An approximate solution to the optimal coordination problem for autonomous vehicles at intersections

In this paper, we address the problem of optimal and safe coordination of autonomous vehicles through a traffic intersection. We state the problem as a finite time, constrained optimal control problem, a combinatorial optimization problem that is difficult to solve in real-time. A low complexity computational scheme is proposed, based on a hierarchical decomposition of the original optimal control formulation, where a central coordination problem is solved together with a number of local optimal control problems for each vehicle. We show how the proposed decomposition allows a reduction of the complexity of the central problem, provided that approximated parametric solutions of the local problems are available beforehand. We derive conditions for the construction of the parametric approximations and demonstrate the method with a numerical example

Time-optimal Coordination of Mobile Robots along Specified Paths

In this paper, we address the problem of time-optimal coordination of mobile robots under kinodynamic constraints along specified paths. We propose a novel approach based on time discretization that leads to a mixed-integer linear programming (MILP) formulation. This problem can be solved using general-purpose MILP solvers in a reasonable time, resulting in a resolution-optimal solution. Moreover, unlike previous work found in the literature, our formulation allows an exact linear modeling (up to the discretization resolution) of second-order dynamic constraints. Extensive simulations are performed to demonstrate the effectiveness of our approach.Comment: Published in 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS