the other hand, the measuring device further away from the vehicle can detect obstacles earlier than the measuring device closer to the vehicle.

[0036] For example, a roadside unit immediately to the right of a vehicle can function as the first measuring device, and if a pedestrian with a smartphone appears as an obstacle around the vehicle, the pedestrian's smartphone can function as the second measuring device. The control device can receive signals from each external measuring device and, for example, determine which measuring device will function as the first and second measuring devices based on signal strength. The obstacle parameter calculation unit can then receive the first and second obstacle parameters from both external devices (preferably via the first and second obstacle parameter acquisition units) and calculate a third obstacle parameter based on the most reliable parameter.

[0037] In this example, since the time delay between the roadside unit and the control device is short, which is crucial for accurately detecting the pedestrian's current position, the obstacle parameter calculation unit can receive, for example, the pedestrian's position from the roadside unit as the first obstacle parameter. Furthermore, since the pedestrian's speed can be assumed to be approximately constant during the observed time slot, the obstacle parameter calculation unit can receive, for example, the pedestrian's speed from the pedestrian's smartphone as the second obstacle parameter. When the smartphone determines the pedestrian's speed significantly longer than the roadside unit, the accuracy and reliability of its determination increases.

[0038] According to one example, the first category of parameters may be position parameters of an obstacle, including static information about the obstacle, while the second category of parameters may be motion parameters of the obstacle, including dynamic information about the obstacle. Static information about an obstacle may include, for example, the type of obstacle (pedestrian, bicycle, vehicle, etc.), the current time (timestamp) at which the obstacle was detected, and its current position and direction of travel. In particular, static information is characterized by the fact that it is not temporally dependent on the moment of acquisition. Dynamic information about an obstacle may include, for example, its velocity, yaw rate, and acceleration. In particular, dynamic information is characterized by the fact that it is temporally dependent on the moment of acquisition.

[0039] Because position parameters such as the obstacle's location and direction of travel change each time they are determined by the first or second measuring device, it is important that they be promptly transmitted to the obstacle parameter calculation unit so that the obstacle parameter calculation unit can obtain the current values ​​of the position parameters. The first measuring device can provide multiple first obstacle parameters within a short delay period, allowing the obstacle parameter calculation unit to calculate multiple third position parameters using the position parameters received from the first measuring device.

[0040] However, it can be assumed that the obstacle's motion parameters, such as velocity, acceleration, and yaw rate, remain constant within the observed time slot. Therefore, the timing of transmitting the motion parameters to the obstacle parameter calculation unit can be less important than the timing of transmitting the position parameters. On the other hand, the reliability of the obstacle parameters increases with each determination; that is, the earlier a constant obstacle parameter is determined, the higher its accuracy and reliability. Because the second measuring device can detect the obstacle earlier than the first measuring device, the obstacle parameter calculation unit can use the motion parameters received from the second measuring device to calculate multiple third position parameters.

[0041] Therefore, it is possible to ensure that the obstacle parameter calculation unit is capable of calculating a plurality of third obstacle parameters, based on which the first obstacle parameter and the second obstacle parameter with the highest accuracy and reliability can be used to activate driving assistance.

[0042] According to one example, the obstacle parameter calculation unit may include a prediction model for calculating a plurality of third obstacle parameters. The prediction model uses one or more parameters from the second category of the plurality of second obstacle parameters as one or more initial parameters to calculate the plurality of third obstacle parameters upon first obstacle detection. In other words, the prediction model may be initialized using the motion parameters of the plurality of second obstacle parameters. This allows the prediction model to begin calculations with reliable values ​​for velocity, acceleration, and yaw rate, for example, thereby improving prediction accuracy. Specifically, the prediction model may include a Kalman filter for calculating the plurality of third obstacle parameters based on the plurality of first obstacle parameters and the second obstacle parameters determined by the first and second measurement devices.

[0043] According to one example, the obstacle parameter calculation unit may calculate a reliability index representing the reliability of multiple third obstacle parameters and transmit the calculated reliability index along with the third obstacle parameters to the activation unit. The reliability index may be, for example, a counter that increments each time an event occurs that increases the reliability of the third obstacle parameters and decrements each time an event occurs that decreases the reliability of the third obstacle parameters. In this case, the activation unit may activate driving assistance when the first determination value is below a specified activation threshold and the value of the reliability index is above the first specified reliability threshold. This ensures that driving assistance is only performed when the multiple third obstacle parameters, which serve as the basis for calculating the determination value for activating driving assistance, have sufficient reliability.

[0044] According to one example, the activation unit may also receive a plurality of first obstacle parameters and calculate a second determination parameter based on the plurality of first obstacle parameters. In this case, the activation unit may activate the driving assistance system when the first determination parameter and / or the second determination parameter is below a specified activation threshold.

[0045] In other words, the activation unit can calculate two determination parameters, wherein the first determination parameter is derived from the plurality of third obstacle parameters calculated by the obstacle parameter calculation unit based on the plurality of first obstacle parameters and the second obstacle parameters, as described above, and the second determination parameter is derived solely from the plurality of first obstacle parameters. By activating driving assistance when at least one of the two determination parameters falls below a predetermined threshold, driving assistance can be activated with high reliability even when the control unit has access only to the first measurement device, such as an onboard sensor of the vehicle.

[0046] According to one example, the obstacle parameter calculation unit can increase the reliability index based on the number of times the first measurement device detects an obstacle. Because the first measurement device's high-speed communication path relies on stable signal transmission, the reliability of the plurality of first obstacle parameters can be considered to be primarily determined by the number of times the first measurement device detects an obstacle, which is significantly shorter than the observation time of a second measurement device that detects an obstacle earlier.

[0047] According to one example, the obstacle parameter calculation unit may calculate a reliability indicator that takes into account the specifications of multiple second obstacle parameters determined by the second measurement device. Because the second measurement device may be significantly further away from the vehicle than the first measurement device, the obstacle parameter detection and transmission method may be significantly more significant than that of the first measurement device. For example, if the second measurement device transmits a GNSS-based message, its accuracy may depend on the second measurement device's environment, as GNSS may not provide a signal in a tunnel, for example.

[0048] The specification of the plurality of second obstacle parameters may include information regarding characteristics / properties / quality of the second obstacle parameters, including characteristics / features / quality of the second measurement device. The specification may include, for example, information regarding the sensor type of the second measurement device, message type, signal resolution, timestamps of the second measurement parameters, and any other information conveying information regarding the characteristics / properties / quality of the second obstacle parameters.

[0049] In one example, the control device may include a specifications acquisition unit configured to acquire specifications for a plurality of second obstacle parameters before transmitting the specifications to the obstacle parameter calculation unit. In this case, the specifications acquisition unit may process signals received from the second measurement device / second obstacle parameter acquisition unit to prepare the signals for calculations performed by the obstacle parameter calculation unit. However, the obstacle parameter calculation unit may also directly receive the specifications for the second obstacle parameters.

[0050] According to one example, the second obstacle parameter specification may include multiple specification parameters, and the obstacle parameter calculation unit may adjust the value of the reliability index based on the values ​​of each specification parameter. Specifically, the multiple specification parameters may include multiple pieces of information regarding boundary conditions that determine the multiple second obstacle parameters. Based on this information, the obstacle parameter calculation unit may increment or decrement the value of the reliability index.

[0051] In one example, the obstacle parameter calculation unit and / or the specification acquisition unit may receive a timestamp as a specification parameter from the second measurement device (or from the second obstacle parameter acquisition unit) and provide the most recent time at which the second measurement device determined the second obstacle parameter. The obstacle parameter calculation unit may then calculate a delay time for the received second obstacle parameter and may reduce / decrement the value of the reliability indicator based on the length of the delay time. In particular, a long delay time may result in a significantly lower value for the reliability indicator than a short delay time. If the delay time is less than a specified threshold, the reliability level may remain constant. The specified threshold for the delay time may correspond to the delay time of the first measurement device, for example.

[0052] In another example, the obstacle parameter calculation unit and / or the specification acquisition unit may acquire the number of times the second measurement device (second obstacle parameter acquisition unit) determines the second obstacle parameter (observation length) as a specification parameter. Furthermore, the obstacle parameter calculation unit may reduce / decrement the reliability index value based on the observation length. In particular, a short observation length may significantly reduce the reliability index value compared to a long observation time. If the observation length exceeds a specified threshold, the reliability level may remain constant.

[0053] In another example, the obstacle parameter calculation unit and / or the specification acquisition unit may receive the variance of a second obstacle parameter determined, such as the variance of the determined speed signal of the obstacle, as a specification parameter. In this case, the obstacle parameter calculation unit may reduce / decrement the value of the reliability indicator based on the variance of the determined parameter. A smaller variance may result in a smaller decrease in the value of the reliability indicator than a larger variance. However, if the variance of the parameter is less than a specified threshold, the reliability level may remain constant.

[0054] In another example, the obstacle parameter calculation unit and / or the specification acquisition unit may receive a message type for the second obstacle parameter as a specification parameter. Possible message categories include, for example, a collaborative awareness message from another vehicle providing information about the vehicle itself, a message from a roadside unit, a collective awareness message from another vehicle providing information about another object, a message provided by a mobile device, and other messages not belonging to any of the aforementioned categories. In this case, the obstacle parameter calculation unit may increase the reliability index value according to the order of the aforementioned message categories, with collaborative awareness messages providing the highest reliability increase and messages not belonging to the aforementioned categories providing the lowest reliability increase.

[0055] In another example, the obstacle parameter calculation unit and / or the specification acquisition unit may acquire the stability of communication with the second measurement device as a specification parameter and adjust the value of the reliability indicator based on this communication stability. In this case, the obstacle parameter calculation unit may, for example, determine the signal strength of wireless communications around the vehicle and derive the stability of communication with the second measurement device based on this signal strength. Specifically, a high signal strength may indicate stable communication, while a low signal strength may indicate unstable communication.

[0056] In another example in which another vehicle acting as an obstacle serves as a second measuring device, the obstacle parameter calculation unit and / or the specification acquisition unit may receive the activation status of the driving assistance system of the other vehicle as a specification parameter, and increase / increment the value of the reliability index when the driving assistance system is activated.

[0057] Each of the aforementioned specification parameters can contribute to the adjustment of the reliability index. Specifically, the value of the reliability index can be a result of a combination of adjustments to multiple specification parameters. In this context, each or at least some of the specification parameters are weighted based on their importance for the reliable calculation of the third obstacle parameters. Specifically, specification parameters with a high importance for accurately calculating the third obstacle parameters may be weighted with a high coefficient, while specification parameters with a low importance for accurately calculating the third obstacle parameters may be weighted with a low coefficient.

[0058] In another example, the obstacle parameter calculation unit or the specification acquisition unit may receive multiple maps of the area surrounding the vehicle and adjust the value of the reliability indicator based on the multiple maps. This map information may be stored in a storage unit of the control device and may, for example, include information regarding building locations and traffic congestion. Based on this information, the obstacle parameter calculation unit can draw conclusions regarding the quality of the second obstacle parameter determined by the second measurement device. In particular, the evaluation of the message type may be modified based on the map information. For example, if a traffic jam occurs near a roadside unit where an obstacle may be disrupted by other vehicles, the obstacle parameter calculation unit may reduce the increase in the reliability indicator based on the message from the roadside unit.

[0059] In the case of map information received as described above, the obstacle parameter calculation unit and / or specification acquisition unit may additionally or alternatively determine the stability of communication with the second measuring device based on information provided by the map information. For example, if the vehicle is traveling in an area with tall buildings, communication stability may be reduced because the buildings may interfere with communication with the second measuring device. The same is true if the vehicle is traveling in a crowded area with high data traffic, which may be very high. These environmental conditions that can be derived from the map information can be used to determine the stability of communication between the obstacle parameter calculation unit and / or specification acquisition unit (or generally the control device) and the second measuring device, and the obstacle parameter calculation unit can increase or decrease the value of the reliability indicator based on the respective corresponding conditions.

[0060] According to one example, the second obstacle parameter acquisition unit may receive multiple second obstacle parameters from more than one second measurement device. In this case, the obstacle parameter calculation unit may select the multiple second obstacle parameters received from the more than one second measurement device based on at least one of the multiple specification parameters and at least one of the multiple map information. For example, the obstacle parameter calculation unit may determine the order of the second measurement devices based on the message type of these second obstacle parameters. If the message received from the second measurement device is a collaborative awareness message that indicates another vehicle is an obstacle, the other vehicle may be selected as the appropriate second measurement device because collaborative awareness messages are highly reliable. However, when selecting the multiple second obstacle parameters received from more than one second measurement device, the environment of the other vehicles may also be considered. If the other vehicles selected as the preferred second measurement device are traveling in a crowded area, the communication path to the obstacle parameter calculation unit may be disrupted. Therefore, when determining the order of the second measurement devices, the obstacle parameter calculation unit may also consider map information.

[0061] After selecting multiple second obstacle parameters received from more than one second measurement device, the obstacle parameter calculation unit can determine whether the obstacle detected by one second measurement device is the same as the obstacle detected by another second measurement device based on at least one of the multiple second obstacle parameters of one second measurement device and another second measurement device.

[0062] For example, the obstacle parameter calculation unit may first determine whether the multiple second obstacle parameters from one second measuring device and another second measuring device include the same obstacle type, for example, whether both second measuring devices detected a bicycle. If the same obstacle type is included, the obstacle parameter calculation unit may calculate the distance between the obstacle position included in the second obstacle parameters of one second measuring device and the obstacle position included in the second obstacle parameters of the other second obstacle device. If the calculated distance is less than a specified distance threshold, the obstacle parameter calculation unit may identify the obstacles detected by the two second measuring devices as the same object. In this case, the second obstacle parameter acquisition unit may receive the multiple second obstacle parameters from at least one of the second measuring devices.

[0063] However, in the case of a negative determination, the second obstacle parameter acquisition unit may receive a plurality of second obstacle parameters from one of the second measurement devices that detects the same obstacle as the obstacle detected by the first measurement device.

[0064] According to one example, when the obstacles detected by one and the other second measuring devices are the same, the obstacle parameter calculation unit may increase the reliability index value, and when the obstacles detected by one and the other second measuring devices are different, the obstacle parameter calculation unit may decrease the reliability index value. If both second measuring devices detect the same obstacle, the reliability of the second obstacle parameters is high because they have been determined twice. However, if one and the other second measuring devices detect different obstacles, the reliability of the second obstacle parameters is low because it is unclear which of the two second measuring devices detected the target obstacle.

[0065] According to one example, the obstacle parameter calculation unit may receive the fields of view of one and another second measurement device and, if the fields of view of one second measurement device overlap with the fields of view of another second measurement device, reduce the value of the reliability indicator. In this case, the overlapping fields of view may lead to conflicting results regarding obstacles detected by the one and other second measurement devices. Therefore, the value of the reliability indicator is reduced when the fields of view of the two second measurement devices overlap.

[0066] According to one example, the activation unit may include a warning activation unit that calculates a warning determination parameter based on multiple third obstacle parameters and, if the calculated warning determination parameter is less than a specified warning activation threshold, activates a warning as a driving assistance. Furthermore, the activation unit may include an intervention activation unit that calculates an intervention determination parameter based on multiple third obstacle parameters and, if the intervention determination parameter is less than a specified intervention activation threshold, activates an intervention as a driving assistance. In particular, the specified warning activation threshold may be greater than the specified intervention activation threshold. For example, if the warning and / or intervention determination parameter is a collision margin time, the warning activation threshold may include a greater collision margin time value than the intervention activation threshold. Thus, the warning may be activated earlier than the intervention.

[0067] In the case where the control device may be further provided with an activation unit, the activation unit may be further provided with a warning activation unit that may activate a warning based on the determination of the warning activation unit; and an intervention activation unit that activates an intervention based on the determination of the intervention activation unit.

[0068] According to one example, when the reliability index is lower than a second predetermined reliability threshold, the obstacle parameter calculation unit may calculate the first plurality of third obstacle parameters and the second plurality of third obstacle parameters. The second predetermined reliability threshold may be higher than the first predetermined reliability threshold.

[0069] In this case, a first plurality of third obstacle parameters can be calculated based on both the first and second obstacle parameters, while a second plurality of third obstacle parameters can be calculated based solely on the first obstacle parameters. Furthermore, the warning activation unit can calculate a warning determination parameter based on the first plurality of third obstacle parameters, and the intervention activation unit can calculate an intervention determination parameter based on the second plurality of third obstacle parameters. In other words, even if the reliability indicator is less than a second prescribed threshold, a warning can be activated based on a combination of position parameters derived from the first plurality of obstacle parameters and motion parameters derived from the second plurality of obstacle parameters. However, in this case, intervention in the driver's driving behavior can be performed solely based on the first obstacle parameter, which can preferably be determined by onboard measurement equipment. This ensures that overall control of the driving assistance system can be maintained in the vehicle even when external measurement equipment may not be 100% reliable.

