Autonomous driving-A crash explained in detail

Johannes Betz, Alexander Heilmeier, Alexander Wischnewski, Tim Stahl, Markus Lienkamp

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Since 2017, a research team from the Technical University of Munich has developed a software stack for autonomous driving. The software was used to participate in the Roborace Season Alpha Championship. The championship aims to achieve autonomous race cars competing with different software stacks against each other. In May 2019, during a software test in Modena, Italy, the greatest danger in autonomous driving became reality: A minor change in environmental influences led an extensively tested software to crash into a barrier at speed. Crashes with autonomous vehicles have happened before but a detailed explanation of why software failed and what part of the software was not working correctly is missing in research articles. In this paper we present a general method that can be used to display an autonomous vehicle disengagement to explain in detail what happened. This method is then used to display and explain the crash from Modena. Firstly a brief introduction into the modular software stack that was used in the Modena event, consisting of three individual parts-perception, planning, and control-is given. Furthermore, the circumstances causing the crash are elaborated in detail.By presented and explaining in detail which software part failed and contributed to the crash we can discuss further software improvements. As a result, we present necessary functions that need to be integrated in an autonomous driving software stack to prevent such a vehicle behavior causing a fatal crash. In addition we suggest an enhancement of the current disengagement reports for autonomous driving regarding a detailed explanation of the software part that was causing the disengagement. In the outlook of this paper we present two additional software functions for assessing the tire and control performance of the vehicle to enhance the autonomous.

Original languageEnglish
Article number5126
JournalApplied Sciences (Switzerland)
Volume9
Issue number23
DOIs
StatePublished - 1 Dec 2019

Keywords

  • Advanced driver assistance systems (ADAS)
  • Automatic control
  • Autonomous system
  • Autonomous vehicle
  • Intelligent transportation systems
  • Path planning
  • Performance evaluation
  • Vehicle crash

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