Sharing is Caring: SociallyCompliant Autonomous Intersection Negotiation Current methods for autonomous management use strict firstcome, firstserve (FCFS) ordering to manage incoming autonomous vehicles at an intersection. In this work, we present a coordination policy that swaps agent ordering to increase the systemwide performance while ensuring that the swaps are socially compliant. By considering an agentxe2x80x99s Social Value Orientation (SVO), a social psychology metric for their willingness to help another vehicle, the central coordinator can reduce system delays while ensuring each individual vehicle increases their own utility. The FCFSSVO algorithm is both computationally tractable and accounts for a variety of realworld agent types, such as human drivers and a variety of social orientations. Simulation results show that average vehicle delays decrease with swapping by enabling cooperation between agents. In addition, we show that the proportion of human drivers, as well as, the distribution of prosocial and egoistic vehicles in the system can have a prominent effect on the performance of the system.

Cooperative ScheduleDriven Intersection Control with Connected and Autonomous Vehicles Recent work in decentralized, scheduledriven traffic control has demonstrated the ability to improve the efficiency of traffic flow in complex urban road networks. In this approach, a scheduling agent is associated with each intersection. Each agent senses the traffic approaching its intersection and in realtime constructs a schedule that minimizes the cumulative wait time of vehicles approaching the intersection over the current lookahead horizon. In this paper, we propose a cooperative algorithm that utilizes both connected and autonomous vehicles (CAV) and scheduledriven traffic control to create better traffic flow in the city. The algorithm enables an intersection scheduling agent to adjust the arrival time of an approaching platoon through use of wireless communication to control the velocity of vehicles. The sequence of approaching platoons is thus shifted toward a new shape that has smaller cumulative delay. We demonstrate how this algorithm outperforms the original approach in a realtime traffic signal control problem.