EP3877231A1 - Prédiction d'un comportement de conduite probable - Google Patents

Prédiction d'un comportement de conduite probable

Info

Publication number
EP3877231A1
EP3877231A1 EP19773368.6A EP19773368A EP3877231A1 EP 3877231 A1 EP3877231 A1 EP 3877231A1 EP 19773368 A EP19773368 A EP 19773368A EP 3877231 A1 EP3877231 A1 EP 3877231A1
Authority
EP
European Patent Office
Prior art keywords
vehicle
control device
determined
feature
expected
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
EP19773368.6A
Other languages
German (de)
English (en)
Inventor
Tobias Strauss
Jan-Hendrik Pauls
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.)
Robert Bosch GmbH
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 EP3877231A1 publication Critical patent/EP3877231A1/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, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B60W30/095—Predicting travel path or likelihood of collision
    • B60W30/0956—Predicting travel path or likelihood of collision the prediction being responsive to traffic or environmental parameters
    • 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
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B60W40/04—Traffic conditions
    • 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
    • B60W50/0097—Predicting future conditions
    • 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
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B60W60/0027—Planning or execution of driving tasks using trajectory prediction for other traffic participants
    • 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
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B60W60/0027—Planning or execution of driving tasks using trajectory prediction for other traffic participants
    • B60W60/00274—Planning or execution of driving tasks using trajectory prediction for other traffic participants considering possible movement changes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
    • G06V20/584—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads of vehicle lights or traffic lights
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C5/00—Registering or indicating the working of vehicles
    • G07C5/008—Registering or indicating the working of vehicles communicating information to a remotely located station
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
    • G08G1/0112—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125—Traffic data processing
    • G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125—Traffic data processing
    • G08G1/0133—Traffic data processing for classifying traffic situation
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
    • G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems
    • G08G1/161—Decentralised systems, e.g. inter-vehicle communication
    • G08G1/163—Decentralised systems, e.g. inter-vehicle communication involving continuous checking
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems
    • G08G1/164—Centralised systems, e.g. external to vehicles
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems
    • G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes
    • 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
    • B60W2420/00—Indexing codes relating to the type of sensors based on the principle of their operation
    • B60W2420/40—Photo or light sensitive means, e.g. infrared sensors
    • B60W2420/403—Image sensing, e.g. optical camera
    • 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
    • B60W2540/00—Input parameters relating to occupants
    • B60W2540/049—Number of occupants
    • 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
    • B60W2554/40—Dynamic objects, e.g. animals, windblown objects
    • B60W2554/404—Characteristics
    • B60W2554/4044—Direction of movement, e.g. backwards
    • 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
    • B60W2554/40—Dynamic objects, e.g. animals, windblown objects
    • B60W2554/404—Characteristics
    • B60W2554/4045—Intention, e.g. lane change or imminent movement
    • 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
    • B60W2554/40—Dynamic objects, e.g. animals, windblown objects
    • B60W2554/404—Characteristics
    • B60W2554/4046—Behavior, e.g. aggressive or erratic
    • 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
    • B60W2554/40—Dynamic objects, e.g. animals, windblown objects
    • B60W2554/404—Characteristics
    • B60W2554/4047—Attentiveness, e.g. distracted by mobile phone
    • 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
    • B60W2556/45—External transmission of data to or from the vehicle
    • 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
    • B60W2556/45—External transmission of data to or from the vehicle
    • B60W2556/55—External transmission of data to or from the vehicle using telemetry
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/62—Text, e.g. of license plates, overlay texts or captions on TV images
    • G06V20/625—License plates
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/08—Detecting or categorising vehicles

