• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    The invention relates to a device for controlling the speed of a vehicle, comprising an environment sensor for recording the current traffic situation in the vicinity of the vehicle, a brake actuator for actuating a braking device of the vehicle, an acceleration actuator for actuating an acceleration device of the vehicle, a computing unit which is designed for this purpose Calculating control values for controlling the brake actuator and the acceleration actuator, wherein the environment sensor is arranged for detecting the motion data of road users in the vicinity of the vehicle, and the arithmetic unit comprises a predictor for calculating a risk function within a predetermined time horizon, the risk function being based at least on Movement data of the own vehicle and the detected road users is calculated, and wherein the arithmetic unit an optimizer for the target acceleration of the vehicle under query of the predictor, which minimizes the risk function within the time horizon or keeps below a predetermined threshold, and wherein the arithmetic unit for calculating the control values from the determined target acceleration of the vehicle is set up. The invention further relates to a method for controlling the speed of a vehicle with a device according to the invention.
    公开号:AT519547A4
    申请号:T50517/2017
    申请日:2017-06-22
    公开日:2018-08-15
    发明作者:Stephen John Jones Dr；Kural Emre；Massoner Alexander；Luigi Del Re Dr；Dominik Moser Dr
    申请人:Avl List Gmbh；
    IPC主号:
    专利说明:

    Summary
    The invention relates to a device for controlling the speed of a vehicle, comprising an environmental sensor for recording the current traffic situation in the area surrounding the vehicle, a brake actuator for actuating a brake device of the vehicle, an acceleration actuator for actuating an acceleration device of the vehicle, and a computing unit which is designed for this purpose To calculate control values for controlling the brake actuator and the acceleration actuator, the environment sensor being set up to detect the movement data of road users in the vicinity of the vehicle, and the computing unit comprising a predictor for calculating a risk function within a predetermined time horizon, the risk function being based at least on the Movement data of the own vehicle and the detected road users is calculated, and the computing unit is an optimizer for the target acceleration of the vehicle under query of the predictor, which minimizes the risk function within the time horizon or keeps it below a predetermined threshold value, and wherein the computing unit is set up to calculate the manipulated values from the determined target acceleration of the vehicle. The invention further relates to a method for controlling the speed of a vehicle with a device according to the invention.
    Fig. 1
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    Device and method for predictive control of the speed of a vehicle
    The invention relates to a device and a method for predictive control of the speed of a vehicle according to the preambles of the independent claims.
    Known driver assistance systems are known, for example, under the name Adaptive Cruise Control and include at least one environmental sensor for recording the current traffic situation in the surroundings of the vehicle, a brake actuator for actuating a braking device of the vehicle, an acceleration actuator for actuating an acceleration device of the vehicle, and a computing unit for this is configured to calculate manipulated values for controlling the brake actuator and the acceleration actuator of the vehicle.
    These systems aim to control the speed of the vehicle in such a way that a desired size, usually the difference between the longitudinal speed and a reference speed, which is usually preset by the driver, is minimized without a minimum distance or a minimum braking time from the vehicle in front, the so-called Vehicle in front, below. If there is no vehicle in front of the vehicle to be controlled, the reference speed preset by the driver is generally maintained.
    The present invention relates to such a driver assistance system for multi-lane roads, where frequent lane change maneuvers of the surrounding traffic occur. In this situation, existing approaches show numerous disadvantages, in particular the frequent changes to the vehicle in front result in frequent braking and acceleration maneuvers, which can impair driving comfort, increase stress for the driver and also have negative effects on the fuel consumption of the vehicle to be controlled. Even in the event of an overtaking maneuver, the vehicle in front changes and can lead to the same or different disadvantages.
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    These and other disadvantages are solved by an apparatus and a method according to the independent claims.
    According to the invention, it is provided that the at least one environmental sensor is set up to detect the movement data of road users in the surroundings of the vehicle, and the computing unit comprises a predictor for calculating a risk function within a predetermined time horizon, the risk function being based at least on the movement data of the driver's own vehicle and the detected road users, and wherein the computing unit comprises an optimizer for the target acceleration of the vehicle by querying the predictor, which minimizes the risk function within the time horizon or keeps it below a predetermined threshold value, and wherein the computing unit calculates the manipulated values for controlling the brake actuator and the Acceleration actuator is set up from the determined target acceleration of the vehicle.
