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

Abstract

Method for operating an assistance system of an ego vehicle (1), in particular a system for automated vehicle control in a curve area, the method comprising the following steps: - Detection of curve curvatures present in the curve area as well as of road users in the curve area (S100), - Determination of vehicle speed, position and direction of travel of the road users detected in the curve area (3) (S200), - predicting, using the determined information on the detected road users (3), whether a road user (3) approaching the ego vehicle (1) will move into the lane of the ego vehicle (1) while negotiating the curve (S300), - Evaluation of a movement corridor (B) for a road user (3) potentially traveling in the lane of the ego vehicle (1) (S400), - Collision check of the ego vehicle (1) with the road user (3) potentially traveling in the lane of the ego vehicle (1) based on its predicted movement corridor (3) (S500), - Control of at least one reaction measure depending on a predicted risk of collision with the road user (3) potentially traveling in the lane of the ego vehicle (1) (S600), characterized in that the vehicle class of the oncoming road users (3) in the curve area is determined, and wherein when a laterally inclinable vehicle is determined, the width of the movement corridor (B) in the curve area is determined on the basis of a predicted inclination.

Description

[0001] The present invention relates to a method for operating an assistance system of an ego vehicle, in particular a system for automated vehicle control in a curve area. The method includes detecting curve curvatures and road users present in the curve area, determining the vehicle speed, position, and direction of travel of the road users detected in the curve area, assessing the risk of collision between the ego vehicle and oncoming road users, and in the event of a predicted risk of collision, initiating at least one reaction measure. Furthermore, the present invention relates to a computer program and an assistance system for an ego vehicle in a curve area.

[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 guidance (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. Movement data of vehicles traveling in the area is determined, and at least one trajectory is predicted for each vehicle based on the movement data. Based on the predicted trajectories, collision probabilities are calculated and stored in the map.

[0004] Curved areas pose an increased risk of accidents in road traffic, as the course of the curve and oncoming traffic are often only visible to the driver late, or the speed permitted for driving dynamics reasons is difficult for the driver to estimate.

[0005] Furthermore, DE 10 2013 020 733 A1 describes an assistance system for supporting a driver during starting and / or turning maneuvers of a vehicle. The assistance system comprises a detection device for detecting at least one road user in the vicinity of the vehicle and a detection device. The detection device serves to determine a predicted, anticipated driver behavior of the driver and / or a predicted driving behavior of the vehicle, to determine a predicted movement behavior of the road user, and, depending on the predicted, anticipated driver behavior of the driver and / or the predicted driving behavior of the vehicle and the predicted movement behavior of the road user, to determine whether or not a collision between the vehicle and the road user is imminent.

[0006] DE 10 2017 114 876 A1 discloses a method for collision avoidance of a potential collision between an ego vehicle and another road user, in which the future trajectories are predicted for the ego vehicle and the one other road user and at least two probability areas with different time intervals are determined along the predicted trajectories, wherein all probability areas with the same time interval are compared with each other and, if an overlap of two probability areas with the same time interval is detected, staggered escalation measures are carried out.

[0007] In addition, DE 10 2012 211 509 A1 describes a method for collision avoidance between an ego vehicle and an object approaching the ego vehicle from behind, wherein a possible collision probability of the object with the ego vehicle is determined and a speed of the ego vehicle is determined and the approach of the object is determined by comparing an approach speed of the object with the speed of the ego vehicle, wherein an action is carried out to avoid the collision or to reduce accident damage, which action includes emitting an acoustic and / or optical warning signal to the object.

[0008] The object of the present invention is to propose a method and assistance system in which a collision risk in a curve area is efficiently reduced.

[0009] 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, and an assistance system is the subject of independent claim 9.

[0010] 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, automatic 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 collision warning, lane guidance, or 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, 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 to detect the curve curvatures of the curve area. The at least one environmental sensor is, for example, a radar, lidar, camera, or ultrasonic sensor.

[0011] Furthermore, road users in the curve area are recorded. These include pedestrians, cyclists, motorcyclists, trucks, and cars, for example, who are on the roadway or in the immediate vicinity of the roadway in the curve area. Furthermore, at least the vehicle speed, position, and direction of travel of the road users recorded in the curve area are determined. Based on the determined direction of travel, it is possible to determine whether a road user is moving in or against the direction of travel of the ego vehicle.

