Developing an Optimal Intersection Control System for Automated Connected Vehicles

In recent years, automated vehicles (AVs) are emerging as a realistic and viable option. Consequently, substantial research efforts are being dedicated to the development of systems and technologies for the field implementation of AVs. One of the challenges researchers need to address is how to optimize the movement of AVs through roadway intersections. In this paper, an attempt to address this need is introduced. The developed model is an optimization problem subjected to dynamical constraints (i.e., ordinary differential equations governing the motion of a vehicle) and static constraints (i.e., maximum achievable velocities). By virtue of Pontryagin's minimum principle, the solution that minimizes the trip time is obtained. Given the problem parameters, the solution to the formulated problem is expected to be the true optimum and delivers the lowest possible delay that satisfies the previously mentioned constraints. This logic is simulated and compared with the operation of a roundabout, a stop sign, and a traffic signal-controlled intersection. The results demonstrate that an 80% reduction in delay is achievable compared with the best of these three intersection control strategies, on average. An interesting byproduct of this new logic is a reduction in vehicular fuel consumption and CO2 emissions by 42.5% and 40%, respectively.