Method for operating an assistance system of an Ego vehicle in a curve area

Abstract

The present invention relates to a method for operating an assistance system of an ego-vehicle 1, in particular a lane guidance assistant or a system for automated vehicle control in a curve area, wherein existing curve curvatures and road users 3 are detected in the curve area, wherein, in the course of detecting the road users 3, their vehicle speed, direction of travel and road user type are determined, wherein a movement corridor B for the ego-vehicle 1 is determined and a reaction measure is controlled depending on a predicted collision risk of the ego-vehicle 1 with an oncoming road user 3.

Description

[0001] The present invention relates to a method for operating an assistance system of an ego vehicle, in particular a lane guidance assistant or a system for automated vehicle control in a curve area, wherein curve curvatures and other road users present in the curve area are detected, wherein in the course of the detection of the other road users their vehicle speed, direction of travel and road user type are determined, wherein a movement corridor for the ego vehicle is determined and a reaction measure is triggered depending on a predicted risk of collision of the ego vehicle with an oncoming road user.

[0002] Generic vehicles, such as passenger cars, trucks, or motorcycles, are increasingly being equipped with assistance systems or driver assistance systems that use sensor systems to detect the environment, recognize traffic situations, and assist the driver, e.g., by braking or steering intervention or by issuing a visual, haptic, or acoustic warning. Radar sensors, lidar sensors, camera sensors, ultrasonic sensors, online functions, or similar are regularly used as sensor systems for environmental detection. Conclusions about the environment can then be drawn from the sensor data acquired by the sensors, which can, for example, also be used to create a so-called environment model. Based on this, instructions can then be issued to warn / inform the driver or for controlled steering, braking, and acceleration.By processing sensor and environmental data, assistance functions can, for example, prevent accidents with other road users or make complex driving maneuvers easier by supporting or even completely taking over the driving task or vehicle control (partially or fully automated). For example, the vehicle can perform automatic emergency braking (AEB, Automatic Emergency Brake) using an emergency brake assist (EBA), control speed and following using a time-gap cruise control or Adaptive Cruise Control (ACC), or keep the vehicle in its lane using a steering assistant (Lane Keep Assist). There are assistance functions like EBA, which are usually activated automatically or activate automatic interventions, and assistance functions that are usually activated by the driver, such as ACC.

[0003] For example, DE 10 2021 204 067 A1 discloses a method for creating a map with collision probabilities for an area. The vehicle speeds of vehicles traveling in the area are determined, and for each of the vehicles, at least one trajectory is predicted based on the vehicle speed. Based on the predicted trajectories, collision probabilities are calculated and stored in the map.

[0004] Statistically, riders of two-wheeled vehicles, such as motorized two-wheelers or cyclists, are particularly at risk of accidents in road traffic, especially on bends.

[0005] The object of the present invention is to provide a generic method or a corresponding assistance system in which the risk of collision with laterally tilting vehicles in curve areas is reduced.

[0006] The above object is achieved by a method having the features of independent claim 1. Preferred embodiments are the subject of the subclaims. A computer program product is the subject of independent claim 8, an assistance system is the subject of independent claim 9, and a vehicle is the subject of independent claim 10.

[0007] According to a first aspect, the invention relates to a method for operating an assistance system, in particular a lane guidance assistant, lane keeping assistant, emergency braking assistant, or a system for automated vehicle control of an ego vehicle, in particular a motor vehicle, in a curve area. In this context, a curve area is understood to mean, in particular, a continuous curve area with an upcoming area of ​​curve entry, curve entry, curve progression with one or more curvature directions, and curve exit. The curve area thus comprises a single curve or several consecutive curves, in particular with an outer and inner lane. The assistance system or the system for automated vehicle control is designed with at least one vehicle function with an SAE (Society of Automotive Engineers) automation level of Level 2, 3, 4, or higher.Examples of vehicle functions include lane guidance and cruise control. The process includes the following steps: First, the curve curvatures present in the curve area are detected. To detect the curve curvatures, at least one environmental sensor of the vehicle is preferably provided, with which the surrounding area of ​​the ego vehicle is detected. Based on the environmental data detected by the at least one environmental sensor, the curve or curve sections visible to the environmental sensor can be detected. The environmental data includes, for example, information from a road model, object information in the vehicle's surroundings, and a driving dynamics model of the vehicle. Alternatively or optionally in addition, digital map material from a navigation system or a vehicle-external database can be accessed, using which the curve curvatures of the curve area can be detected.

