Collaborative Analysis Framework of Safety and Security for Autonomous Vehicles

J. Cui, G. Sabaliauskaite, L.S. Liew, Fengjun Zhou, B. Zhang

Research output: Contribution to journalArticle

1 Citation (Scopus)
5 Downloads (Pure)

Abstract

Human error has been statistically proven to be the primary cause of road accidents. This undoubtedly is a contributory cause of the rising popularity of autonomous vehicles as they are presumably able to maneuver appropriately/optimally on the roads while diminishing the likelihood of human error and its repercussion. However, autonomous vehicles are not ready for widespread adoption because their safety and security issues are yet to be thoroughly investigated/addressed. Little literature could be found on collaborative analysis of safety and security of autonomous vehicles. This paper proposes a framework for analyzing both safety and security issues, which includes an integrated safety and security method (S&S) with international vehicle safety and security standards ISO 26262 and SAE J3061. The applicability of the proposed framework is demonstrated using an example of typical autonomous vehicle model. Using this framework, one can clearly understand the vehicle functions, structure, the associated failures and attacks, and also see the vulnerabilities that are not yet addressed by countermeasures, which helps to improve the in-vehicle safety and security from researching and engineering perspectives.
Original languageEnglish
Pages (from-to)148672 - 148683
Number of pages12
JournalIEEE Access
Volume7
DOIs
Publication statusPublished - 11 Oct 2019
Externally publishedYes

Bibliographical note

This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/

Keywords

  • Autonomous vehicle
  • safety
  • security
  • ISO 26262
  • SAE J3061
  • SAE J3016

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