EP3833587A1 - Procédé de conception d'un véhicule - Google Patents

Procédé de conception d'un véhicule

Info

Publication number
EP3833587A1
EP3833587A1 EP19734280.1A EP19734280A EP3833587A1 EP 3833587 A1 EP3833587 A1 EP 3833587A1 EP 19734280 A EP19734280 A EP 19734280A EP 3833587 A1 EP3833587 A1 EP 3833587A1
Authority
EP
European Patent Office
Prior art keywords
vehicle
autonomous vehicle
scenario
permissible
trajectory
Prior art date
Legal status (The legal status 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 status listed.)
Pending
Application number
EP19734280.1A
Other languages
German (de)
English (en)
Inventor
Heiko Bald
Frank Bonarens
Ulrich Eberle
Olaf Schaedler
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Stellantis Auto SAS
Original Assignee
PSA Automobiles SA
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 PSA Automobiles SA filed Critical PSA Automobiles SA
Publication of EP3833587A1 publication Critical patent/EP3833587A1/fr
Pending legal-status Critical Current

Links

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
    • B60W30/18—Propelling the vehicle
    • B60W30/18009—Propelling the vehicle related to particular drive situations
    • B60W30/18163—Lane change; Overtaking manoeuvres
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing 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
    • 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
    • B60W2050/0001—Details of the control system
    • B60W2050/0002—Automatic control, details of type of controller or control system architecture
    • B60W2050/0018—Method for the design of a control system

