Strategies for Negotiation between Autonomous Vehicles and Pedestrians

Franz Keferböck, Andreas Riener

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

Abstract

Autonomous cars seem on the verge to reality, with vehicle manufacturers presenting their first prototypes and the topic of self-driving vehicles being discussed in mass media. Until now, in individual traffic humans covered distances from A to B using a personal car or a motorcycle, riding a bike or walking by foot (from strongest to weakest modality). All these modalities coexist in parallel in typical traffic situations, and it should be clear that different situations require clarification and communication between the different road participants, e.g., to negotiate who has right of way and who has to wait. Many drivers spend a considerable time each day in their car – for commuting, shopping, and traveling. In order to save time for the driver it is expected that manual driving will be eliminated in the near future and replaced by automated systems. One of the problems not brought up by autonomous vehicle manufacturers so far is when the „strongest“ road user (vehicle or truck) is no longer human-driven, as then the chance for vulnerable road users (VRUs) to communicate, interact and negotiate could be evicted too. In this work, based on the showcase of Mercedes Benz’s F015 at CES this year, we want to show that it is important to substitute the means of pedestrian-vehicle communication by autonomous cars to understand the signs and gestures of pedestrians and also communicating actively (e.g., using visual feedback on windscreen, bonnet or headlights) towards them. ...
Original languageEnglish
Title of host publicationMensch und Computer 2015, September 6-9, 2015, Stuttgart, Germany, Workshop Automotive HMI
Editors S. Geisler, A. van Laack, S. Wolter, A. Riener, B. Pfleging
Number of pages8
Publication statusPublished - Sept 2015

Fields of science

  • 102 Computer Sciences
  • 102009 Computer simulation
  • 102013 Human-computer interaction
  • 102019 Machine learning
  • 102021 Pervasive computing
  • 102022 Software development
  • 102025 Distributed systems

JKU Focus areas

  • Computation in Informatics and Mathematics
  • Engineering and Natural Sciences (in general)

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