WO2020053170A1 - Procédé de génération d'une collecte d'informations sur des scénarios de roulement d'au moins un véhicule, et véhicule, dispositif et système formé de ceux-ci - Google Patents

Procédé de génération d'une collecte d'informations sur des scénarios de roulement d'au moins un véhicule, et véhicule, dispositif et système formé de ceux-ci Download PDF

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Publication number
WO2020053170A1
WO2020053170A1 PCT/EP2019/074032 EP2019074032W WO2020053170A1 WO 2020053170 A1 WO2020053170 A1 WO 2020053170A1 EP 2019074032 W EP2019074032 W EP 2019074032W WO 2020053170 A1 WO2020053170 A1 WO 2020053170A1
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WO
WIPO (PCT)
Prior art keywords
vehicle
driving
data
driving scenario
information
Prior art date
Application number
PCT/EP2019/074032
Other languages
German (de)
English (en)
Inventor
Peter Schlicht
Fabian HÜGER
Original Assignee
Volkswagen Aktiengesellschaft
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 Volkswagen Aktiengesellschaft filed Critical Volkswagen Aktiengesellschaft
Publication of WO2020053170A1 publication Critical patent/WO2020053170A1/fr

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/38—Electronic maps specially adapted for navigation; Updating thereof
    • G01C21/3804—Creation or updating of map data
    • G01C21/3807—Creation or updating of map data characterised by the type of data
    • G01C21/3815—Road data
    • G01C21/3822—Road feature data, e.g. slope data
    • 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
    • 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
    • G05D1/0088—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours
    • 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
    • G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
    • G07C5/0841—Registering performance data
    • G07C5/085—Registering performance data using electronic data carriers
    • 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
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
    • G08G1/0141—Measuring and analyzing of parameters relative to traffic conditions for specific applications for traffic information dissemination