[0070] However, when the reliability index is higher than a second prescribed reliability threshold, meaning that the second obstacle parameter determined by the external measurement device also has high reliability, the obstacle parameter calculation unit may calculate only the first plurality of third obstacle parameters, and the warning enabling unit and the intervention enabling unit may respectively calculate the warning determination parameter and the intervention determination parameter based on the first plurality of third obstacle parameters.

[0071] The disclosed subject matter may also include a control system comprising a control device as described above and a first measuring device and / or a second measuring device.The disclosed subject matter also includes a vehicle comprising a control device as described above and at least a first measuring device.

[0072] The disclosed subject matter also includes a method for controlling a driver assistance system for a vehicle, wherein a plurality of first obstacle parameters of a detected obstacle include one or more parameters of a first category and one or more parameters of a second category, and a plurality of second obstacle parameters of the detected obstacle include one or more parameters of the first category and one or more parameters of the second category.

[0073] Then, the plurality of first obstacle parameters and second obstacle parameters are received by an obstacle parameter calculation unit, and the plurality of third obstacle parameters of the detected obstacle are calculated by the obstacle parameter calculation unit. The plurality of third obstacle parameters are calculated based on the plurality of first obstacle parameters and the second obstacle parameters, and include one or more parameters of a first category and one or more parameters of a second category, the one or more parameters of the first category being calculated based on the plurality of first obstacle parameters, and the one or more parameters of the second category being calculated based on the plurality of second obstacle parameters.

[0074] Then, a determination parameter based on the plurality of third obstacle parameters received from the obstacle parameter calculation unit is calculated by the activation unit, and if the determination parameter is lower than a prescribed threshold value, the driving assistance is activated by the activation unit.

[0075] Furthermore, each component of the disclosed control device or the above-described control system is also encompassed by a method which can itself be recited in the claims and / or by a claim for a computer program product.

[0076] The disclosed subject matter is further described below based on multiple examples with reference to the accompanying drawings. Like elements are denoted by like reference numerals, and repetitive description of like elements will be avoided. Furthermore, the accompanying drawings illustrate embodiments that may be modified from the above-described embodiments and their further variations and / or the variations described in conjunction with the detailed description of the accompanying drawings. In particular, this also applies to providing separate or integrated adaptations for the first measurement device / second measurement device and / or the first obstacle parameter acquisition device / second obstacle parameter acquisition device, as well as data transmission / reception inputs and outputs. In other words, when the measurement device and obstacle parameter acquisition unit are configured as separate units, sending information / data regarding detected obstacles to the corresponding obstacle parameter acquisition unit is a preferred option. This data may already include or be parameters required for further processing. In this case, the obstacle parameter acquisition unit primarily serves as an input unit for the control device and transmits this data (or modified data) to a subsequent unit, such as an obstacle parameter calculation unit. This data may also include raw detection data / information regarding detected objects. In this case, the obstacle parameter acquisition unit is configured to extract, select, and / or determine target parameters and the corresponding data, and transmit them to a subsequent unit, such as an obstacle parameter calculation unit. Of course, any of the options can also be combined. Otherwise, if the measurement device and the respective obstacle parameter acquisition device are integrated into a combined unit or a single unit, they can also perform the functions described above together. Preferably, in the combined case, only the first measurement device and the first obstacle parameter acquisition unit are combined, while the second measurement device (located outside the vehicle in a preferred embodiment) is provided separately from the second obstacle parameter acquisition unit. As will be apparent from the following description of the drawings and the drawings themselves, all four units are primarily shown below as being separately provided, but this is not intended to limit the present disclosure and any other options and variations, such as those described above. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 This is a diagram schematically showing a control device as an example of the disclosed subject matter. Figure 2 It is an explanation Figure 1 Flowchart showing an example of the initialization procedure of the control device shown. Figure 3a It schematically indicates that Figure 1 A diagram showing a plurality of first obstacle parameters, second obstacle parameters, and third obstacle parameters determined by a control device is shown. Figure 3b It schematically indicates that Figure 1 A diagram showing a plurality of first obstacle parameters, second obstacle parameters, and third obstacle parameters determined by a control device is shown. Figure 4a It is a schematic representation of the use Figure 1 FIG. 1 is an example of an external control device used to track an obstacle. Figure 4b It is a schematic representation of the use Figure 1 Figure 1 shows an example of a control device tracking an obstacle. Figure 5 Is explained through Figure 1 The flowchart shown is an example of a control device recognizing that the first measurement unit and the second measurement unit have detected the same obstacle. Figure 6 Is explained through Figure 1 The flowchart shown is an example of a control device activating driving assistance. Figure 7a It is a schematic representation of the use Figure 1 This figure shows an example of activating driving assistance using control devices other than those shown. Figure 7b It is a schematic representation of the use Figure 1 FIG. 1 shows an example of a control device for activating a driving assistance system. Figure 8 This is a diagram schematically showing a control device according to another example of the disclosed subject matter. Figure 9a This is a specification for receiving multiple second obstacle parameters and passing Figure 8 The flowchart shown is an example of a control device adjusting the reliability index of the second obstacle parameter based on the received specifications. Figure 9b This is a specification for receiving multiple second obstacle parameters and passing Figure 8 The flowchart shown is an example of a control device adjusting the reliability index of the second obstacle parameter based on the received specifications. Figure 10a Is explained through Figure 8 The flowchart shown is an example of how a control device adjusts a reliability index based on specification parameters. Figure 10b Is explained through Figure 8 The flowchart shown is an example of how a control device adjusts a reliability index based on specification parameters. Figure 11a Is explained through Figure 8 The flowchart shown is an example of a control device adjusting a reliability index based on another specification parameter. Figure 11b Is explained through Figure 8 The flowchart shown is an example of a control device adjusting a reliability index based on another specification parameter. Figure 12 Is explained through Figure 8The flowchart shown is an example of a control device adjusting a reliability index based on yet another specification parameter. Figure 13 Is explained through Figure 8 The flowchart shown is an example of how the control device adjusts the reliability index based on map information. Figure 14 Is explained through Figure 8 The flowchart shown is an example of a control device adjusting a reliability index based on yet another specification parameter. Figure 15a Is explained through Figure 8 The flowchart shown is an example of a control device processing a plurality of second obstacle parameters received from more than one second measurement device. Figure 15b Is explained through Figure 8 The flowchart shown is an example of a control device processing a plurality of second obstacle parameters received from more than one second measurement device. Figure 16 Is explained through Figure 8 The flowchart shown is an example of a control device prioritizing a plurality of second obstacle parameters received from more than one second measurement device. Figure 17a Is explained through Figure 8 The flowchart shown is an example of a control device identifying a plurality of second obstacle parameters received from more than one second measurement device. Figure 17b Is explained through Figure 8 The flowchart shown is an example of a control device identifying a plurality of second obstacle parameters received from more than one second measurement device. FIG. 17c illustrates the Figure 8 The flowchart shown is an example of a control device identifying a plurality of second obstacle parameters received from more than one second measurement device. Figure 18a It is a schematic representation of the use Figure 8 The control device shown is a diagram of an example of driving assistance when an obstacle is detected by the second measuring device. Figure 18b It is a schematic representation of the use Figure 8 The control device shown is a diagram of an example of driving assistance when an obstacle is detected by the second measuring device. Figure 19a It is a schematic representation of the use Figure 8 The control device shown is a diagram of an example of driving assistance when an obstacle is detected by more than one second measuring device. Figure 19b It is a schematic representation of the use Figure 8The control device shown is a diagram of an example of driving assistance when an obstacle is detected by more than one second measuring device. Figure 20a Is explained through Figure 8 The flowchart shown is an example of a control device adjusting a reliability indicator based on different fields of view of more than one second measurement device. Figure 20b Is explained through Figure 8 The flowchart shown is an example of a control device adjusting a reliability indicator based on different fields of view of more than one second measurement device. Figure 20c Is explained through Figure 8 The flowchart shown is an example of a control device adjusting a reliability indicator based on different fields of view of more than one second measurement device. Figure 21 This is a diagram schematically showing a control device according to another example of the disclosed subject matter. Figure 22 This is a specification for receiving multiple second obstacle parameters and passing Figure 21 The flowchart shown is an example of a control device adjusting the reliability index of the second obstacle parameter based on the received specifications. Figure 23a It is an explanation Figure 21 FIG. 1 is a flowchart of an example of an initialization process of a control device. Figure 23b It is an explanation Figure 21 FIG. 1 is a flowchart of an example of an initialization process of a control device. Figure 24 Is explained through Figure 21 The flowchart shown is an example of a control device activating driving assistance. Figure 25a Will use Figure 21 The control device shown performs driving assistance and use Figure 21 A diagram schematically illustrates driving assistance performed by control devices other than those shown in the figure for comparison. Figure 25b Will use Figure 21 The control device shown performs driving assistance and use Figure 21 A diagram schematically illustrates driving assistance performed by control devices other than those shown in the figure for comparison. Figure 26 It is schematically represented Figure 25a and Figure 25b Graph showing the results of the driving assistance example. Figure 27 This is a diagram schematically showing a control device according to another example of the disclosed subject matter. Figure 28 It is a schematic representation of the use Figure 27 The diagram shows an example of driving assistance when the control device detects an obstacle. Figure 29a It is a schematic representation of the use Figure 27 The diagram shows another example of driving assistance when the control device detects an obstacle. Figure 29b It is a schematic representation of the use Figure 27 The diagram shows another example of driving assistance when the control device detects an obstacle. Figure 30 This is a diagram schematically showing a control device according to another example of the disclosed subject matter. Figure 31 Is explained by Figure 30 A flowchart of an example of a control process performed by the control device shown. Figure 32 Will use Figure 30 An example of driving assistance performed by the control device shown and the use Figure 30 A diagram schematically illustrates an example of driving assistance performed by control devices other than those shown in the figure. DETAILED DESCRIPTION

[0078] Figure 1 This figure schematically illustrates a control device 1, an example of the disclosed subject matter. The control device 1 is mounted on a vehicle V, which is equipped with an onboard sensor (first measuring device) 100 for detecting obstacles around the vehicle V. For example, the first measuring device / onboard sensor 100 may include a radar sensor, a camera sensor, a lidar sensor, a sonar sensor, a GNSS sensor, and / or any other sensor suitable for detecting obstacles around the vehicle V. Furthermore, the control device 1 is communicatively connected to an external sensor (second measuring device) 102, which may be connected to the control device 1 via vehicle-to-location (V2X) communication. The external sensor 102 may also be a radar sensor, a camera sensor, a lidar sensor, a sonar sensor, a GNSS sensor, and / or any other sensor suitable for detecting obstacles around the vehicle V. For example, the external sensor 102 may be included in another vehicle, a roadside unit, and / or a mobile device. Communication between the onboard sensor 100 and the control device 1 can be performed in real time, while communication between the external sensor 102 and the control device 1 can be performed, for example, via a cellular network with a longer latency.

[0079] Both the onboard sensor 100 and the external sensor 102 can detect obstacles in the area around the vehicle V and can determine multiple first obstacle parameters and second obstacle parameters, including, for example, obstacle type, position, direction of travel, speed, yaw rate and acceleration of the detected obstacle.

[0080] The plurality of first obstacle parameters and second obstacle parameters can be divided into a first group including one or more parameters of a first category and a second group including one or more parameters of a second category. The categories of parameters can be defined, for example, by features / attributes / properties that one parameter shares with another parameter. Specifically, the parameters of the first category may be position parameters of the obstacle including static information about the obstacle, while the parameters of the second category may be motion parameters of the obstacle including dynamic information about the obstacle.

[0081] Static information about an obstacle can include, for example, the obstacle's type (pedestrian, bicycle, vehicle, etc.), the current time (timestamp) at which the obstacle was detected, and its current location and direction of travel. In particular, static information is characterized by its temporal dependence on the moment of acquisition. In contrast, dynamic information about an obstacle can include, for example, its velocity, yaw rate, and acceleration. In particular, dynamic information is characterized by its temporal dependence on the moment of acquisition.

[0082] Furthermore, the control device 1 of the illustrated example includes first and second obstacle (parameter) acquisition units 101 and 103, which can receive a plurality of first and second obstacle parameters from the onboard sensor 100 and the external sensor 102. The obstacle parameter acquisition units 101 and 103 can, for example, process the first and second obstacle parameters (e.g., smoothing, filtering, averaging) before transmitting them to the obstacle parameter calculation unit 104 of the control device 1, or can determine or select the parameters, particularly when the first and second measurement devices are primarily configured to detect objects. Alternatively, the obstacle parameter calculation unit 104 can receive the first and second obstacle parameters directly from the onboard sensor 100 and the external sensor 102.

[0083] Figure 1 The control device 1 is shown as a part of the vehicle V, and the external sensor (second measuring device) 102 is remotely located relative to the vehicle V. However, in an alternative modification, both measuring devices 100 and 102 may be located outside the vehicle V / remotely located relative to the vehicle V. Additionally or alternatively, Figure 1The example (or other control devices 1a-1d) can also be modified so that at least one of the sensors (first measuring device / second measuring device) can be combined with the respective obstacle parameter acquisition unit 101, 103. For example, in another modification, the first measuring device 100 and the first obstacle parameter acquisition unit 101 can be the same or an integrated unit (rather than separate units), and therefore more preferably both can be part of the control device 1. In this same modification, the second measuring device 102 can be located remotely relative to the vehicle V, so that the second obstacle parameter acquisition unit 103 can be as Figure 1 Configure as shown.

[0084] The obstacle parameter calculation unit 104 then calculates a plurality of third obstacle parameters based on the plurality of first obstacle parameters and the second obstacle parameters, which may include one or more position parameters and one or more motion parameters. In other words, the obstacle parameter calculation unit 104 calculates a new set of third obstacle parameters using the plurality of first obstacle parameters and the second obstacle parameters determined by the onboard sensor 100 and the external sensor 102 (or the obstacle parameter acquisition unit).

[0085] Positional parameters such as the obstacle's position and direction of travel change each time they are determined by the first / second measuring devices (sensors) 100, 102. Therefore, they are preferably transmitted immediately to the obstacle parameter calculation unit 104, allowing the obstacle parameter calculation unit 104 to obtain the current values ​​of the positional parameters. However, it can be assumed that the obstacle's motional parameters, such as velocity, acceleration, and yaw rate, remain constant within the observed time slot. Therefore, the timing of transmitting the motional parameters to the obstacle parameter calculation unit 104 is less important than the timing of transmitting the positional parameters. On the other hand, the accuracy and reliability of obstacle parameter determination improve with each determination (step); that is, the earlier a certain obstacle parameter is determined, the higher its accuracy and reliability.

[0086] As described above, the obstacle parameter acquisition unit can also determine the parameters of the obstacle based on the detected object data received from the sensors 100 and 102. In the following, for simplicity, an example will be described in which the sensors 100 and 102 determine the parameters of the detected obstacle and, even if not explicitly stated, preferably transmit them to the next unit such as the obstacle parameter calculation unit 104 of the control device 1 via the first obstacle parameter unit / second obstacle parameter unit 101 and 103. This also has Figure 8 、 Figure 21 A further modification of the control device shown in etc.

[0087] Therefore, in order to calculate a new set of third obstacle parameters, the obstacle parameter calculation unit 104 preferably reads out position parameters that can be determined with higher reliability by the onboard sensor 100 from multiple first obstacle parameters, and motion parameters that can be determined with higher reliability by the external device 102 from multiple second obstacle parameters.

[0088] The illustrated control device 1 also includes an activation unit 105, which calculates a first determination parameter based on multiple third obstacle parameters received from the obstacle parameter calculation unit 104 and activates driving assistance when the determination parameter is less than a specified activation threshold. In other words, the obstacle parameter calculation unit 104 transmits the multiple third obstacle parameters to the activation unit 105, which derives comparison data (determination parameter) from the third obstacle parameters to determine whether to activate driving assistance. Driving assistance can include, for example, automatic braking, acceleration, or maneuvering. Alternatively or additionally, driving assistance can also be an auditory or visual signal prompting the driver to perform a specific operation.

[0089] The activation unit 105 then compares the determination parameter with a specified activation threshold and activates driving assistance when the determination parameter is below the threshold. For example, the activation unit 105 may calculate the time until the vehicle reaches the obstacle (collision margin time) or the difference between the vehicle and the obstacle as the determination parameter based on the third obstacle parameter. The specified activation threshold in this case may also be a specified time or a specified distance.