[0008] Furthermore, other road users in the curve area are recorded, with their vehicle speed, direction of travel, and road user type being determined as part of the recording process. The road user type refers in particular to the vehicle classification, such as a car, a truck, a bicycle, a motorcycle, a moped, a scooter, or a pedestrian.

[0009] A movement corridor is determined for the ego vehicle and the identified oncoming road users. The movement corridor is understood to be a pre-calculated driving corridor of the ego vehicle, which is determined based on the vehicle's size, direction of travel, vehicle speed, and / or the planned trajectory. For vehicles with a tendency to tilt laterally, the movement corridor is determined based on a predicted inclination in the curve area. This takes into account the movement corridor of tilting vehicles, which varies in object width. Events such as acceleration, the relative position in the lane, or lateral movement can be used to determine the movement corridor of the ego vehicle and / or road users.

[0010] A collision risk between the ego vehicle and an oncoming road user is predicted if a temporal and spatial overlap between the determined movement corridors of the ego vehicle and the corresponding road user has been identified. Preferably, a collision risk is determined based on the curve course and the last and / or updated recorded vehicle speed, the direction of travel, the road user type of the ego vehicle, and the oncoming road user. For example, at least one criticality limit is defined for the temporal and spatial overlap; if exceeded, a collision risk with a specific probability value is determined. Depending on the predicted collision risk, at least one reaction measure is triggered to avert the collision risk as far as possible.

[0011] Predicting the lean angle allows the changing width of objects tilted laterally in curves to be taken into account, enabling improved, and more precise, collision prediction, thus preventing a collision or at least reducing the severity of a collision. The predictive calculation of the road user's movement corridor allows for the initiation of the most convenient response measure possible, especially without immediate emergency measures. This advantageously increases the driver's confidence in the assistance system or the automated vehicle control system.

[0012] It is possible that the vehicle speed, direction of travel and, if applicable, other information about the respective road user is recorded once, for example at the time the ego vehicle enters the curve area or, alternatively, at the time an oncoming road user enters the curve area while the ego vehicle is already in the curve area. In this way, an overview of the current situation regarding road users in the curve area can be generated as early as possible. It is also conceivable that the information about road users in the curve area is recorded at regular intervals in order to be able to achieve more precise forecasts about the road users, in particular about their trajectories through the curve area.

[0013] According to a preferred embodiment, the information about the respective road user is collected via car-to-X and / or car-to-car communication. Alternatively, or optionally in addition, the information about the respective road user is evaluated using environmental data collected by the environment sensors of the ego vehicle.

[0014] According to a preferred embodiment, in the event of a predicted risk of collision, information is output to the driver via an output device as a reaction measure. The output information may, for example, be an acoustic, haptic, and / or visual warning to draw attention to the risk of collision as early as possible. Alternatively, or optionally in addition, the information may include specific instructions to the driver, such as a recommendation to change lanes, perform a braking maneuver, or perform a steering maneuver.

[0015] According to another preferred embodiment, in the event of a predicted risk of collision, the speed of the ego vehicle is regulated to a value that prevents or at least reduces the predicted risk of collision. By accelerating or decelerating the ego vehicle, the temporal distance between the ego vehicle and the road user is adjusted, i.e., reduced or increased, in order to adjust the time of local collision in the curve area. It has been shown that such a control improves the driver's driving experience, since abrupt emergency braking maneuvers are avoided whenever possible.