Definitions

  • the invention relates to a method for performing a prediction of a driving behavior of a second vehicle by a control device and a control device for coupling to at least one sensor and for evaluating measurement data of the at least one sensor.
  • Vehicle sensors that serve to perceive an environment.
  • the environment In addition to static obstacles and the road, the environment also includes dynamic objects and in particular other road users.
  • the previous behavior of road users in combination with the appearance of the road user is usually used to predict an expected behavior of the road user.
  • the expected behavior of the road user is usually used to predict an expected behavior of the road user.
  • Road users are used to enter into an interaction or cooperation with the corresponding road users.
  • the object on which the invention is based can be seen in proposing a method by which an expected behavior of road users can be determined reliably and dynamically.
  • a method for performing a prediction of a driving behavior of a second vehicle is provided by a control device of a first vehicle.
  • an expected driving behavior of at least one second vehicle and / or of a driver of the second vehicle can be calculated by the control device of the first vehicle.
  • data of a vehicle environment of the second vehicle and / or data of a vehicle driver and / or a load of the second vehicle are received by the control device.
  • the data can be recorded by at least one sensor and transmitted to the control unit.
  • the control unit can be any suitable control unit.
  • Measurement data of the vehicle environment are received by the control unit from a database.
  • the measurement data of the second vehicle one
  • the driver and / or a load on the second vehicle can be determined by at least one vehicle-side sensor of the first vehicle and transmitted to the control unit.
  • the control unit calculates an expected driving behavior of the second vehicle.
  • At least one feature of the vehicle environment, the second vehicle, the driver of the second vehicle, the passengers and / or the loading of the second vehicle can be determined by the control device of the first vehicle.
  • the data can be measurement data received by at least one sensor of the first vehicle and / or information or data from at least one database.
  • a control device which is set up to carry out the method.
  • Control unit can be coupled to at least one sensor and / or to at least one database.
  • the method can be used to obtain semantic information and / or holistic knowledge of the vehicle environment and the vehicles.
  • the method can be carried out by a control device.
  • the control device can, for example, be arranged inside or outside the vehicle.
  • control device can be mounted in the first vehicle or in further vehicles and connected to the vehicle sensor system.
  • infrastructure units such as traffic monitoring units, can also be equipped with such a control device.
  • the infrastructure sensors with the
  • Control unit connected to data and for example to predictive
  • the method can thus be used to gain an understanding of the scene, which is determined on the basis of features of the vehicle environment observed by sensors.
  • the area recorded by the sensor is preferably considered holistically here. As many features as possible are extracted from the measurement data and further processed by the control device.
  • control device can be used, for example, to restrict the options for operating the observed vehicles, such as the at least one second vehicle. This means that a probable one is more likely
  • Braking operations or evasive maneuvers can be determined.
  • the anticipated driving behavior of the at least one second vehicle which can be determined by the control device, can have, for example, an anticipated vehicle dynamics, an anticipated driving style, an anticipated trajectory and the like. Based on the expected driving behavior of the second vehicle and / or the driver of the second vehicle, the control unit can send the corresponding data about the expected driving behavior to a driver
  • the first vehicle can thus be controlled in a manner adapted to the anticipated behavior, as a result of which critical situations can be avoided.
  • the first vehicle can set a larger safety distance or react differently to braking maneuvers of vehicles in front, for example by evasive action.
  • an overtaking process by the first vehicle can be delayed if the vehicle in front has a high probability of taking an exit and thus will release the current lane.
  • the corresponding control commands can alternatively also be generated directly by the control device and transmitted to the vehicle control system.
  • the measurement data of the vehicle surroundings of the second vehicle can in particular have local and temporal information, which is shown in
  • the information or measurement data can have vacation times, usual times for after-work traffic, events, trade fairs and the like.
  • map data for example about possible trajectories, so-called "points of interest", information about city areas, taxi ranks, bus stops, business addresses and the like can be stored as measurement data of the vehicle surroundings.
  • the measurement data of the vehicle environment can be determined directly by the vehicle sensor system of the first vehicle or can be obtained from one or more databases by the control device of the first vehicle.
  • the database can be an internal database of the first vehicle and / or the control device or a database external to the vehicle.
  • the control device can establish a wireless communication connection to the database external to the vehicle and access the locally and temporally relevant data.
  • the driver of the at least one second vehicle and / or of the first vehicle can be a person in particular in the case of manually controlled or partially autonomous vehicles and a vehicle controller in the case of highly automated or fully automated or driverless vehicles.
  • the at least one sensor can be one or more cameras, lidar sensor, radar sensor, infrared sensor, thermal imaging camera and the like.
  • the features can be detected by the control device of the first vehicle if, for example, a relevant reference is made to the possible driving behavior of the second vehicle in the received measurement data. This can be done, for example, on the basis of static or dynamic factors or conditions.
  • the method can be used to collect and use a large number of features for an optimized prediction of the behavior of road users.
  • control unit of the first one can evaluate mutual dependencies on a large number of characteristics of other road users in the form of a holistic understanding of the scene
