Overcoming Challenges of Validation Automated Driving and Identification of Critical Scenarios

Wang, Cheng; Winner, Hermann

doi:10.1109/itsc.2019.8917045

Cited by 17 publications

(5 citation statements)

References 18 publications

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“…Previous research developed an approach to conduct a passive form of real-world testing for ADS assessment. In this approach, the automated driving function is installed in an actual testing vehicle and provided with the real-world inputs of the sensors, without access to the actuators of the test vehicle, i.e., the so-called shadow mode testing [10]. The system's performance can then be evaluated based on its decisions toward real traffic situations.…”

Section: B Related Workmentioning

confidence: 99%

Defining Reasonably Foreseeable Parameter Ranges Using Real-World Traffic Data for Scenario-Based Safety Assessment of Automated Vehicles

et al. 2022

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This work was supported by the Ministry of Economy, Trade and Industry of Japan through the SAKURA Project (https://www.sakura-prj.go.jp/). This work involved human subjects or animals in its research. Approval of all ethical and experimental procedures and protocols was granted by the Ethical Committee of the Japan Automobile Research Institute under Application No. 20-014 and 21-017, and performed in line with the Code of Ethics and Conduct published by the Japanese Psychological Association.

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Section: B Related Workmentioning

confidence: 99%

Defining Reasonably Foreseeable Parameter Ranges Using Real-World Traffic Data for Scenario-Based Safety Assessment of Automated Vehicles

et al. 2022

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“…Wang and Winner [30] present a method, whereby the automated driving function is executed passively in series production vehicles, which is sometimes known as shadow mode. The driving function is provided with the real inputs of the sensors, but cannot access the actuators of the vehicle.…”

Section: ) Shadow Modementioning

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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“…This approach is based on set invariance, divides the given data into separate groups, and validates each group independently. These solutions aim to improve the accuracy and reliability of critical scenario validation by providing methods for comparing scenarios to real-world data, adjusting them as needed, and evaluating the safety and security of ADS [86], [87], [88].…”

Section: Critical Scenario Validationmentioning

confidence: 99%

Critical Scenario Techniques for Automated Vehicles: Literature Review

Durak¹,

Gupta²,

Akgün³

2023

ASIM WS 2023 Proceedings Langbeiträge

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As Automated Driving Systems (ADS) become more widely used, there is rising worry regarding their safety and security. Traditional verification techniques, such as evaluating the vehicle's performance over a certain number of miles or kilometres, are insufficient to assess ADS risk. Instead, alternate approaches, such as scenario-based testing, which involves assessing the vehicle's performance in simulated situations that match real-world settings, are required to determine the system's safety and performance. This article presents a literature review on the importance of critical scenario analysis in ensuring the safety and reliability of ADS. Critical scenario analysis is a complete approach for identifying, quantifying, prioritising, selecting, and validating the most critical situations for ADS development and testing. ADS can reduce the frequency of accidents and fatalities caused by human error. Through this literature review, readers will understand the importance and benefits of critical scenario analysis methods and approaches, allowing them to systematically evaluate risks and opportunities and better comprehend the potential outcomes of future scenarios.

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Overcoming Challenges of Validation Automated Driving and Identification of Critical Scenarios

Cited by 17 publications

References 18 publications

Defining Reasonably Foreseeable Parameter Ranges Using Real-World Traffic Data for Scenario-Based Safety Assessment of Automated Vehicles

Defining Reasonably Foreseeable Parameter Ranges Using Real-World Traffic Data for Scenario-Based Safety Assessment of Automated Vehicles

Survey on Scenario-Based Safety Assessment of Automated Vehicles

Critical Scenario Techniques for Automated Vehicles: Literature Review

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