Resolving conflict in decision-making for autonomous driving

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

Abstract / Description of output

Recent work on decision-making and planning for autonomous driving has made use of game theoretic methods to model interaction between agents. We demonstrate that methods based on the Stackelberg game formulation of this problem are susceptible to an issue that we refer to as Conflict. Our results show that when Conflict occurs, it can cause sub-optimal and potentially dangerous behaviour. In response, we develop a theoretical framework for analysing the extent to which such methods are impacted by Conflict, and apply this framework to several existing approaches modelling interaction between agents. Moreover, we propose Augmented Altruism, a novel approach to modelling interaction between players in a Stackelberg game, and show that it is less prone to Conflict than previous techniques. Finally, we investigate the behavioural assumptions that underpin our approach by performing experiments with human participants. The results show that our model approximates human decision-making more accurately than existing game-theoretic models of interactive driving.
Original languageEnglish
Title of host publicationRobotics: Science and Systems XVII
EditorsDylan A. Shell, Marc Toussaint, M. Ani Hsieh
Place of PublicationVirtual
PublisherThe Robotics: Science and Systems Foundation
Number of pages11
ISBN (Electronic)978-0-9923747-7-8
Publication statusPublished - 12 Jul 2021
EventRobotics: Science and Systems 2021 - Online
Duration: 12 Jul 202116 Jul 2021

Publication series

NameRobotics: Science and Systems Proceedings
ISSN (Electronic)2330-765X


ConferenceRobotics: Science and Systems 2021
Abbreviated titleR:SS 2021
Internet address


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