Studying the Impact of Semi-Cooperative Drivers on Overall Highway Flow
This work addresses traffic flow optimization for autonomous driving systems by modeling semi-cooperative behaviors, but it is incremental as it builds on existing game-theoretic methods.
The study investigated how the proportion of prosocial agents affects traffic flow in semi-cooperative driving scenarios, finding that it has a minor impact overall and disproportionately benefits egoistic and high-speed drivers.
Semi-cooperative behaviors are intrinsic properties of human drivers and should be considered for autonomous driving. In addition, new autonomous planners can consider the social value orientation (SVO) of human drivers to generate socially-compliant trajectories. Yet the overall impact on traffic flow for this new class of planners remain to be understood. In this work, we present study of implicit semi-cooperative driving where agents deploy a game-theoretic version of iterative best response assuming knowledge of the SVOs of other agents. We simulate nominal traffic flow and investigate whether the proportion of prosocial agents on the road impact individual or system-wide driving performance. Experiments show that the proportion of prosocial agents has a minor impact on overall traffic flow and that benefits of semi-cooperation disproportionally affect egoistic and high-speed drivers.