WO2019011536A1 - Procédé, dispositif, programme informatique et support d'enregistrement lisible par machine pour faire fonctionner un véhicule - Google Patents

Procédé, dispositif, programme informatique et support d'enregistrement lisible par machine pour faire fonctionner un véhicule Download PDF

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Publication number
WO2019011536A1
WO2019011536A1 PCT/EP2018/064859 EP2018064859W WO2019011536A1 WO 2019011536 A1 WO2019011536 A1 WO 2019011536A1 EP 2018064859 W EP2018064859 W EP 2018064859W WO 2019011536 A1 WO2019011536 A1 WO 2019011536A1
Authority
WO
WIPO (PCT)
Prior art keywords
collision
vehicle
trajectory
probability
collision object
Prior art date
Application number
PCT/EP2018/064859
Other languages
German (de)
English (en)
Inventor
Thomas Lich
Thomas GUSSNER
Thomas Schlender
Original Assignee
Robert Bosch Gmbh
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Robert Bosch Gmbh filed Critical Robert Bosch Gmbh
Publication of WO2019011536A1 publication Critical patent/WO2019011536A1/fr

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Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B60W30/09—Taking automatic action to avoid collision, e.g. braking and steering
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0062—Adapting control system settings
    • B60W2050/0075—Automatic parameter input, automatic initialising or calibrating means
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
    • B60W2556/10—Historical data