  • the anticipated driving behavior of the second vehicle is calculated by a simulation model, by at least one algorithm and / or by an artificial intelligence.
  • the driving behavior can be flexibly determined using static or dynamic systems.
  • an age, gender and / or condition of the vehicle driver is determined as a feature by the control device of the first vehicle. Based on such features of the vehicle driver, an anticipated driving style can be estimated by the control device. For example, in the context of probabilities, an older driver can be expected to drive more moderately than a young driver. Furthermore, the vehicle sensors or
  • a vehicle class, a vehicle state, at least one vehicle registration number and / or a state of a rotating beacon is determined as a feature by the control device of the first vehicle. Based on the characteristics of the vehicle, in particular an expected trajectory of the second vehicle can be estimated or calculated by the control device of the first vehicle.
  • a vehicle is most likely to be headed toward the country of registration or circle of approval as determined
  • holiday driving can also be taken into account. In this way, in particular at intersections or exits, it can be calculated which lane or departure is most likely to be traveled by the second vehicle.
  • the vehicle category and in particular the vehicle price can provide information about which part of the city a vehicle will drive into.
  • the rotating beacon of fire engines, police vehicles and ambulances can also tell whether the vehicle is moving away from a station or a hospital.
  • a light in the body of an ambulance can also provide information that the ambulance has picked up a patient and is likely to drive to the hospital.
  • an advertising space and / or an inscription on the second vehicle are determined as a feature by the control device of the first vehicle and a driving behavior of the second vehicle is estimated therefrom.
  • Inscriptions and signals such as a taxi from a defined district, can also be used by the control unit to calculate an expected direction of travel. For example, the taxi will continue from the district in an occupied state and return to the district in an empty state.
  • an expected trajectory of the second vehicle is calculated by the control device of the first vehicle on the basis of the determined feature.
  • the features of the vehicle and in particular the external features, such as number plates and inscriptions, can be used by the control unit to estimate the expected trajectory.
  • an anticipated driving style of the second vehicle is determined by the control device of the first vehicle based on the at least one feature determined by the vehicle driver.
  • Control unit is detected and the driving style of the first vehicle is adapted.
  • a loading state of the second vehicle is determined by the control device of the first vehicle, an anticipated one being based on the loading state of the second vehicle Vehicle dynamics of the second vehicle is calculated by the control device of the first vehicle. In this way, information about a direction of travel or driving dynamics of the second vehicle can be obtained.
  • Passengers of the second vehicle calculate an expected vehicle dynamics of the second vehicle by the control device of the first vehicle.
  • the load state of the vehicle can thus be used to:
  • a fully loaded vehicle can react less agilely to situations than an empty vehicle.
  • an anticipated braking distance of the second vehicle can thus be estimated by the control device of the first vehicle.
  • the at least one second vehicle can be arranged in the surroundings of the first vehicle that are visible to sensors.
  • the second vehicle can drive in front of the first vehicle or drive offset to the first vehicle.
  • all of the features determined can be taken into account in combination or individually by the control unit when calculating the expected driving behavior.
  • Fig. 1 is a schematic representation of a system with vehicles and an infrastructure unit and
  • Fig. 2 is a schematic flow diagram to illustrate a
  • FIG. 1 shows a schematic illustration of a system 1 with a first vehicle 2, a second vehicle 4 and an external database 6.
  • the first vehicle 2 drives behind the second vehicle 4.
  • the first vehicle 2 has two sensors 8, 10, which are designed as cameras.
  • the camera sensors 8, 10 are connected in a data-conducting manner to a control unit 12 on the vehicle.
  • the control unit 12 can receive and evaluate the measurement data from the sensors 8, 10.
  • the control device 12 has an artificial intelligence, which was learned in advance.
  • the detection areas of the sensors 8, 10 are shown schematically.
  • the sensors 8, 10 of the first vehicle 2 detect the second vehicle 4. Based on the measurement data from the sensors 8, 10, the control unit 12 can determine or detect features of the second vehicle 4. According to the exemplary embodiment, an identifier 14 of the second becomes an example
  • control device 12 can
  • the control device 12 of the first vehicle 2 can be wireless
  • Communication link 20 Obtain data from database 6.
  • the database 6 can in particular have local and temporal information which can be used for the expected trajectory 22. According to the
  • the control unit 12 can provide information about the exemplary embodiment
  • the probability of driving down the exit 16 is approximately 50:50, or only a fixed a-priori probability can be assumed.
  • FIG. 2 shows a schematic flowchart to illustrate a method 24 according to an embodiment of the invention.
  • a step 25 measurement data of the vehicle environment F are obtained by the control unit 12 from the database 6 external to the vehicle.
  • measurement data of the vehicle environment F can be determined 26 by the vehicle sensors 8, 10.
  • the measurement data are evaluated by the control device 12 in a further step 28 and features 14 are detected or ascertained.
  • At least one feature 14 of the vehicle environment F, the second vehicle 4, the driver of the second vehicle 4, the passengers and / or the loading of the second vehicle 4 is determined by the control device 12 of the first vehicle 2 on the basis of the measurement data.
  • an expected driving behavior 22 of the second vehicle 4 is calculated by the control device 12 of the first vehicle 2 based on the determined features.
  • Vehicle control of the first vehicle 2 by the control unit 12 takes place 30, whereby the driving style of the first vehicle 2 can be set in accordance with the expected driving behavior 22 of the second vehicle 4.