[0012] It is preferred that, in addition to the vehicle speed, position, and direction of travel, further information about the road user be determined. For example, the acceleration, lateral acceleration, lateral movement, and / or yaw rate of the road user can be recorded. Furthermore, it is preferred that the vehicle width, vehicle size, and / or road user type be determined. In this context, the road user type is the vehicle class, such as a car, a truck, a bicycle, a motorcycle, a moped, a scooter, or a pedestrian.

[0013] According to a preferred embodiment, the detection of road users and the associated information, in particular the vehicle speed, position, vehicle class, trajectory, and / or direction of travel to the respective road user, takes place via car-to-X and / or car-to-car communication. Alternatively, or optionally in addition, the road users and associated information about the respective road user are evaluated using environmental data collected by the ego vehicle's environmental sensors.

[0014] Using the determined information, i.e., at least the determined vehicle speed, position, and direction of travel of the road users detected in the curve area, a prediction is made as to whether an oncoming road user will move into the movement corridor of the ego vehicle while negotiating the curve, i.e., whether the road user will enter its oncoming lane. In particular, entering the oncoming lane is predicted if the oncoming road user's vehicle speed is determined to be excessive for the upcoming curve, and if the driver is expected to cross the oncoming lane as a countermeasure. The evaluation of potential corner cutting based on the vehicle speed is computationally efficient and therefore quickly available.

[0015] A movement corridor is evaluated for the road user potentially traveling in the lane of the ego vehicle. The movement corridor is understood to be a pre-calculated driving corridor, which is determined based on the vehicle width, direction of movement, vehicle class, vehicle speed, and / or the trajectory determined by the system. Events such as acceleration, relative position in the lane, and / or lateral movement can also be used to determine the road user's movement corridor. The width of the movement corridor is preferably set according to the vehicle width.

[0016] It is conceivable that a movement corridor could be evaluated for all road users. However, it is preferable to evaluate the movement corridor exclusively for road users approaching the ego vehicle and potentially entering the ego lane in order to obtain a situation analysis in a computationally efficient and timely manner.

[0017] The next step involves a collision check between the ego vehicle and the road user potentially traveling in the ego vehicle's lane based on the predicted movement corridor. For example, a potential collision is predicted if the movement corridor of the oncoming road user runs into the movement corridor of the ego vehicle. A potential collision can also be predicted, for example, only if a spatial and temporal collision between the ego vehicle and the road user has been determined.

[0018] Depending on the predicted collision with the road user potentially traveling in the lane of the ego vehicle, at least one or exactly one reaction measure is triggered to avert the predicted collision risk. The reaction measure is preferably a countermeasure tailored to the collision situation.

[0019] The method according to the invention advantageously ensures that, despite the often confusing nature of a curve, a rapid and reliable situation analysis is performed, allowing one or more response measures to be implemented based on the situation analysis if necessary. This ensures an efficient reduction of the risk of collision in curves. The early prediction of the risk of collision also results in the most convenient safety action possible for the driver.

[0020] According to a preferred embodiment, a movement corridor of the ego vehicle in the curve area is evaluated. To check the risk of collision, this movement corridor is preferably compared with the predicted movement corridor of the road user potentially traveling in the lane of the ego vehicle for temporal and spatial overlap. In particular, a collision risk is predicted if an encounter, i.e., a temporal and spatial overlap of the determined movement corridors in the curve area of the ego vehicle and oncoming road users, has been detected.

[0021] Preferably, when a collision risk is determined, one or more trajectories are calculated or recalculated for the ego vehicle. The trajectories are calculated in such a way that, when driving through a trajectory, collision between the ego vehicle and the road user is excluded as far as possible. For example, the trajectories have different speed and acceleration profiles. This results in multiple trajectories being calculated that differ in the temporal progression of speed and acceleration.

