A Methodology for Safety Assessment of Highly Automated Vehicles

Jinwei Zhou

Research output: ThesisDoctoral thesis

Abstract

Autonomous driving represents a technological leap forward that will likely solve key aspects of the transport problem and so have beneficial effects for some ciritical social and ecological issues as well. However, testing and validation of the Highly Automated Vehicle (HAV), so as to guarantee safety, is one of the most challenging tasks that still prevent the HAV from commercial release. As HAVs will include many functions which can be updated frequently and require re-evaluation in short time, fast re-evaluations will be needed to prevent new dangers arising from the updates. This research work is focused on developing such a methodology. The key idea is to replace on-road testing – well defined testing method for classical vehicles – by accident statistics and to use model based methods as well as Design of Experiments to determine a limited set of cases to be tested.
Original languageEnglish
Publication statusPublished - 2019

Fields of science

  • 206002 Electro-medical engineering
  • 207109 Pollutant emission
  • 202 Electrical Engineering, Electronics, Information Engineering
  • 202027 Mechatronics
  • 202034 Control engineering
  • 203027 Internal combustion engines
  • 206001 Biomedical engineering

JKU Focus areas

  • Digital Transformation
  • Sustainable Development: Responsible Technologies and Management

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