[0090] In the example shown, control device 1 may further include an activation unit 106 that can activate driving assistance based on an activation signal received from the activation unit. In this case, activation unit 105 can send an activation signal to activation unit 106, which then activates actuators / control elements for driving assistance in the vehicle, such as hydraulic valves for braking or steering and / or signal outputs for providing acoustic or visual information. Actuators can also be activated directly by activation unit 105 (by a signal sent).

[0091] When the activation unit 105 derives the first determination parameter from a plurality of third obstacle parameters based on the most reliable obstacle parameters derived from the onboard sensor 100 and the external sensor 102, the activation unit 105 can determine the first determination parameter early with high accuracy. This enables the control device to activate driving assistance before an obstacle appears beside the vehicle, thereby avoiding abrupt driving operations and improving driving comfort.

[0092] Figure 2 It is an explanation Figure 1 Flowchart of an example of the initialization sequence of the control device 1 shown. In particular, Figure 2 express Figure 1The initialization process of the prediction model included in the obstacle parameter calculation unit 104 of the control device 1 is shown.

[0093] To verify whether the prediction model needs to be initialized, in step S200 , the obstacle parameter calculation unit 104 loads a plurality of previously calculated third obstacle parameters OP3[t-1][Q], where the variable Q represents a matrix of the third obstacle parameters and the variable t represents time.

[0094] In the subsequent step S201, the prediction model of the obstacle parameter calculation unit 104 calculates the current set of third obstacle parameters OP3p[t][Q] based on the third obstacle parameter OP3[t-1][Q] determined in the previous step. Then, in step S202, the obstacle parameter calculation unit 104 receives the current set of first obstacle parameters OP1[t][M], where the variable M represents the matrix of the first obstacle parameters.

[0095] Next, in step S203 , the obstacle parameter calculation unit 104 compares the obstacle positions from the current set OP3p[t][Q] of the third obstacle parameters with the obstacle positions from the set OP1[t][M] of the first obstacle parameters.

[0096] If the two positions are the same, then in step S208, the prediction model of the obstacle parameter calculation unit 104 is updated using the current set OP3p[t][Q] obtained by calculating the third obstacle parameter and the position parameters OP1[t][m] of the plurality of first obstacle parameters.

[0097] Furthermore, in step S208, when the obstacle parameter calculation unit 104 receives a new set of first obstacle parameters from the onboard sensor 100, the reliability index OP3[t][q].CONF of the third obstacle parameter is incremented. Each received set of first obstacle parameters from the onboard sensor 100 increases the reliability of obstacle detection, and therefore, each time the obstacle parameter calculation unit 104 receives a new set of first obstacle parameters from the onboard sensor 100, the reliability index OP3[t][q].CONF is incremented.

[0098] Next, it is verified whether the reliability index OP3[t][q].CONF is greater than the first predetermined reliability threshold TH_CONF. If it is greater, in step S209, the reliability flag OP3[t][q].TGFLG of the third obstacle parameter is set to 1, indicating that the activation unit 105 can use multiple third obstacle parameters to determine the collision margin time TTC[Q] as a determination parameter (refer to Figure 6 ).

[0099] However, if the position parameters of the first obstacle parameter and the third obstacle parameter are different, in step S204, the obstacle parameter calculation unit 104 receives a plurality of second obstacle parameters OP2[t][N] determined by the external sensor 102, where the variable N represents a matrix of second obstacle parameters. In the next step S205, due to the delay involved in communication between the external sensor 102 and the obstacle parameter calculation unit 104, the prediction model of the obstacle parameter calculation unit 104 calculates a current set of second obstacle parameters OP2p[t][N] based on the determined second obstacle parameters OP2[t][N].

[0100] Next, in step S206 , the obstacle parameter calculation unit 104 compares the positions of obstacles from the current set OP2p[t][N] of the second obstacle parameters with the positions of obstacles from the first set OP1[t][M].

[0101] When the two positions are the same, in step S207, the prediction model of the obstacle parameter calculation unit 104 is initialized using the motion parameter OP2p[t][n] of the current second obstacle parameter OP2p[t][N] and the position parameter OP1[t][m] of the first obstacle parameter.

[0102] After that, as described above, the process continues by verifying whether the reliability indicator OP3[t][q].CONF is greater than the prescribed reliability threshold TH_CONF. At this time, in step S209, the reliability flag OP3[t][q].TGFLG of the third obstacle parameter is set to 1, indicating that the activation unit 105 can use multiple third obstacle parameters to determine the collision margin time TTC[Q] as a determination parameter (refer to Figure 6 ).

[0103] If the positions of the obstacles in the first and second obstacle parameters differ, the obstacle parameter calculation unit 104 considers the obstacle detected by the onboard sensor 100 to be a new obstacle or another obstacle in the first obstacle parameters. In this case, the described process is repeated until the external sensor 102 detects a new obstacle in the second obstacle parameters.

[0104] Figure 3a and Figure 3b It schematically indicates that Figure 1 A diagram illustrating examples of a plurality of first obstacle parameters, second obstacle parameters, and third obstacle parameters determined by a control device is shown.

[0105] In particular, Figure 3a represents a plurality of first obstacle parameters OP1[t][M], which are represented by Figure 1The plurality of first obstacle parameters OP1[t][M] are determined by a first measuring device, such as an onboard sensor 100. The plurality of first obstacle parameters OP1[t][M] include the position of the obstacle detected by the first measuring device 100 at x- and y-coordinates PX1 and PY1, as well as the detected obstacle's travel direction TH1, x- and y-direction velocities VX1 and VY1, yaw rate YAW1, and x- and y-direction accelerations AX1 and AY1. Furthermore, the plurality of first obstacle parameters OP1[t][M] shown include a reliability indicator CONF1 indicating the reliability of the determined first obstacle parameters OP1[t][M] and the type / classification CLS1 of the detected obstacle. Here, the classification can represent the type of vehicle or obstacle, or other traffic participants such as cars, bicycles, fixed obstacles, or pedestrians.

[0106] Figure 3a It also represents a plurality of second obstacle parameters OP2[t][N] comprising the same type of parameters as the plurality of first obstacle parameters OP1[t][M]. The second obstacle parameters are represented by Figure 1 The second measuring device, such as the external sensor 102, is shown and is accordingly indicated by "2".

[0107] The first obstacle parameters are represented in plain font, while the second obstacle parameters are marked with bold symbols (letters, numbers, etc.). Therefore, to determine the initial values ​​used by the prediction model of the obstacle parameter calculation unit 104, it is emphasized which of the third obstacle parameters are derived from the first obstacle parameters and which are derived from the second obstacle parameters.

[0108] In other words, Figure 3a When the value of the third obstacle parameter is derived from the value of the second obstacle parameter, or when the value of the second obstacle parameter is the same as the value of the second obstacle parameter, the value of the third obstacle parameter is indicated in bold, and the value of the third obstacle parameter not in bold is the value obtained from the value of the first obstacle parameter.

[0109] The third obstacle parameter OP3[t][Q] is as follows Figure 3a As shown on the right side of the figure, the timestamp TM1, position PX1, PY1 and direction of travel TH1 of the position parameters are not marked in bold, that is, they are obtained from the first obstacle parameters, and the speed VX2, VY2, yaw rate YAW2 and acceleration AX2, AY2 of the motion parameters are marked in bold, that is, they are obtained from the second obstacle parameters.

[0110] The illustrated third obstacle parameters OP3[t][Q] also include a reliability indicator preferably composed of the reliability indicators CONF1 and CONF2 of the first and second obstacle parameters (here, for example, added together as indicated by a "+"), and the same type / classification of the detected vehicle as the first and second obstacle parameters CLS1 and CLS2. Furthermore, the third obstacle parameters preferably include a reliability flag TGFLG, which is set to 0 at the first moment that the first and second measurement devices 100, 102 detect an obstacle.

[0111] exist Figure 3b , a case is shown where the obstacle is another vehicle that also functions as the second measuring device 102. In this case, the second obstacle parameter OP2[t][N] also includes the width WD2 and height HT2 of the vehicle, which are passed to the third obstacle parameter to initialize the prediction model of the obstacle parameter calculation unit 104.

[0112] Figure 4a It is a schematic representation of the use Figure 1 FIG. 1 shows an example of an obstacle tracking control device other than the one shown. Figure 4b It is a schematic representation of the use Figure 1 A diagram showing an example of a control device to track an obstacle.

[0113] exist Figure 4a In the example shown, only the onboard sensor 100a is used to detect obstacles. In this case, when an obstacle is detected, only the first obstacle parameters determined by the onboard sensor 100a are used to initialize the obstacle tracking unit 400a. Furthermore, obstacle tracking is performed based solely on the first obstacle parameters determined by the onboard sensor 100a. The reliability of the determined parameters increases with the number of times the onboard sensor 100a determines the obstacle parameters. When this reliability exceeds a specified threshold, the obstacle tracking unit 400a changes the determined parameters from a low reliability (value) to a high reliability (value). Subsequently, if the collision margin time and the like can be calculated by the activation unit 105a, the driving assistance system can be activated by the activation unit 106a if the collision margin time is less than the specified threshold.

[0114] Therefore, in Figure 4b The example shown shows an example of the teaching disclosed in this specification. Figure 1In this example of the control device, in addition to the vehicle-mounted sensor 100b, another external sensor 102 is also used. The other external sensor 102 can detect obstacles earlier than the vehicle-mounted sensor 100b, but may have a longer communication path / slower communication speed than the obstacle tracking unit 400b. In this case, at least Figure 1 The obstacle tracking unit 400b of the obstacle parameter calculation unit 104 of the control device in FIG. 1 is initialized using the position parameters obtained from the first obstacle parameters determined by the onboard sensor 100b and the motion parameters obtained from the second obstacle parameters determined by the external sensor 102. Since the obstacle parameters with the highest initial reliability can be obtained / selected from the two sensors 100b, 102, the determined parameter reliability (value) is higher than Figure 4a The example shown focuses / increases more quickly. As a result, the collision margin time can be calculated more quickly by the enabling unit 105b, resulting in earlier activation of the driving assistance by the activating unit 106b.

[0115] Figure 5 express Figure 1 The flowchart of the subroutine of the control device is used to illustrate an example of identifying whether the first measurement unit detects the same obstacle as the second measurement unit. Specifically, Figure 5 The process shown in the flowchart shows an example in which by comparing Figure 2 The first obstacle parameter and the second obstacle parameter of step S206 are used to determine the position of the obstacle to evaluate whether the same obstacle is detected.

[0116] exist Figure 5 After the process starts, the obstacle parameter calculation unit 104 first checks whether the first measuring device and the second measuring device detect obstacles of the same type / classification ( Figure 5 The first decision step), Figure 5 In the example, the term CLS refers to the type / classification of the obstacle, and the variables n and m represent the second obstacle parameter and the first obstacle parameter, respectively. Next, in step S500, the obstacle parameter calculation unit 104 calculates the distance dis between the positions of the obstacles detected by the first measuring device and the second measuring device using the least squares method (sqrt: square root), where the terms PX and PY refer to the x-coordinate and y-coordinate of the obstacle positions. If the distance dis is less than the specified distance threshold TH_DISTANCE, then in step S501, the detected obstacles are identified as the same obstacle, and Figure 2 The process shown in the flowchart of FIG206 continues to step S206. However, if the distance dis is greater than the prescribed distance threshold TH_DISTANCE, then two different obstacles are identified in step S502, and the obstacles are identified as follows: Figure 2The process shown in the flowchart returns to step S204. This also applies to the obstacle parameter calculation unit 104 determining different types of obstacles (from Figure 5 The "No" path of the first decision step).

[0117] Figure 6 Is explained through Figure 1 A flow chart showing an example of how a control device enables / activates driving assistance.

[0118] In the first step S600 , in this example, an activation flag AEB_FLG for driving assistance with automatic emergency braking (AEB) is set to 0, ie, the automatic emergency braking is disabled.

[0119] In the next calculation cycle, Figure 1 The activation unit 105 of the control device shown checks whether a reliability flag TGFLG=1 is set for each of the plurality of first obstacle parameters m=1, ..., N. If the result is positive, the time to collision margin is calculated based on each of the plurality of first obstacle parameters m=1, ..., N (S601). If the determined time to collision margin TTC[m] is less than a prescribed activation threshold TH_TTC, the activation unit activates automatic emergency braking by setting an activation flag AEB_FLG to 1 in step S602. If any of the above checks is negative, the process ends the current calculation cycle and proceeds to a second calculation cycle in which the time to collision margin TTC[q] is calculated based on the plurality of third obstacle parameters q=1, ..., Q.

[0120] In a second calculation loop, including steps S603 and S604, the process is performed for a plurality of third obstacle parameters q = 1, ..., Q. In step S603, the activation unit 105 calculates the time to collision (TTC[q]) based on the plurality of third obstacle parameters q = 1, ..., Q. In step S604, if the determined time to collision (TTC[q]) is less than a prescribed activation threshold TH_TTC, the automatic emergency braking (AEB_FLG = 1) is activated by the activation unit. If any of the checks performed in the second calculation loop is negative, the process returns to step S600 and continues until the activation flag AEB_FLG for the automatic emergency braking is set to 1.

[0121] This means that automatic emergency braking can be activated using the collision margin TTC[m] calculated based on the first obstacle parameter and / or the collision margin TTC[q] calculated based on the third obstacle parameter. Using two sets of parameters—the first obstacle parameter and the third obstacle parameter—ensures that automatic emergency braking is initiated even when the second obstacle measurement device is unavailable. Furthermore, because the third obstacle parameter enables the reliability flag TGFLG=1 to be set early, using the third obstacle parameter to calculate the collision margin time allows for early activation of automatic emergency braking when the second obstacle measurement device is available. This improves driving comfort while further enhancing the reliability of the AEB function.

[0122] Figure 7a It is a schematic representation of the use Figure 1 An example of a control device other than that shown in the figure to realize driving assistance is shown in the figure. Figure 7b It is a schematic representation of the use Figure 1 The control device 1 shown is a diagram of an example of implementing driving assistance.

[0123] in particular, Figure 7a This shows an example of enabling driving assistance such as emergency braking based only on a plurality of first obstacle parameters. Figure 7b An example of driving assistance such as activation of emergency braking based on a plurality of first obstacle parameters and second obstacle parameters is shown.

[0124] Both figures show a pedestrian 70 , a boundary 72 (eg, a building wall), and a vehicle 75 or V having an onboard sensor as a first measuring device. At time T, pedestrian 70 approaches vehicle 75 or V from an area behind boundary 72 .

[0125] according to Figure 7a , the vehicle's onboard sensor determines a first obstacle parameter OP1[T][m] at time T when the pedestrian 70 is first detected.

[0126] The position of the pedestrian initially determined by the onboard sensors is indicated by a box surrounding the pedestrian. The first obstacle parameter OP1[T][m] includes the x- and y-coordinates of this position PX1 and PY1, but does not include the speed of pedestrian 70, as the pedestrian's speed is unknown at this point in time. This is based on the pedestrian's previous position determined by the onboard sensors of vehicle 75. Therefore, the reliability indicator CONF1 of the first obstacle parameter OP1[T][n] is low at time T.

[0127] At time T+t1, the onboard sensors of vehicle 75 determine first obstacle parameter OP1[T+t1][n] at least once more (indicated by the length of the dashed arrow on the box surrounding pedestrian 70). Because the number of measurement points at this point in time is limited, the speed of pedestrian 70, including in the x- and y-directions VX and VY, is adversely affected by a coefficient α, which indicates that the variance of the determined speeds is still high and is smaller than 1. The reliability indicator CONF1 of the first obstacle parameter OP1[T+t1][n] at time T+t1 increases by only the number ΣCONF of times the onboard sensors of vehicle 75 have determined the first obstacle parameter for pedestrian 70.

[0128] At time T+t2, the vehicle's onboard sensors observe pedestrian 70 for an extended period (indicated by the increasing length of the dashed arrow on the box surrounding pedestrian 70), allowing the pedestrian's velocities VX1 and VY1 to be determined with suitable accuracy at that time. That is, the reliability indicator CONF1 of the first obstacle parameter exceeds the first prescribed reliability threshold TM_CONF, and the collision margin time can be reliably calculated based on the first obstacle parameter OP1[T+t2][n] at time T+t2.

[0129] on the contrary, Figure 7b An example is shown in which a plurality of first obstacle parameters are also determined by vehicle V's onboard sensors 100, and a plurality of second obstacle parameters are determined by external sensors, such as a mobile device, of pedestrian 70. The external sensors are able to determine the second obstacle parameters of pedestrian 70 before the vehicle's onboard sensors first detect pedestrian 70 at time T. This is indicated by the dashed box surrounding the position of pedestrian 70 while the pedestrian is still behind boundary 72, where the onboard sensors of vehicle V cannot see the pedestrian. In this case, the position of pedestrian 70 first detected by the onboard sensors is again marked by the solid line surrounding pedestrian 70. At this point, the pedestrian has been observed by the external sensors for a specific period of time, as indicated by the length of the dashed arrow within the solid box surrounding pedestrian 70.