[0022] The evaluation of the movement corridor of the ego vehicle and / or the oncoming road user is based, for example, on the vehicle width or size, direction of movement, vehicle speed, acceleration, lateral acceleration, lateral movement and / or the yaw rate of the ego vehicle or road user, and the curve curvature. Another possible factor for evaluating the movement corridor is, for example, a system-determined trajectory of the ego vehicle or the oncoming road user.

[0023] The recording of vehicle speed, position, and any other information about the respective road user occurs, for example, at least at the time the ego vehicle enters the curve and / or at the time an oncoming road user enters the curve while the ego vehicle is already in the curve. In this way, an overview of the current situation regarding road users in the curve can be generated as early as possible. It is also conceivable that the recording of information regarding road users in the curve could occur at regular intervals in order to be able to achieve more precise forecasts regarding road users, in particular regarding their trajectories in the curve.

[0024] According to the invention, the vehicle class of the oncoming road users in the curve area is determined. If a laterally tiltable vehicle, such as a motorcycle, has been detected, it is preferable that the width of the movement corridor be determined based on a predicted inclination in the curve area. The prediction of the inclination thus takes into account the varying vehicle width in the curve area and consequently allows for the protrusion of the laterally tiltable vehicle or its driver into the oncoming lane to be evaluated and reacted accordingly. In the case of four-wheeled vehicles or vehicles that essentially cannot be tilted laterally, the width of the movement corridor is determined once and according to the vehicle width.

[0025] It is preferred that the prediction of the risk of collision comprises the evaluation of a criticality and a probability, wherein the at least one reaction measure is initiated depending on the evaluated criticality and probability. On the one hand, an assessment is made of how likely a collision with the road user is. For example, the probability of a collision is classified as high if a road user takes the bend at a significantly excessive vehicle speed or if the road user is already crossing into the oncoming lane. On the other hand, an assessment is made of how critical the collision would be if it were to occur. For example, a collision is classified as not very critical if the road user and the ego vehicle are traveling at such a low speed that personal injury or property damage can be ruled out.The evaluation of probability and criticality makes it possible to initiate an appropriate response measure.

[0026] According to a preferred development, if at least one specified criticality threshold and / or at least one specified probability threshold is exceeded, a collision warning and / or specific instructions are issued to the driver as a reaction measure. The collision warning may, for example, be a haptic, acoustic, and / or visual warning, giving the driver the opportunity to react independently to the risk of collision. The specific instructions to the driver may, for example, be a recommendation to brake, steer, park, or swerve.

[0027] According to a further preferred development, if at least one specified criticality and / or probability threshold of the collision risk is exceeded, the speed of the ego vehicle is regulated to a value that adjusts the trajectory of the ego vehicle in time. Accordingly, a vehicle speed of the ego vehicle should be achieved that prevents a temporal and spatial overlap of the movement corridors of the vehicles, thus excluding the evaluated location of the potential collision as far as possible.

[0028] According to a further preferred development, if the at least one specified criticality and / or probability threshold of the collision risk is exceeded, an intervention in the lane guidance of the ego vehicle occurs, preventing or at least reducing the spatial overlap of the movement corridors at the time of the predicted collision risk. This reaction measure can also prevent the potential collision or at least mitigate its impact.

[0029] It is possible that a first, second and possibly further criticality and / or probability thresholds are defined, and if these are exceeded, one or more response measures are initiated.

[0030] 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 a second or third response measure to make a spatial and / or temporal adjustment of the trajectory, particularly if the risk of collision is still predicted despite the driver being warned.

[0031] Preferably, the response measure to be initiated is linked to the calculated remaining time until the potential collision. If sufficient time is available, it is conceivable to issue a request to take over control of the vehicle or a warning to the driver so that they can react promptly and independently. However, if there is insufficient time for a safe driver reaction, taking into account the driver's reaction time, it is conceivable that the system could intervene immediately in the vehicle's control.

[0032] 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 assistance 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.

[0033] In addition or subordinately, the present invention claims an assistance system, in particular a system for automated vehicle control of an ego vehicle in a curve area, which is preferably operated by means of a method according to the preceding description.

[0034] The assistance system comprises an evaluation unit designed to detect curve curvatures and road users in the curve area. The evaluation unit can, for example, be an ECU or a component of a central ECU in the ego vehicle.