Definitions

  • the invention relates to a method for generating an information collection on or, in other words, about driving scenarios of at least one vehicle, as well as a vehicle, an arrangement and a system consisting of the vehicle and the arrangement.
  • Autonomy levels level 3 to level 5 the driving functions are usually checked using simulations or in real operation based on driving scenarios that a vehicle typically expects as expected.
  • the driving scenarios have so far been derived from so-called catalogs, which are based on road building regulatory standards (rules for the construction of roads, the design of intersections and bridges, markings on construction sites etc.) and
  • Map data for example curve radii and rises
  • the catalogs are created based on a set of rules based on a "top down" approach. It is also assumed that the applicable traffic regulations such as a
  • the task is therefore to enable improved validation of at least partially automated and in particular highly automated driving functions from level 3.
  • Driving scenarios run through are not only derived from predefined rules and presumptions, but from a collection of information that is actually based on
  • driving scenarios run through by at least one vehicle can be carried out using
  • Vehicle sensors are recorded and stored as part of a collection of information.
  • the collection of information e.g. in the form of a database or also one
  • Data backends can then be evaluated, for example in order to determine a frequency of actually occurring driving scenarios and / or driving scenario parameters.
  • Frequently occurring driving scenarios can then be used for a validation of driving functions (for example in the context of a simulation or by re-enacting these driving scenarios in the context of a real ferry operation).
  • the driving functions can thus be validated realistically and based on actual driving scenarios that are frequently present, which increases the validity of the validation and generally the operational safety of the vehicle.
  • Map vehicle sensor data in particular (at least partially external) driving conditions while the vehicle is traveling;
  • Vehicle sensor data which describe existing driving scenarios or driving conditions of this vehicle.
  • Receiving vehicle sensor data and / or generating driving scenario data can be vehicle-specific or vehicle-specific. For example, this can be carried out by a vehicle-based (control) device that generates driving scenario data from preferably only the corresponding vehicle. At least with the
  • Saving the driving scenario data can also take into account driving scenario data of different vehicles, for example from a test vehicle fleet.
  • the vehicle sensor data may include at least one of the following
  • Vehicle sensors are detected, a plurality of each sensor type also being present can: a light sensor, a rain sensor, a distance sensor (for example based on optical or radar-based radiation), a camera sensor, a
  • Geoposition sensor an inclination sensor, an object detection sensor that performs object detection based on, for example, at least one camera sensor, image detection, a lidar sensor, a radar sensor, a
  • Ultrasonic sensor Furthermore, other systems (in particular driver assistance systems and / or control or regulating systems) can also be used within the scope of the present disclosure
  • ABS for example ABS or ESP systems
  • ESP ESP systems
  • the vehicle sensor data and / or driving conditions depicted here can at least partially relate to conditions external to the vehicle, that is to say, for example, environmental conditions (weather) and static and / or dynamic traffic conditions (traffic infrastructure, road users).
  • the driving conditions preferably do not affect
  • Vehicle diagnostic parameters This could reduce the informative value of the information collection or only for an application to the specific vehicle type
  • driving scenarios can be understood primarily or at least partially as vehicle-independent environmental influences or driving conditions that arise due to the environmental influences, e.g. from one to be validated
  • Driving function must be mastered.
  • mapping the driving conditions through the vehicle sensor data e.g.
  • vehicle sensor data either specify driving conditions in the sense of predetermined driving scenario parameters or contain information from which the driving conditions and / or driving scenario parameters can be determined.
  • driving scenario data In order to generate driving scenario data from the vehicle sensor data, these can be combined in accordance with predetermined regulations (for example program instructions) and / or in accordance with a predetermined data format. In particular, they can be compressed and / or converted into a desired data format. According to one variant, driving scenario data are predetermined from the vehicle sensor data
  • the driving scenario data can be in the form of several description codes and / or data records, each of which describes a single driving scenario, which is preferably composed of a plurality of driving scenario parameters.
  • the driving scenario parameter values can be derived from the vehicle sensor data or can be contained therein.
  • vehicle sensor data can be considered that are present and recorded within a common time period, at a common time or generally at the same time, and the driving scenario data can preferably also be determined for this time period or time.
  • driving scenario data can be determined for this time period or time.
  • the driving scenario data (or individual data records contained therein) can relate to a specific point in time or a period of time and can preferably be determined continuously, so that, for example, a type of data stream and / or an interval output of driving scenario data is generated.
  • the driving scenario data can thus comprise several individual time-related data records or can be composed of these.
  • Each data record can specify an individual driving scenario, which was determined on the basis of the vehicle sensor data, and optionally comprise a description code for this driving scenario.
  • a driving scenario can be defined on the basis of several driving scenario parameters or coded or described on the basis of these.
  • Each driving scenario parameter can correspond to information of the type explained below and / or indicate or number it, wherein the information can be included in the vehicle sensor data.
  • a single driving scenario mapped by the driving scenario data (or a single data record included therefrom) can contain values for a corresponding plurality of driving scenario parameters and / or be defined thereby. Such a compilation of values of individual driving scenario parameters for defining a driving scenario using the
  • Vehicle sensor data can correspond to a coding explained above or can emerge from this as a result.
  • the vehicle sensor data and / or driving scenario data can be continuously recorded during a journey and stored, for example, at regular time intervals and / or at least when a change has been detected. It is possible that
  • Driving scenario data and / or vehicle sensor data can generally take place wirelessly, for example via mobile radio or a wireless Internet connection. It is preferred that the information is stored on a vehicle-independent storage device that is part of a computer system in a vehicle development center, for example.
  • the vehicle sensor data is evaluated by the vehicle itself in order to generate driving scenario data therefrom.
  • the driving scenario data are encoded and / or compressed in accordance with predetermined regulations, the amount of data to be transmitted to a vehicle-independent device can thus be limited. This can also guarantee higher data protection in the sense of anonymization and / or deletion of personal data.
  • Vehicle-independent devices are transferred, they can be processed in a suitable manner in the vehicle in order to take account of data protection regulations.
