Controlling Lane-Free Signal-Free Intersections via Model Predictive Control

Abstract

The operation of signal-free intersections, where connected automated vehicles (CAVs) cross simultaneously for all origin-destination (OD) movements, has the potential to greatly increase throughput and decrease fuel consumption. Since the intersection crossing areas naturally include no lanes, an extended crossing area, appropriately delineated, can be considered as a lane-free infrastructure so as to enable further improved exploitation. This paper presents a Model Predictive Control (MPC) scheme to manage CAVs on a signal-free and lane-free intersection. In fact, the control inputs of all vehicles are optimized over a time-horizon by online solving of a joint optimal control problem (OCP) that minimizes a cost function including proper terms to ensure smooth and collision-free vehicle motion, while also considering fuel consumption and desiredspeed tracking, when possible. An efficient and fast Feasible Direction Algorithm is employed to solve the introduced OCP numerically. Simulation results verify the effectiveness of the presented approach and its computational feasibility as a real-time scheme.