Definitions

  • the present invention relates to a method for designing a vehicle.
  • the recorded data of the scenario depend on the sensor equipment of the receiving vehicle, i.e. if one of the sensor equipment includes a camera with which the surroundings of the receiving vehicle can be monitored, then the images that such a camera delivers and the conclusions that the vehicle derives from the images e.g. with regard to the distance and speed of other road users, among other things from the installation location of the camera on the vehicle. Therefore, if an autonomous vehicle to be optimized is supplied with image data from such a scenario as part of a simulation and analyzed based on its own camera installation position, this can lead to incorrect conclusions about the surroundings of the vehicle and, as a consequence, inappropriate decisions by the autonomous control of the Drive vehicle that are not due to errors in the programs on which the control system is based.
  • the technical performance data of the vehicle to be optimized generally differ from that of the vehicle with which the scenario was taken, with the result that the trajectory that the vehicle to be optimized chooses to master the traffic situation of the scenario will differ from that actually driven in the recorded scenario, but these differences are not due to an error in the control programs of the let the optimizing vehicle close.
  • An object of the present invention is to enable the optimization of a vehicle design with the aid of scenarios from a database, despite the problems described above.
  • the object is achieved by a method for designing a vehicle with the steps:
  • step d) evaluating the vehicle as suitable for the selected scenario if the search of step c) is successful.
  • An incident in the above sense can be any type of undesirable behavior of the vehicle, but at least a collision with another road user or a stationary object and / or the crossing of a lane boundary and / or violations of any traffic rule or a route ban.
  • the scenario can also include further data on the surroundings of this vehicle, such as the trajectories of other road users, information on the course of the road, route progress and / or - offered and included for stationary objects.
  • the aim of the optimization cannot be to achieve the greatest possible match between the trajectory of the selected traffic scenario and the trajectory selected for the vehicle to be designed, but only lent that the vehicle to be optimized has to master the scenario without being involved in an accident. This goal is achieved as soon as a trajectory is found that the vehicle is able to drive taking into account its performance parameters and on which it does not leave the common rooms.
  • step c) can be repeated using a modified value of the at least one parameter in order to finally find a value for which a trajectory running through the common rooms exists.
  • the vehicle is unsuitable for the scenario examined, i.e. unable to drive the scenario without incident if it reaches the limit of the allowable lounge in the direction of travel or transverse to the direction of travel.
  • This case is tantamount to bumping or an impermissibly close approach to an object next to or in front of the autonomous vehicle, such as a vehicle driving in front or alongside or a lane limitation, and can occur in particular if it is up to the scenario at all to be able to drive at the time of reaching the border, to accelerate the vehicle to a speed that is now no longer manageable.
  • the autonomous vehicle reaches the limit of the permissible lounge opposite to the direction of travel.
  • the prerequisite for this is that the rear limit of the permissible recreational area is defined by a vehicle traveling behind and that it drives faster than the autonomous vehicle. It must be taken into account here that the vehicle with which the scenario was originally recorded generally drove a different trajectory is assumed to be the one assumed for the autonomous vehicle and the trajectory of the following vehicle has been coordinated with that of the receiving vehicle, but the trajectory chosen for the autonomous vehicle is not taken into account. In other words: if the receiving vehicle had driven the trajectory now examined for the autonomous vehicle at the time the scenario was recorded, the following vehicle would have taken this into account and avoided collision.
  • Step c) can be repeated using different values of at least one parameter. If several trajectories running through the permissible common rooms are found, all of the parameter values on which they are based are obviously suitable for mastering the scenario. In order to select one of these several parameter values, a cost function of the at least one parameter can be defined and the ideal parameter value in relation to this cost function can be implemented when the autonomous vehicle is built.
  • Fig. 1 shows an initial state
  • a vehicle 1 shows a traffic situation on a freeway entrance as an elementary application example of the invention.
  • a vehicle 1 is in a threading lane 2 and from there has to cut into the flowing traffic in an adjacent lane 3 with vehicles 4, 5, 6. To do this, it must reach the speed of the flowing traffic on the threading track 2 and then cut into a gap between the vehicles 4, 5, 6.
  • a scenario that describes the movements of vehicles 1, 4, 5, 6 is in the form of a sequence of data recorded during acceleration and reeving by one or more environmental sensors of vehicle 1.
  • a camera 7 is particularly suitable as an environmental sensor; the sequence of the recorded data can then e.g. available as a video.
  • the scenario can be obtained by simulation or by capturing ambient data during a driving maneuver of real vehicles and is stored in a database from which it is downloaded in order to use it for the optimization of an autonomous vehicle.
  • step S1 of the flowchart in FIG. 3 it may be necessary (in accordance with step S1 of the flowchart in FIG. 3) to adapt the recorded data of the downloaded scenario to the sensors of the autonomous vehicle. If the installation position of the camera 7 on the autonomous vehicle is different from that of the real vehicle 1, then correct control of the autonomous vehicle by its on-board computer 8 would not be guaranteed if these were the original video films of the stored scenario as input data. Since these show the objects in the surroundings of the vehicle 1 over time and the movement of the vehicle 1 from different angles, it is possible to first convert the original video films into a sequence of three-dimensional models of the surroundings and from this in turn video films to be derived, which show the surroundings from the perspective of the camera 7 of the autonomous vehicle and can be used as input data for its on-board computer 8.
  • each of these three-dimensional models contains, among other things, the current coordinates of vehicles 4, 5, 6 and their dimensions.
  • a permissible lounge for the autonomous vehicle is calculated for the respective point in time (S2), in which it can find space without reaching the other vehicles 4, 5, 6 and the limits of the road .
  • Such a permissible lounge 9 includes the current location of vehicle 1 and locations in the vicinity to which vehicle 1 could be moved at a given time in the scenario, without the other vehicles 4, 5, 6 at their current locations or touch other objects.
  • the permissible lounge includes, for example, as shown in Fig. 1, 2, at the beginning of the scenario, the threading lane 2 in front of the vehicle 1 and towards the end the space between the vehicles 5, 6 in the lane 3.
  • the on-board computer 8 of the autonomous vehicle is programmed according to any known technique to carry out a sequence of steering commands for actuators, e.g. to control the steering, the fuel metering or the stroke of a brake cylinder of the autonomous vehicle in such a way that they lead the autonomous vehicle from the threading lane 2 to the lane 3 without collision.
  • these steering commands are not received by real vehicle components, but by a likewise computer-implemented kinematic model that measures the movement of the autonomous vehicle resulting from the steering commands, taking into account vehicle-specific parameters such as engine power or braking deceleration of the vehicle, slip resistance, self-steering gradient or coefficient of adhesion calculated.
  • a realistic value is defined for each of the parameters mentioned (S3), and on the basis of these values, a sequence of steering commands is determined by the on-board computer 8 (S4), which guide the autonomous vehicle into lane 3. If the trajectory of the autonomous vehicle ascertained on the basis of these steering commands from the kinematic model in step S5 ends between vehicles 5, 6, then a check is carried out (S6) to determine whether the entire length of the trajectory is within the permitted spaces 9. If so, then the vehicle is up to the scenario with the currently selected set of parameter values. Then the process could be terminated at this point and the autonomous vehicle built with the selected parameter values.
  • the autonomous vehicle reaches the rear limit of the permissible lounge, then this does not have to do with a driving error of the autonomous vehicle, but merely means that the speed of the following vehicle 5 is predetermined in the scenario and the movement of the vehicle autonomous vehicle cannot take into account.
  • the scenario for the autonomous vehicle is irrelevant (S14), and another scenario should be used to optimize the autonomous vehicle.
  • a new set of parameter values can be selected (S10) and the process can be repeated from step S4, in which case the change which can aim parameter values to minimize costs.
  • iterations of steps S4 to S10 can be used to find one or more sets of parameter values which allow a trajectory to be driven which runs completely within the permissible recreational spaces 9. If a cost function is stored for the parameters, which makes it possible to quantify production costs or a different size to be optimized for a given selection of parameter values, then one is selected in step S13 from among the several sets that achieves the best value of the cost function , and the autonomous vehicle is built with the parameter values selected in this way (S14).

