Freeway Traffic Jam Mitigation via Connected Automated Vehicles

Other conference contribution, 2019

We consider the problem of altruistic control of connected automated vehicles (CAVs) on multi-lane highways to mitigate phantom traffic jams resulting from car-following dynamics of human-driven vehicles (HDVs). In most of the existing studies on CAVs in multi-lane settings, vehicle controller design philosophy is based on a selfish driving strategy that exclusively addresses the ego vehicle objectives. To improve overall traffic smoothness, we propose an altruistic control strategy for CAVs that aims to maximize the driving comfort and traffic efficiency of both the ego vehicle and surrounding HDVs. We formulate the problem of altruistic control under a model predictive control (MPC) framework to optimize acceleration and lane change sequences of CAVs. Simulation results demonstrate significant improvements in traffic flow via altruistic CAV actions over selfish strategies.