[0035] Furthermore, the vehicle speed, position, and direction of travel of the road users detected in the curve area are determined. These, the curve curvature, and any other environmental information are determined using a sensor unit such as a radar, lidar, and / or camera sensor unit.

[0036] The evaluation unit is designed to predict, using the determined environmental information, in particular the vehicle speed, position, vehicle class, and direction of travel relative to the detected road users, whether a road user approaching the ego vehicle will move into the ego vehicle's lane while negotiating the curve. The evaluation unit is further designed to evaluate a movement corridor for a road user potentially traveling in the ego vehicle's lane. Furthermore, the evaluation unit is designed to check the risk of collision between the ego vehicle and the road user potentially traveling in the ego vehicle's lane based on the predicted movement corridor. Furthermore, the evaluation unit is designed to determine the width of the movement corridor in the curve area based on a predicted inclination when a vehicle capable of tilting laterally is detected.

[0037] Furthermore, the assistance system comprises a control unit configured to trigger at least one reaction measure depending on a collision risk predicted by the evaluation unit. 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.

[0038] 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.

[0039] According to a preferred embodiment, the assistance system can be provided with a communication unit with which information from other road users and / or the infrastructure can be received, wherein the information is 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 the evaluation unit of the assistance system or a standalone (radio) unit of the ego vehicle, which can transmit data to and / or receive data from the evaluation unit either wired or wirelessly (e.g., via Wi-Fi, radio, or Bluetooth).

[0040] According to a further preferred embodiment, at least one environment sensor can be provided, with which information about other 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 environment sensor can be, for example, a radar, lidar, camera, or ultrasonic sensor.

[0041] 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.

[0042] The invention is explained in more detail below with reference to exemplary embodiments and 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 in a lane in a curve area and, according to a first embodiment, initiates a first reaction measure to a road user potentially traveling in the lane of the ego vehicle; Fig. 3 a simplified representation of the traffic scenario from Fig. 2, in which, according to a second embodiment, a second reaction measure is initiated against the road user potentially traveling in the lane of the ego vehicle; Fig. 4 a simplified representation of the traffic scenario from Fig. 2, in which, according to a third embodiment, a third reaction measure is initiated against a road user potentially traveling in the lane of the ego vehicle; Fig. 5 a simplified representation of a traffic scenario in which a collision risk of the ego vehicle with a road user leaning sideways and potentially entering the lane of the ego vehicle is evaluated; Fig. 6 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.

[0043] 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.

[0044] The ego vehicle 1 includes an environment sensor unit 4 for detecting its surroundings, which includes, for example, a front camera. Of course, other or additional environment sensors such as radar, lidar, satellite cameras, and / or ultrasonic sensors are also possible.

[0045] The assistance system 2 comprises an evaluation unit 5, which is coupled to the environment sensor unit 4 and configured to process the sensor data transmitted by the environment sensor 4. For example, the evaluation unit 5 is configured to perform a situation analysis in which the respective traffic situation of the ego vehicle 1 is recorded. The assistance system 2 further comprises a control unit 6, which is configured to automatically control the ego vehicle 1 based on the situation analysis of the evaluation unit 5. The assistance system 2 further comprises a control unit 6, which is configured to automatically control the ego vehicle 1 based on the situation analysis of the evaluation unit 5.

[0046] Fig. Figure 2 shows a bird's-eye view of a traffic scenario in which the ego vehicle 1 and a road user 3 approaching the ego vehicle 1 are driving in a curve. The curve area includes, purely as an example, several consecutive curves with different curvatures.

[0047] When the ego vehicle 1 is about to enter 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 evaluating sensor data from the environmental sensors 4 and / or using digital map material.

