Optimal Coordination of Automated Vehicles at Intersections: Theory and Experiments
With the introduction of Cooperative Automated Vehicles, traffic lights can be replaced by coordination algorithms. In this paper, we present a bi-level, model predictive controller for coordination of automated vehicles at intersection. The bi- level controller consists of a coordination level, where intersection occupancy timeslots are allocated, and vehicle-level controllers, where the control commands for the vehicles are computed. We establish persistent feasibility and stability of the bi-level controller under some mild assumptions, and derive conditions under which closed-loop collision avoidance can be ensured with bounded position uncertainty. We thereafter detail an implemen- tation of the coordination controller on a three-vehicle test bed, where the intersection-level optimization problem is solved using a distributed Sequential Quadratic Programming (SQP) method. We present and discuss results from an extensive experimental campaign where the proposed controller was validated. The experimental results indicate the practical applicability of the proposed controller, and validates that safety can be ensured for large positioning uncertainties.
Model Predictive Control
Networked Mobile Systems