Online Safety Assessment of Automated Vehicles Using Silent Testing

Cheng Wang, Kai Storms, Hermann Winner

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Safety validation is a challenge for releasing automated driving, even though substantial effort has been made in this field. This paper proposes an online safety validation method within the frame of virtual assessment of automation in field operation (VAAFO). The basic idea of VAAFO is that a virtual automated vehicle runs in the background, while the physical vehicle is driven in an automated or manual mode. The virtual automated vehicle receives input from real sensors, but has no access to the actuators. Thus, the risk-free nature of simulation-based testing and the validity of field operational testing are combined. The testing of automated vehicles is accelerated by applying the approach in customer vehicles. In this paper, we elaborate on and implement this approach. Essential parameters are studied and specified, while the necessary coordinate transformation is performed. Triggers are defined and concretized by a newly developed criticality index. Two derived simulated cases and a real-world case are utilized to illustrate the VAAFO approach. The study cases show that the safety of automated vehicles can be assessed online and critical scenarios can be discovered by the defined triggers under the framework of VAAFO. The results demonstrate that the proposed approach is able to safely and efficiently test automated vehicles online under real driving conditions and discover unknown unsafe scenarios.
Original languageEnglish
Pages (from-to)13069-13083
Number of pages15
JournalIEEE Transactions on Intelligent Transportation Systems
Volume23
Issue number8
Early online date26 Oct 2021
DOIs
Publication statusPublished - 1 Aug 2022

Keywords / Materials (for Non-textual outputs)

  • Automated vehicle
  • online verification
  • safety assessment
  • vehicle safety

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