Abstract

L'invention concerne un procédé servant à mettre en œuvre une prévision d'un comportement de conduite d'un deuxième véhicule par un appareil de commande d'un premier véhicule. Des données d'un environnement de véhicule du deuxième véhicule et/ou des données d'un conducteur de véhicule et/ou d'un chargement du deuxième véhicule sont reçues par l'appareil de commande. Au moins une caractéristique est déterminée à l'aide des données et un comportement de conduite probable du deuxième véhicule est calculé par l'appareil de commande sur la base de la caractéristique déterminée. L'invention concerne par ailleurs un appareil de commande.
EP19773368.6A 2018-11-06 2019-09-16 Prédiction d'un comportement de conduite probable Pending EP3877231A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102018218922.6A DE102018218922A1 (de) 2018-11-06 2018-11-06 Prädiktion eines voraussichtlichen Fahrverhaltens
PCT/EP2019/074652 WO2020094279A1 (fr) 2018-11-06 2019-09-16 Prédiction d'un comportement de conduite probable

Publications (1)

Publication Number Publication Date
EP3877231A1 true EP3877231A1 (fr) 2021-09-15

Family

ID=68051752

Family Applications (1)

Application Number Title Priority Date Filing Date
EP19773368.6A Pending EP3877231A1 (fr) 2018-11-06 2019-09-16 Prédiction d'un comportement de conduite probable

Country Status (5)

Country Link
US (1) US20210362707A1 (fr)
EP (1) EP3877231A1 (fr)
CN (1) CN112955361A (fr)
DE (1) DE102018218922A1 (fr)
WO (1) WO2020094279A1 (fr)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102019134922A1 (de) * 2019-12-18 2021-06-24 Audi Ag Verfahren zum Betrieb eines autonomen bewegten Verkehrsteilnehmers
DE102021200803A1 (de) 2021-01-29 2022-08-04 Siemens Mobility GmbH Auswerteinrichtung für eine technische Einrichtung und Verfahren zum Herstellen einer Auswerteinrichtung
DE102021203482A1 (de) 2021-04-08 2022-10-13 Volkswagen Aktiengesellschaft Verfahren und optisches Ausgabesystem für ein Fahrzeug zur optischen Ausgabe eines Merkmals eines in einem Fahrzeugumfeld befindlichen zu erfassenden Fahrzeugs
US20240051581A1 (en) * 2022-08-15 2024-02-15 Motional Ad Llc Determination of an action for an autonomous vehicle in the presence of intelligent agents

Family Cites Families (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8577088B2 (en) * 2010-08-05 2013-11-05 Hi-Tech Solutions Ltd. Method and system for collecting information relating to identity parameters of a vehicle
US8493196B2 (en) * 2010-11-15 2013-07-23 Bendix Commercial Vehicle Systems Llc ACB following distance alert and warning adjustment as a function of forward vehicle size and host vehicle mass
DE102013208763A1 (de) * 2013-05-13 2014-11-13 Robert Bosch Gmbh Verfahren und Vorrichtung zum Erkennen einer Anfahrabsicht eines haltenden Fahrzeugs
SE539157C2 (sv) * 2014-02-19 2017-04-18 Scania Cv Ab Identifikation av säkerhetsrisker i ett fordon för att meddela medtrafikanter
US9731713B2 (en) * 2014-09-10 2017-08-15 Volkswagen Ag Modifying autonomous vehicle driving by recognizing vehicle characteristics
DE102014225804A1 (de) * 2014-12-15 2016-06-16 Bayerische Motoren Werke Aktiengesellschaft Unterstützung beim Führen eines Fahrzeugs
SE540619C2 (en) * 2016-04-22 2018-10-02 Scania Cv Ab Method and system for adapting platooning operation according to the behavior of other road users
DE102017204393A1 (de) * 2017-03-16 2018-09-20 Robert Bosch Gmbh Verfahren zum Ansteuern eines Fahrbetriebs eines Fahrzeugs
DE102017207097A1 (de) * 2017-04-27 2018-10-31 Robert Bosch Gmbh Verfahren und Vorrichtung zur Steuerung eines Fahrzeugs
US10134279B1 (en) * 2017-05-05 2018-11-20 Toyota Motor Engineering & Manufacturing North America, Inc. Systems and methods for visualizing potential risks
WO2018237018A1 (fr) * 2017-06-20 2018-12-27 nuTonomy Inc. Traitement de risque pour véhicules ayant des capacités de conduite autonome
US10957201B2 (en) * 2017-09-15 2021-03-23 Qualcomm Incorporated System and method for relative positioning based safe autonomous driving
US11110932B2 (en) * 2017-11-03 2021-09-07 Toyota Research Institute, Inc. Methods and systems for predicting object action
EP3820753B1 (fr) * 2018-07-14 2023-08-02 Moove.AI Analytique de données de véhicule

