Test Scenario Design for Intelligent Driving System Ensuring Coverage and Effectiveness

Xia, Qing; Duan, Jianli; Gao, Feng; Hu, Qingmei; He, Yingdong

doi:10.1007/s12239-018-0072-6

Cited by 41 publications

(17 citation statements)

References 9 publications

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“…Instead of focusing on the minimum number of test cases in the covering array, covering array generation methods can also be customized. For example, in [117], [118], [119], [120], the generated covering array fulfills not only the Nwise coverage but also maximizes the overall complexity of all the scenarios.…”

Section: Exploration Methodsmentioning

confidence: 99%

“…Besides the KPIs mentioned above, in order to increase the efficiency of critical scenario detection, complexity can be regarded as an auxiliary property of criticality in some studies [117], [118], [119], [120]. Compared to traditional software testing, critical scenario generation focuses on finding triggering conditions instead of explicit software bugs.…”

Section: Criticality Assessment Methodsmentioning

confidence: 99%

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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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Section: Exploration Methodsmentioning

confidence: 99%

Section: Criticality Assessment Methodsmentioning

confidence: 99%

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

Zhang¹,

Tao²,

Tan³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Several references [118]- [120] develop a procedure that combines combinatorial testing and the definition of complex test scenarios. The complexity is described by a complexity index, which assigns a weighting to each parameter of a scenario, using the Analytic Hierarchy Process.…”

Section: Complexity-based Selectionmentioning

confidence: 99%

Survey on Scenario-Based Safety Assessment of Automated Vehicles

et al. 2020

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When will automated vehicles come onto the market? This question has puzzled the automotive industry and society for years. The technology and its implementation have made rapid progress over the last decade, but the challenge of how to prove the safety of these systems has not yet been solved. Since a market launch without proof of safety would neither be accepted by society nor by legislators, much time and many resources have been invested into safety assessment in recent years in order to develop new approaches for an efficient assessment. This paper therefore provides an overview of various approaches, and gives a comprehensive survey of the so-called scenario-based approach. The scenario-based approach is a promising method, in which individual traffic situations are typically tested by means of virtual simulation. Since an infinite number of different scenarios can theoretically occur in real-world traffic, even the scenario-based approach leaves the question unanswered as to how to break these down into a finite set of scenarios, and find those which are representative in order to render testing more manageable. This paper provides a comprehensive literature review of related safety-assessment publications that deal precisely with this question. Therefore, this paper develops a novel taxonomy for the scenario-based approach, and classifies all literature sources. Based on this, the existing methods will be compared with each other and, as one conclusion, the alternative concept of formal verification will be combined with the scenario-based approach. Finally, future research priorities are derived.

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“…Otherwise, it enters the exploration stage or the exploitation stage based on a specified probability. At the exploration stage, it applies the analytic hierarchy method [112] to determine the importance value of each feature. Each field's importance value is then used to determine the mutation magnitude for that field.…”

Section: Othermentioning

confidence: 99%

A Survey on Scenario-Based Testing for Automated Driving Systems in High-Fidelity Simulation

Zhong¹,

Tang²,

Zhou³

et al. 2021

Preprint

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Automated Driving Systems (ADSS) have seen rapid progress in recent years. To ensure the safety and reliability of these systems, extensive testings are being conducted before their future mass deployment. Testing the system on the road is the closest to real-world and desirable approach, but it is incredibly costly. Also, it is infeasible to cover rare corner cases using such real-world testing. Thus, a popular alternative is to evaluate an ADS's performance in some well-designed challenging scenarios, a.k.a. scenario-based testing. High-fidelity simulators have been widely used in this setting to maximize flexibility and convenience in testing what-if scenarios. Although many works have been proposed offering diverse frameworks/methods for testing specific systems, the comparisons and connections among these works are still missing. To bridge this gap, in this work, we provide a generic formulation of scenario-based testing in high-fidelity simulation and conduct a literature review on the existing works. We further compare them and present the open challenges as well as potential future research directions.

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Test Scenario Design for Intelligent Driving System Ensuring Coverage and Effectiveness

Cited by 41 publications

References 9 publications

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

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

Survey on Scenario-Based Safety Assessment of Automated Vehicles

A Survey on Scenario-Based Testing for Automated Driving Systems in High-Fidelity Simulation

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