Validation of vehicles with automated features through the detection of behavioral differences between humans and machines

DI Manuel Schwarz, Luc Rolland, James Bruce Johnston

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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Abstract

The development of automated vehicles has not achieved the desired success over the past decade, despite numerous technological and methodological successes. Currently, no production-ready autonomous vehicle on the market can operate without a human driver in a wide range of regions and environmental conditions. Due to the high complexity of the systems and the varied traffic scenarios, development, and validation are challenging and time-consuming. With the aid of simulation technology, good validation in a scalable form can be performed during development. However, the current standards for traffic safety validation require a final validation under real conditions. In this work, a framework called Shadow System (SS) is presented, which independently captures the control commands of the human driver and the vehicle. This unique approach enables the detection of problems in automated systems by identifying behavioral differences. Up to a defined safety range allows the human driver and the vehicle to execute control commands without affecting each other. This makes it possible, for example, to determine how a human driver steers the vehicle compared to the automated system in a given traffic situation. The developed method enables safe use under real conditions, as control can be taken over directly by the human driver at any time. Scenarios identified as critical will provide information about the safety of the system during the validation process.

Original languageEnglish
Title of host publication2022 IEEE 28th International Conference on Engineering, Technology and Innovation, ICE/ITMC 2022 and 31st International Association for Management of Technology, IAMOT 2022 Joint Conference - Proceedings
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages1-9
Number of pages9
ISBN (Electronic)9781665488174
ISBN (Print)9781665488181
DOIs
Publication statusPublished - 10 Feb 2023
Event28th IEEE International Conference on Engineering, Technology and Innovation, ICE/ITMC 2022 and 31st International Association for Management of Technology, IAMOT 2022 Joint Conference - Nancy, France
Duration: 19 Jun 202223 Jun 2022

Conference

Conference28th IEEE International Conference on Engineering, Technology and Innovation, ICE/ITMC 2022 and 31st International Association for Management of Technology, IAMOT 2022 Joint Conference
Country/TerritoryFrance
CityNancy
Period19/06/2223/06/22

Keywords

  • autonomous vehicles
  • critical scenarios
  • difference detection
  • human behavior
  • real-world testing
  • road safety
  • vehicle validation

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