[0048] The evaluation unit 5 is designed to detect other road users 3 using the sensor data and to determine at least the vehicle speed, position and direction of travel of the road users 3 detected in the curve area. In the embodiment according to Fig. 2 to 4, the road user 3 approaching the ego vehicle 1 is a passenger car. The evaluation unit 5 is configured to use the determined vehicle speed, position, and direction of travel of the oncoming road user 3 to predict whether the oncoming road user 3 will move into the lane of the ego vehicle 1 while negotiating the curve, i.e., whether it will cut the curve. In order to predict whether the oncoming road user 3 will cut the curve, for example, the last determined vehicle speed or a vehicle speed profile of the oncoming road user 3 derived therefrom is correlated with the upcoming curve curvatures of the road user 3. In this exemplary embodiment, a corner cutting was predicted.Based on this result, i.e., that road user 3 will potentially enter the lane of ego vehicle 1, a movement corridor B is evaluated for road user 3. Although the evaluation of movement corridor B involves increased computational effort, it enables a collision check, unlike predicted corner cutting. Preferably, movement corridor B for road user 3 is only evaluated if corner cutting has been predicted. This way, computing capacity is not unnecessarily consumed.

[0049] Based on the predicted movement corridor 3 of the road user 3 potentially traveling in the lane of the ego vehicle 1, the risk of collision with the ego vehicle 1 traveling through the curve is assessed. The specified width of the movement corridor B corresponds at least approximately to the vehicle width of the road user 3, since this is invariable for a passenger car. "At least approximately" in the sense of the invention means a deviation from the exact value by + / - 10%, preferably by + / - 5%. According to the Fig. In the embodiment shown in Figure 2, road user 3 will move partially into the lane of ego vehicle 1 according to movement corridor B. A collision risk is evaluated, for example, if the ego vehicle 1 falls below a predetermined distance limit from the location of the determined curve intersection. A collision risk can also be evaluated, for example, if a local overlap of a movement corridor determined for ego vehicle 1 with the movement corridor of road user 3 has been determined.

[0050] If a risk of collision between the ego vehicle 1 and the road user 3 has been predicted due to the cornering by the road user 3, the control unit 6 triggers one or more reaction measures.

[0051] Fig. Figures 2 to 4 show examples of possible reaction measures in the event of a predicted collision risk. Fig. 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 take over 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.

[0052] Fig. 3 shows the embodiment of the Fig. 2 with a smaller distance between ego vehicle 1 and oncoming road user 3 in the curve area. Despite the warning issued to the driver, the collision risk is still being assessed, e.g., because the driver of the ego vehicle has not reduced their speed. In a next step, a second reaction measure is initiated, namely a lateral intervention in the vehicle's steering to the edge of the road to avoid a collision between the vehicles as much as possible.

[0053] According to Fig. 4, a third reaction measure is initiated at a time offset from the first and second reaction measures, namely a braking intervention, in particular a comfortable braking intervention, in order to avert the potential collision. In this context, a comfortable braking intervention is understood to mean a safe and stable reduction in speed, in particular avoiding sudden emergency braking. This advantageously increases the driver's sense of trust in the assistance system.

[0054] Fig. 5 shows, as in the previous figures, a traffic scenario from a bird's eye view in which the ego vehicle 1 and a road user 3 approaching the ego vehicle 1 are driving in a curve. The oncoming road user 3 is a laterally tilting vehicle, e.g., a motorcycle. The special feature of laterally tilting vehicles is the changing object width in a curve depending on the vehicle speed and curve curvature. This increases the difficulty of evaluating a potential collision. Against this background, the movement corridor B for a laterally tilting vehicle in the curve is determined based on a predicted inclination in the curve. The prediction of the inclination makes it possible to take into account the changing object width of the movement corridor of the laterally tilting vehicle in the curve.Events such as acceleration, the relative position in the lane or the beginning of a lateral movement of the laterally tilting vehicle can be used to predict the lean angle.

[0055] In all of the preceding embodiments, the initiation of the reaction measure can be linked to a determined criticality and / or probability of the collision risk. Likewise, for all of the preceding embodiments, it is conceivable that the reaction measures are issued or triggered simultaneously and / or multiple times.

[0056] The method and assistance system according to the invention implements traffic-safe cornering, which can be optimized if necessary, and which achieves the highest possible level of comfort for the vehicle occupants.

[0057] Fig.6 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.

