Generating Critical Test Scenarios for Automated Vehicles with Evolutionary Algorithms

Klischat, Moritz; Althoff, Matthias

doi:10.1109/ivs.2019.8814230

Cited by 124 publications

(89 citation statements)

References 18 publications

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“…3. Figure 3 shows that outputs of the STM are concrete scenarios which could complement the accident database and can be used for parameter identification as in [20] and [21]. Concrete scenarios are well described in [22].…”

Section: B Test Methods Descriptionmentioning

confidence: 99%

Stress Testing Method for Scenario-Based Testing of Automated Driving Systems

Nalic

Eichberger

et al. 2020

IEEE Access

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Section: B Test Methods Descriptionmentioning

confidence: 99%

Stress Testing Method for Scenario-Based Testing of Automated Driving Systems

Nalic

Eichberger

et al. 2020

IEEE Access

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“…The generation of critical scenarios from complex urban scenarios is the focus of [116], [117]. The criticality of a scenario is calculated based on the area that can be used safely by the AV.…”

Section: B Criticality-based Selectionmentioning

confidence: 99%

“…This is done by adapting the behavior of the surrounding traffic participants. The definition of criticality used in [116], [117] differs from the definition used in other publications, because criticality is not dependent on the performance of the AV, which is similar to complexity in other publications. A validation of whether the generated scenarios in [116], [117] also lead to critical situations is not performed.…”

Section: B Criticality-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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“…Parameter regions for critical scenarios based on constraint satisfaction are computed in [29]. In our previous work, we presented an optimizationbased method to increase the criticality of initially uncritical traffic scenarios [30], [31] by decreasing the space of possible solutions for the vehicle under test, called the drivable area.…”

Section: A Related Workmentioning

confidence: 99%

Scenario Factory: Creating Safety-Critical Traffic Scenarios for Automated Vehicles

Klischat

Liu

Holtke

et al. 2020

2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)

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The safety validation of motion planning algorithms for automated vehicles requires a large amount of data for virtual testing. Currently, this data is often collected through real test drives, which is expensive and inefficient, given that only a minority of traffic scenarios pose challenges to motion planners. We present a workflow for generating a database of challenging and safety-critical test scenarios that is not dependent on recorded data. First, we extract a large variety of road networks across the globe from OpenStreetMap. Subsequently, we generate traffic scenarios for these road networks using the traffic simulator SUMO. In the last step, we increase the criticality of these scenarios using nonlinear optimization. Our generated scenarios are publicly available on the CommonRoad website.

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Generating Critical Test Scenarios for Automated Vehicles with Evolutionary Algorithms

Cited by 124 publications

References 18 publications

Stress Testing Method for Scenario-Based Testing of Automated Driving Systems

Stress Testing Method for Scenario-Based Testing of Automated Driving Systems

Survey on Scenario-Based Safety Assessment of Automated Vehicles

Scenario Factory: Creating Safety-Critical Traffic Scenarios for Automated Vehicles

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