[0016] According to a further preferred embodiment, in the case of the predicted risk of collision, an intervention in the lane guidance of the ego vehicle takes place, which prevents or at least reduces the local overlap of the movement corridors at the time of the predicted risk of collision.

[0017] According to a preferred embodiment of the present invention, multi-stage response measures can be initiated to avoid the risk of collision. For example, it is possible for a warning to be issued to the driver as the first response measure, allowing them to react independently to the risk of collision. In a subsequent step, a lateral and / or longitudinal intervention can be performed as the second and / or third response measure to make a spatial and / or temporal adjustment of the vehicle trajectory, particularly if the risk of collision is still predicted despite the driver being warned.

[0018] As part of the determination of the lean angle in the curve area, the speed and / or the acceleration and / or the lateral acceleration and / or the lateral movement and / or the yaw rate of the tilting vehicle and the curve curvature can be expediently recorded.

[0019] According to a preferred embodiment, a communication unit can be provided with which information from road users and / or the infrastructure can be received, wherein the information can be used in particular for situation interpretation and / or collision prediction. A suitable communication unit or transmitting and receiving device can, for example, be part of a control unit of the ego vehicle or a standalone (radio) unit of the ego vehicle, which can transmit data to and / or receive data from the control unit either wired or wirelessly (e.g., via Wi-Fi, radio, or Bluetooth).

[0020] According to a further preferred embodiment, at least one environmental sensor can be provided, with which information about road users and / or the vehicle's surroundings can be acquired, wherein the information is used in particular for situation interpretation and / or collision prediction. The environmental sensor can be, for example, a radar, lidar, camera, or ultrasonic sensor.

[0021] The method according to the invention can expediently be a purely computer-implemented method, wherein the term “computer-implemented method” in the sense of the invention describes a process plan or procedure that is realized or carried out using a computer. The computer, such as a computer, a computer network, an evaluation and / or a control unit (e.g. ECU or Electronic Control Unit or ADCU or Assisted & Automated Driving Control Unit) or a computing device therein or another programmable device known from the prior art, can process the corresponding data using programmable computing instructions. With regard to the method according to the invention or the system according to the invention, the essential properties can be brought about, for example, by a new program, new programs, an algorithm or the like that is executed on the control unit.A computer program with program code for implementing the method according to the invention can be provided when the computer program is executed on a computer or other programmable computer known from the prior art. In addition to the computer program, the present invention also encompasses a computer-readable storage medium comprising instructions that cause the computer on which they are executed to execute the method according to the invention.

[0022] In addition or subordinately, the present invention claims an assistance system, in particular a lane guidance assistant or a system for automated vehicle control for an ego vehicle in a curve area, which is preferably operated by means of a method according to the preceding description.

[0023] The environmental conditions of the ego vehicle are thus recorded, for example, by at least one sensor unit, such as a radar, lidar, and / or camera sensor unit, which generates sensor data. Alternatively, or optionally additionally, the ego vehicle comprises a communication unit configured to receive environmental and / or road user data relating to the vehicle surroundings of the ego vehicle using car-to-X and / or car-to-car communication. The assistance system comprises an evaluation unit configured to receive and evaluate the sensor, environmental, and / or road user data.

[0024] The evaluation unit is designed to detect curve curvatures and road users present in the curve area, as well as to determine the vehicle speed, direction of travel, and the road user type. The evaluation unit can, for example, be an ECU or a component of a central ECU in the ego vehicle.

[0025] The evaluation unit is designed to use the sensor, environment, and / or road user data to determine a movement corridor for the ego vehicle and the identified oncoming road users. The movement corridor for tilting vehicles is determined based on a predicted inclination in the curve area.

[0026] The evaluation unit is designed to evaluate the risk of collision between the ego vehicle and an oncoming road user when the determined movement corridors overlap in time and space.

