Virtual Assessment of Automated Driving: Methodology, Challenges, and Lessons Learned

Wagner, Sebastian; Knoll, Alois; Groh, Korbinian; Kühbeck, Thomas; Watzenig, Daniel; Eckstein, Lutz

doi:10.4271/12-02-04-0020

Cited by 9 publications

(10 citation statements)

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“…There are two types of concrete → concrete methods. The first type refines a concrete scenario to make it more critical by tuning its parameters [47], [57], [65], [71], [91], [118], [119], [124]. These methods can be found in Sections 6.1, 6.2 and 6.5.…”

Section: Level Of Abstractionmentioning

confidence: 99%

Finding Critical Scenarios for Automated Driving Systems: A Systematic Mapping Study

Zhang¹,

Tao²,

Tan

et al. 2023

IIEEE Trans. Software Eng.

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Scenario-based approaches have been receiving a huge amount of attention in research and engineering of automated driving systems. Due to the complexity and uncertainty of the driving environment, and the complexity of the driving task itself, the number of possible driving scenarios that an Automated Driving System or Advanced Driving-Assistance System may encounter is virtually infinite. Therefore it is essential to be able to reason about the identification of scenarios and in particular critical ones that may impose unacceptable risk if not considered. Critical scenarios are particularly important to support design, verification and validation efforts, and as a basis for a safety case. In this paper, we present the results of a systematic mapping study in the context of autonomous driving. The main contributions are: (i) introducing a comprehensive taxonomy for critical scenario identification methods; (ii) giving an overview of the state-of-the-art research based on the taxonomy encompassing 86 papers between 2017 and 2020; and (iii) identifying open issues and directions for further research. The provided taxonomy comprises three main perspectives encompassing the problem definition (the why), the solution (the methods to derive scenarios), and the assessment of the established scenarios. In addition, we discuss open research issues considering the perspectives of coverage, practicability, and scenario space explosion.

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Section: Level Of Abstractionmentioning

confidence: 99%

Finding Critical Scenarios for Automated Driving Systems: A Systematic Mapping Study

Zhang¹,

Tao²,

Tan

et al. 2023

IIEEE Trans. Software Eng.

View full text Add to dashboard Cite

show abstract

“…There are two types of concrete → concrete methods. The first type refines a concrete scenario to make it more critical by tuning its parameters [47], [57], [65], [71], [88], [115], [116], [121]. These methods can be found in Sections 6.1, 6.2 and 6.5.…”

Section: Level Of Abstractionmentioning

confidence: 99%

“…On the other hand, for optimization or learning-based methods, diversity can be considered part of either the objective or the constraint. The diversity can be realized either by examining the distance among scenarios [77], or by exploring multiple local minima [88], [95]. For the latter approach, Wagner et al [88] extracted key features from critical scenarios by principal component analysis (PCA) and added noise in a lower-dimensional component space to reconstruct more varied critical scenarios.…”

Section: Coveragementioning

confidence: 99%

“…The diversity can be realized either by examining the distance among scenarios [77], or by exploring multiple local minima [88], [95]. For the latter approach, Wagner et al [88] extracted key features from critical scenarios by principal component analysis (PCA) and added noise in a lower-dimensional component space to reconstruct more varied critical scenarios. Gangopadhyay et al [95] applied Bayesian Optimization to identify multiple minima regions from a non-convex function, where critical scenarios are situated in minima regions.…”

Section: Coveragementioning

confidence: 99%

“…Database: All primary studies referring to the database in this cluster employ it to analyze parameter distribution as prior knowledge. Based on our findings, we cluster the database into three types: naturalistic driving data [86], [87], [88], [106], traffic flow data [53], [79] and collision accident data [104]. It is worth noting that NDS databases exclusive to autonomous driving (e.g., Safety Pool) are available but have not been found applied in the field of this cluster.…”

Section: Required Informationmentioning

confidence: 99%

See 2 more Smart Citations

Finding Critical Scenarios for Automated Driving Systems: A Systematic Literature Review

Zhang¹,

Tao²,

Tan³

et al. 2021

Preprint

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Scenario-based approaches have been receiving a huge amount of attention in research and engineering of automated driving systems. Due to the complexity and uncertainty of the driving environment, and the complexity of the driving task itself, the number of possible driving scenarios that an ADS or ADAS may encounter is virtually infinite. Therefore it is essential to be able to reason about the identification of scenarios and in particular critical ones that may impose unacceptable risk if not considered. Critical scenarios are particularly important to support design, verification and validation efforts, and as a basis for a safety case. In this paper, we present the results of a systematic literature review in the context of autonomous driving. The main contributions are: (i) introducing a comprehensive taxonomy for critical scenario identification methods; (ii) giving an overview of the state-of-the-art research based on the taxonomy encompassing 86 papers between 2017 and 2020; and (iii) identifying open issues and directions for further research. The provided taxonomy comprises three main perspectives encompassing the problem definition (the why), the solution (the methods to derive scenarios), and the assessment of the established scenarios. In addition, we discuss open research issues considering the perspectives of coverage, practicability, and scenario space explosion.

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Methods for Improving the Accuracy of the Virtual Assessment of Autonomous Driving

Notz

Sigl

Kühbeck

et al. 2019

2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)

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Virtual Assessment of Automated Driving: Methodology, Challenges, and Lessons Learned

Cited by 9 publications

References 0 publications

Finding Critical Scenarios for Automated Driving Systems: A Systematic Mapping Study

Finding Critical Scenarios for Automated Driving Systems: A Systematic Mapping Study

Finding Critical Scenarios for Automated Driving Systems: A Systematic Literature Review

Methods for Improving the Accuracy of the Virtual Assessment of Autonomous Driving

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