Also Published As

Publication number Publication date
US20210362707A1 (en) 2021-11-25
DE102018218922A1 (de) 2020-05-07
CN112955361A (zh) 2021-06-11
WO2020094279A1 (fr) 2020-05-14

Similar Documents

Publication Publication Date Title
EP3155603B1 (fr) Procédé de détermination de données de position à utiliser lors de l'exploitation d'un système de véhicule d'un véhicule automobile ainsi que système de détermination et de distribution de données de position
DE112012006226B4 (de) Fahrassistenzvorrichtung
EP3877231A1 (fr) Prédiction d'un comportement de conduite probable
DE112017007713T5 (de) Systeme und Verfahren zur Fahrzeugbelegungsverwaltung
DE112017006530T5 (de) Rückmeldung für ein autonomes fahrzeug
DE102017129076A1 (de) Autonomer schulbus
DE102017217444B4 (de) Verfahren und System zum Aktualisieren eines Steuerungsmodells für eine automatische Steuerung zumindest einer mobilen Einheit
DE102016205152A1 (de) Fahrerassistenzsystem zum Unterstützen eines Fahrers beim Führen eines Fahrzeugs
DE102018222601A1 (de) Verfahren und Fahrerassistenzsystem zum Unterstützen eines Fahrers eines Fahrzeugs beim Führen des Fahrzeugs
DE102017223846B4 (de) System zum Geben einer Meldung vom Vorhandensein eines Insassen in einem Fahrzeug durch historische Muster und Verfahren davon
DE102018212286A1 (de) Verfahren und Vorrichtung zur Unterstützung einer Aufmerksamkeit und/oder Fahrbereitschaft eines Fahrers bei einem automatisierten Fahrvorgang eines Fahrzeugs
DE102020122757A1 (de) Systeme und verfahren für mitfahrgelegenheiten unter verwendung von blockchain
DE102016223830A1 (de) Verfahren zum Betreiben eines automatisierten Fahrzeugs
DE102017216202A1 (de) Verfahren zur Prädiktion einer optimalen Fahrspur auf einer mehrspurigen Straße
WO2020212061A1 (fr) Procédé de prédiction d'une situation de circulation routière pour un véhicule
WO2020083962A1 (fr) Dispositif et unité de commande servant à automatiser une modification d'état d'une vitre de fenêtre d'un véhicule
DE102021107602A1 (de) Fahrassistenzvorrichtung und datensammelsystem
DE102018219760A1 (de) Kollisionsprädiktionssystem
DE102017217131B3 (de) Verfahren zur Unterstützung einer Parkplatzsuche für einen Fahrzeugführer eines Lastkraftwagens sowie ein System, welches dazu eingerichtet ist, ein solches Verfahren durchzuführen
DE102021201133A1 (de) Verfahren zum infrastrukturgestützten Assistieren eines Kraftfahrzeugs
DE102017223621A1 (de) Verfahren und Steuereinheit zur Steuerung einer Funktion eines zumindest teilweise automatisiert fahrenden Fahrzeugs
DE102020113611A1 (de) Verfahren und Sicherheitssystem zum Absichern einer automatisierten Fahrzeugfunktion und Kraftfahrzeug
WO2019211293A1 (fr) Procédé pour faire fonctionner un système d'aide à la conduite d'un véhicule autonome équipé d'au moins un capteur d'environnement pour détecter un environnement du véhicule autonome, support lisible par ordinateur, système et véhicule
DE112018006674T5 (de) Fahrassistenzvorrichtung, Fahrassistenzsystem, Fahrassistenzverfahren und Aufzeichnungsmedium, in dem ein Fahrassistenzprogramm gespeichert ist
DE102018211726A1 (de) Verfahren zum automatischen maschinellen Trainieren eines elektronischen Fahrzeugführungssystems, sowie Kraftfahrzeug

Legal Events

Date Code Title Description
STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: UNKNOWN

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE INTERNATIONAL PUBLICATION HAS BEEN MADE

PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: REQUEST FOR EXAMINATION WAS MADE

17P Request for examination filed

Effective date: 20210607

AK Designated contracting states

Kind code of ref document: A1

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

DAV Request for validation of the european patent (deleted)
DAX Request for extension of the european patent (deleted)