Increasing Traffic Throughput by Controlling Autonomous Vehicles at Low Penetration Rates

Human drivers may behave in an imprecise/unstable manner, leading to traffic oscillations which are harmful to traffic throughput. Recent field experiments have shown that the control of a single autonomous vehicle (AV) can increase traffic throughput on a circular test track, as well as reduce traffic oscillations on straight roads. We consider a mixed traffic environment consisting of humans and autonomous vehicles, where the goal is to find a control policy for the autonomous vehicles which maximizes traffic throughput by preventing oscillations in speed. We formulate this problem as an optimization problem which can be solved using gradient based optimization. Numerical experiments on a circular road show that the optimized control policy improves traffic throughput by 28%.