Optimization based coordination of autonomous vehicles in confined areas

Abstract

Confined areas present an opportunity for early deployment of autonomous vehicles (AV) due to the absence of non-controlled traffic participants. In this paper, we present an approach for coordination of multiple AVs in confined sites. The method computes speed-profiles for the AVs such that collisions are avoided in cross-intersection and merge crossings. Specifically, this is done through the solution of an optimal control problem where the motion of all vehicles is optimized jointly. The order in which the vehicles pass the crossings is determined through the solution of a Mixed Integer Quadratic Program (MIQP). Through simulation results, we demonstrate the capability of the algorithm in terms of performance and satisfaction of collision avoidance constraints.

A Two-Stage MIQP-Based Optimization Approach for Coordinating Automated Electric Vehicles in Confined Sites

“…In our previous work [31] and [32], we proposed optimization-based heuristics to coordinate vehicles in confined sites, ensuring conflict avoidance in all MUTEX zones. This paper introduces a control strategy that extends the optimal control formulation from [32] to address the inclusion of charging zone MUTEX constraints.…”

“…As explained in [31], [32], finding a solution to MINLP problems is known to be difficult, especially when the constraints or the objective function are non-convex [37]. Therefore, a common procedure is to apply an approach where the integer part of the solution is obtained first using a heuristic, and the continuous part of the solution thereafter is obtained by solving the nonlinear program (NLP) that results from fixing the integers to the values found with the heuristic.…”