    The optimizer calculates the ideal course of the manipulated variables, for example with the aim of minimizing the speed difference from the reference speed. This optimization is not necessarily free, but if necessary taking into account boundary conditions. These include, for example, common conditions such as the maximum possible acceleration or the possible curve radius.
    If necessary, this also includes boundary conditions that arise due to the predictor. The predictor predicts trajectories, i.e. possible movements, of the surrounding road users. If necessary, the optimizer can calculate all possible trajectories of the controlled vehicle with knowledge of these trajectories. This can take into account vehicles in the same lane or in a different lane. When changing lanes, the associated risk of a collision can be estimated within a predetermined time horizon. The calculation is carried out not only in relation to the vehicle in front, but also taking into account several, possibly all, vehicles within the range of the sensors. It is selected by the optimizer
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    According to the invention, it can be provided that the functionalities of the predictor and the optimizer are implemented in a single module, in particular in a single algorithm.
    The road users can in particular be vehicles. As a result of the switch according to the invention to compliance with a risk threshold value or to the limitation of a risk function instead of maintaining a constant braking time or a minimum distance from the vehicle in front, the actual risk of a traffic situation is depicted and abrupt changes in acceleration are avoided. In addition, the risk perception of a person is represented by the invention, so that the results are more similar to human driving behavior.
    According to the invention, it can be provided that the device is also set up to control the lateral position of the vehicle, a steering angle actuator being provided for setting the steering angle and the arithmetic unit being designed to calculate manipulated values for controlling this steering angle actuator, the optimizer also being used to determine the target Steering angle of the vehicle is set up while minimizing the risk function, and the computing unit is set up for calculating the manipulated values from the target steering angle.
    In this context, the lateral position of the vehicle denotes the position of the vehicle at right angles to the direction of travel, both on different lanes and within a lane.
    According to the invention, it can be provided that the detected movement data is at least the position, speed, acceleration and direction of the road users. This can be, in particular, movement data from vehicles that are moving on adjacent lanes of a multi-lane roadway.
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    According to the invention, it can be provided that the environmental sensor comprises at least one radar sensor, at least one camera, and / or at least one lidar sensor for distance and speed measurement. These sensors can be arranged in the front area, in the rear area or in the side areas of the vehicle.
    According to the invention, it can be provided that the environment sensor is designed to detect the type of traffic participants detected, and the computing unit is configured to take the type of traffic users detected into account when calculating the risk function.
    According to the invention, it can be provided that the predictor is designed to calculate the possible trajectories of the neighboring road users on the basis of the data measured by the environmental sensor and a stochastic model. The predictor can also be designed to take information about the traffic infrastructure, for example traffic lights, into account.
    Various factors can be used as influencing factors or criteria of the risk function generated by the predictor, for example the expected braking time, the expected braking distance, or the presence of sufficient space (e.g. lateral offset or free additional lanes) in order to be able to drive past the other vehicle safely.
    The predictor can also use the knowledge or prediction about the intention of other vehicles, which has been obtained, for example, via digital or visual communication, as a criterion for generating the risk function.
    The estimated time in which the vehicle is exposed to an increased risk can also be used when generating the risk function.
    Finally, the predictor can also evaluate the complexity of the
    Carry out traffic situation over the prediction horizon. This includes, for example, determining the risk on the basis of the number and / or density of other road users, which can represent a possible restriction within the prediction horizon for the ego vehicle.
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    It can thus be provided according to the invention that the predictor is designed to generate the risk function on the basis of predetermined criteria, for example on the basis of a function of the minimum time until a collision with a road user (time-to-collision). In particular, the risk function can be formed as the inverse of the time-to-collision.
    Of course, the predictor can also combine some or all of the criteria mentioned for generating the risk function.
    For this purpose, the predictor can take into account a large number of possible changes in the speed and acceleration of the vehicle and of the neighboring road users, and in each case calculate the expected time-to-collision and / or other values. The values of the time-to-collision or other calculated criteria are subjected to a function, for example inverted, and form the respective risk value associated with the movement data under consideration.
    The optimizer according to the invention takes into account various possible ones
    Changes in the speed of the vehicle in order to keep the risk value below a predetermined threshold or to minimize it within the period under consideration.