[0027] Furthermore, the assistance system comprises a control unit configured to trigger at least one reaction measure depending on the predicted collision risk. In particular, the vehicle is controlled in such a way that the temporal and / or spatial distance between the ego vehicle and the road user at risk of collision is changed and / or a collision warning is issued to the driver. The control unit can, in particular, comprise a microcontroller or microprocessor, a central processing unit (CPU), a graphics processor (GPU), a digital signal processor (DSP), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), and the like, as well as software for implementing the corresponding method steps.

[0028] Furthermore, the assistance system may be a system comprising a computer, processor, controller, computer or the like in order to carry out the method according to the invention.

[0029] Furthermore, the present invention claims an (ego) vehicle which has an assistance system according to the invention or an assistance system which is operated with the method according to the invention.

[0030] Further developments, advantages, and possible applications of the invention will become apparent from the following description of exemplary embodiments and from the figures. All described and / or illustrated features, individually or in any combination, are fundamentally part of the invention, regardless of their summary in the claims or their reference back to them. The content of the claims is also incorporated into the description.

[0031] The invention is explained in more detail below with reference to exemplary embodiments and the figures. They show: Fig. 1 shows, by way of example, a schematic representation of an ego vehicle with an assistance device for automated vehicle control in a curve area; Fig. 2 a simplified representation of a traffic scenario in which an ego vehicle according to Fig. 1 travels on a lane in a curve area and, according to a first embodiment, initiates a first reaction measure to an oncoming, laterally tilting vehicle; Fig. 3 a simplified representation of the traffic scenario from Fig. 2, in which the ego vehicle according to Fig. 1 drives on the lane in the curve area and, according to a second embodiment, initiates a second reaction measure to the oncoming, laterally tilting vehicle; Fig. 4 a simplified representation of the traffic scenario from Fig. 2, in which the ego vehicle according to Fig. 1 drives on the lane in the curve area and, according to a third embodiment, initiates a third reaction measure to the oncoming, laterally tilting vehicle; Fig. 5 a flowchart showing the process steps of the method for operating an assistance system of the ego vehicle from Fig. 1 in a curve area.

[0032] Fig. Figure 1 shows a bird's-eye view of an assistance system 2 for automated vehicle control of an ego vehicle 1. The assistance system 2 includes, for example, a lane guidance assistant and an ACC. The assistance system 2 is configured, for example, to control the ego vehicle 1 along a planned trajectory.

[0033] The ego vehicle 1 comprises an environment sensor 4 for detecting an area surrounding the vehicle 1, which is illustrated by way of example as a front camera. Of course, other vehicle sensors such as radar, lidar, satellite cameras and / or ultrasonic sensors are also possible. The assistance system 2 further comprises an evaluation unit 5, which is designed to process the sensor data transmitted by the environment sensor 4. For example, the evaluation unit 5 is designed to perform a situation analysis in which the respective traffic situation of the ego vehicle 1 is detected. The assistance system 2 further comprises a control unit 6, which is designed to automatically control the ego vehicle 1 based on the situation analysis of the evaluation unit 5.

[0034] Fig. Figure 2 shows a bird's-eye view of a traffic scenario in which the ego vehicle 1 and a laterally tilting vehicle 3 approaching the ego vehicle 1 are traveling in a curve. The curve includes, purely as an example, several consecutive curves with different curvatures.

[0035] When the ego vehicle 1 is about to enter and / or enter the curve area, the evaluation unit 5 is configured to detect the curve curvatures present in the curve area. This can be done, for example, by means of a sensor data evaluation of the vehicle surroundings sensors and / or by means of digital map material. Furthermore, the evaluation unit 5 is configured to detect road users 3. Furthermore, the vehicle speed, direction of travel and the type of road user are evaluated by the evaluation unit 5. In the embodiment according to Fig. 2 to 4, the road user is an oncoming motorcyclist 3.

[0036] The evaluation unit 5 is designed to determine a movement corridor B for the ego vehicle 1 and the detected oncoming road user 3. The movement corridor B for the motorcyclist is determined based on a predicted inclination in the curve area. Fig. Figure 2 schematically shows the changing object width of the motorcycle, and thus the changing width of the movement corridor when negotiating a curve due to the lean angle. While the motorcycle still has a relatively narrow object width on a straight section compared to a car, the movement corridor can widen significantly in the curve section depending on the lean angle. For example, events such as speed, acceleration, the relative position in the lane, or the onset of a lateral movement of the oncoming motorcyclist can be used to evaluate the lean angle and thus the movement corridor course in the curve area.