  • vehicle-independent devices In principle, however, it is also possible to at least partially transfer the vehicle sensor data (e.g. without evaluations or driving scenario data generation taking place in the vehicle) to vehicle-independent devices. The latter can then generate at least parts of the driving scenario data from the received vehicle sensor data. This reduces the requirements e.g. to the computing power to be provided by the vehicle.
  • the driving scenario data generation can at least partially in the
  • Vehicle or external or independent of the vehicle.
  • a computing unit which also includes or is connected to the aforementioned storage device.
  • the computing unit can be provided generally independently of the vehicle and in particular outside the vehicle.
  • a vehicle-bound variant is also possible, in which case statically evaluated driving scenario data of the corresponding vehicle, for example to an external one
  • the evaluation can generally comprise from the total of the present
  • Driving scenario data To determine which conclusions about typical, frequent and / or less frequent driving scenarios are possible.
  • the statistical evaluation can determine a frequency of driving scenarios and / or individual ones
  • an at least partially automated driving function (preferably from at least level 3 up to level 5) is designed based on the statistical evaluation.
  • a partially automated driving function can be understood to mean that at least certain driving operations
  • Laying out can be understood to mean, for example, control and / or regulating regulations or parameters for the driving function and / or
  • the vehicle sensor data preferably comprise at least one of the following
  • Lane course a number of lanes, the presence of an intersection and / or a predetermined type of intersection; a street type, recognized traffic signs or traffic lights;
  • the ambient light intensity for example, can be determined using a light sensor
  • a precipitation intensity for example, can be determined by Rain sensor
  • an ambient temperature for example, can be determined using an ESP assistance function
  • Pedestrians which, for example, using object detection algorithms e.g.
  • driver assistance systems e.g. step-by-step in the sense of: works, does not work, works with restrictions, works with a low confidence value and / or a predetermined error code occurs, whereby each of the states mentioned can be assigned its own code value Activation or non-activation are recorded;
  • Corner cases also called pathological cases, in which e.g. an algorithm can no longer make a reliable state determination or decision).
  • the type of error e.g. an algorithm outputs a specific error message
  • the current data record can be the
  • Driving scenario data e.g. be marked appropriately to include therein
  • the type of road, the type of intersection, traffic signs and / or traffic lights can be recognized, for example, based on image evaluation or geolocation algorithms which search image information for previously classified objects (in this case
  • the course of the lane and the number of lanes can be determined, for example, based on image information of the vehicle surroundings captured by a camera.
  • the vehicle sensor data include and / or
  • Driving scenario data furthermore at least one of the following: location information (for example related to the location at which the vehicle sensor data was recorded and / or the
  • Driving scenario was present), in particular a location-based satellite-based (for example by GPS); a time information (for example based on the point in time at which the vehicle sensor data was recorded and / or the driving scenario was available), which the
  • Specifies the time of acquisition of the data ie vehicle sensor data and / or driving scenario data. This can increase the information content of the vehicle sensor data and also the driving scenario data derived therefrom and / or for a plausibility check of the determined Driving scenarios are used.
  • the driving scenario data can be verified or checked for plausibility on the basis of driving scenarios that appear likely, the latter being able to be determined on the basis of map information and / or weather service information.
  • the time information and / or the location information can preferably also be deleted again before the driving scenario data are stored as part of the information collection.
  • this information can be used for the plausibility check explained above and, e.g. if this is positive, then deleted from the driving scenario data.
  • Vehicle sensor data are at least partially transmitted to a vehicle-independent (i.e. vehicle-external) storage device, on which the information collection is preferably also stored. As described, this can be done anonymously and / or wirelessly.
  • the invention further relates to a vehicle, in particular an automobile, for example a passenger car, with:
  • control device which is set up to record vehicle sensor data generated by vehicle sensors of the vehicle and to generate driving scenario data therefrom which describe (preferably currently) driving scenarios;
  • a transmission device which is set up to transmit the driving scenario data generated by the control device to a vehicle-independent storage device. So it is one in the vehicle
  • the invention also relates to a vehicle having a control device which is set up to record vehicle sensor data generated by vehicle sensors of the vehicle; and a transmission device which is set up to detect those detected by the control device To transmit vehicle sensor data to a vehicle-independent driving scenario data generating device. It is therefore a matter of generating the driving scenario data from the vehicle.
  • the transmission device can be set up for wireless data transmission, for example via mobile radio or a wireless Internet connection.
  • transmission by storage medium for example a USB stick
  • a readout or diagnostic device is also possible, which can in each case be coupled to the transmission device.
  • the control device can be designed as a control device and, for example, control a process sequence of the type explained above. For this purpose, it can provide corresponding data acquisition and / or generation functions or the data required for this
  • the control device can be set up for any of the driving scenario data generation and / or coding described above or below.
  • control device can access a vehicle bus or another connection which carries the vehicle sensor data.
  • the invention further relates to an arrangement, in particular a stationary and / or vehicle-external or vehicle-independent arrangement, with:
  • a receiving device that is configured to receive driving scenario data generated by at least one vehicle; a storage device, which is set up to contain an information collection received by the receiving device
  • an evaluation device for example in the form or comprising an arithmetic unit or processor unit which is set up to:
  • the arrangement can be provided, for example, in the form of or as part of a computer system, in particular comprising at least one PC and / or at least one server.
  • the arrangement can include a receiving device for receiving
  • vehicle sensor data and a driving scenario data generating device which is set up to generate driving scenario data, which describe the present driving scenarios, from transmitted vehicle sensor data. This corresponds to driving scenario data generated externally by the vehicle.
  • the invention also relates to a system comprising at least one vehicle and an arrangement according to the preceding aspects, wherein these are combined accordingly to carry out vehicle-scenario-related or vehicle-external driving scenario data generation.
  • the system can be set up, for example, to transmit driving scenario data generated by the vehicle to the arrangement, there as part of the
  • Parameter correlations can be determined.
  • Fig. 1 is a schematic diagram of a system according to an embodiment of the