    According to the invention, it can be provided that the predictor is designed to use current traffic data, in particular by querying a traffic information service, to generate the risk function.
    According to the invention, it can be provided that the predictor is designed to use the current weather situation, in particular by querying a temperature and humidity sensor and / or an internet-based weather service, to generate the risk function.
    According to the invention, it can be provided that the time horizon of the predictor is 0.5 seconds to 30 seconds, for example approximately one second to three seconds.
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    According to the invention, it can be provided that the predictor is designed to take stochastic disturbances into account when generating the risk function, in particular for modeling sudden lane changes of adjacent road users, within the time horizon.
    For this purpose, it can be provided that the predictor models a dynamic system in which disturbance terms are provided which simulate the random change of lane or the random occurrence of another obstacle. The stochastic distribution of these random terms can follow a Gaussian distribution, the mean value and standard deviation of which are adapted to the real application.
    Thus, in particular in the case of high traffic volumes or in known local areas, it can be provided that the interference terms occur more frequently than in the case of low traffic volumes or in other local areas.
    According to the invention, it can be provided that the optimizer is designed to adapt the threshold value of the risk function to the vehicle or the driver of the vehicle, in particular by means of an adaptive algorithm.
    In the method according to the invention for controlling the speed of a vehicle, the current traffic situation in the surroundings of the vehicle is detected by at least one environment sensor and control values for controlling a brake actuator for actuating a brake device of the vehicle and an acceleration actuator for actuating an acceleration device of the vehicle are calculated by a computing unit.
    The method according to the invention is characterized in that the
    Environment sensor detects the movement data of road users in the area surrounding the vehicle, and a predictor calculates a risk function within a predetermined time horizon, the risk function being based on at least
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    Based on the movement data of the own vehicle and the detected road users is calculated, and an optimizer optimizes the target acceleration of the vehicle by querying the predictor, the optimizer minimizing the risk function within the time horizon or keeping it below a predetermined threshold value, and wherein the computing unit evaluates the manipulated values the determined target acceleration of the vehicle is calculated.
    According to the invention, it can be provided that the method also controls the lateral position of the vehicle, a control value for controlling a steering angle actuator being calculated by the computing unit, the optimizer also optimizing the target steering angle of the vehicle by querying the predictor, the optimizer optimizing the Risk function minimized within the time horizon or kept below a predetermined threshold, and wherein the computing unit calculates the manipulated value for controlling the steering angle actuator from the determined target steering angle of the vehicle.
    According to the invention, it can be provided that the environment sensor detects the type of road users and the computing unit takes into account the type of road users detected when calculating the risk function.
    According to the invention, it can be provided that the predictor generates the risk function on the basis of predetermined criteria, for example on the basis of a function of the minimum time until a collision with a road user (time-to-collision). In particular, the predictor can form the risk function as an inverse of the time-to-collision.
    Of course, other criteria can also be used to generate the risk function, for example the criteria mentioned above.
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    According to the invention, it can be provided that the predictor uses current traffic data, in particular by querying a traffic information service, to generate the risk function.
    According to the invention, the predictor can be the current one
    Weather situation, especially by querying a temperature and
    Moisture sensor and / or an internet-based weather service, to generate the risk function.
    According to the invention, it can be provided that the time horizon of the predictor is 0.5 seconds to 30 seconds, for example approximately one second to three seconds.
    According to the invention, it can be provided that the predictor takes stochastic disturbances into account within the time horizon when generating the risk function, in particular for modeling sudden changes of lane of neighboring road users.
    According to the invention, it can be provided that the optimizer adapts the threshold value of the risk function to the vehicle or the driver of the vehicle, in particular by means of an adaptive algorithm.
    Further features according to the invention result from the description of the exemplary embodiment, the drawings and the patent claims.
    The invention is explained in more detail below using an exemplary embodiment.
    Fig. 1 shows an embodiment of the device according to the invention. This includes an environmental sensor that is connected to a computing unit.
    The environment sensor includes numerous individual sensors that are set up to record the traffic situation in the area surrounding the vehicle, for example radar sensors and cameras in the front and rear areas of the vehicle. In addition, temperature and humidity sensors and interfaces to internet or radio-based weather and traffic services can be provided.
