An adaptive system for autonomous driving

Martin Zimmermann, Franz Wotawa*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Having systems that can adapt themselves in case of faults or changing environmental conditions is of growing interest for industry and especially for the automotive industry considering autonomous driving. In autonomous driving, it is vital to have a system that is able to cope with faults in order to enable the system to reach a safe state. In this paper, we present an adaptive control method that can be used for this purpose. The method selects alternative actions so that given goal states can be reached, providing the availability of a certain degree of redundancy. The action selection is based on weight models that are adapted over time, capturing the success rate of certain actions. Besides the method, we present a Java implementation and its validation based on two case studies motivated by the requirements of the autonomous driving domain. We show that the presented approach is applicable both in case of environmental changes but also in case of faults occurring during operation. In the latter case, the methods provide an adaptive behavior very much close to the optimal selection.

Original languageEnglish
Pages (from-to)1189-1212
Number of pages24
JournalSoftware Quality Journal
Issue number3
Early online date1 Jan 2020
Publication statusPublished - 1 Sept 2020


  • 68T05
  • Adaptive control
  • Self-adaptive systems
  • Validation using simulation

ASJC Scopus subject areas

  • Software
  • Safety, Risk, Reliability and Quality


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