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Remote Sensing (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Multimedia (AREA)
  • Mechanical Engineering (AREA)
  • Electromagnetism (AREA)
  • Transportation (AREA)
  • Traffic Control Systems (AREA)

Abstract

L'invention concerne un procédé d'optimisation d'un véhicule autonome qui comprend les étapes suivantes : a) sélectionner un scénario de trafic, décrivant une trajectoire d'un véhicule, dans une base de données ; b) déterminer, pour une séquence de lieux d'arrêt du véhicule le long de la trajectoire, un espace d'arrêt autorisé (8) qui contient le lieu d'arrêt et dans lequel le véhicule peut s'arrêter sans risque de collision ; c) rechercher, sur la base d'une valeur d'au moins un paramètre du véhicule autonome, une trajectoire du véhicule autonome qui passe par la séquence de lieux d'arrêt autorisés, d) évaluer le véhicule comme adapté au scénario sélectionné si la recherche de l'étape c) est réussie.
EP19734280.1A 2018-08-08 2019-06-13 Procédé de conception d'un véhicule Pending EP3833587A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102018006265.2A DE102018006265A1 (de) 2018-08-08 2018-08-08 Verfahren zum Auslegen eines Fahrzeuges
PCT/EP2019/065457 WO2020030333A1 (fr) 2018-08-08 2019-06-13 Procédé de conception d'un véhicule

Publications (1)

Publication Number Publication Date
EP3833587A1 true EP3833587A1 (fr) 2021-06-16

Family

ID=67107380

Family Applications (1)

Application Number Title Priority Date Filing Date
EP19734280.1A Pending EP3833587A1 (fr) 2018-08-08 2019-06-13 Procédé de conception d'un véhicule

Country Status (4)

Country Link
EP (1) EP3833587A1 (fr)
DE (1) DE102018006265A1 (fr)
MA (1) MA53260A (fr)
WO (1) WO2020030333A1 (fr)

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE10036276A1 (de) * 2000-07-26 2002-02-07 Daimler Chrysler Ag Automatisches Brems- und Lenksystem für ein Fahrzeug
DE102006044086B4 (de) * 2006-09-20 2013-05-29 Audi Ag System und Verfahren zur Simulation von Verkehrssituationen, insbesondere unfallkritischen Gefahrensituationen, sowie ein Fahrsimulator
US9821801B2 (en) * 2015-06-29 2017-11-21 Mitsubishi Electric Research Laboratories, Inc. System and method for controlling semi-autonomous vehicles
DE102016220913A1 (de) * 2015-11-06 2017-05-11 Ford Global Technologies, Llc Verfahren und Vorrichtung zur Generierung von Testfällen für autonome Fahrzeuge
DE102017200180A1 (de) * 2017-01-09 2018-07-12 Bayerische Motoren Werke Aktiengesellschaft Verfahren und Testeinheit zur Bewegungsprognose von Verkehrsteilnehmern bei einer passiv betriebenen Fahrzeugfunktion
CN108304605B (zh) * 2017-11-09 2019-08-06 清华大学 汽车驾驶辅助***传感器优选配置方法

Also Published As

Publication number Publication date
DE102018006265A1 (de) 2020-02-13
WO2020030333A1 (fr) 2020-02-13
MA53260A (fr) 2021-11-17

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Owner name: STELLANTIS AUTO SAS