Using Extreme Value Theory for Vehicle Level Safety Validation and Implications for Autonomous Vehicles

Åsljung, Daniel; Nilsson, Jonas; Fredriksson, Jonas

doi:10.1109/tiv.2017.2768219

Cited by 81 publications

(39 citation statements)

References 18 publications

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“…An accelerated approach using Extreme Value Theory is presented by Åsljung et al [90], [91]. Based on real data and a criticality metric, the safety level of the system is predicted using near misses.…”

Section: B Sampling From Parameter Distributionsmentioning

confidence: 99%

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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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Section: B Sampling From Parameter Distributionsmentioning

confidence: 99%

“…They note that the prediction depends considerably on the criticality metric used. Their results in [91] show that the Brake Threat Number is a promising criticality metric. According to them, this approach requires 45 times less measurement data than a statistical approach.…”

Section: B Sampling From Parameter Distributionsmentioning

confidence: 99%

Survey on Scenario-Based Safety Assessment of Automated Vehicles

et al. 2020

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“…In the latter, the BM approach was used to analyse the safety of signalised intersections, using data collected with video cameras in 18 locations for 8 h. Some years later, Zheng et al in 2014 [15,16] applied both BM and POT approaches to assess the safety of lane-change manoeuvres in freeways; collecting data with video cameras in 29 locations for ∼3 h. EVT applications to road safety involved the use of driving simulator to collect data, as in the case of Tarko [8], who investigated road departures with POT approach; Farah and Azevedo [3], who analysed head-on collision during passing manoeuvres with both BM and POT approaches; and lastly, Orsini et al [17], who dealt with entering-circulating collisions in roundabouts with both BM and POT approaches. There have also been examples of naturalistic driving experiments, as in the case of Jonasson and Rootzen [18], who analysed rear-end crashes and Asljung et al [19], who analysed the safety of autonomous vehicles.…”

Section: Literature Reviewmentioning

confidence: 99%

Large‐scale road safety evaluation using extreme value theory

Orsini

Gecchele²,

Gastaldi

et al. 2020

IET Intelligent Transport Systems

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“…Recent research has proposed methods aimed at reducing the amount of realworld testing required from manufacturers. Such methods include testing in virtual and hardware-in-the-loop simulations, limiting the scope of real-world testing to safety-critical scenarios, and using threat measures from near-collisions to quantify system safety [1], [30], [35]- [37].…”

Section: Application To Autonomous Vehiclesmentioning

confidence: 99%

Closed-Loop Policies for Operational Tests of Safety-Critical Systems

Morton

Wheeler

Kochenderfer

2018

IEEE Trans. Intell. Veh.

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Manufacturers of safety-critical systems must make the case that their product is sufficiently safe for public deployment. Much of this case often relies upon critical event outcomes from real-world testing, requiring manufacturers to be strategic about how they allocate testing resources in order to maximize their chances of demonstrating system safety. This work frames the partially observable and belief-dependent problem of test scheduling as a Markov decision process, which can be solved efficiently to yield closed-loop manufacturer testing policies. By solving for policies over a wide range of problem formulations, we are able to provide high-level guidance for manufacturers and regulators on issues relating to the testing of safety-critical systems. This guidance spans an array of topics, including circumstances under which manufacturers should continue testing despite observed incidents, when manufacturers should test aggressively, and when regulators should increase or reduce the real-world testing requirements for safety-critical systems.

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Using Extreme Value Theory for Vehicle Level Safety Validation and Implications for Autonomous Vehicles

Cited by 81 publications

References 18 publications

Survey on Scenario-Based Safety Assessment of Automated Vehicles

Survey on Scenario-Based Safety Assessment of Automated Vehicles

Large‐scale road safety evaluation using extreme value theory

Closed-Loop Policies for Operational Tests of Safety-Critical Systems

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