Analysis of optimal solutions to robot coordination problems to improve autonomous intersection management policies

The deployment of Cooperative Intelligent Transportation Systems (C-ITS) raises the question of future traffic management systems, which will be operating with an increasing amount of information and control over the infrastructure and the vehicles. This topic of research shares some similarities with robot coordination problems, inspiring our research on autonomous intersection management. In this article, we use a mixed-integer linear programming formulation for time-optimal robots coordination along specified paths and apply it to intersection management for autonomous vehicles. Our formulation allows to simultaneously solve a discrete optimal vehicle ordering problem, and a (discretized) continuous optimal velocity planning problem taking into account kinodynamics constraints. This allows faster pruning of the decision tree for the discrete problem, thus reducing computation time. A possible application for ITS is to evaluate the efficiency loss from a given vehicle ordering policy, or dynamically adapt policies to improve their efficiency. Moreover, any intermediary solution found by the solver can be used as a heuristically good policy, with proved bounds on sub-optimality.