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    The arithmetic unit includes a predictor, which is based on the
    Environment sensor supplied data can make a prediction of the time-to-collision, that is the time span until the vehicle will collide with one of the detected road users while maintaining the same course, speed and acceleration. In addition to or instead of predicting the time-to-collision, the predictor can also calculate other criteria. The predictor's prediction model is limited to a specific prediction period, for example one second.
    On the basis of the movement data of the road users detected by the environment sensor, an optimization problem is set up and solved by an optimizer. The limitation or minimization of the risk function, which is defined as the inverse of the time-to-collision calculated by the predictor, aims to make collisions with the detected road users as unlikely as possible. As mentioned, the risk function can also include other criteria instead of the inverse of the time-to-collision.
    The speed of the vehicle is used as the variable of the optimizer
    The vehicle's longitudinal direction and lateral acceleration are used so that the optimizer provides those control values for the vehicle where the risk function remains below a threshold value or is minimal. Instead of minimizing the risk function, it can also be provided that the optimization process is terminated as soon as the risk function is reduced below a predetermined threshold value.
    On the basis of the speed determined by the optimizer as a result of the optimization process, the computing unit calculates control values for controlling a brake actuator and an acceleration actuator of the vehicle in order to achieve the calculated target values of the speed of the vehicle.
    2a shows a typical application of a device and a method according to the invention using the example of a typical traffic situation.
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    The ego vehicle A, the speed of which is to be optimized, is located in the middle lane of a multi-lane highway and travels at a defined distance from a vehicle in front B (phase I). From the right lane, a third vehicle C turns into the middle lane at a higher speed (phase II). The third vehicle C leaves the middle lane and turns into the left lane (phase III). Finally, the third vehicle C is in the left lane and the starting situation is restored (phase IV).
    Fig. 2b shows the time course of the distance to the vehicle in front (upper timeline) and the acceleration of the ego vehicle (lower timeline) in the case of a conventional distance control, which aims to maintain a sufficient braking time to the vehicle in front. In phase I, the distance to vehicle B remains essentially constant and the acceleration approximately zero. Even in phase II, when the vehicle C is already turning into the lane of the vehicle A, nothing changes since the vehicle C is not yet in the lane of the vehicle A. Only in phase III is the vehicle C defined as the new vehicle in front and the vehicle A has to brake suddenly to ensure a constant braking time to the new vehicle in front. In phase IV, when the vehicle C leaves the lane again, the vehicle B is again defined as the vehicle in front, and the vehicle A is again accelerated positively in order to achieve the predefined braking time. So there are two abrupt changes in acceleration in a traffic situation that occurs very frequently in practice.
    2c shows the same situation using an embodiment of a device according to the invention and a method according to the invention, the risk function calculated by the predictor being shown in the uppermost timeline.
    In this case, due to the consideration of stochastic disturbances, it is already taken into account in phase I that the movement data of vehicle C make a collision in the middle lane possible, so that the distance to vehicle B is already slightly increased in this phase without a noticeable change in acceleration to be carried out (so-called predictive fall-back).
    In phase II, vehicle C enters the middle lane and the risk function increases. This causes the vehicle A to brake slightly so that the distance
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    In phase III, vehicle C completely enters the middle lane and is defined as a new vehicle in front, so that the distance to the vehicle in front suddenly decreases. However, there is no sudden change in the acceleration, since the risk of a collision is low due to the high detected speed of the vehicle C. In contrast to the example from FIG. 2a, the method according to the invention aims at reducing the risk function and not at constant braking time to the vehicle in front.
    In the course of phase III, in which vehicle C is in the middle lane, the risk function remains above the original value, but is continuously reduced despite almost constant acceleration and a short distance from the vehicle in front, as another is due to the detected movement data of vehicle C. Lane change of vehicle C is anticipated.
    In phase IV, vehicle C leaves the middle lane, so that the original situation is restored and the distance to the vehicle in front, i.e. vehicle B, suddenly increases again. Again, there is no abrupt change in acceleration.
    The device according to the invention and the method according to the invention thus allow a predictive treatment of typical traffic situations, abrupt changes in acceleration being avoided, so that fuel consumption is also reduced.
    In addition, by taking into account one or more vehicle-specific or general fuel consumption characteristic curve fields, the target acceleration and vehicle deceleration can be selected in such a way that the lowest possible fuel consumption occurs within the prediction horizon.