[0058] In the method, curve curvatures present in the curve area as well as road users in the curve area are recorded S100. The vehicle speed, position and direction of travel of the road users 3 recorded in the curve area are determined S200. Using the determined information on the recorded road users 3, a forecast is made as to whether a road user 3 coming towards the ego vehicle 1 will move into the lane of the ego vehicle 1 while negotiating the curve S300. A movement corridor B for a road user 3 potentially traveling in the lane of the ego vehicle 1 is evaluated S400. The risk of collision between the ego vehicle 1 and the road user 3 potentially traveling in the lane of the ego vehicle 1 is checked S500 based on the predicted movement corridor, and at least one reaction measure is triggered S600 depending on a predicted risk of collision.

[0059] 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.

Claims

[1] Method for operating an assistance system of an ego vehicle (1), in particular a system for automated vehicle control in a curve area, the method comprising the following steps: - Detection of curve curvatures present in the curve area as well as of road users in the curve area (S100), - Determination of vehicle speed, position and direction of travel of the road users detected in the curve area (3) (S200), - predicting, using the determined information on the detected road users (3), whether a road user (3) approaching the ego vehicle (1) will move into the lane of the ego vehicle (1) while negotiating the curve (S300), - Evaluation of a movement corridor (B) for a road user (3) potentially traveling in the lane of the ego vehicle (1) (S400), - Collision check of the ego vehicle (1) with the road user (3) potentially traveling in the lane of the ego vehicle (1) based on its predicted movement corridor (3) (S500), - Activation of at least one reaction measure depending on a predicted risk of collision with the road user (3) potentially traveling in the lane of the ego vehicle (1) (S600) characterized by that the vehicle class of the oncoming road users (3) in the curve area is determined, and wherein when a vehicle which can tilt laterally is determined, the width of the movement corridor (B) in the curve area is determined on the basis of a predicted inclination. [2] Method according to claim 1, characterized bythat a movement corridor (B) of the ego vehicle (1) is evaluated in the curve area, whereby a risk of collision of the ego vehicle (1) with an oncoming road user (3) is predicted, should a temporal and spatial overlap of the determined movement corridors (B) have been determined. [3] Method according to claim 2, characterized by that the evaluation of the movement corridor (B) of the ego vehicle (1) and / or the oncoming road user (3) is based on the vehicle width, direction of movement, vehicle speed, acceleration, lateral acceleration, transverse movement, a trajectory determined by the system and / or the yaw rate of the ego vehicle (1) or road user (3) and the curve curvature. [4] Method according to one of the preceding claims, characterized bythat the prediction of the collision risk comprises the evaluation of a criticality and a probability, whereby at least one reaction measure is initiated depending on the evaluated criticality and probability. [5] Method according to claim 4, characterized by that if at least one specified criticality threshold and / or probability threshold is exceeded, a collision warning and / or specific instructions are issued to the driver as a reaction measure. [6] Method according to claim 4 or 5, characterized by that when the at least one specified criticality and / or probability threshold is exceeded, the speed of the ego vehicle (1) is regulated to a value such that the trajectory of the ego vehicle (1) is adapted in time. [7] Method according to one of the preceding claims 4 to 6, characterized bythat if the at least one specified criticality and / or probability threshold of the collision risk is exceeded, 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 collision risk. [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 system for automated vehicle control of 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 present in the curve area as well as road users (3) in the curve area, wherein the evaluation unit (5) is designed to determine the vehicle speed, position, direction of travel and vehicle class of the road users (3) detected in the curve area and, using the determined information on the detected road users (3), to predict whether a road user (3) approaching the ego vehicle (1) will move into the lane of the ego vehicle (1) while negotiating the curve, wherein the evaluation unit (5) is designed to evaluate a movement corridor (B) for a road user (3) potentially traveling in the lane of the ego vehicle (1), and to check a collision risk of the ego vehicle (1) with the road user (3) potentially traveling in the lane of the ego vehicle (1) based on the predicted movement corridor (B), and wherein the evaluation unit (5) is designed, upon detection of a laterally tiltable vehicle, to determine the width of the movement corridor (B) in the curve area on the basis of a predicted inclination, with a control unit (6) which is designed to control at least one reaction measure depending on a predicted risk of collision with the road user (3) potentially traveling in the lane of the ego vehicle (1).

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