View in EDS

A Driver-Vehicle Model for ADS Scenario-Based Testing

Saved in:
Bibliographic Details
Title: A Driver-Vehicle Model for ADS Scenario-Based Testing
Authors: Queiroz, Rodrigo, Sharma, Divit, Diniz Caldas, Ricardo, 1994, Czarnecki, Krzysztof, García Gonzalo, Sergio, 1989, Berger, Thorsten, 1981, Pelliccione, Patrizio, 1975
Source: IEEE Transactions on Intelligent Transportation Systems. 25(8):8641-8654
Subject Terms: road traffic, Scalability, Vehicles, DSL, Vehicle dynamics, Testing, simulation, autonomous driving, system testing, Trajectory, Roads, Intelligent vehicles, autonomous vehicles
Description: Scenario-based testing for automated driving systems (ADS) must be able to simulate traffic scenarios that rely on interactions with other vehicles. Although many languages for high-level scenario modelling have been proposed, they lack the features to precisely and reliably control the required micro-simulation, while also supporting behavior reuse and test reproducibility for a wide range of interactive scenarios. To fill this gap between scenario design and execution, we propose the Simulated Driver-Vehicle (SDV) model to represent and simulate vehicles as dynamic entities with their behavior being constrained by scenario design and goals set by testers. The model combines driver and vehicle as a single entity. It is based on human-like driving and the mechanical limitations of real vehicles for realistic simulation. The model leverages behavior trees to express high-level behaviors in terms of lower-level maneuvers, affording multiple driving styles and reuse. Furthermore, optimization-based maneuver planners guide the simulated vehicles towards the desired behavior. Our extensive evaluation shows the model’s design effectiveness using NHTSA pre-crash scenarios, its motion realism in comparison to naturalistic urban traffic, and its scalability with traffic density. Finally, we show the applicability of our SDV model to test a real ADS and to identify crash scenarios, which are impractical to represent using predefined vehicle trajectories. The SDV model instances can be injected into existing simulation environments via co-simulation.
File Description: electronic
Access URL: https://research.chalmers.se/publication/540691
https://research.chalmers.se/publication/540691/file/540691_Fulltext.pdf
Database: SwePub
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://research.chalmers.se/publication/540691#
    Name: EDS - SwePub (s4221598)
    Category: fullText
    Text: View record in SwePub
  – Url: https://resolver.ebscohost.com/openurl?sid=EBSCO:edsswe&genre=article&issn=15249050&ISBN=&volume=25&issue=8&date=20240101&spage=8641&pages=8641-8654&title=IEEE Transactions on Intelligent Transportation Systems&atitle=A%20Driver-Vehicle%20Model%20for%20ADS%20Scenario-Based%20Testing&aulast=Queiroz%2C%20Rodrigo&id=DOI:10.1109/TITS.2024.3373531
    Name: Full Text Finder
    Category: fullText
    Text: Full Text Finder
    Icon: https://imageserver.ebscohost.com/branding/images/FTF.gif
    MouseOverText: Full Text Finder
  – Url: https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=EBSCO&SrcAuth=EBSCO&DestApp=WOS&ServiceName=TransferToWoS&DestLinkType=GeneralSearchSummary&Func=Links&author=Queiroz%20R
    Name: ISI
    Category: fullText
    Text: Nájsť tento článok vo Web of Science
    Icon: https://imagesrvr.epnet.com/ls/20docs.gif
    MouseOverText: Nájsť tento článok vo Web of Science
Header DbId: edsswe
DbLabel: SwePub
An: edsswe.oai.research.chalmers.se.c0b89c8b.8f9c.42c9.8fdb.8a405630c2d3
RelevancyScore: 1064
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 1064.41540527344
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: A Driver-Vehicle Model for ADS Scenario-Based Testing
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Queiroz%2C+Rodrigo%22">Queiroz, Rodrigo</searchLink><br /><searchLink fieldCode="AR" term="%22Sharma%2C+Divit%22">Sharma, Divit</searchLink><br /><searchLink fieldCode="AR" term="%22Diniz+Caldas%2C+Ricardo%22">Diniz Caldas, Ricardo</searchLink>, 1994<br /><searchLink fieldCode="AR" term="%22Czarnecki%2C+Krzysztof%22">Czarnecki, Krzysztof</searchLink><br /><searchLink fieldCode="AR" term="%22García+Gonzalo%2C+Sergio%22">García Gonzalo, Sergio</searchLink>, 1989<br /><searchLink fieldCode="AR" term="%22Berger%2C+Thorsten%22">Berger, Thorsten</searchLink>, 1981<br /><searchLink fieldCode="AR" term="%22Pelliccione%2C+Patrizio%22">Pelliccione, Patrizio</searchLink>, 1975
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <i>IEEE Transactions on Intelligent Transportation Systems</i>. 25(8):8641-8654