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    权利要求:
    Claims (24)
    [1]
    claims
    1. A device for predictive control of the speed of a vehicle, comprising
    a. at least one environmental sensor for recording the current traffic situation in the area surrounding the vehicle,
    b. a brake actuator for actuating a brake device of the vehicle,
    c. an acceleration actuator for actuating an acceleration device of the vehicle,
    d. a computing unit which is designed to calculate control values for controlling the brake actuator and the acceleration actuator, characterized in that
    e. the environment sensor is set up to detect the movement data of road users in the vicinity of the vehicle, and
    f. the computing unit comprises a predictor for calculating a risk function within a predetermined time horizon, the risk function being calculated at least on the basis of the movement data of the driver's own vehicle and the detected road users, and wherein
    G. the computing unit includes an optimizer for the target acceleration of the vehicle by querying the predictor, which minimizes the risk function within the time horizon or keeps it below a predetermined threshold value, and wherein the computing unit is set up to calculate the manipulated values from the determined target acceleration of the vehicle.
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    [2]
    2. Device according to claim 1, characterized in that the device is also set up to control the lateral position of the vehicle, a steering angle actuator being provided for setting the steering angle and the computing unit being designed to calculate manipulated values for controlling this steering angle actuator, the optimizer also is set up for determining the target steering angle of the vehicle while minimizing the risk function, and wherein the computing unit is set up for calculating the manipulated values from the target steering angle.
    [3]
    3. Device according to claim 1 or 2, characterized in that it is at least the position, speed, acceleration and direction of the road users, in particular the vehicles, in the detected movement data.
    [4]
    4. Device according to one of claims 1 to 3, characterized in that the environmental sensor at least one radar sensor, at least one camera, and / or at least one lidar sensor for distance and
    Includes speed measurement.
    [5]
    5. Device according to one of claims 1 to 4, characterized in that the environment sensor is designed to detect the type of the detected road users, and the computing unit is designed to take into account the type of the road users detected when calculating the risk function.
    [6]
    6. Device according to one of claims 1 to 5, characterized in that the predictor is configured to the risk function on the basis of predetermined criteria, for example on the basis of a function of the minimum time to a collision with a road user (time-to-collision) to generate.
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    [7]
    7. Device according to one of claims 1 to 6, characterized in that the predictor is designed to use current traffic data, in particular by querying a traffic information service, for calculating the risk function.
    [8]
    8. Device according to one of claims 1 to 7, characterized in that the predictor is designed to use the current weather situation, in particular by querying a temperature and humidity sensor and / or an internet-based weather service, to calculate the risk function.
    [9]
    9. Device according to one of claims 1 to 8, characterized in that the time horizon of the predictor is 0.5 seconds to 30 seconds, for example about one second to three seconds.
    [10]
    10. The device according to one of claims 1 to 9, characterized in that the predictor is designed to take into account stochastic disturbances in the calculation of the risk function, in particular for modeling suddenly occurring obstacles or sudden change of lane of adjacent road users, within the time horizon.
    [11]
    11. The device according to one of claims 1 to 10, characterized in that the optimizer is designed to adapt the threshold value of the risk function to the vehicle or the driver of the vehicle, in particular by means of an adaptive algorithm.
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    [12]
    12. A method for predictive control of the speed of a vehicle, wherein the current traffic situation in the surroundings of the vehicle is detected by at least one environmental sensor and control values for controlling a brake actuator for actuating a braking device of the vehicle and an acceleration actuator for actuating an acceleration device of the vehicle are calculated by a computing unit are characterized in that
    a. the environment sensor detects the movement data of road users in the vicinity of the vehicle, and
    b. a predictor calculates a risk function within a predetermined time horizon, the risk function being calculated at least on the basis of the movement data of the driver's own vehicle and the detected road users, and wherein
    c. an optimizer optimizes the target acceleration of the vehicle by querying the predictor, the optimizer minimizing the risk function within the time horizon or keeping it below a predetermined threshold value, and wherein the computing unit calculates the manipulated values from the determined target acceleration of the vehicle.