  • Invention comprising an arrangement according to the invention and a vehicle according to the invention, the system executing a method according to the invention;
  • Fig. 2 is a flowchart of the method carried out by the system.
  • FIG. 1 A system 1 according to the invention is shown in FIG. 1 that a vehicle 2 and a
  • Arrangement 3 according to an embodiment of the invention comprises.
  • the arrangement 3 is provided independently of the vehicle (i.e. as a component not physically connected to it and / or moved together with it) and, for example, as a stationary component
  • the system 1 enables vehicle-bound driving scenario data generation with information-gathering storage and evaluation external to the vehicle.
  • Alternative variants which relate to driving scenario data generation external to the vehicle have been generally described above and are not explained separately below.
  • the vehicle 2 comprises a plurality of vehicle sensors 10, one of which is marked on a vehicle front merely by way of example.
  • the vehicle 2 preferably comprises at least one vehicle sensor 10 on each side (i.e. on the front and rear as well as on the two sides comprising the entrance doors), which sensor detects the surroundings and
  • Vehicle sensors 10 and information which can be ascertained herewith have been generally discussed above and are partly explained in more detail below.
  • the vehicle 2 comprises a control device 12 which is connected to a vehicle bus, not shown separately. All vehicle sensors 10 directly or indirectly feed the information recorded by you into the vehicle bus (for example in the form of a digital signal or as vehicle sensor data). In other words, the vehicle sensors 10 write the acquired information onto the common vehicle bus.
  • the control device 12 can read the corresponding ones by reading out the vehicle bus
  • the control device 12 which is an example of a driving scenario data generation device 13, comprises a processor unit with which the vehicle sensor data
  • Driving scenario data are generated.
  • the vehicle sensor data are converted in accordance with a predetermined coding or data generation specification
  • Driving scenario) of the driving scenario data can be put together (for example according to the following order).
  • Image processing uses a number of lanes (e.g. 1 - 10), an indication of the lane on which the vehicle is located (so-called ego lane), a road type from a pre-stored classification of different road types (e.g. types 1 to 6) and the existence of an intersection (yes / no, specified as 1/0) is determined.
  • Determined location information for example GPS information
  • Information on dynamic objects is taken into account, which is done, for example, based on image or radar-based object detection.
  • a recognized vehicle type, a distance to this vehicle type, information on which lane this vehicle type is located, and in the same way a number and position of pedestrians can be summarized as a code block.
  • the code block 1 10 3 15 1 0 3 indicates, for example, that there is a type 1 vehicle (in this case a car) in a left lane (first position in the code block) and that it is located 10 m away from your own position (see second position (10) in the code block). It is also stated that there is a type 3 vehicle (in this case a motorcycle) in a right lane (third position in the code block) and that it is located 15 m away from your own position (see fourth position (15) in the code block) ). The distance considerations can e.g. in each case in or against the direction of travel. Finally, it is also stated that there is a single pedestrian to the left of the lane (fifth position in the code block) (see value 1) and that to the right of the lane (seventh position in
  • Precipitation via rain sensor
  • temperature and smoothness via ESP driver assistance function
  • time of entry is also taken into account.
  • the code block 60 5 15 10.5 0 would then stand, for example, for a 60 percent light intensity (based on a maximum measurable light intensity), a precipitation of strength 5 (based on a previous precipitation classification, for example from 0 to 10), an outside temperature of 15 °, a time of 10.30 a.m. (given here as 10.5) and a roadway specified as not smooth (based on a previous one
  • Each of the values represents a single driving scenario parameter value and the total value obtained or the parameter value sequence can also be referred to as a hash value.
  • the driving scenario data is thus composed of individual (driving scenario) data records, which in turn are each formed by a sequence of driving scenario parameter values and relate to a single recorded driving scenario.
  • Driving scenario parameter values indicate the information contained in or derived from the vehicle sensor data, in particular with regard to existing driving conditions.
  • Such a data record can optionally also be compressed before a transmission to the arrangement 3 explained below in order to reduce the amount of data to be transferred. Furthermore, such data records can be continuously generated and transmitted by reading out or recording the vehicle sensor data after the expiry of predetermined time intervals. The data records transmitted as a whole then form the driving scenario data which are sent to the
  • Transfer arrangement 3 and be stored there as part of a (driving scenario) information collection.
  • the information collection generally collects the determined
  • Vehicle 2 includes one for transmitting the driving scenario data
  • Transmission device 14 which transmits the data to a receiving device 16 of the arrangement 3, for example by mobile radio and thus wirelessly (see dashed line in FIG. 1). This can take place immediately after receiving a single data record of the type explained above.
  • the arrangement 3 comprises a storage device 18, on which the received data records are stored as part of a driving scenario data information collection.
  • An evaluation device 20, comprising at least one processor (and / or one microcontroller), also accesses the memory device 18.
  • the data records Before or after the transfer, the data records can be checked for plausibility and / or anonymized.
  • the control device 12 before the transmission
  • the transmission or the
  • Evaluation device 20 (after the transfer) at least selected
  • a further possibility of anonymization consists in not determining or transmitting driving scenario data for a predetermined period of time at the beginning or at the end of a journey and / or retrospectively after the end of the journey, the driving scenario data for such
  • Information collection can be continuously supplemented over a longer period (for example, several weeks or months). Furthermore, the information collection can be statistically evaluated by the evaluation device 20, in particular by frequently
  • the storage device 18 contains information relating to actually relevant driving scenarios that are generated by the vehicle 2 (or a possible plurality thereof, for example one Test car fleet) were run through. This can be used to validate and design automated driving functions based on these driving scenarios.
  • FIG. 2 shows a flow diagram of the method explained above.
  • vehicle sensor data are acquired with the vehicle sensors 10.
  • these are transmitted to the control device 12 or detected by the latter by reading out the vehicle bus.
  • an individual driving scenario data record is determined on the basis of the vehicle sensor data. This takes place after a predetermined time interval and continuously while driving. If a corresponding data record has been determined, it is transferred to the arrangement 3 in a step S4 and stored there as part of the information collection in the storage device 18.
  • step S5 it is checked whether a predetermined evaluation condition is fulfilled (for example the expiration of a predetermined time interval, the presence of a
  • step S6 a statistical evaluation of the information collection is carried out in step S6 by means of the evaluation device 20.