[0037] The evaluation unit 5 is configured to evaluate a collision risk between the ego vehicle 1 and an oncoming road user 3 when the determined movement corridors B overlap in time and space. In other words, a stationary area has been determined where the movement corridors B overlap, and consequently, a collision between the ego vehicle 1 and road user 3 is predicted. It is preferable to update the determination of the movement corridors B at regular intervals in order to be able to promptly detect a collision risk or changed conditions as precisely and reliably as possible. The control unit 6 is configured to trigger at least one reaction measure depending on the predicted collision risk.

[0038] Fig. 2 - 4 show examples of possible reaction measures in the event of a predicted collision risk. Fig. Figure 2 shows a diagram in which time is plotted on the x-axis and the required deceleration of the ego vehicle 1 is plotted on the y-axis. If a collision risk has been predicted, a warning is issued to the driver as a reaction measure in this exemplary embodiment. The warning includes, for example, a note about the detected collision risk, a request to initiate braking, and / or that the driver must assume control of the vehicle. A warning as a reaction measure is useful, for example, when there is a sufficiently large distance to the collision risk, allowing the driver to react in a timely manner.

[0039] Fig. 3 shows how Fig. 2 shows a bird's-eye view of the ego vehicle 1 and the oncoming motorcycle 3 in the curve area. In this exemplary embodiment, a distinction is made between criticality levels as a reaction measure. Thus, a collision risk is detected in a first criticality level, and a warning is issued to the driver of the ego vehicle 1 as a linked reaction measure. The criticality level is defined, for example, when a distance limit between the ego vehicle 1 and the location of the collision risk is undershot. The second reaction measure, which in this exemplary embodiment is initiated at a time interval from the first reaction measure, is a lateral intervention in the vehicle guidance. This results in, in particular, in an adjustment of the planned trajectory. In this exemplary embodiment, the ego vehicle 1 is guided to the right of the outside lane in order to be able to avert or at least reduce an overlap area of ​​the movement corridors B.The second response measure can be initiated, for example, if the collision risk has been determined at a second criticality level. At the second criticality level, for example, a second distance limit between ego vehicle 1 and the determined location of the collision risk is exceeded. In particular, the distance limit of the second criticality level is lower than the distance value of the first criticality level.

[0040] Fig. 4 shows how Fig. 3 shows a bird's eye view of the ego vehicle 1 and the oncoming motorcycle 3 in the curve area. In comparison to the embodiment in Fig. 3, in this exemplary embodiment, a further reaction measure is initiated. The further reaction measure is initiated after a third criticality level is reached, for example, when a specified third distance limit between ego vehicle 1 and the determined location of the collision risk is undershot. The distance limit of the third criticality level has, in particular, a lower value than the distance value of the second criticality level. The criticality levels can, for example, also be linked to a calculated collision probability. The third reaction measure, which is initiated at a time interval from the second reaction measure, is a braking intervention, in particular a comfortable braking intervention, in order to be able to avert or at least reduce an overlap area of ​​the movement corridors B.Early braking is a particularly comfortable process that gives the driver a greater sense of safety compared to emergency braking.

[0041] Fig. 5 shows a schematic flow chart illustrating the sequences of the method for operating an assistance system 2 of the ego vehicle 1 in the curve area.

[0042] In the method, curve curvatures present in the curve area are recorded S100. Furthermore, road users 3 are recorded in the curve area, wherein during the recording of the road users 3 their vehicle speed, direction of travel and road user type are determined S200. On the one hand, a movement corridor B is determined for the ego vehicle 1, and on the other hand, a movement corridor B is determined for each of the identified oncoming road users 3, wherein the movement corridor B for laterally inclinable vehicles is determined based on a predicted inclination in the curve area S300. A risk of collision between the ego vehicle 1 and an oncoming road user 3 is predicted S400 if the determined movement corridors overlap in time and space, and at least one reaction measure is triggered S500 depending on the predicted risk of collision.