[0130] In this case, the control device 1 has calculated a plurality of third obstacle parameters OP3[T][q] at time T, including the position PX1 and PY1 of the pedestrian 70a determined by the onboard sensor, and the speed VX and VY of the pedestrian 70 determined, for example, by the pedestrian's mobile device. Due to the limited number of measurement points, the speed is adversely affected by the coefficient α, which is less than 1, indicating that the variance of the determined speed is still high. However, it is possible to provide the speed of the pedestrian 70 at the first moment when the pedestrian 70 is detected by the onboard sensor of the vehicle V. Since the third obstacle parameter is calculated based on the position parameter of the first obstacle parameter and the motion parameter of the second obstacle parameter, the reliability index takes into account the reliabilities CONF1 and CONF2 of the first obstacle parameter and the second obstacle parameter, and therefore is better than Figure 7aThe reliability index CONF1 at time T is high.

[0131] At time T+t1, the onboard sensor 100 determines the first obstacle parameter OP1[T+t1][n] at least once more. Consequently, the reliability indicator CONF1+CONF2 increases by the number of times ΣCONF that the onboard sensor has determined the first obstacle parameter for pedestrian 70. Therefore, the value of the reliability indicator exceeds the prescribed threshold value TH_CONF at time T+t1. As a result, the collision margin time can be calculated with high reliability based on the third obstacle parameter OP3[T+t1][n] at time T+t1.

[0132] Figure 8 1 is a diagram schematically showing a control device 1a of another example of the disclosed subject matter. Figure 1 In addition to the control device 1 shown, the illustrated control device 1a further includes a specification acquisition unit 802, which can receive specifications for a plurality of second obstacle parameters from an external sensor (second measurement device) 102 and / or a second obstacle parameter acquisition unit 103. Furthermore, the vehicle V is provided with a memory 800 storing map information related to the surroundings of the vehicle V and a signal strength acquisition unit 801 capable of acquiring the signal strength of wireless communications around the vehicle V (as shown). The specification acquisition unit 802, map information memory 800, and signal strength acquisition unit 801 are included in the obstacle parameter calculation unit 104 and can therefore also be included in the control device 1a (not shown). Alternatively, the storage device 800 and signal strength acquisition unit 801 can be located remotely from the vehicle V (not shown).

[0133] exist Figure 8 In the example shown, the obstacle parameter calculation unit 104 can calculate a reliability index that takes into account the specifications of a plurality of second obstacle parameters determined by the external sensor (second measurement device) 102. Since the external sensor 102 is located remotely from the vehicle V, the influence of the detection and transmission method of the second obstacle parameters may be greater than in the case of the onboard sensor 100. For example, in the case where the external sensor transmits a GNSS-based message, its accuracy may depend on the environment of the external sensor 102 because GNSS cannot provide a signal in a tunnel, for example.

[0134] Therefore, the settings / specifications for the plurality of second obstacle parameters may include information regarding the characteristics / properties / quality of the second obstacle parameters (specification parameters), including the characteristics / features / quality of the external sensor 102. The specifications may include, for example, information regarding the sensor type of the external sensor 102, the message type, the signal resolution, the timestamp of the second measurement parameter, and / or any other transmitted information regarding the characteristics / properties / quality of the plurality of second obstacle parameters. The specifications acquisition unit 802 may receive the specifications for the plurality of second obstacle parameters from the external sensor 102 and / or the second obstacle parameter acquisition unit 103 before transmitting them to the obstacle parameter calculation unit 104 for further processing by the obstacle parameter calculation unit 104. The obstacle parameter calculation unit 104 may then adjust the value of the reliability indicator based on the plurality of specification parameters received from the specifications acquisition unit 802.

[0135] In addition to the specifications of the second obstacle parameter, the specification acquisition unit 802 can also receive multiple map information from the map information memory 801 on which the obstacle parameter calculation unit 104 further infers the quality of the second obstacle parameter determined by the external sensor 102, and the multiple map information includes, for example, information about the location of buildings, etc. and traffic information such as traffic jams.

[0136] Further, the specification acquisition unit 802 may receive, from the signal strength acquisition unit 801 , signal strength of wireless communications around the vehicle, which is used as a basis for determining the stability of the communication path between the external sensor 102 and the obstacle parameter calculation unit 104 and / or the specification acquisition unit 802 .

[0137] Additionally or alternatively, the obstacle parameter calculation unit 104 and / or the specification acquisition unit 802 can determine the stability of the communication path between the external sensor 102 and the obstacle parameter calculation unit 104 and / or the specification acquisition unit 802 based on information provided in the map information. For example, if the vehicle V is traveling in an area with tall buildings, the stability, reliability, and quality of communication may be reduced because the buildings may interfere with communication with the external sensor 102. The same is true when the vehicle is traveling in a congested area where data traffic is sometimes very high. These environmental conditions that can be derived from the map information can be used to determine the stability of communication between the obstacle parameter calculation unit 104 and / or the specification acquisition unit 802 and the external sensor 102, and the obstacle parameter calculation unit 104 can increase or decrease the value of the reliability indicator based on the respective conditions.

[0138] Figure 9a and 9b are specifications for receiving multiple second obstacle parameters, and are Figure 8The illustrated flowchart is a flowchart of an example of how the control device 1 a adjusts the reliability index of the second obstacle parameter according to the received specifications.

[0139] In particular, Figure 9a Shown by Figure 8 The obstacle parameter calculation unit 104 and / or the specification acquisition unit 802 of the control device shown in FIG. In this exemplary case, the obstacle is another vehicle that has its own onboard measurement device and sends a cooperative awareness message about its own state. Therefore, the vehicle acting as an obstacle can also play the role of the second measurement device 102 that sends the multiple specification parameters. Figure 9a In steps S900 to S905, the obstacle parameter calculation unit 104 and / or the specification acquisition unit 802 receives: a timestamp indicating the latest second obstacle parameter determination of the other vehicle (S900), a tracking time (observation length) of the other vehicle including the number of times the second obstacle parameter is acquired (S901), a variance of the speed of the other vehicle (S902), an AEB flag indicating whether the automatic emergency braking of the other vehicle is activated or not (S903), a message type of each second obstacle parameter (S904), and communication stability between the other vehicle and the obstacle parameter calculation unit 104 and / or the specification acquisition unit 802 (S905).

[0140] also, Figure 9b shows the operations performed when the obstacle parameter calculation unit 104 and / or the specification acquisition unit 802 receives a plurality of specification parameters from other vehicles. Figure 2 In step S207 , the obstacle parameter calculation unit 104 initializes the prediction model.

[0141] After the above process starts, in step S910, the obstacle parameter calculation unit 104 sets the reliability offset CONF_OFFSET to 0. The reliability offset CONF_OFFSET may vary according to the specification parameters and may be added to the reliability index CONF2 of the second obstacle parameter. In subsequent steps S920 to S970, the obstacle parameter calculation unit 104 calculates the reliability index CONF_OFFSET based on the second obstacle parameter. Figure 9a The reliability offset CONF_OFFSET is adjusted based on each of the multiple specification parameters received from other vehicles in steps S900 to S905. Then, in step S980, the prediction model of the obstacle parameter calculation unit 104 is initialized considering the adjusted reliability offset CONF_OFFSET in the reliability index CONF2. Figure 2The process described in this specification is continued by verifying whether the reliability indicator OP3[t][q].CONF is greater than the reliability threshold TH_CONF. Of course, the second measuring device can also be a different obstacle or a substantially different entity besides a vehicle.

[0142] Figure 10a and Figure 10b All of them are explained by Figure 8 The flowchart shown is an example of how the control device 1a adjusts the reliability index based on the specification parameters.

[0143] in particular, Figure 10a The flowchart shows the Figure 9b The process begins with the adjustment of the reliability offset CONF_OFFSET based on the received timestamp representing the latest second obstacle parameter determination for the other vehicle, performed in step S920. After the process begins, in step S1001, the reliability offset caused by the delay time OFFSET_DT is set to 0. Next, in steps S1002 and S1003, the current time NOW_TM and the received timestamp OP2[t][n].TM representing the latest second obstacle parameter determination for the other vehicle are determined. Based on these, the delay time dt for transmitting the second obstacle parameter to the obstacle parameter calculation unit 104 is calculated in step S1004.

[0144] When the delay time dt is greater than the specified delay time threshold TH_DT, the reliability offset caused by the delay time OFFSET_DT is set to the value DELAY_BIG (S1005). When the delay time dt is less than the specified delay time threshold TH_DT, the reliability offset caused by the delay time OFFSET_DT is set to the value DELAY_SMALL (S1006). Instead of a single value DELAY_BIG or DELAY_SMALL, a characteristic curve or formula that depends on the delay time dt can be used to determine the reliability offset caused by the delay time OFFSET_DT.

[0145] Finally, in step S1007, the reliability offset CONF_OFF is reduced by the value of the reliability offset determined by the delay time OFFSET_DT. Since the value DELAY_SMALL is smaller than the value DELAY_BIG, the reliability offset CONF_OFF is reduced by a smaller amount when the delay time dt is smaller than the specified delay time threshold TH_DT, and is reduced by a larger amount when the delay time dt is greater than the specified delay time threshold TH_DT. Next, the process of adjusting the reliability index based on the specification of the second obstacle parameter enters Figure 10b The flowchart shown in Figure 9bStep S930.

[0146] Figure 10b The flowchart shows the Figure 9b The reliability offset CONF_OFFSET based on the received tracking time (observation length) of the other vehicle is adjusted in step S930. After the process starts, in step S1010, the reliability offset caused by the tracking time OFFSET_TRTM of the other vehicle is set to 0. Then, in step S1020, the tracking time OP2[t][n].TRTM is received from the other vehicle and then compared with the specified tracking time threshold TH_TRTM.

[0147] When the tracking time OP2[t][n].TRTM is greater than the prescribed tracking time threshold TH_TRTM, the reliability offset caused by the tracking time OFFSET_TRTM of other vehicles is set to the value TRTM_LONG (S1030). When the tracking time OP2[t][n].TRTM is less than the prescribed tracking time threshold TH_TRTM, the reliability offset caused by the tracking time OFFSET_TRTM of other vehicles is set to the value TRTM_SHORT (S1040).

[0148] Finally, in step S1050, the reliability offset CONF_OFF is reduced by the value of the reliability offset determined by the tracking time OFFSET_TRTM of the other vehicle (indicated by "-="). Since the value TRTM_LONG is smaller than the value TRTM_SHORT, the reliability offset CONF_OFF is reduced by a smaller amount in the case where the tracking time OP2[t][n].TRTM of the other vehicle is greater than the prescribed tracking time threshold TH_TRTM, and is reduced by a larger amount in the case where the tracking time OP2[t][n].TRTM of the other vehicle is less than the prescribed tracking time threshold TH_TRTM. Next, the process of adjusting the reliability index based on the specification of the second obstacle parameter enters Figure 11a The flowchart shown in Figure 9b Step S940.

[0149] Figure 11a and Figure 11b All of them are explained through Figure 8 The illustrated flowchart is a flowchart of an example of adjusting a reliability index of the control device 1 a based on another specification parameter.

[0150] in particular, Figure 11a The flowchart shows the Figure 9bThe reliability offset CONF_OFFSET based on the received variance of the other vehicle's speed is adjusted in step S940. After the process starts, in step S1100, the reliability offset caused by the variance OFFSET_VVAR of the other vehicle's speed is set to 0. Next, in step S1101, the variance OP2[t][n].VVAR of the other vehicle's speed is received from the other vehicle (or another entity acting as / having a second measurement device), and then compared with a specified variance threshold TH_VAR.

[0151] When the received variance OP2[t][n].VVAR of the speed of other vehicles is less than the prescribed variance threshold TH_VAR, the reliability offset caused by the variance OFFSET_VVAR of the speed of other vehicles is set to the value VVAR_SMALL (S1102), and when the variance OP2[t][n].VVAR of the speed of other vehicles is greater than the prescribed variance threshold TH_VAR, the reliability offset caused by the variance OFFSET_VVAR of the speed of other vehicles is set to the value VVAR_BIG (S1103).

[0152] Finally, in step S1104, the reliability offset CONF_OFF is reduced by the value of the reliability offset determined by the variance OFFSET_VVAR of the speeds of the other vehicles. Since the value VVAR_SMALL is smaller than the value VVAR_BIG, the reliability offset CONF_OFF is reduced by a smaller amount when the speeds of the other vehicles OP2[t][n].VVAR are less than the prescribed variance threshold TH_VAR, and is reduced by a larger amount when the variance OP2[t][n].VVAR of the speeds of the other vehicles is greater than the prescribed variance threshold TH_VAR. Next, the process of adjusting the reliability index based on the specification of the second obstacle parameter enters Figure 11b The flowchart shown in Figure 9b Step S950.

[0153] Figure 11b The flowchart shows the adjustment of the reliability offset CONF_OFFSET based on the received AEB flag, which indicates whether the automatic emergency braking of the other vehicle is activated or not. Figure 9bis not executed in step S950. After the process starts, in step S1110, the reliability offset caused by the setting of the AEB flag OFFSET_AEBFLG of the other vehicle is set to 0. Then, in step S1120, the setting of the AEB flag of the other vehicle is received. In the case where the AEB flag OP2[t][n].AEB_FLG is set to 1, it means that the automatic emergency braking of the other vehicle is activated, and the reliability offset caused by the setting of the AEB flag OFFSET_AEBFLG of the other vehicle is set to the value AEBFLG_ON in step S1130, and in step S1140, the reliability offset CONF_OFFSET is increased by the value ("+="). When the AEB flag OP2[t][n].AEB_FLG is set to 0, it means that the automatic emergency braking of the other vehicle is disabled, and the reliability value CONF_OFFSET will not increase due to the setting of the AEB flag of the other vehicle. Next, the process of adjusting the reliability index based on the specification of the second obstacle parameter enters Figure 12 The flowchart shown in Figure 9b Step S960.

[0154] Figure 12 Is explained by Figure 8 The control device 1a shown is a flowchart of an example of adjusting the reliability index based on yet another specification parameter.

[0155] in particular, Figure 12 The flowchart shows the Figure 9b The reliability offset CONF_OFFSET of each second obstacle parameter received is adjusted in step S960. After the process starts, in step S1200, the reliability offset of the second obstacle parameter caused by the message type OFFSET_MSGTYPE is set to 0. Then, in step S1201, the message type OP2[t][n].MSG.TYPE of the second obstacle parameter is received from another vehicle (or the same vehicle in other examples).

[0156] In the case where the message type is a cooperative awareness message providing information about other vehicles (MSG_TYPE=DIRECT_FROM_CAR), the reliability offset caused by the message type OFFSET_MSGTYPE of the second obstacle parameter is set to a value of OS_DIRECT_FROM_CAR in step S1202.

[0157] Otherwise, it is checked whether a message (MSG_TYPE=DETECT_FROM_RSU) has been received from the roadside unit. If received, then in step S1203, the reliability offset caused by the message type OFFSET_MSGTYPE of the second obstacle parameter is set to the value OS_DETECT_FROM_RSU.

[0158] If not, it is checked whether the message is a collective awareness message received from another vehicle providing information about other objects (MSG_TYPE=DETECT_FROM_CAR). If so, in step S1204, the reliability offset caused by the message type OFFSET_MSGTYPE of the second obstacle parameter is set to the value OS_DETECT_FROM_CAR.

[0159] Otherwise, it is checked whether a message (MSG_TYPE=DETECT_CELLULAR) has been received from the mobile device. If so, in step S1205, the reliability offset caused by the message type OFFSET_MSGTYPE of the second obstacle parameter is set to the value OS_DETECT_CELLULAR.

[0160] If not, it is checked whether a message has been received from any other vehicle, and the reliability offset due to the message type OFFSET_MSGTYPE of the second obstacle parameter is set to the value OS_DETECT_OTHERS in step S1206.

[0161] Based on the message type, in step S1207, the reliability offset CONF_OFFSET is increased by the value of the reliability offset caused by the message type OFFSET_MSGTYPE of the second obstacle parameter. In particular, regarding the value of the reliability offset caused by the message type OFFSET_MSGTYPE of the second obstacle parameter, the following order from large to small can be applied: OS_DIRECT_FROM_CAR > OS_DETECT_FROM_RSS > OS_DETECT_FROM_CAR > OS_DETECT_CELLULAR > OS_DETECT_OTHERS.

[0162] In other words, in the case where the message type is a collaborative perception message that provides direct information about other vehicles, the reliability offset CONF_OFFSET can be increased by the maximum amount, and in the case where the message is received from another vehicle, roadside unit or device other than a mobile device, the reliability offset CONF_OFFSET can be increased by the minimum amount.