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Abstract

L'invention concerne un procédé de génération d'une collecte d'informations sur des scénarios de roulement d'au moins un véhicule (2). Ledit procédé comprend : - l'obtention de données de capteur d'au moins un véhicule (2) ; - la génération de données de scénarios de roulement sur la base des données de capteurs de véhicule qui décrivent les scénarios de roulement existants ; - la sauvegarde des données de scénario de roulement dans le cadre d'une collecte d'informations sur les scénarios de roulement. L'invention concerne en outre un véhicule (2), un dispositif (3) et un système (1) formé de ceux-ci.
PCT/EP2019/074032 2018-09-10 2019-09-10 Procédé de génération d'une collecte d'informations sur des scénarios de roulement d'au moins un véhicule, et véhicule, dispositif et système formé de ceux-ci WO2020053170A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102018215351.5A DE102018215351A1 (de) 2018-09-10 2018-09-10 Verfahren zum Erzeugen einer Informationssammlung zu Fahrszenarien wenigstens eines Fahrzeugs, sowie Fahrzeug, Anordnung und daraus bestehendes System
DE102018215351.5 2018-09-10

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WO2020053170A1 true WO2020053170A1 (fr) 2020-03-19

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CN111582018A (zh) * 2020-03-24 2020-08-25 北京掌行通信息技术有限公司 无人车动态交互场景的判定方法、系统、判定终端及存储介质
CN112380137A (zh) * 2020-12-04 2021-02-19 清华大学苏州汽车研究院（吴江） 一种自动驾驶场景的确定方法、装置、设备及存储介质
CN113494938A (zh) * 2020-04-02 2021-10-12 三菱电机株式会社 物体识别装置及物体识别方法
CN113932945A (zh) * 2021-09-26 2022-01-14 北京罗克维尔斯科技有限公司 车辆外部温度的确定方法、设备及存储介质
CN114228735A (zh) * 2021-12-29 2022-03-25 阿波罗智联(北京)科技有限公司 智能驾驶车辆的可视化方法、装置及系统
WO2023226733A1 (fr) * 2022-05-27 2023-11-30 中国第一汽车股份有限公司 Procédé et appareil d'acquisition de données de scène de véhicule, support de stockage et dispositif électronique

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DE102022119715A1 (de) 2022-08-05 2024-02-08 Dr. Ing. H.C. F. Porsche Aktiengesellschaft Verfahren, System und Computerprogrammprodukt zur objektiven Bewertung der Leistungsfähigkeit eines ADAS/ADS-Systems

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