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Connected Automated Driving: A Model-Based Approach to the Analysis of Basic Awareness Services

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Version 2 2021-01-19, 09:30
Version 1 2020-07-21, 13:50
conference contribution
posted on 2021-01-19, 09:30 authored by Hugo Araujo, Ties Hoenselaar, Mohammad reza Mousavi, Alexey Vinel
Cooperative awareness basic services are key components of several Connected Autonomous Vehicles (CAV) functions. We present a rigorous approach to the analysis of cooperative awareness basic services in a CAV setup. Our approach addresses a major challenge in the traditional analysis techniques of such services, namely, coming up with effective scenarios that can meaningfully cover their various behaviours, exercise the limits of these services and come up with a quantitative means for design-space exploration.Our approach integrates model-based testing and search-based testing to automatically generate scenarios and steer the scenario generation process towards generating inputs that can lead to the most severe hazards. Additionally we define other objectives that maximise the coverage of the model and the diversity of the generated test inputs. The result of applying our technique to the analysis of cooperative awareness services leads to automatically generated hazardous scenarios for parameters that abide by the ETSI ITS-G5 vehicular communications standard. We show that our technique can be used as an effective design-space exploration method and can be used to design adaptive protocols that can mitigate the hazards detected through our initial analysis.

History

Author affiliation

School of Informatics

Source

31st IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 31 August-3 September 2020 // Virtual Conference

Version

  • AM (Accepted Manuscript)

Published in

Proceedings of the 31st IEEE International Symposium on Personal, Indoor and Mobile Radio Communications

Publisher

IEEE

eissn

2166-9589

isbn

978-1-7281-4490-0

Acceptance date

2020-06-20

Copyright date

2020

Available date

2020-10-08

Spatial coverage

London, United Kingdom, United Kingdom

Temporal coverage: start date

2020-08-31

Temporal coverage: end date

2020-09-03

Language

en

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