Evaluating pedestrian interaction preferences with a game theoretic autonomous vehicle in virtual reality. (April 2021)

• Record Type: Journal Article
• Authors: Camara, Fanta; Dickinson, Patrick; Fox, Charles
• Is Part Of: Transportation research. Volume 78(2021)
• Page Start: 410
• Page End: 423
• Publication Date: 2021-04
• Subjects: Autonomous vehicles -- Pedestrian crossing behaviour -- Interactions -- Game theory -- Human factors; Automobile drivers -- Psychology -- Periodicals; Automobile driving -- Psychological aspects -- Periodicals; Transportation -- Psychological aspects -- Periodicals; 629.283019
• DOI: 10.1016/j.trf.2021.02.017
• Languages: English
• ISSNs: 1369-8478

Abstract

Highlights: Pedestrian crossing behaviour with a game theoretic autonomous vehicle (AV). Paper shows the importance of virtual reality (VR) for pedestrian behaviour study. First attempt to evaluate quantitatively pedestrian interaction preferences in VR. A new method to infer specific numerical values for AV interaction control software. Development and testing of autonomous vehicle algorithms in VR. Abstract: Localisation and navigation of autonomous vehicles (AVs) in static environments are now solved problems, but how to control their interactions with other road users in mixed traffic environments, especially with pedestrians, remains an open question. Recent work has begun to apply game theory to model and control AV-pedestrian interactions as they compete for space on the road whilst trying to avoid collisions. But this game theory model has been developed only in unrealistic lab environments. To improve their realism, this study empirically examines pedestrian behaviour during road crossing in the presence of approaching autonomous vehicles in more realistic virtual reality (VR) environments. The autonomous vehicles are controlled using game theory, and this study seeks to find the best parameters for these controls to produce comfortable interactions for the pedestrians. In a first experiment, participants' trajectories reveal a more cautious crossing behaviour in VR than in previous laboratory experiments. In two further experiments, a gradient descent approach is used to investigate participants' preference for AV driving style. The results show that the majority of participants were not expecting the AV to stop in some scenarios, and there was no change in their crossing behaviour in two environments and with different car models suggestive of car and last-mile style vehicles. These results provide some initial estimates for game theoretic parameters needed by future AVs in their pedestrian interactions and more generally show how such parameters can be inferred from virtual reality experiments.