[0163] Figure 13Is explained through Figure 8 The flowchart of an example of the control device 1a adjusting the reliability index based on map information is shown. In particular, Figure 13 The figure shows how the reliability offset caused by the message type OFFSET_MSGTYPE for the second obstacle parameter changes in response to vehicle environmental conditions determined based on map information stored in map information memory 800. After the process begins, in step S1300, the obstacle parameter calculation unit 104 and / or the specification acquisition unit 802 receive map information providing information regarding the presence of tall structures such as tunnels or enclosed environments in the area surrounding the vehicle. Furthermore, in step S1301, information regarding whether the vehicle is traveling under congested road conditions is received as map information. Next, in step S1302, for each message type in the table, a value for the reliability offset caused by the message type OFFSET_MSGTYPE for the second obstacle parameter is selected, such as OS_DIRECT_FROM_CAR, OS_DETECT_FROM_RSS, OS_DETECT_FROM_CAR, OS_DETECT_CELLULAR, and / or OS_DETECT_OTHERS. The table of OFFSET_MSGTYPE values ​​can be stored, for example, in the map information memory 800 of the control device. If the message type is a cooperative awareness message providing information about other vehicles (MSG_TYPE = DIRECT_FROM_CAR), a check is performed to determine whether the other vehicle has stopped. If it has stopped, the value OS_DIRECT_FROM_CAR is set equal to the value OS_DETECT_FROM_RSS because the other vehicle is acting like a roadside unit at that moment. If it has not stopped, the OFFSET_MSGTYPE value may remain unchanged.

[0164] Figure 14 Is explained by Figure 8 The control device 1a shown is a flowchart of an example of adjusting the reliability index based on yet another specification parameter.

[0165] in particular, Figure 14 The flowchart shows the Figure 9bThe process begins with the adjustment of the reliability offset CONF_OFFSET based on the received communication stability between other vehicles and the obstacle parameter calculation unit 104 and / or the specification acquisition unit 802, performed in step S970. After the process begins, in step S1400, map information is loaded from the map information memory 800 and transferred to the obstacle parameter calculation unit 104 and / or the specification acquisition unit 802. Next, in step S1401, the reliability offset OFFSET_COMST caused by the communication stability between other vehicles and the obstacle parameter calculation unit 104 and / or the specification acquisition unit 802 is set to 0. The map information is then checked to see if there are any buildings in the area surrounding the vehicle. If so, in step S1402, the value of the reliability offset OFFSET_COMST caused by the communication stability is reduced by a value of MINUS_BUILD.

[0166] If not, it is checked whether there is heavy traffic in the area around the vehicle. If so, the value of the reliability offset OFFSET_COMST caused by the communication stability is reduced by the value MINUS_TC in step S1403.

[0167] If not, it is checked whether the vehicle V is traveling in a smooth communication area without obstacles and / or other equipment interference. If traveling, the value of the reliability offset OFFSET_COMST caused by communication stability is increased by the value PLUS_COMGOOD in step S1404.

[0168] When the vehicle is not in motion, the signal strength of wireless communication around the vehicle is received in step S1405 to check whether the signal strength is low. If the signal strength is low, the value of the reliability offset OFFSET_COMST caused by the communication stability is reduced by the value MINUS_INTBAD in step S1406. Finally, in step S1407, the reliability offset CONF_OFFSET is increased by the value resulting from the reliability offset OFFSET_COMST caused by the communication stability. Then, the process of adjusting the reliability index based on the second obstacle parameter specification enters the process of initializing the prediction model of the obstacle parameter calculation unit 104 using the reliability offset CONF_OFFSET. Figure 9b Step S980.

[0169] Of course, multiple reliability adjustment methods as described in conjunction with the above figures may be combined, or one or more of them may be selected.

[0170] Figure 15a and 15b All of them are explained by Figure 8The flowchart shown is an example of how the control device 1 a processes a plurality of second obstacle parameters detected by more than one second measurement device.

[0171] in particular, Figure 15a The following diagram shows the case where a plurality of sets of second obstacle parameters OP2[t][N] are received from a plurality of second measuring devices. Figure 2 The process is performed in step S204 of the initialization sequence shown in FIG. After the process starts, it is determined whether more than one plurality / set of second obstacle parameters have been received from more than one second measurement device. In this case, the plurality of sets of second obstacle parameters are processed in step S1500. Otherwise, the received set of second obstacle parameters is used in step S1501. The process then returns to Figure 2 Step S205, wherein the current second obstacle parameter is calculated / predicted.

[0172] Further, Figure 15b Shows how to Figure 15a In step S1500, multiple sets of second obstacle parameters are processed. After the process starts, multiple sets of second obstacle parameters are received in step S1510. Then, in step S1520, the priority of the multiple sets is determined. Then, in step S1530, the set of second obstacle parameters with the highest priority is selected as the multiple second obstacle parameters. Then, the process returns to Figure 2 Step S205, wherein the current second obstacle parameter is calculated / predicted.

[0173] Figure 16 Is explained by Figure 8 The flowchart shown is an example of a control device 1a prioritizing a plurality of second obstacle parameters detected by more than one second measuring device.

[0174] in particular, Figure 16 Shows how to Figure 15bA preferred example of determining the priorities of multiple sets of second obstacle parameters in step 1520. After the process starts, in step S1600, map information is received from the map information memory. Based on the received map information, it is determined whether the vehicle V is traveling in a closed environment such as a tunnel. In the case of traveling in a closed environment, the condition of the vehicle is set to a value INSIDE indicating reduced reliability of wireless communication around the vehicle. Otherwise, it is further determined whether the vehicle is traveling in a crowded environment. In the case of traveling in a crowded environment, in step S1602, the condition of the vehicle is set to a value CROWDED indicating reduced reliability of wireless communication around the vehicle. Otherwise, in step S1603, the condition of the vehicle is set to a value NORMAL indicating average reliability of wireless communication around the vehicle. Next, in step S1604, the message type of each second obstacle parameter is received, and then in step 1605, the priority of each set of second obstacle parameters is determined based on the status value and the message type. In other words, the set of second obstacle parameters that provides the highest reliability is the result of the highest priority. The process then returns to Figure 15b Step S1530 , wherein a set of second obstacle parameters having the highest priority is selected as the plurality of second obstacle parameters.

[0175] Figure 17a~1 7c are all explained by Figure 8 The flowchart shown is another example of the control device 1a processing a plurality of obstacle parameters detected by more than one second measurement device.

[0176] in particular, Figure 17a Represents Figure 15b Steps S1510 to S1530 are equivalent to steps S1700 to S1702. Figure 17a The method further comprises step S1703 , wherein the reliability indicator OP2[t][N].CONF of the second obstacle parameter is adjusted based on more than one set of the second obstacle parameters.

[0177] exist Figure 17bThe process for adjusting the reliability indicator OP2[t][N].CONF in step S1703 is shown in FIG. After the method begins, the obstacle parameter calculation unit 104 executes a calculation loop in which the reliability indicator CONF_A is determined based on each of the second obstacle parameters OP2[t][n], with n=1, ..., N, of at least two sets of second obstacle parameters. In step S1710 of the calculation loop, the reliability indicator CONF_A is initially set to 0. A check is then performed to determine whether one set of second obstacle parameters OP2[t][n] and another set OP2_s[t][ns] have been received, where the variables n and ns represent one and another second obstacle parameter, respectively. If so, the two sets of second obstacle parameters are compared in step S1711 to determine whether two different second measurement devices 102 have detected the same obstacle. If the result is positive, the reliability indicator CONF_A is increased by the value of the reliability indicator OP2_s[t][n].CONF for the other set of second obstacle parameters. If the result is negative, the reliability index CONF_A remains at 0.

[0178] In step 1713, the reliability index OP2[t][n].CONF for one set of second obstacle parameters is increased by the reliability index value CONF_A. Thus, when two second measurement devices 102 detect the same obstacle, the reliability index OP2[t][n].CONF for one set of second obstacle parameters is increased.

[0179] Figure 17c shows that Figure 17b The process of determining whether the two second measuring devices 102 have detected the same obstacle is performed in step S1711. After the process starts, it is checked whether one and the other second measuring devices have detected obstacles of the same type / classification, where the term CLS refers to the type / classification of the obstacle. In the case where obstacles of the same type / classification are detected, in step S1720, the distance dis between the positions of the obstacles detected by one and the other second measuring devices is calculated using the least squares method (sqrt: square root), where the terms PX and PY refer to the x-coordinate and y-coordinate of the obstacle position. In the case where the calculated distance dis is smaller than the prescribed distance threshold TH_DISTANCE, in step S1721, the detected obstacles are identified as the same obstacle, Figure 17bThe process shown in the flowchart follows step S1712, where the reliability indicator CONF_A is incremented by the reliability indicator value OP_s[t][n].CONF for the other set of second obstacle parameters. However, if the distance dis is greater than the specified distance threshold TH_DISTANCE, two different obstacles are identified in step S1722, and the reliability indicator CONF_A remains at 0. At the start of the process, even if different types of obstacles are identified in one and the other sets of second obstacle parameters, the reliability indicator CONF_A remains at 0.

[0180] Figure 18a and 18b All of them are explained through Figure 8 The illustrated flowchart is an example of a control device 1 a adjusting a reliability index based on different fields of view of more than one second measurement device.

[0181] Therefore, steps S1800 to S1802 and step S1804 are the same as Figure 17b The steps S1710 to S1713 are the same. Figure 18a The method includes step S1803, wherein the reliability indicator CONF_A is adjusted based on the field of view of another second measuring device. Figure 18b The process of adjusting the reliability index CONF_A is described in .

[0182] In particular, after the process starts, in step S1810, the field of view FOV of another second measuring device is received, which determines another set of second obstacle parameters OP_s[t][Ns], where the term Ns represents a matrix of another second obstacle parameters. It is then checked whether the detected obstacle is recognized in the field of view of the other second obstacle device. In the case of recognition, the reliability indicator CONF_A remains unchanged and the process returns to Figure 18a Otherwise, it is checked whether the determined obstacle is recognized in the field of view of one of the second measuring devices 102. If not, the determined obstacle is not recognized in the field of view of any of the two second measuring devices, so the reliability indicator CONF_A remains unchanged and the process returns to Figure 18a Step S1804.

[0183] However, if the determined obstacle is identified in the field of view of one of the second measuring devices, it is determined that there is a conflict between the two second measuring devices, and the process returns to Figure 18a Before step S1804, Figure 18b In step S1820, the reliability indicator CONF_A is reduced by the value CONF_CONTRADICTION.

[0184] Figure 19a and 19b It is a schematic representation of the use Figure 8 The control device 1a shown in FIG. 1 is an example of a driving assistance usage scenario when an obstacle is detected by the second measuring device 102. In particular, Figure 19a Vehicle 75a is shown traveling between boundaries 72, resulting in a pedestrian 70 walking behind one of the two boundaries 72 (e.g., a building) not being detected by the onboard sensors 100 of vehicle V (here, 75a). However, pedestrian 70 is recognized in the field of view of the onboard sensors of another vehicle 75b, such as another vehicle 75b traveling in a different direction and / or location.

[0185] Figure 19b The field of view 190 of the onboard sensor of another vehicle 75b and the detection result 191 obtained by the onboard sensor are shown. Figure 19a and Figure 19b It can be seen that although the position of pedestrian 70 is correctly captured by the detection result 191 of the vehicle-mounted sensor of other vehicle 75b, vehicle 75a cannot "see" pedestrian 70 using the vehicle-mounted sensor such as a stereo camera.

[0186] Figures 20a to 20c It is a schematic representation of the use Figure 8 The control device 1 a shown in the figure is an example in which an obstacle is detected by more than one second measurement device 102 .

[0187] in particular, Figure 20a Shown Figure 19a The vehicle V (here 75a), pedestrian 70, boundary 72 and other vehicles 75b have been shown. Figure 20a A roadside unit 80 (eg, a traffic camera, etc.) is shown having a field of view that is (eg,) perpendicular to the field of view of the onboard sensors of the other vehicle 75b.

[0188] Figure 20b The field of view 190a of the onboard sensor of the other vehicle 75b and Figure 19b The detection result 191a has been shown. In addition, Figure 20b The field of view 190b of the roadside unit 80 is shown. According to the field of view 190b of the roadside unit, two different detection results 191b and 191f are captured. Figure 20a and Figure 20b It can be seen that the position of pedestrian 70 is correctly captured by detection result 191b and is incorrectly captured by detection result 191f.

[0189] at last, Figure 20cThe results are shown taking into account two second measuring devices 102 , namely the onboard sensor of the other vehicle 75 b and the field of view 190 a , 190 b of the roadside unit 80 .

[0190] When the detection result 190b of the roadside unit and the detection result 190a of the vehicle-mounted sensor are taken into account, the position of the pedestrian can be correctly detected by the two second measurement devices, and the reliability index can be increased. However, when the detection result 190f of the roadside unit and the detection result 190a of the vehicle-mounted sensor are taken into account, there may be a conflict between the two second measurement devices 75b and 80, and the reliability index may need to be reduced.

[0191] Figure 21 1 is a diagram schematically showing another example of a control device 1b of the disclosed subject matter. Figure 8 In addition to the control devices shown, Figure 21 The control device includes an intervention enabling unit 105a and a warning enabling unit 105b instead of a single enabling unit, and an associated intervention activating unit 106a and a warning activating unit 106b instead of a single activating unit. The warning enabling unit 105b may calculate a warning determination parameter based on a plurality of third obstacle parameters, and the third obstacle parameter may generate a warning activation by the warning activating unit 106b when the parameter is lower than a prescribed warning activation threshold. Therefore, the intervention enabling unit 105a may calculate an intervention determination parameter based on a plurality of third obstacle parameters, and the third obstacle parameter may generate an intervention activation by the intervention activating unit 106b when the parameter is lower than a prescribed intervention activation threshold. Preferably, the prescribed warning activation threshold may be greater than the prescribed intervention activation threshold. For example, in the case where the warning and / or intervention determination parameter is a collision margin time, the warning activation threshold may include a collision margin time value that is greater than the intervention activation threshold. Therefore, the warning may be activated earlier than the intervention. As combined Figure 8 As illustrated, other embodiments not shown are possible, for example, the memory 800 and / or the signal strength acquisition unit 801 may be part of the control device 1 b , or they may be located remotely / outside the vehicle V.

[0192] Figure 22 is a specification for receiving multiple second obstacle parameters and is represented by Figure 21 The flowchart shown is an example of a control device adjusting the reliability index of the second obstacle parameter based on the received specifications.

[0193] in particular, Figure 22The present invention shows the use of the method when the obstacle parameter calculation unit 104 and / or the specification acquisition unit 802 receives a plurality of specification parameters from the second measurement device 102 which may be another vehicle (or may be included in the vehicle) (in addition, in this case, the parameters may also be obtained as described above and in the obstacle parameter calculation unit 104 from the second measurement device 102). Figure 8 or Figure 21 Each obstacle parameter acquisition unit shown in FIG receives the initialization of the prediction model of the obstacle parameter calculation unit 104 of the reliability offset CONF_OFFSET. Figure 22 The reliability offset CONF_OFFSET is adjusted based on the specification parameters and Figure 9a and 9b In particular, Figure 22 Steps S2200 to S2207 in Figure 9b This means that the reliability offset CONF_OFFSET in steps S2201 to S2207 is adjusted to take into account the received specification parameters, and then the adjusted reliability offset CONF_OFFSET is used to initialize the prediction model in step S2207. Figure 9b Based on the initialization process shown, after initialization in step S2207, the obstacle parameter calculation unit 104 checks whether the reliability indicator OP3[t],[q].CONF of the third obstacle parameter is greater than a second predetermined threshold value TH_SEPARATE. If it is greater than the threshold value, the prediction model is initialized using the same third obstacle parameter in step S2208, regardless of whether the third obstacle parameter is used to calculate the warning determination parameter, the intervention determination parameter, or the overall determination parameter as a basis for enabling driving assistance (OP3W[t][q]=OP3I[t][q]=OP3[t][q]). If it is not greater than the threshold value, two separate sets of third obstacle parameter units are initialized in step S2209, where the third obstacle parameter OP3W[t][q] used to calculate the warning determination parameter is based on the first obstacle parameter and the second obstacle parameter, and the third obstacle parameter OP3I[t][q] used to calculate the intervention determination parameter is based only on the first obstacle parameter.

[0194] This means that even when the reliability indicator OP3[t],[q].CONF is less than the second specified threshold TH_SEPARATE, a warning can be enabled / triggered based on the combination of position parameters derived from the plurality of first obstacle parameters and motion parameters derived from the plurality of second obstacle parameters. However, in this case, intervention in the driver's driving behavior can be performed based solely on the first obstacle parameters, which can preferably be determined by on-board measurement equipment of the vehicle. This ensures that the overall control of the driver assistance system can be maintained in the vehicle even in situations where the reliability of the external measurement equipment may be unknown or below a predefined threshold.

