Time to Arrival as Predictor for Uncertainty and Cooperative Driving Decisions in Highly Automated Driving

Linda Miller, Jasmin Leitner, Johannes Kraus, Jieun Lee, Tatsuru Daimon, Satoshi Kitazaki, Martin Baumann

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Due to the technical advances of automated vehicles (AVs), new uncertainties for human road users arise. To overcome these uncertainties, driving strategies of AVs might be aligned to human interaction styles. In vehicle-vehicle interactions, driving behavior is informed by remaining time gaps between vehicles. This video-based experiment investigated the influence of gap sizes and the measurement method on driving decisions. N=32 participants experienced a highly automated drive in which their AV approached narrow passages. The time to arrival (TTA) of the oncoming traffic was varied. Participants had to decide to drive first or second, indicate their decision certainty, and the situation's criticality. The videos were presented in ascending, descending, and random order. Moreover, participants adjusted the TTA at which they would drive first and second. The results indicated a higher probability of driving first and lower criticality with increasing TTA. Decision certainty was lowest around the 50% threshold, while longer and shorter TTAs resulted in higher certainty. Results differed between the methods. The findings provide guidance for the design of automated systems to mimic human driving behavior.

Original languageEnglish
Title of host publication2022 IEEE Intelligent Vehicles Symposium, IV 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781665488211
Publication statusPublished - 2022
Event2022 IEEE Intelligent Vehicles Symposium, IV 2022 - Aachen, Germany
Duration: 2022 Jun 52022 Jun 9

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings


Conference2022 IEEE Intelligent Vehicles Symposium, IV 2022

ASJC Scopus subject areas

  • Computer Science Applications
  • Automotive Engineering
  • Modelling and Simulation


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