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22road+traffic%22">road traffic</searchLink><br /><searchLink fieldCode="DE" term="%22Scalability%22">Scalability</searchLink><br /><searchLink fieldCode="DE" term="%22Vehicles%22">Vehicles</searchLink><br /><searchLink fieldCode="DE" term="%22DSL%22">DSL</searchLink><br /><searchLink fieldCode="DE" term="%22Vehicle+dynamics%22">Vehicle dynamics</searchLink><br /><searchLink fieldCode="DE" term="%22Testing%22">Testing</searchLink><br /><searchLink fieldCode="DE" term="%22simulation%22">simulation</searchLink><br /><searchLink fieldCode="DE" term="%22autonomous+driving%22">autonomous driving</searchLink><br /><searchLink fieldCode="DE" term="%22system+testing%22">system testing</searchLink><br /><searchLink fieldCode="DE" term="%22Trajectory%22">Trajectory</searchLink><br /><searchLink fieldCode="DE" term="%22Roads%22">Roads</searchLink><br /><searchLink fieldCode="DE" term="%22Intelligent+vehicles%22">Intelligent vehicles</searchLink><br /><searchLink fieldCode="DE" term="%22autonomous+vehicles%22">autonomous vehicles</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: Scenario-based testing for automated driving systems (ADS) must be able to simulate traffic scenarios that rely on interactions with other vehicles. Although many languages for high-level scenario modelling have been proposed, they lack the features to precisely and reliably control the required micro-simulation, while also supporting behavior reuse and test reproducibility for a wide range of interactive scenarios. To fill this gap between scenario design and execution, we propose the Simulated Driver-Vehicle (SDV) model to represent and simulate vehicles as dynamic entities with their behavior being constrained by scenario design and goals set by testers. The model combines driver and vehicle as a single entity. It is based on human-like driving and the mechanical limitations of real vehicles for realistic simulation. The model leverages behavior trees to express high-level behaviors in terms of lower-level maneuvers, affording multiple driving styles and reuse. Furthermore, optimization-based maneuver planners guide the simulated vehicles towards the desired behavior. Our extensive evaluation shows the model’s design effectiveness using NHTSA pre-crash scenarios, its motion realism in comparison to naturalistic urban traffic, and its scalability with traffic density. Finally, we show the applicability of our SDV model to test a real ADS and to identify crash scenarios, which are impractical to represent using predefined vehicle trajectories. The SDV model instances can be injected into existing simulation environments via co-simulation.
– Name: Format
  Label: File Description
  Group: SrcInfo
  Data: electronic
– Name: URL
  Label: Access URL
  Group: URL
  Data: <link linkTarget="URL" linkTerm="https://research.chalmers.se/publication/540691" linkWindow="_blank">https://research.chalmers.se/publication/540691</link><br /><link linkTarget="URL" linkTerm="https://research.chalmers.se/publication/540691/file/540691_Fulltext.pdf" linkWindow="_blank">https://research.chalmers.se/publication/540691/file/540691_Fulltext.pdf</link>
PLink https://erproxy.cvtisr.sk/sfx/access?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsswe&AN=edsswe.oai.research.chalmers.se.c0b89c8b.8f9c.42c9.8fdb.8a405630c2d3
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1109/TITS.2024.3373531
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 8641
    Subjects:
      – SubjectFull: road traffic
        Type: general
      – SubjectFull: Scalability
        Type: general
      – SubjectFull: Vehicles
        Type: general
      – SubjectFull: DSL
        Type: general
      – SubjectFull: Vehicle dynamics
        Type: general
      – SubjectFull: Testing
        Type: general
      – SubjectFull: simulation
        Type: general
      – SubjectFull: autonomous driving
        Type: general
      – SubjectFull: system testing
        Type: general
      – SubjectFull: Trajectory
        Type: general
      – SubjectFull: Roads
        Type: general
      – SubjectFull: Intelligent vehicles
        Type: general
      – SubjectFull: autonomous vehicles
        Type: general
    Titles:
      – TitleFull: A Driver-Vehicle Model for ADS Scenario-Based Testing
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Queiroz, Rodrigo
      – PersonEntity:
          Name:
            NameFull: Sharma, Divit
      – PersonEntity:
          Name:
            NameFull: Diniz Caldas, Ricardo
      – PersonEntity:
          Name:
            NameFull: Czarnecki, Krzysztof
      – PersonEntity:
          Name:
            NameFull: García Gonzalo, Sergio
      – PersonEntity:
          Name:
            NameFull: Berger, Thorsten
      – PersonEntity:
          Name:
            NameFull: Pelliccione, Patrizio
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 15249050
            – Type: issn-print
              Value: 15580016
            – Type: issn-locals
              Value: SWEPUB_FREE
            – Type: issn-locals
              Value: CTH_SWEPUB
          Numbering:
            – Type: volume
              Value: 25
            – Type: issue
              Value: 8
          Titles:
            – TitleFull: IEEE Transactions on Intelligent Transportation Systems
              Type: main
ResultId 1