[0195] Figure 23a It is an explanation Figure 21 Flowchart of an example of the initialization process of the control device shown. In particular, Figure 23a The calculation result of the third obstacle parameter OP3W[t][q] used for calculating the warning determination parameter is shown. Figure 21 FIG. 1 shows an initialization process of the prediction model included in the obstacle parameter calculation unit 104 of the control device.

[0196] In order to verify whether the prediction model needs to be initialized, Figure 23a In step S2300, the obstacle parameter calculation unit 104 loads the previously calculated plurality / set of third obstacle parameters OP3W[t-1][Q], where the variable Q represents a matrix of the third obstacle parameters and the variable t represents time.

[0197] In the subsequent step S2301, the prediction model of the obstacle parameter calculation unit 104 calculates the current set of third obstacle parameters OP3Wp[t][Q] based on the third obstacle parameter OP3W[t-1][Q] determined in the previous step. Then, in step S2302, the obstacle parameter calculation unit 104 receives the current set of first obstacle parameters OP1[t][M], where the variable M represents the matrix of the first obstacle parameters.

[0198] Next, in step S2303 , the obstacle parameter calculation unit 104 compares the obstacle positions from the current set OP3Wp[t][Q] of the third obstacle parameters with the obstacle positions from the set OP1[t][M] of the first obstacle parameters.

[0199] If the two positions are the same, in step S2308, the prediction model of the obstacle parameter calculation unit 104 is updated using the current set OP3Wp[t][Q] obtained by calculating the third obstacle parameter and the position parameters OP1[t][m] of the plurality of first obstacle parameters.

[0200] Furthermore, in step S2308, when the obstacle parameter calculation unit 104 receives a new set of first obstacle parameters from the onboard sensor 100, the reliability indicator OP3W[t][q].CONF for the third obstacle parameter is incremented (not shown). Each received set of first obstacle parameters from the onboard sensor 100 increases the reliability of obstacle detection. Therefore, the reliability indicator OP3W[t][q].CONF is incremented each time the obstacle parameter calculation unit 104 receives a new set of first obstacle parameters from the onboard sensor 100.

[0201] Next, it is verified whether the reliability index OP3W[t][q].CONF is greater than a prescribed warning reliability threshold TH_CONF_W. If it is greater, in step S2309, the reliability flag OP3W[t][q].TGFLG of the third obstacle parameter is set to 1, indicating that the activation unit 105 can use multiple third obstacle parameters to determine the collision margin time TTC[Q] as a warning determination parameter (see Figure 24 ).

[0202] However, if the position parameters of the first obstacle parameter and the third obstacle parameter are different, in step S2304, the obstacle parameter calculation unit 104 receives a plurality of second obstacle parameters OP2[t][N] determined by the external sensor 102, where the variable N represents a matrix of second obstacle parameters. In the next step S205, due to the delay involved in communication between the external sensor 102 and the obstacle parameter calculation unit 104, the prediction model of the obstacle parameter calculation unit 104 calculates a current set of second obstacle parameters OP2p[t][N] based on the determined second obstacle parameters OP2[t][N].

[0203] Next, in step S2306 , the obstacle parameter calculation unit 104 compares the position of the obstacle from the current set OP2p[t][N] of the second obstacle parameters with the position of the obstacle from the set OP1[t][M] of the first obstacle parameters.

[0204] When the two positions are the same, in step S2307, the prediction model of the obstacle parameter calculation unit 104 is initialized using the motion parameter OP2p[t][n] of the current second obstacle parameter OP2p[t][N] and the position parameter OP1[t][m] of the first obstacle parameter.

[0205] Thereafter, as described above, the process continues by verifying whether the reliability index OP3W[t][q].CONF is greater than the prescribed warning reliability threshold TH_CONF_W. In this case, in step S2309, the reliability flag OP3W[t][q].TGFLG of the third obstacle parameter is set to 1, indicating that the warning activation unit 105b is able to use a plurality of third obstacle parameters to determine the collision margin time TTC[Q] as a determination parameter (refer to Figure 24 ).

[0206] In step S2309, after the reliability flag OP3W[t][q].TGFLG of the third obstacle parameter is set to 1, the process continues to Figure 23b .

[0207] Figure 23b The calculation result of the third obstacle parameter OP3I[t][q] used for calculating the intervention determination parameter is shown. Figure 21 The illustrated example is an initialization process of the prediction model included in the obstacle parameter calculation unit 104 of the control device 1b.

[0208] To verify whether the prediction model needs to be initialized, in step S2310, the obstacle parameter calculation unit 104 loads the previously calculated multiple / set third obstacle parameters OP3I[t-1][Q], where the variable Q represents the matrix of the third obstacle parameters and the variable t represents time.

[0209] In the subsequent step S2311, the prediction model of the obstacle parameter calculation unit 104 calculates the current set of third obstacle parameters OP3Ip[t][Q] based on the third obstacle parameters OP3I[t-1][Q] determined in the previous step. Then, in step S2312, the obstacle parameter calculation unit 104 receives the current set of first obstacle parameters OP1[t][M], where the variable M represents the matrix of the first obstacle parameters.

[0210] Next, in step S2313 , the obstacle parameter calculation unit 104 compares the obstacle positions from the current set OP3Ip[t][Q] of the third obstacle parameters with the obstacle positions from the set OP1[t][M] of the first obstacle parameters.

[0211] If the two positions are the same, then in step S2318, the prediction model of the obstacle parameter calculation unit 104 is updated using the current set OP3Ip[t][Q] obtained by calculating the third obstacle parameter and the position parameters OP1[t][m] of the plurality of first obstacle parameters.

[0212] Furthermore, in step S208, when the obstacle parameter calculation unit 104 receives a new set of first obstacle parameters from the onboard sensor 100, the reliability indicator OP3I[t][q].CONF of the third obstacle parameter is incremented (not shown). Each received set of first obstacle parameters from the onboard sensor 100 improves the reliability of obstacle detection. Therefore, the reliability indicator OP3I[t][q].CONF is incremented each time the obstacle parameter calculation unit 104 receives a new set of first obstacle parameters from the onboard sensor 100.

[0213] Next, it is verified whether the reliability index OP3I[t][q].CONF is greater than the prescribed intervention reliability threshold TH_CONF_1. If it is greater, in step S2319, the reliability flag OP3I[t][q].TGFLG of the third obstacle parameter is set to 1, indicating that the activation unit 105 can use multiple third obstacle parameters to determine the collision margin time TTC[Q] as a determination parameter (see Figure 24 ).

[0214] However, if the position parameters of the first obstacle parameter and the third obstacle parameter are different, in step S2314, the obstacle parameter calculation unit 104 receives a plurality of second obstacle parameters OP2[t][N] determined by the external sensor 102, where the variable N represents a matrix of second obstacle parameters. In the next step S2315, due to the delay involved in communication between the external sensor 102 and the obstacle parameter calculation unit 104, the prediction model of the obstacle parameter calculation unit 104 calculates a current set of second obstacle parameters OP2p[t][N] based on the determined second obstacle parameters OP2[t][N].

[0215] Next, in step S206 , the obstacle parameter calculation unit 104 compares the positions of obstacles from the current set OP2p[t][N] of the second obstacle parameters with the positions of obstacles from the first set OP1[t][M].

[0216] When the two positions are the same, in step S2317, the prediction model of the obstacle parameter calculation unit 104 is initialized using the motion parameter OP2p[t][n] of the current second obstacle parameter OP2p[t][N] and the position parameter OP1[t][m] of the first obstacle parameter.

[0217] Thereafter, as described above, the process continues by verifying whether the reliability index OP3I[t][q].CONF is greater than the prescribed intervention reliability threshold TH_CONF_I. At this time, in step S2319, the reliability flag OP3I[t][q].TGFLG of the third obstacle parameter is set to 1, indicating that the activation unit 105 is able to use multiple third obstacle parameters to determine the collision margin time TTC[Q] as the intervention determination parameter (see Figure 24 ).

[0218] Figure 24 Is explained by Figure 21 The flow chart shown shows a control device 1 b initiating a warning and / or intervention as an example of driver assistance.

[0219] After starting the process, in steps S2400 and S2401 , a warning activation flag WARN_FLG and an activation flag AEB_FLG of automatic emergency braking (AEB) are set to 0, which means that the warning device and automatic emergency braking are disabled.

[0220] In the next calculation cycle, Figure 21 The warning enabling unit 105a of the control device shown checks whether the reliability flag TGFLG=1 is set for each of the multiple first obstacle parameters m=1, ..., N, and if the result is positive, calculates the collision margin time TTC[m] based on each of the multiple first obstacle parameters m=1, ..., N (S2402).

[0221] In a case where the determined collision margin time TTC[m] is smaller than the prescribed warning activation threshold TH_TMC_W, the warning enabling unit 105 a activates the warning by setting the activation flag WARN_FLG to 1 in step S2403 .

[0222] Then, the intervention enabling unit 105b checks whether the collision margin time TTC[m] is less than a prescribed intervention activation threshold TH_TMC_I. If less than the threshold, the automatic emergency braking activation flag AEB_FLG is set to 1 in step S2404 to activate the automatic emergency braking.

[0223] In the case that any one of the above checks is negative, the process ends the current calculation loop and further enters a second calculation loop in which the collision margin time TTC[q] is calculated based on a plurality of third obstacle parameters q=1, . . . , Q.

[0224] In the second calculation loop including steps S2405 to S2408, the above process is implemented for a plurality of third obstacle parameters q = 1, ..., Q. In step S2405, the time to collision margin TTC[q] is calculated by the warning activation unit 105a based on the plurality of third obstacle parameters q = 1, ..., Q, and in step S604, when the determined time to collision margin TTC[q] is less than a prescribed warning activation threshold TH_RTC_W, a warning is activated by the warning activation unit (WARN_FLG = 1).

[0225] Next, it is verified whether the reliability flag TGFLG=1 is set for each of the third obstacle parameters OP3I[t][q]. If set, the intervention enabling unit 105b calculates the collision margin time TTC[q] based on each of the plurality of third obstacle parameters q=1, ..., Q.

[0226] In a case where the determined collision margin TTC[q] is smaller than the prescribed intervention activation threshold TH_TMC_I, the intervention enabling unit 105 b activates automatic emergency braking by setting the activation flag AEB_FLG to 1 in step S2408 .

[0227] In the event that any one of the checks performed in the second calculation cycle is negative, the process returns to step S2400 and continues until the warning flag WARN_FLG and / or the automatic emergency brake activation flag AEB_FLG are set to 1.

[0228] This means that automatic emergency braking and warnings can be activated based on either the time to collision (TTC[m]) calculated based on the first obstacle parameter and / or the time to collision (TTC[q]) calculated based on the third obstacle parameter. Using these two sets of parameters—the first obstacle parameter and the third obstacle parameter—ensures that warnings and automatic emergency braking are initiated even when the second obstacle measurement device is unavailable. Furthermore, by using the third obstacle parameter to calculate the time to collision, early activation of warnings or automatic emergency braking is possible when the second obstacle measurement device is available.

[0229] Figure 25a It is a schematic representation of the use Figure 21 A diagram showing an example of driving assistance performed by a control device other than that shown, Figure 25b It is a schematic representation of the use Figure 21 The diagram shows an example of driving assistance performed by the control device 1b.

[0230] in particular, Figure 25a An example is shown in which warning and emergency braking (AEB) is subsequently performed based only on a plurality of first obstacle parameters determined by the vehicle's onboard sensors, while Figure 25bAn example is shown in which warnings and emergency braking are subsequently performed based on a plurality of first obstacle parameters and second obstacle parameters.

[0231] In both figures, a pedestrian 70, a boundary 72 (e.g., a wall or a building) and a vehicle 75 (in the example) having an onboard sensor 100 as a first measuring device are shown. Figure 25b At time T, pedestrian 70 approaches from the area behind boundary 72 to the front of vehicle 75 .

[0232] according to Figure 25a , the vehicle's onboard sensor determines a first obstacle parameter OP1[T][m] at the time T when the pedestrian 70 is first detected.

[0233] The position of the pedestrian initially determined by the onboard sensors is indicated by a box surrounding the pedestrian. The first obstacle parameter OP1[T][m] includes the x- and y-coordinates of the position PX1 and PY1. However, at this point in time, the speed of the pedestrian 70 is not included because the pedestrian's previous position, which can be determined by the onboard sensors of vehicle 75 based on this position, is unknown. Figure 25a The reliability indicator at the time instant T comprises the reliability CONF1 of the first obstacle parameter at the current time instant and an offset which may depend on environmental conditions that influence the reliability of the received message, for example.

[0234] At time T+t1, the onboard sensors of vehicle 75 determine the first obstacle parameter OP1[T+t1][n] at least once more (indicated by the length of the dashed arrow in the box surrounding pedestrian 70). Because the number of measurement points at this point in time is limited, the speed of pedestrian 70, including in the x- and y-directions VX and VY, is adversely affected by a coefficient α, which indicates that the variance of the determined speeds remains high and is smaller than 1. The reliability index CONF1 of the first obstacle parameter OP1[T+t1][n], which is the number of times ΣCONF that the onboard sensors of vehicle 75 have determined the first obstacle parameter for pedestrian 70, increases at time T+t1. Specifically, because the reliability index is above the prescribed warning reliability threshold TH_CONF_W, the warning determination parameter can be determined with sufficient reliability based on the first obstacle parameter present at time T+t1, and the warning can be activated by warning activation unit 105a.

[0235] At time T+t2, the onboard sensors of vehicle 75 can observe pedestrian 70 for a longer period of time (indicated by the increased length of the dashed arrow on the box surrounding pedestrian 70), and thus can determine pedestrian 70's velocities VX1 and VY1 with suitable accuracy at that point in time. Furthermore, the reliability indicator CONF1 of the first obstacle parameter exceeds a prescribed intervention reliability threshold TM_CONF_1. Therefore, the intervention determination parameter can be calculated with high reliability based on the first obstacle parameter OP1[T+t2][n] at time T+t2, and automatic emergency braking can be activated by intervention enabling unit 105b.

[0236] On the contrary, Figure 25b An example is shown in which a warning and automatic emergency braking (AEB) are subsequently performed based on a plurality of first obstacle parameters and a second obstacle parameter. In other words, Figure 25b An example is shown in which a plurality of first obstacle parameters are also determined by onboard equipment / sensors 100 of vehicle V, and a plurality of second obstacle parameters are determined by external sensors 102, such as a mobile device of pedestrian 70. The external sensors are able to determine the second obstacle parameters of pedestrian 70 before the onboard sensors of vehicle V first detect pedestrian 70 at time T. While pedestrian 70 is still located behind boundary 72, which is invisible to the onboard sensors of vehicle 75, this is indicated by the dashed box surrounding the position of pedestrian 70. The position of pedestrian 70 first detected by the onboard sensors is also marked here by the solid line surrounding pedestrian 70. At this point, the pedestrian is observed by the external sensors at a specific time, which is indicated by the length of the dashed arrow on the solid box surrounding pedestrian 70.

[0237] according to Figure 25b , Figure 21 The obstacle parameter calculation unit 104 of the illustrated control device 1b determines a first plurality of third obstacle parameters for use in determining warning determination parameters, and a second plurality of third obstacle parameters for use in determining intervention determination parameters. The first plurality of third obstacle parameters is based on both the first and second obstacle parameters, while the second plurality of third obstacle parameters is based solely on the first obstacle parameter. This means that interventions in the driver's driving behavior can be performed based solely on the first obstacle parameter, which can preferably be determined by onboard measurement equipment of the vehicle V. This ensures that the overall control of the driving assistance system can be maintained even if external measurement equipment is not 100% reliable.

[0238] At time T, the first plurality of third obstacle parameters OP3W[T][q] includes the positions PX1 and PY1 of pedestrian 70 determined by onboard sensors, and the velocities VX and VY of pedestrian 70 determined by external sensors. Due to the limited number of measurement points, these velocities are adversely affected by a coefficient ω less than 1, which indicates that the variance of the determined velocities remains high. However, the velocity of pedestrian 70 at the first moment when pedestrian 70 is detected by the onboard sensors of vehicle V is provided. Figure 25b The reliability index at the moment T includes the reliability CONF1, CONF2 and offset of the first obstacle parameter and the second obstacle parameter at the current moment, so it is higher than Figure 25a reliability index.

[0239] The second plurality of third obstacle parameters OP3I[T][q] only includes the positions PX1 and PY1 of pedestrian 70 determined by onboard sensors. Because these third obstacle parameters are based solely on the first obstacle parameters, they cannot provide the pedestrian's velocity at time T. However, when the second obstacle parameters are available in both cases, the reliability indicator of the second plurality of third obstacle parameters is the same as the reliability indicator of the first plurality of third obstacle parameters OP3W[T][q]. This is why the reliability of the second plurality of third obstacle parameters OP3I[T][q] also increases faster than the reliability of the first obstacle parameters.

[0240] At time T+t1', the first obstacle parameter is determined at least once more. Therefore, the reliability indicators of the first plurality of third obstacle parameters and the second plurality of third obstacle parameters OP3W[T+t1'][q] and OP3i[T+t1'][q] are increased by the number of times ∑CONF that the first obstacle parameter of pedestrian 70 was determined by the onboard sensors of vehicle V at time T+t1'. Furthermore, the variance of the velocities VX and VY included in the first plurality of third obstacle parameters OP3W[T+t1'][q] decreases due to the increased observation time. The velocities are still negatively affected by the coefficient β, but may be higher than the coefficient ω. At this point in time, a second plurality of third obstacle parameters is calculated based on the first obstacle parameters determined by the onboard sensors of vehicle V. This second plurality of third obstacle parameters includes velocities negatively affected by the coefficient α, which is smaller than the coefficient β. The reliability indicator of the first plurality of third obstacle parameters exceeds the prescribed warning reliability threshold TH_CONF_W at time T+t1′, so the warning determination parameter can be determined with sufficient reliability based on the first plurality of third obstacle parameters OP3W[T+t1′][q] existing at time T+t1′, and a warning can be activated by the warning enabling unit 105a.

[0241] The moment t1' is less than the moment t1, i.e., in this case, Figure 25aCompared to the case shown in , the warning enabling unit 105a can enable the warning earlier, and in order to determine the warning determination parameter, only the first obstacle parameter is used as a basis.

[0242] Since the reliability index CONF2 of the second obstacle parameter is considered in the first plurality of third obstacle parameters and the second plurality of third obstacle parameters OP3W[T+t2'][q] and OP3I[T+t2'][q], it is also possible to compare Figure 26 a Execute automatic emergency braking earlier, that is, execute automatic emergency braking at time T+t2'.

[0243] At this time, the reliability index of the second plurality of third obstacle parameters exceeds the intervention reliability threshold TH_CONF_I, so the intervention determination parameter can be determined with sufficient reliability based on the second plurality of third obstacle parameters OP3I[T+T2'][q] existing at time T+t2', and the automatic emergency braking can be activated by the intervention enabling unit 105b.

[0244] Figure 26 The timeline t from the first observation at time T to the activation of the automatic emergency brake at time T+t2 and T+t2' is schematically shown. Figure 25a and Figure 25b Here, the upper portion of the timeline shows the timing of an example using only onboard sensors, and the lower portion of the timeline shows the timing of an example using both onboard sensors and external sensors.

[0245] As can be seen, the combination of onboard sensors 100 and external sensors 102 allows for earlier triggering of automatic emergency braking (AEB) and warnings compared to using only onboard sensors 100. This also applies to determining parameters for automatic emergency braking without using parameters from external sensors 102. However, because these parameters can be used to activate warnings, the reliability of the parameters used for emergency braking is also increased.

[0246] Figure 27 1 is a diagram schematically showing a control device 1 c of another example of the disclosed subject matter. Figure 27 Control equipment and Figure 1The control device shown differs in that the first and second measuring devices are external sensors 102a and 102b, meaning both sensors are located outside the vehicle V. In this case, the external sensors 102a and 102b closer to the vehicle V function as the first measuring device, while the external sensors 102a and 102b farther from the vehicle V function as the second measuring device. Therefore, the external sensors 102a and 102b closer to the vehicle have a shorter latency than those farther away. On the other hand, the external sensors 102a and 102b farther away can detect obstacles earlier than those closer. It can also be seen that the two external sensors 102a and 102b provide data to the respective first and second obstacle parameter acquisition units 101 and 103 within the control device 1c.

[0247] For example, a roadside unit (e.g., a camera) immediately to the right of the vehicle can function as the first measurement device, and if a pedestrian with a smartphone appears as an obstacle around the vehicle, the pedestrian's smartphone can function as the second measurement device. The control device 1c can receive signals from each of the external sensors 102a and 102b and, for example, determine which of the external sensors 102a and 102b should function as the first and second measurement devices based on signal strength. The obstacle parameter calculation unit 104 can then receive the first and second obstacle parameters from both external sensors 102a and 102b (preferably via the first and second obstacle parameter acquisition units 101 and 103 described above) and calculate a third obstacle parameter based on the most reliable parameter.

[0248] Figure 28 It is a schematic representation of the use Figure 27 The control device 1c shown in FIG. 1 is an example of driving assistance when an obstacle is detected. In particular, Figure 28 Shown are a vehicle V, a roadside unit 80, a boundary 72 (a wall, building, etc.), a pedestrian 70a, and a cellular base station 85. Pedestrian 70a carries a mobile device that sends and receives GNSS-based messages via the cellular network provided by cellular base station 85 (represented by two lightning bolts shown between cellular base station 85 and the pedestrian). The cellular network also reaches vehicle V (represented by a lightning bolt between cellular base station 85 and vehicle V), enabling pedestrian 70a's mobile device to exchange messages with vehicle V.

[0249] Pedestrian 70a approaches vehicle V from an area behind boundary 72, which is outside vehicle V's field of view. Vehicle V moves backward, causing its onboard sensor's field of view 190a to face the wrong direction, making it no longer usable as a first measurement device. However, the roadside unit 80 is located next to vehicle V, ensuring high-speed communication with the control device 1c, which may be located on vehicle V (indicated by two lightning bolts between the roadside unit 80 and vehicle V). Furthermore, because its field of view 190b captures the entire area surrounding the vehicle, the roadside unit is able to detect obstacles around vehicle V. Therefore, the roadside unit can function as a first measurement device, providing positional parameters for pedestrian 70a, while the pedestrian's mobile device can function as a second measurement device, providing motion parameters for pedestrian 70a. Consequently, the control device's obstacle parameter calculation unit 104 can calculate pedestrian 70a's third obstacle parameters with high reliability based on the multiple first obstacle parameters received from the roadside unit 80 and the multiple second obstacle parameters received from the pedestrian's mobile device.

[0250] Figure 29a and 29b Is with use Figure 27 An example of driving assistance performed by the control device 1c shown schematically illustrates the use of Figure 27 Figure 2 shows an example of driving assistance performed by a control device other than the one shown. Figure 28 , where the vehicle 75 / V is moving backward and a pedestrian 70 , 70 a approaches the rear of the vehicle 75 / V from an area behind the boundary 72 .

[0251] Specifically, Figure 29a The figure shows an example in which only a plurality of first obstacle parameters are determined by roadside unit 80, and pedestrian 70's mobile device is not used as a second measuring device (indicated by the lack of a lightning icon between cellular base station 85 and pedestrian 70). At time T, roadside unit 80 initially identifies pedestrian 70 and determines the pedestrian's position PX1, PY1. The position where roadside unit 80 initially detects pedestrian 70 is marked by a box surrounding pedestrian 70. Because pedestrian 70's previous position, from which the pedestrian's speed can be determined, is unknown at this point in time, the speed of pedestrian 70 is determined by roadside unit 80 to be zero at time T. Therefore, the reliability indicator CONF1 of the first obstacle parameter OP1[T][n] is low at time T.

[0252] At time T+t1, roadside unit 80 determines first obstacle parameters OP1[T+t1][n] at least once more, including the speeds of pedestrian 70 in the x- and y-directions VX and VY. These speeds are adversely affected by coefficient α, indicating a low reliability of speeds VX and VY, at this point in time. A reliability indicator CONF1 for first obstacle parameters OP1[T+t1][n] increases at time T+t1 based on the number of times SCONF that roadside unit 80 determines the first obstacle parameters for pedestrian 70.

[0253] At time T+t2, the roadside unit 80 observes the pedestrian 70 for a longer period of time, allowing the pedestrian's velocities VX1 and VY1 to be determined with reasonable accuracy at that time. That is, the reliability indicator of the first obstacle parameter CONF1 exceeds the first prescribed reliability threshold TM_CONF, and the collision margin time can be calculated with high reliability based on the first obstacle parameter OP1[T+t2][n] at time T+t2.

[0254] on the contrary, Figure 29b An example is shown in which a plurality of first obstacle parameters are determined by the roadside unit 80 , and a plurality of second obstacle parameters are determined by the mobile device of the pedestrian 70 a .

[0255] In this case, the control device 1c has calculated a plurality of third obstacle parameters OP3[T][q] at time T, including the position PX1 and PY1 of the pedestrian 70a determined by the roadside unit 80 and the speed VX and VY of the pedestrian 70a determined by the pedestrian's mobile device. In order to indicate that the pedestrian 70a had been observed before the roadside unit 80 initially detected the pedestrian 70a, the pedestrian's previous position is marked with a dotted box. Due to the limited number of measurement points, the speed is adversely affected by a coefficient β that is less than 1, which indicates that the variance of the determined speed is still high. However, it is possible to provide the speed of the pedestrian 70a at the first moment when the pedestrian 70a is detected by the roadside unit 80. In order to indicate that the pedestrian 70a had been observed by the pedestrian 70a's mobile device before being initially detected by the roadside unit 80, the pedestrian's previous position is marked with a dotted box.

[0256] Since the third obstacle parameter is calculated based on the position parameter of the first obstacle parameter and the motion parameter of the second obstacle parameter, the reliability index considers the reliability CONF1 and CONF2 of the first obstacle parameter and the second obstacle parameter, and is therefore higher than Figure 29a The reliability index CONF1 at time T.

[0257] At time T+t1, the roadside unit 80 determines the first obstacle parameter OP1[T+t1][n] at least once more, increasing the reliability indicator CONF1+CONF2 by the number ΣCONF of times the roadside unit 80 has determined the first obstacle parameter for the pedestrian 70. Therefore, the reliability indicator value at time T+t1 exceeds the prescribed threshold TH_CONF. As a result, the collision margin time can be calculated with high reliability based on the third obstacle parameter OP3[T+t1][n] at time T+t1.

[0258] Figure 30 1 is a diagram schematically showing a control device 1d of another example of the disclosed subject matter. Figure 30 The control device is different from Figure 1 The control device shown is that the enabling unit 3105 and the activating unit 3105 enable / activate the adaptive cruise control ACC, and therefore the control device 1d also includes a camera recognition unit 3107 and a map information memory 3108. However, these units may be provided outside the control device 1d and inside or outside the vehicle V.

[0259] Figure 31 Is explained by Figure 30 Flowchart of an example of a control process implemented by the control device 1d shown in FIG. Figure 31 It is explained in Figure 30 ACC control is enabled / activated by the control device. After the process begins, in step S3200, the activation unit of ACC control 3105 receives lane information from camera recognition unit 3107. Alternatively or additionally, ACC control activation unit 3105 may determine lane information based on map information provided by map information memory 3108. Next, in step S3201, ACC_Target_ID is set to 0, indicating that the vehicle is following the preceding vehicle. In the following step S3202, the target distance ACC_Target_Distance to the preceding vehicle is set to 512.

[0260] In the next calculation cycle, Figure 30ACC control activation unit 3105 of control device 1d shown checks whether a reliability flag TGFLG = 1 is set for each of a plurality of first obstacle parameters m = 1, ..., N, and whether the preceding vehicle providing the plurality of first obstacle parameters is in the same lane as the vehicle itself. If so, in step S3203, ACC control activation unit 3105 calculates the distance to the preceding vehicle and verifies whether the calculated distance is greater than a target distance ACC_TARGET_DISTANCE. If the result is positive, the value of ACC_Target_ID is set to a constant speed m that can be set by the driver, and the target distance ACC_Target_Distance is set to the distance calculated in step S3203.

[0261] If any of the above checks is negative, the process ends the present calculation loop and further enters the second calculation loop to calculate ACC_Target_ID and target distance based on a plurality of third obstacle parameters.

[0262] During the first calculation cycle, the system initially checks whether the reliability flag TGFLG=1 is set for each of the plurality of third obstacle parameters q=1, ..., Q in the second calculation cycle, and whether the preceding vehicle providing the plurality of third obstacle parameters is in the same lane as the vehicle itself. If so, in step S3206, ACC control activation unit 3105 calculates the distance to the preceding vehicle and verifies whether the calculated distance is greater than the target distance ACC_TARGET_DISTANCE. If the result is positive, the value of ACC_Target_ID is set to the constant speed q that can be set by the driver, and the target distance ACC_Target_Distance is set to the distance calculated in step S3206.

[0263] In the event that any of the above checks is negative, the process ends the second calculation loop and returns to step S3200, and repeats the process until the ACC control enabling unit 3105 calculates a distance greater than the target distance ACC_Target_Distance.

[0264] Figure 32 a and 32b are used with Figure 30 An example of driving assistance performed by the control device 1d shown schematically illustrates the use of Figure 30 A diagram showing an example of driving assistance performed by a control device other than those shown.

[0265] in particular, Figure 32Figure 1 a shows ACC control based only on a plurality of first obstacle parameters provided by a vehicle 75c traveling in a lane 90 ahead of the vehicle 75a (host vehicle) performing ACC control. In front of the vehicle 75c, a low-speed vehicle 75d is traveling, which is invisible to the ACC control of the host vehicle 75a.

[0266] At time T, the plurality of first obstacle parameters OP1[T][1] received by the host vehicle 75a includes the position PX11, PY1 and the speed VX11, VY11 of the vehicle 75c in front. At this time, the reliability indicator CONF11 of the first obstacle parameters depends only on the parameters currently received at time T.

[0267] At time T+t1, vehicle 75c passes low-speed vehicle 75d, making the low-speed vehicle the vehicle providing the plurality of first obstacle parameters OP1[T][2] at this point in time. Since low-speed vehicle 75d is not yet visible to the host vehicle, the first obstacle parameters OP1[T][2] at time T+t1 do not include the speed of low-speed vehicle 75d. Therefore, the reliability indicator CONF12 can only rely on the current first obstacle parameters OP1[T][2], which do not include information about the speed of vehicle 75d ahead of host vehicle 75a at the current point in time, and thus may result in a lower reliability indicator CONF12 at time T+t1.

[0268] Due to the loss of speed information, the host vehicle 75a may not be able to maintain the target distance d2 from the leading low-speed vehicle 75d, and may need to maintain at least a short distance d1 from the leading low-speed vehicle 75d and apply the brakes strongly at time T+t2 to avoid a collision.

[0269] On the contrary, Figure 32 FIG. 2 b shows ACC control based on a plurality of first and second obstacle parameters, wherein host vehicle V also receives first obstacle parameter OP1[T][1] from vehicle 75c traveling in lane 90 ahead at time T. Second obstacle parameter OP2[T][1] at this point in time is provided by low-speed vehicle 75d traveling in lane 90 ahead of vehicle 75c. Thus, at time T, the host vehicle recognizes positions PX11, PY11, PX21, PY21 and speeds VX11, VY11, VX21, VY21 from both vehicles 75c and 75d ahead.

[0270] When vehicle 75c passes low-speed vehicle 75d at time T+t1, ACC control of host vehicle V is able to calculate a third obstacle parameter OP3[T][1] based on the current position PX12, PY12 of low-speed vehicle 75d provided in the first obstacle parameter, and calculate the speeds VX21 and VY21 of the low-speed vehicle that have been determined at time T and provided as the second obstacle parameter.

[0271] Thus, the reliability indicator at time T+t1 can depend on the reliability of the first obstacle parameter and the second obstacle parameter (CONF12 + CONF21). If the speed information at time T+t1 is available, the host vehicle can maintain the target distance d2 relative to the low-speed vehicle at time T+t2 without emergency braking, thereby improving driving comfort when using ACC control.

[0272] In summary, a method, device and / or computer program product can be provided that improves driving comfort for a driver of a vehicle using the method / device or computer program product, in particular because sudden interventions in assisted driving can be reduced or avoided.

[0273] Furthermore, it should be noted that the embodiments of the present disclosure may be implemented as an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, microcode, etc.), or a combination of software and hardware. Furthermore, the embodiments of the present disclosure may be implemented as a computer program product on a computer-readable medium having computer-executable program code embodied in the medium.

[0274] It should be noted that arrows may be used in the accompanying figures to represent communications, forwarding, or other activities involving more than two entities. Double arrows generally indicate that activity can occur in both directions (e.g., a command / request in one direction and a corresponding response in the other direction, or peer-to-peer communication initiated by either entity), but in some cases, activity may not necessarily occur in both directions.