Definitions

  • VRU Vulnerable Road Users
  • Collision object neglected because there are dependencies between future and historical movement behavior that can assist in a decision-making (Dodge or brakes). Thus, it can occur when initiating full braking or avoidance operations due to - possibly
  • the present invention provides and provides a method, apparatus, computer program, and machine-readable
  • Storage medium for operating a vehicle for operating a vehicle.
  • the present invention provides a method of operating a vehicle, comprising the steps of:
  • a collision object is understood to mean an object detected by the sensor system of the vehicle with which a collision is likely to take place if neither the movement of the vehicle nor, if possible, the movement of the object change. It is advantageous if, from the set of recognized objects only those for the method of the present invention are pursued, which approach the vehicle in critical.
  • a critical approximation can be understood as an approximation in which the approximation parameters, such as type of object, direction, distance, speed, etc., are mapped to a criticality value and this
  • Criticality value exceeds a predetermined threshold for a critical approach.
  • collision object can also be an increased risk
  • a prediction model for the collision object is a
  • Understood calculation rule which derives based on measurements of, for example, sensors of the vehicle a probability of residence of the collision object.
  • an avoidance trajectory is understood as a movement path for the vehicle which is suitable for avoiding a collision with the collision object with high probability.
  • a collision trajectory is understood to mean a movement path for the vehicle which is suitable in the event that a collision with the vehicle
  • Collision object based on the underlying model is inevitable, too a collision whose consequences are minimal, based on the underlying model.
  • the result of the collision can be mitigated by appropriately influencing the movement of the vehicle.
  • the collision object is a vehicle
  • this vehicle could be made such that optimal absorption of the collision energy is enabled.
  • the consequences for the occupants of the vehicles involved can be minimized.
  • Such movement paths can be converted into sequences for the means for longitudinal or lateral acceleration of the vehicle.
  • both the positive acceleration i. the actual increase in the speed of the
  • transverse acceleration is understood to mean the movement of the vehicle transversely to the longitudinal orientation of the vehicle.
  • the lateral acceleration may also be due to steering or braking
  • the motion history of the collision object is taken into account in the prediction model.
  • An evasion trajectory is considered to be more optimal in accordance with the present invention if it is capable of minimizing the probability of collision with the collision object while minimizing the effect on the movement of the vehicle.
  • a collision trajectory is considered to be more optimal in accordance with the present invention if it is capable of minimizing the collision sequences.
  • the predicted model considers the predicted impact point of the collision object on the vehicle.
  • the consideration of the predicted impact point leads to an improved determination of the probability of the collision object, since it has been shown that depending on the predicted impact point, the future behavior of the collision object, especially if the collision object is a pedestrian, is significantly influenced.
  • certain movement states of the pedestrian or, more generally, of the collision object may possibly be disregarded, this reduces the calculation resources for the avoidance trajectory and leads overall to a more accurate determination of the avoidance trajectory.
  • the collision area of the vehicle in which the predicted impact point of the vehicle in which the predicted impact point of the vehicle
  • Collision object on the vehicle is considered.
  • the predicated one may be any predicated one.
  • Impact point be assigned to a collision area (Near Side, Center Area, Far Side) of the vehicle. This reduces the computation resources because the predicated behavior of the collision object is uniform within a collision area.
  • Multi-objective optimization determined. It is beneficial as goals of minimizing the
  • This embodiment has the advantage that methods for multi-objective optimization can be carried out efficiently.
  • Multi-objective optimization also has at least one of the following constraints:
  • the avoidance trajectory or the collision trajectory is represented as an nth-order polynomial, in particular of the 5th order.
  • An nth-order polynomial can be solved iteratively quickly by known efficient methods.
  • the collision probability is determined as a function of a passing point.
  • the passing point is understood to be the point at which the vehicle moves during the evasive maneuver or the collision at the height of the vehicle
  • Pedestrian is located.
  • the prediction model is updatable.
  • This embodiment of the method offers the advantage that the prediction model can be adapted in advance. For example. then, if more recent findings are available or if more up-to-date data is available. The updating of the prediction model can take place, for example, during a service visit to a workshop. Also conceivable is an implementation of the updatability by a so-called. Flash Over the Air method. It will be over
  • Radio transmission technologies corresponding updates performed on the vehicle or vehicles.
  • Another aspect of the present invention is an apparatus adapted to carry out an embodiment of the method of the present invention.
  • a device may be a controller or a
  • Control unit network of the vehicle act.
  • various aspects of the method are performed by different controllers.
  • the controllers exchange data with each other.
  • the data exchange takes place via one of the communication networks in the vehicle, for example via the CAN or FlexRay bus.
  • Another aspect of the present invention is a computer program configured to carry out an embodiment of the method of the present invention.
  • Another aspect of the present invention is a machine-readable one
  • Storage medium on which the computer program according to the present invention is stored.
  • Show it 1 is an illustration of a prediction model according to the present invention.
  • FIG. 2 shows an example of a prediction model according to the present invention
  • FIG. 3 shows another example of a prediction model according to the present invention
  • FIG. 4 is a flowchart of a method according to the present invention.
  • Evidence trajectory based on the described model can be performed.
  • the future position of a pedestrian is determined by probability distributions Pi (x, y) for several equidistant times t, up to a maximum
  • Prediction horizon t n shown. These distributions are a weighted sum of normal distributions with standard deviations Ok and mean values k
  • V ⁇ x. y) ELiW fc , / v (x, y, a fc ⁇ fc ).
  • the three components Wi, W2, Wa of the distribution represent three possible and exemplary states of movement of the pedestrian:
  • the standard deviations ⁇ result from the prediction uncertainty for the respective state of motion resulting from the uncertainty of the
  • Position measurement and velocity measurement propagated over the prediction period result. Distributions are also assumed for the states in which the pedestrian accelerates or stops.
  • Possible distributions may be, for example, Tiemann, N. et al: "Predictive Pedestrian
  • Fig. 1 shows the illustration of a prediction model according to the present invention.
  • the illustrated prediction model is based on the three previously introduced
  • Each dimension Wi, W2, W3 is assigned a weight which reflects the probability with which the collision object will be in the respective movement state or will change into it.
  • the parameters can be collected based on accident data from near misses or real accidents.
  • the choice of weights Wk which in turn has a significant impact on the outcome of
  • the weights Wk are not fixed, but chosen depending on the situation.
  • the weights are chosen depending on the predicted impact point y C0 n.
  • the front area of the vehicle can, for example, be divided into three areas. Center Area, ie the central area of the vehicle front, as well as the Near Side and the Far Side. The near side is the side area of the
  • Vehicle front which is closer to the pedestrian. That is, when the pedestrian approaches the vehicle from the right, the area to the right of the center area.
  • the far side is corresponding to the side area of the vehicle front, which is located farther away from the pedestrian.
  • Velocity of the EGO Vehicle The determination of the avoidance trajectories or collision trajectory is carried out according to an embodiment of the present invention by means of a multi-objective optimization. Typical optimization goals are included
  • constraints In addition to the optimization of the above goals, constraints must be met.
  • a typical selection constraints are:
  • a collision risk is understood to mean a value to which
  • a limit can be predetermined which, when using the
  • Avoidance trajectory on the vehicle may not be exceeded.
  • the risk of collision with the pedestrian to be evaded can be determined according to the present invention depending on the passing point (XPP, VPP).
  • the travel corridor can be determined in such a way that it is guaranteed that no (other) collision with static and dynamic obstacles, e.g. Oncoming traffic, takes place,
  • the predetermined limit for the lateral acceleration can be physically motivated.
  • the limit values for stable guidance of the vehicle must be taken into account, e.g. Stiction, loads.
  • the predetermined limit for the transverse offset may, for example, be based on the typical or current track width.
  • n-order polynomial has proved to be an efficient way to determine the avoidance trajectory.
  • a polynomial of the 5th order has proved to be an efficient way to determine the avoidance trajectory.
  • FIGS. 2 and 3 show by way of example two different situations
  • an evasion trajectory 20 ' is selected as the evasion trajectory 20', which provides a lateral offset to the right for the vehicle.
  • the corresponding probabilities can be based on empirical data and, accordingly, applied as parameters and updated as needed or in the presence of new findings or more recent data.
  • the table in Fig. 4 shows a flow chart of a method according to the present invention.
  • step 401 a collision object 2, in particular an increased risk
  • VRU Road users (VRU), such as a pedestrian, on the sensors of the
  • Vehicle 1 or the like recognized. After the detection of a collision object 2, it is necessary to determine an optimal counteraction which, if possible, should be used to prevent the collision while minimizing the risk of further traffic, including the driver and the occupants of the vehicle 1. For this purpose, first in step 402 a probability of residence of
  • Collision object 2 determines. If the determination of the probability of residence is based on the prediction model according to the present invention, a particularly accurate determination of the probability of residence takes place
  • step 403 based on the determined probability of residence of the collision object, an optimal avoidance trajectory 20, 20 'can be determined or determined.
  • the corresponding longitudinal and lateral acceleration means of the vehicle 1 are controlled in step 404 such that the vehicle 1 substantially follows the evasion trajectory.

Abstract

L'invention concerne un procédé (400) pour faire fonctionner un véhicule (1), comprenant les étapes consistant : à détecter (401) un objet de collision (2), en particulier un usager de la route exposé à un danger élevé, en particulier un piéton ; à déterminer (402) une probabilité de présence de cet objet de collision (2), en particulier en fonction d'un modèle de prédiction pour cet objet de collision (2) ; à déterminer (403) une trajectoire de déviation (20, 20') pour éviter une collision avec l'objet de collision (2) ou une trajectoire de collision en fonction de la probabilité de présence déterminée ; à commander (404) le véhicule (1) de manière que ce véhicule (1) soit guidé au moins en partie de manière automatique le long de la trajectoire de déviation (20, 20') ou de la trajectoire de collision déterminée.
PCT/EP2018/064859 2017-07-11 2018-06-06 Procédé, dispositif, programme informatique et support d'enregistrement lisible par machine pour faire fonctionner un véhicule WO2019011536A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102017211815.6A DE102017211815A1 (de) 2017-07-11 2017-07-11 Verfahren, Vorrichtung, Computerprogramm und ein maschinenlesbares Speichermedium zum Betreiben eines Fahrzeugs
DE102017211815.6 2017-07-11

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WO (1) WO2019011536A1 (fr)

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CN110826275A (zh) * 2019-10-31 2020-02-21 清华大学 车辆前舱罩盖设计参数的优化方法
CN113895460A (zh) * 2021-11-11 2022-01-07 中国第一汽车股份有限公司 行人轨迹预测方法、装置及存储介质
CN116223056A (zh) * 2022-12-14 2023-06-06 清华大学 虚拟碰撞测试方法、装置、设备、存储介质和程序产品

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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110826275A (zh) * 2019-10-31 2020-02-21 清华大学 车辆前舱罩盖设计参数的优化方法
CN113895460A (zh) * 2021-11-11 2022-01-07 中国第一汽车股份有限公司 行人轨迹预测方法、装置及存储介质
CN113895460B (zh) * 2021-11-11 2023-01-13 中国第一汽车股份有限公司 行人轨迹预测方法、装置及存储介质
CN116223056A (zh) * 2022-12-14 2023-06-06 清华大学 虚拟碰撞测试方法、装置、设备、存储介质和程序产品
CN116223056B (zh) * 2022-12-14 2024-03-12 清华大学 虚拟碰撞测试方法、装置、设备、存储介质和程序产品

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