Conflict Simulation for Shared Autonomy in Autonomous Driving

Stefan Reitmann, Elin Anna Topp, Tsvetomila Mihaylova, Ville Kyrki

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

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We present a tool for modeling conflict situations that enables simulation and testing of situation awareness in shared autonomy, in this case in an autonomous driving scenario. The flexibility of the tool allows definition of new conflict situations, integration with various control and conflict detection systems, as well as customization of Takeover Request (TOR) signals and different means of communication to the human operator. We start with one particular conflict situation - loss of lane markings, for which we demonstrate a simple conflict detection system. We conduct a preliminary user evaluation, which provides useful insights about the usability of the tool. The feedback from the participants indicates that TORs without indication feel uncomfortable and providing explicit information about the conflict situation is necessary when switching to manual control is required.

Original languageEnglish
Title of host publicationHRI 2024 Companion - Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction
Number of pages6
ISBN (Electronic)9798400703232
Publication statusPublished - 11 Mar 2024
MoE publication typeA4 Conference publication
EventACM/IEEE International Conference on Human-Robot Interaction - Boulder, United States
Duration: 11 Mar 202415 Mar 2024

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
ISSN (Electronic)2167-2148


ConferenceACM/IEEE International Conference on Human-Robot Interaction
Abbreviated titleHRI
Country/TerritoryUnited States


  • autonomous driving
  • conflict detection
  • driving simulation
  • explainability
  • Human-AI interaction
  • shared autonomy


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