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From operational design domain to test cases: A methodology to include harsh weather: [version 1; peer review: 1 approved with reservations]
RISE Research Institutes of Sweden, Safety and Transport, Electrification and Reliability.ORCID iD: 0000-0003-4069-6252
University of Warwick, UK.
University of Warwick, UK.
University of Warwick, UK.
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2024 (English)In: Open Research Europe, Vol. 4, article id 238Article in journal (Refereed) Published
Abstract [en]

[Background] To gain widespread use, assisted and automated driving (AAD) systems will have to cope with harsh weather conditions, such as rain, fog, and snow. This affects the development and testing of perception and decision-making systems. Since the weather cannot be controlled in field tests, the availability and use of virtual simulation and test facilities that can accurately reproduce harsh weather becomes vital. Test cases subjecting the system under test to harsh conditions, covering all expected weather phenomena in both typical and challenging scenarios, must be defined to evaluate all aspects of the system. [Methods] State-of-the-art in scenario-based and hash weather testing for AAD systems was analysed; based on the analysis, a team with diverse expertise in AAD development and testing defined a methodology for defining a set of harsh weather test cases. [Results] This paper proposes, and exemplifies the use of, a methodology to develop a representative set of test cases based on the defined operational design domain and use cases for an AAD system under development, considering the possibility of reproducing tests in different test environments with a focus on harsh weather. [Conclusions] We believe that our proposed methodology can accelerate the overall testing process and contribute to the difficult safety assurance challenges for automated vehicles.

Place, publisher, year, edition, pages
2024. Vol. 4, article id 238
Keywords [en]
Automated driving, operational design domain, test scenario, harsh weather testing
National Category
Robotics and automation Embedded Systems
Identifiers
URN: urn:nbn:se:ri:diva-76267OAI: oai:DiVA.org:ri-76267DiVA, id: diva2:1921048
Projects
ROADVIEW - Robust Automated Driving in Extreme Weather
Funder
EU, Horizon 2020, 101069576
Note

Funding: EU Horizon

Available from: 2024-12-13 Created: 2024-12-13 Last updated: 2025-02-05Bibliographically approved

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fulltext(2343 kB)24 downloads
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Type fulltextMimetype application/pdf

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Open Research Europe - Full text

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Warg, Fredrik

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