    [13]
    13. The method according to claim 12, characterized in that the method also controls the lateral position of the vehicle, a control value for controlling a steering angle actuator being calculated by the computing unit, the optimizer also optimizing the target steering angle of the vehicle by querying the predictor , wherein the optimizer minimizes the risk function within the time horizon or keeps it below a predetermined threshold value, and wherein the computing unit calculates the manipulated value for controlling the steering angle actuator from the determined target steering angle of the vehicle.
    [14]
    14. The method according to claim 12 or 13, characterized in that the environment sensor detects the type of road users, and the computing unit takes into account the type of road users detected when calculating the risk function.
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    [15]
    15. The method according to any one of claims 12 to 14, characterized in that the predictor generates the risk function on the basis of predetermined criteria, for example a function of the minimum time until a collision with a road user (time-to-collision).
    [16]
    16. The method according to any one of claims 12 to 15, characterized in that the predictor uses current traffic data, in particular by querying a traffic information service, to generate the risk function.
    [17]
    17. The method according to any one of claims 12 to 16, characterized in that the predictor uses the current weather situation, in particular by querying a temperature and humidity sensor and / or an internet-based weather service, to generate the risk function.
    [18]
    18. The method according to any one of claims 12 to 17, characterized in that the time horizon of the predictor is 0.5 seconds to 30 seconds, for example about one second to three seconds.
    [19]
    19. The method according to any one of claims 12 to 18, characterized in that the predictor takes into account stochastic disturbances in the generation of the risk function, in particular for modeling suddenly occurring obstacles or sudden lane changes of neighboring road users, within the time horizon.
    [20]
    20. The method according to any one of claims 12 to 19, characterized in that the optimizer adapts the threshold value of the risk function to the vehicle or the driver of the vehicle, in particular by means of an adaptive algorithm.
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    Distance to the front
    vehicle
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    claims
    1. A device for predictive control of the speed of a vehicle, comprising
    a. at least one environmental sensor for recording the current traffic situation in the area surrounding the vehicle,
    b. a brake actuator for actuating a brake device of the vehicle,
    c. an acceleration actuator for actuating an acceleration device of the vehicle,
    d. a computing unit which is designed to calculate manipulated values for controlling the brake actuator and the acceleration actuator, wherein
    e. the environment sensor is set up to detect the movement data of road users in the surroundings of the vehicle, characterized in that
    f. the computing unit comprises a predictor for calculating a risk function within a predetermined time horizon, the risk function being calculated at least on the basis of the movement data of the driver's own vehicle and the detected road users, and wherein
    G. the computing unit includes an optimizer for the target acceleration of the vehicle by querying the predictor, which minimizes the risk function within the time horizon or keeps it below a predetermined threshold value, and wherein the computing unit is set up to calculate the manipulated values from the determined target acceleration of the vehicle.
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    2. Device according to claim 1, characterized in that the device is also set up to control the lateral position of the vehicle, a steering angle actuator being provided for setting the steering angle and the computing unit being designed to calculate manipulated values for controlling this steering angle actuator, the optimizer also is set up for determining the target steering angle of the vehicle while minimizing the risk function, and wherein the computing unit is set up for calculating the manipulated values from the target steering angle.
    3. Device according to claim 1 or 2, characterized in that it is at least the position, speed, acceleration and direction of the road users, in particular the vehicles, in the detected movement data.
    4. Device according to one of claims 1 to 3, characterized in that the environmental sensor comprises at least one radar sensor, at least one camera, and / or at least one lidar sensor for distance and speed measurement.
    5. Device according to one of claims 1 to 4, characterized in that the environment sensor is designed to detect the type of the detected road users, and the computing unit is designed to take into account the type of the road users detected when calculating the risk function.
    6. Device according to one of claims 1 to 5, characterized in that the predictor is configured to the risk function on the basis of predetermined criteria, for example on the basis of a function of the minimum time to a collision with a road user (time-to-collision) to generate.
    [21]
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    7. Device according to one of claims 1 to 6, characterized in that the predictor is designed to use current traffic data, in particular by querying a traffic information service, for calculating the risk function.
    8. Device according to one of claims 1 to 7, characterized in that the predictor is designed to use the current weather situation, in particular by querying a temperature and humidity sensor and / or an internet-based weather service, to calculate the risk function.
    9. Device according to one of claims 1 to 8, characterized in that the time horizon of the predictor is 0.5 seconds to 30 seconds, for example about one second to three seconds.
