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A Driver-Vehicle Model for ADS Scenario-Based Testing

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Názov: A Driver-Vehicle Model for ADS Scenario-Based Testing
Autori: Queiroz, Rodrigo, Sharma, Divit, Diniz Caldas, Ricardo, 1994, Czarnecki, Krzysztof, García Gonzalo, Sergio, 1989, Berger, Thorsten, 1981, Pelliccione, Patrizio, 1975
Zdroj: IEEE Transactions on Intelligent Transportation Systems. 25(8):8641-8654
Predmety: road traffic, Scalability, Vehicles, DSL, Vehicle dynamics, Testing, simulation, autonomous driving, system testing, Trajectory, Roads, Intelligent vehicles, autonomous vehicles
Popis: 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.
Popis súboru: electronic
Prístupová URL adresa: https://research.chalmers.se/publication/540691
https://research.chalmers.se/publication/540691/file/540691_Fulltext.pdf
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  Data: A Driver-Vehicle Model for ADS Scenario-Based Testing
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  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
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  Data: <i>IEEE Transactions on Intelligent Transportation Systems</i>. 25(8):8641-8654
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  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.
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        Value: 10.1109/TITS.2024.3373531
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      – Text: English
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        PageCount: 14
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    Subjects:
      – SubjectFull: road traffic
        Type: general
      – SubjectFull: Scalability
        Type: general
      – SubjectFull: Vehicles
        Type: general
      – SubjectFull: DSL
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      – SubjectFull: Vehicle dynamics
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      – SubjectFull: Testing
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      – SubjectFull: simulation
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      – SubjectFull: autonomous driving
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      – SubjectFull: system testing
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      – SubjectFull: Trajectory
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      – SubjectFull: Roads
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      – SubjectFull: Intelligent vehicles
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      – SubjectFull: autonomous vehicles
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      – TitleFull: A Driver-Vehicle Model for ADS Scenario-Based Testing
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              Y: 2024
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