Abstract

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.