Real-time optimal intersection control system for automated/cooperative vehicles

Abstract

Automated vehicles (AVs) are an emerging technology in the automotive industry. The numerous research efforts that are being dedicated to the development of these systems makes them achievable in the near future. The need to make this technology mature is justified by potential safety gains from the elimination of human error, the enhancement of mobility through the reduction of congestion, and the protection of the environment through the reduction in vehicle emissions. Algorithms are needed to deliver optimal and/or sub-optimal solutions for situations and/or scenarios that AVs would encounter in the field. In this paper, an attempt to optimize the movement of AVs through intersections is developed. The developed model is a real-time optimization problem subjected to dynamic constraints (i.e., ordinary differential equations governing the motion of a vehicle) and static constraints (i.e., maximum achievable velocities). By virtue of the Lagrangian formulation used in Pontryagin’s minimum principle and convex optimization, the solution that minimizes the trip time is obtained. This logic is simulated and compared to the operation of a roundabout, an all-way stop sign, and a traffic-signal-controlled intersection. The results demonstrate that a 55% reduction in delay is achievable compared to the best of these three intersection control strategies, on average. An interesting byproduct of this new logic is a 43% reduction in fuel consumption (reduction from an average of 200 mL to 115 mL) and CO2 emissions (a reduction from 445 g for the roundabout to 265 g).