    10. The device according to one of claims 1 to 9, characterized in that the predictor is designed to take into account stochastic disturbances in the calculation of the risk function, in particular for modeling suddenly occurring obstacles or sudden change of lane of adjacent road users, within the time horizon.
    11. The device according to one of claims 1 to 10, characterized in that the optimizer is designed to adapt the threshold value of the risk function to the vehicle or the driver of the vehicle, in particular by means of an adaptive algorithm.
    [22]
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    12. A method for predictive control of the speed of a vehicle, wherein the current traffic situation in the surroundings of the vehicle is detected by at least one environmental sensor and control values for controlling a brake actuator for actuating a braking device of the vehicle and an acceleration actuator for actuating an acceleration device of the vehicle are calculated by a computing unit are characterized in that
    a. the environment sensor detects the movement data of road users in the vicinity of the vehicle, and
    b. a predictor calculates a risk function within a predetermined time horizon, the risk function being calculated at least on the basis of the movement data of the driver's own vehicle and the detected road users, and wherein
    c. an optimizer optimizes the target acceleration of the vehicle by querying the predictor, the optimizer minimizing the risk function within the time horizon or keeping it below a predetermined threshold value, and wherein the computing unit calculates the manipulated values from the determined target acceleration of the vehicle.
    13. The method according to claim 12, characterized in that the lateral position of the vehicle is also controlled by the method, a control value for controlling a steering angle actuator being calculated by the computing unit, the optimizer also optimizing the target steering angle of the vehicle by querying the predictor, wherein the optimizer minimizes the risk function within the time horizon or keeps it below a predetermined threshold value, and the computing unit calculates the manipulated value for controlling the steering angle actuator from the determined target steering angle of the vehicle.
    14. The method according to claim 12 or 13, characterized in that the environment sensor detects the type of road users, and the computing unit takes into account the type of road users detected when calculating the risk function.
    [23]
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    15. The method according to any one of claims 12 to 14, characterized in that the predictor generates the risk function on the basis of predetermined criteria, for example a function of the minimum time until a collision with a road user (time-to-collision).
    16. The method according to any one of claims 12 to 15, characterized in that the predictor uses current traffic data, in particular by querying a traffic information service, to generate the risk function.
    17. The method according to any one of claims 12 to 16, characterized in that the predictor uses the current weather situation, in particular by querying a temperature and humidity sensor and / or an internet-based weather service, to generate the risk function.
    18. The method according to any one of claims 12 to 17, characterized in that the time horizon of the predictor is 0.5 seconds to 30 seconds, for example about one second to three seconds.
    19. The method according to any one of claims 12 to 18, characterized in that the predictor takes into account stochastic disturbances in the generation of the risk function, in particular for modeling suddenly occurring obstacles or sudden lane changes of neighboring road users, within the time horizon.
    20. The method according to any one of claims 12 to 19, characterized in that the optimizer adapts the threshold value of the risk function to the vehicle or the driver of the vehicle, in particular by means of an adaptive algorithm.
    [24]
    24/24 [LAST CLAIMS
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    AT519547B1|2018-08-15|
    DE102018210065A1|2018-12-27|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    DE102004051909A1|2004-09-30|2006-04-06|Robert Bosch Gmbh|Method and device for influencing the longitudinal speed of a motor vehicle|
    EP2052925B1|2007-10-26|2017-08-30|Hyster-Yale Group, Inc.|Predictive vehicle controller|
    DE112009004844T5|2009-06-02|2012-07-19|Toyota Jidosha Kabushiki Kaisha|VEHICLE MONITORING DEVICE ENVIRONMENT|
    EP3916697A1|2020-05-25|2021-12-01|Robert Bosch GmbH|Method and device for predicting the trajectory of a traffic participant, and sensor system|
    法律状态:
    优先权:
    申请号 | 申请日 | 专利标题
    ATA50517/2017A|AT519547B1|2017-06-22|2017-06-22|Device and method for the predictive control of the speed of a vehicle|ATA50517/2017A| AT519547B1|2017-06-22|2017-06-22|Device and method for the predictive control of the speed of a vehicle|
    DE102018210065.9A| DE102018210065A1|2017-06-22|2018-06-21|Device and method for the predictive control of the speed of a vehicle|
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