[0043] The invention has been described above using exemplary embodiments. It is understood that numerous changes and modifications are possible without departing from the scope of protection defined by the patent claims. LIST OF REFERENCE SYMBOLS 1 (ego) vehicle 2 Assistance system 3 road users 4 Environment sensor 5 Evaluation unit 6 Control unit B Movement corridor QUOTES CONTAINED IN THE DESCRIPTION

[0000] This list of documents submitted by the applicant was generated automatically and is included solely for the convenience of the reader. This list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions. Cited patent literature

[0000] DE 10 2021 204 067 A1

[0003]

Claims

[1] Method for operating an assistance system of an ego vehicle (1), in particular a lane guidance assistant or a system for automated vehicle control in a curve area, the method comprising the following steps: - Detection of the curve curvatures present in the curve area, - Detection of road users (3) in the curve area, whereby the vehicle speed, direction of travel and type of road user are determined as part of the detection of the road users (3), - Determination of a movement corridor (B) for the ego vehicle (1) and the respectively determined oncoming road users (3), wherein the movement corridor (B) for laterally tiltable vehicles is determined on the basis of a predicted inclination in the curve area, - Prediction of a collision risk of the ego vehicle (1) with an oncoming road user (3) in the case of temporal and spatial overlap of the determined movement corridors, - Activation of at least one reaction measure depending on the predicted collision risk. [2] Method according to claim 1, characterized by that in the event of a predicted risk of collision, information, in particular a warning and / or specific instructions, are issued to the driver via an output device as a reaction measure. [3] Method according to claim 1 or 2, characterized by that in the case of the predicted risk of collision, the speed of the ego vehicle (1) is regulated to a value that prevents or at least reduces the predicted risk of collision. [4] Method according to one of the preceding claims, characterized bythat in the event of the predicted risk of collision, an intervention in the lane guidance of the ego vehicle (1) takes place, which prevents or at least reduces the local overlap of the movement corridors (B) at the time of the predicted risk of collision. [5] Method according to one of the preceding claims, characterized by that in order to determine the lean angle in the curve area, the speed, acceleration, lateral acceleration, lateral movement and / or yaw rate of the laterally tilting vehicle and the curve curvature are recorded. [6] Method according to one of the preceding claims, characterized by that a communication unit is provided with which information from road users (3) and / or the infrastructure can be received, the information being used in particular for situation interpretation and / or collision prediction. [7] Method according to one of the preceding claims, characterized bythat at least one environment sensor (4) is provided with which information about the road users (3) and / or the vehicle environment can be recorded, wherein the information is used in particular for situation interpretation and / or collision prediction. [8] Computer program with program code for carrying out a method according to one of claims 1-7, when the computer program is executed by a computer. [9] Assistance system (2), in particular a lane guidance assistant or a system for automated vehicle control for an ego vehicle (1) in a curve area, which is preferably operated by means of a method according to one of the preceding claims, with an evaluation unit (5) which is designed to detect curve curvatures and road users (3) present in the curve area and to determine vehicle speed, direction of travel and road user type of the road users (3), wherein the evaluation unit (5) is designed to determine a movement corridor for the ego vehicle and the respectively determined oncoming road users (3), wherein the movement corridor (B) for inclinable vehicles is determined on the basis of a predicted inclination in the curve area, wherein the evaluation unit (5) is designed to evaluate a collision risk of the ego vehicle (1) with an oncoming road user (3) in the event of temporal and spatial overlap of the determined movement corridors (B), with a control unit (6) which is designed to control at least one reaction measure depending on the predicted collision risk. [10] Vehicle (1) comprising an assistance system (2), in particular according to claim 9, which is operated with a method according to one of claims 1-7.

Images