[0275] It should be noted that although a unidirectional arrow may generally indicate only one direction or primarily one direction of activity, in certain circumstances, such directional activity may include activities in both directions (e.g., a message from a sending source to a receiving destination, a receipt notification from the receiving destination to the sending source, or the establishment of a connection before transmission and the termination of the connection after transmission). Therefore, the types of arrows used to represent specific activities in certain figures are exemplary and should not be considered limiting.

[0276] The above describes the modes / embodiments with reference to flowcharts and / or block diagrams of methods and apparatuses, etc. It should be understood that each block in the flowcharts or block diagrams or both, and combinations of blocks in the flowcharts or block diagrams or both, can be implemented by computer-executable program code.

[0277] The above-mentioned computer-executable program code can be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a specific machine, so that the program code executed by the processor of the computer or other programmable data processing device creates a device for implementing the functions / operations / outputs explained in the flowcharts, blocks of the block diagrams, diagrams and / or the described description.

[0278] These computer-executable program codes may also be stored in a computer-readable memory, where the program codes stored in the computer-readable memory may enable a computer or other programmable data processing device to operate in a specific manner to manufacture a product including instruction means for implementing the functions / operations / outputs described in the flowcharts, block diagrams, diagrams and / or the described descriptions.

[0279] In order for the program code executed on the computer or other programmable device to provide steps for implementing the functions / operations / outputs set forth in the flowchart, block diagram, diagram, and / or the description, the computer executable program code may be further loaded into a computer or other programmable data processing device so that the computer executable program code can be executed on the computer or other programmable device to create a series of operational steps to create a computer-implemented process. Alternatively, the computer program implemented steps or operations may be combined with steps or operations performed by an operator or human to implement an embodiment.

[0280] The communication network may generally include a public network and / or a private network, and may include a local area network, a wide area network, a metropolitan area network, storage and / or other types of networks, and may use communication technologies including analog technology, digital technology, optical technology, wireless technology (e.g., Bluetooth (registered trademark)), networking technology and Internet technology, but is not limited thereto.

[0281] It should also be noted that devices may use communication protocols and messages (eg, messages created, sent, received, stored, and / or processed by the devices) that may be conveyed by a communication network or medium.

[0282] Unless the context requires, the present invention should not be construed as being limited to any particular communication message type, communication message format or communication protocol.Therefore, communication messages may generally include, but are not limited to, frames, packets, datagrams, user datagrams, cells or other types of communication messages.

[0283] It should be understood that unless the context requires otherwise, references to specific communication protocols are illustrative and that alternative embodiments may employ variations of such communication protocols (e.g., modifications or extensions of protocols that may be created from time to time) or any other protocols known or created in the future, as desired.

[0284] It should also be noted that although logic flows may be described in this specification to demonstrate logic in various ways, this should not be understood as limiting the present disclosure to a specific logic flow or logic implementation. The described logic can be divided into different logic blocks (e.g., procedures, modules, functions, or subroutines) without changing the overall results of the present disclosure.

[0285] In many cases, logic elements may be added, modified, deleted, and executed in different orders, and may be implemented using different logic structures (e.g., logic gates, loop primitives, conditional logic, and other logic structures) without changing the overall results of the present disclosure.

[0286] The present disclosure may be implemented in a variety of different ways, including but not limited to computer program logic used with a processor (e.g., a microprocessor, a microcontroller, a digital signal processor, or a general-purpose computer), programmable logic used with a programmable logic device (e.g., a field programmable gate array (FPGA) or other PLD), discrete components, a series of integrated circuits (e.g., an application-specific integrated circuit (ASIC)), or any other device comprising any combination of these. The computer program logic that implements some or all of the above-described functionality is typically implemented as a collection of computer program instructions, which are themselves stored in a computer-readable medium and converted into a computer-executable form that is executed by a microprocessor under the control of an operating system. The hardware-based logic that implements some or all of the above-described functionality may be implemented using one or more appropriately configured FPGAs.

[0287] The computer program logic that implements all or part of the functions described above in this specification can be implemented in various forms, including but not limited to source code form, computer executable form and various intermediate forms (for example, forms generated by an assembler, compiler, linker or locator).

[0288] Source code may include a series of computer program instructions implemented in any of a variety of programming languages ​​(e.g., object code, assembly language, or a high-level language such as Fortran, C, C++, Java (registered trademark), or HTML) for use with various operating systems or operating environments. Source code may define and use various data structures and communication messages. Source code may be in a computer-executable form (e.g., by an interpreter) or may be converted into a computer-executable form (e.g., by a converter, assembler, or compiler).

[0289] The computer-executable program code for performing the operations of the embodiments of the present disclosure may be written in an object-oriented, scripting, or non-scripting programming language such as Java, Perl, Smalltalk, C++, etc. However, the computer program code for performing the operations of the embodiments may also be written in a conventional procedural programming language such as the "C" programming language or a similar programming language.

[0290] The computer program logic that implements all or part of the functions described above in this specification may be executed at different timings on a single processor (e.g., simultaneously), or may be executed at the same or different timings on multiple processors, and may be executed under a process / thread of a single operating system or under processes / threads of different operating systems.

[0291] Thus, the term "computer process" may generally refer to a collection of executing computer program instructions, regardless of whether different computer processes execute on the same or different processors, and regardless of whether different computer processes execute under processes / threads of the same operating system or processes / threads of different operating systems.

[0292] A computer program may be fixed permanently or temporarily in any form (e.g., source code form, computer executable form, or intermediate form) on a tangible storage medium such as a semiconductor memory device (e.g., RAM, ROM, PROM, EEPROM, or flash programmable RAM), a magnetic memory device (e.g., a magnetic disk or fixed disk), an optical memory device (e.g., a CD-ROM), a PC card (e.g., a PCMCIA card), or other memory device.

[0293] The computer program may be fixed in any form in a signal that can be transmitted to a computer using any of a variety of communication technologies, including but not limited to analog technology, digital technology, optical technology, wireless technology (e.g., Bluetooth), networking technology, and Internet technology.

[0294] A computer program can be distributed in any form as a removable storage medium with attached printed or electronic documentation (e.g., prepackaged software) and can be preloaded into a computer system (e.g., in system ROM or on a fixed disk) or can be distributed over a communications system (e.g., the Internet or the World Wide Web) from a server or electronic bulletin board.

[0295] Hardware logic (including programmable logic used with programmable logic devices) that implements all or part of the functionality described in this specification can be designed using traditional manual methods, or can be electronically designed, captured, simulated, or recorded using various tools such as computer-aided design (CAD), hardware description languages ​​(such as VHDL or AHDL), or PLD programming languages ​​(such as PALASM, ABEL, or CUPL).

[0296] Any suitable computer readable medium may be used. The computer readable medium may be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or medium.

[0297] More specific examples of computer-readable media include, but are not limited to, electrical connections having one or more wires or other tangible storage media such as a portable computer diskette, hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), compact disk read-only memory (CD-ROM), or other optical or magnetic storage devices.

[0298] Programmable logic may be permanently or temporarily fixed to a tangible storage medium, such as a semiconductor memory device (e.g., RAM, ROM, PROM, EEPROM, or flash programmable RAM), a magnetic memory device (e.g., a magnetic disk or fixed disk), an optical memory device (e.g., a CD-ROM), or other memory device.

[0299] Programmable logic may be fixed as a signal that can be transmitted to a computer using any of a variety of communication technologies including, but not limited to, analog, digital, optical, wireless (eg, Bluetooth), networking, and Internet technologies.

[0300] Programmable logic can be distributed as a removable storage medium (e.g., prepackaged software) with attached printed or electronic documentation and can be preloaded into a computer system (e.g., on a system ROM or fixed disk), or can be distributed from a server or electronic bulletin board via a communication system (e.g., the Internet or the World Wide Web). Of course, some implementations can be a combination of both software (e.g., a computer program product) and hardware. Other embodiments can be implemented entirely as hardware or entirely as software.

[0301] It should be understood that although specific exemplary methods have been described and shown in the accompanying drawings, such methods are merely exemplary and that, in addition to the content described above, various other changes, combinations, deletions, modifications and substitutions may be made, and therefore the embodiments should not be limited to the specific structures and compositions illustrated and described.

[0302] Those skilled in the art will appreciate that various adaptations, modifications, and / or combinations of the above-described embodiments can be made. Therefore, it should be understood that, within the scope of the appended claims, the embodiments of the present disclosure are not limited to the contents specifically described in the specification. For example, unless otherwise indicated, the steps of the processes described in this specification may be performed in an order different from the order described in this specification, and one or more steps may be combined, split, or performed simultaneously. Those skilled in the art will further appreciate that, in view of the present disclosure, the different embodiments or methods described in this specification may be combined to form other embodiments. Explanation of symbols

[0303] 100 Vehicle-mounted sensors for obstacle detection 101 First obstacle parameter acquisition unit 102 External Sensors 103 Second obstacle parameter acquisition unit 104 Obstacle parameter calculation unit 105 Enable Unit 106 Activation Unit 800 map information memory 801 Signal Strength Acquisition Unit 802 Specification Acquisition Unit 3107 Camera Recognition Unit 3108 Map information storage.

Claims

1. A control device for controlling a driving assistance system of a vehicle, characterized in that: have: a first obstacle parameter acquisition unit that receives a plurality of first obstacle parameters of obstacles in the area around the vehicle detected by a first measurement device, wherein the plurality of first obstacle parameters include one or more parameters of a first category and one or more parameters of a second category; a second obstacle parameter acquiring unit that receives a plurality of second obstacle parameters of obstacles in the area around the vehicle detected by a second measuring device, wherein the plurality of second obstacle parameters include one or more parameters of the first category and one or more parameters of the second category; an obstacle parameter calculation unit that receives the plurality of first obstacle parameters and second obstacle parameters from the first obstacle parameter acquisition unit and the second obstacle parameter acquisition unit, and calculates a plurality of third obstacle parameters of the detected obstacle, including one or more parameters of the first category and one or more parameters of the second category, based on the plurality of first obstacle parameters and the second obstacle parameters, wherein the obstacle parameter calculation unit calculates the one or more parameters of the first category based on the plurality of first obstacle parameters and calculates the one or more parameters of the second category based on the plurality of second obstacle parameters; and An activation unit is configured to calculate a first determination parameter based on the plurality of third obstacle parameters and activate driving assistance when the first determination parameter is lower than a prescribed activation threshold.

2. The control device according to claim 1, characterized in that The obstacle parameter calculation unit determines whether the first and second measurement devices detect the same obstacle based on a comparison result of at least one of the plurality of first and second obstacle parameters, and calculates the plurality of third obstacle parameters only if the determination is positive.

3. The control device according to at least one of claims 1 to 2, characterized in that The first measuring device is a measuring device that communicates with the control device at a higher speed than the second measuring device but detects the obstacle after the second measuring device. The second measuring device is a measuring device that detects the obstacle before the first measuring device but communicates with the control device at a lower speed than the first measuring device.

4. The control device according to at least one of claims 1 to 3, characterized in that The parameters of the first category are position parameters of the obstacle including static information about the obstacle, and the parameters of the second category are motion parameters of the obstacle including dynamic information about the obstacle.

5. The control device according to at least one of claims 1 to 4, characterized in that The obstacle parameter calculation unit includes a prediction model for calculating the plurality of third obstacle parameters, the prediction model using the one or more parameters from the second category of the plurality of second obstacle parameters as one or more initial parameters, and calculating the plurality of third obstacle parameters when the obstacle is first detected.

6. The control device according to at least one of claims 1 to 5, characterized in that The obstacle parameter calculation unit calculates a reliability index indicating the reliability of the plurality of third obstacle parameters, and sends the calculated reliability index together with the plurality of third obstacle parameters to the activation unit. The activation unit activates the driving assistance when the first determination parameter is lower than the prescribed activation threshold and the value of the reliability indicator is higher than a first prescribed reliability threshold.

7. The control device according to at least one of claims 1 to 6, characterized in that The activation unit receives the plurality of first obstacle parameters from the first obstacle parameter acquisition unit, Calculating a second determination parameter based on the plurality of first obstacle parameters, In a case where the first determination parameter and / or the second determination parameter is lower than the prescribed activation threshold, the driving assistance is activated.

8. The control device according to claim 7, characterized in that The obstacle parameter calculation unit increases the value of the reliability index based on the number of times the obstacle is detected by the first measurement device.

9. The control device according to claim 7 or 8, characterized in that The obstacle parameter calculation unit calculates the reliability index in consideration of specifications of the plurality of second obstacle parameters.

10. The control device according to claim 9, characterized in that The specifications of the plurality of second obstacle parameters include a plurality of specification parameters, The obstacle parameter calculation unit adjusts the value of the reliability index based on the values ​​of each specification parameter.

11. The control device according to at least one of claims 7 to 10, characterized in that The obstacle parameter calculation unit receives a plurality of map information of an area around the vehicle and adjusts a value of the reliability index based on the plurality of map information.

12. The control device according to claim 11, characterized in that The obstacle parameter calculation unit receives the plurality of second obstacle parameters detected by more than one second measurement device, selecting the plurality of second obstacle parameters received from the more than one second determination devices based on at least one of the plurality of specification parameters and at least one of the plurality of map information, determining whether the obstacle detected by the one second measuring device is the same as the obstacle detected by the other second measuring device based on at least one of the plurality of second obstacle parameters of the one second measuring device and the other second measuring device, In the case where the determination is positive, receiving the plurality of second obstacle parameters from at least one of the second determining devices, In the case where the determination is negative, The plurality of second obstacle parameters detected by one of the second measuring devices that detected the same obstacle as the obstacle detected by the first measuring device are received.

13. The control device according to claim 12, characterized in that When the obstacle detected by the one second measuring device and the obstacle detected by the other second measuring device are the same, the obstacle parameter calculation unit increases the value of the reliability index. The obstacle parameter calculation unit reduces the value of the reliability index when the obstacles detected by the one second measurement device and the other second measurement device are different.

14. The control device according to claim 12 or 13, characterized in that The obstacle parameter calculation unit receives the fields of view of the one second measuring device and the other second measuring device, In a case where the field of view of the one second measurement device overlaps with the field of view of the other second measurement device, the value of the reliability indicator is reduced.

15. Control device according to at least one of claims 1 to 14, characterized in that Equipped with warning enabling unit and intervention enabling unit, The warning activation unit calculates a warning determination parameter based on the plurality of third obstacle parameters, and activates a warning as a driving assistance when the calculated warning determination parameter is lower than a predetermined warning threshold value. The intervention enabling unit calculates an intervention determination parameter based on the plurality of third obstacle parameters, If the calculated intervention decision parameter is below a predetermined intervention threshold, an intervention is initiated as a driving assistance.

16. The control device according to claim 15, characterized in that When the reliability index is lower than a second predetermined reliability threshold, The obstacle parameter calculation unit calculates a first plurality of third obstacle parameters and a second plurality of third obstacle parameters, the first plurality of third obstacle parameters being calculated based on the first plurality of obstacle parameters and the second plurality of obstacle parameters, the second plurality of third obstacle parameters being calculated based solely on the first plurality of obstacle parameters, the warning enabling unit calculating the warning determination parameter based on the first plurality of third obstacle parameters, the intervention enabling unit calculating the intervention determination parameter based on the second plurality of third obstacle parameters, When the reliability index is higher than the second prescribed reliability threshold, The obstacle parameter calculation unit only calculates the first plurality of third obstacle parameters, The warning enabling unit and the intervention enabling unit calculate the warning determination parameter and the intervention determination parameter, respectively, based on the first plurality of third obstacle parameters.

17. A method for controlling a driving assistance system for a vehicle, the method comprising the steps of: determining a plurality of first obstacle parameters of the detected obstacle, wherein the obstacle is detected by a first determination device, the plurality of first obstacle parameters comprising one or more parameters of a first category and one or more parameters of a second category; determining a plurality of second obstacle parameters of the detected obstacle, wherein the obstacle is detected by a second determination device, the plurality of second obstacle parameters comprising one or more parameters of the first category and one or more parameters of the second category; Receiving, by an obstacle parameter calculation unit, the plurality of first obstacle parameters and the second obstacle parameters; calculating, by the obstacle parameter calculation unit, a plurality of third obstacle parameters of the detected obstacle, wherein the plurality of third obstacle parameters are calculated based on the plurality of first obstacle parameters and the second obstacle parameters, and include one or more parameters of the first category and one or more parameters of the second category, the one or more parameters of the first category being calculated based on the plurality of first obstacle parameters, and the one or more parameters of the second category being calculated based on the plurality of second obstacle parameters; calculating a determination parameter based on the plurality of third obstacle parameters; and When the determination parameter is lower than a predetermined threshold value, the driving assistance is activated by the activation unit.

18. A computer program product storable in a memory, characterized in that The method comprises instructions that, when executed by a computer, cause the computer to perform the method recited in claim 17 .

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