This paper develops a method for a safe and autonomous intersection crossing. A centralized system controls autonomous vehicles within a certain surrounding of the intersection and generates optimized trajectories for all vehicles in the area. A recently proposed design approach, [10], where this problem is expressed as a convex optimization problem using space sampling instead of time sampling, is formulated as a MPC problem solved by a QP algorithms so that it can be executed in real time. The MPC controller is then integrated in CarMaker using Matlab/Simulink so that the controller can be validated against the advanced vehicle models and sensor models available in CarMaker. Preliminary results of this validation are presented. Also, a method is designed to obtain time gaps between the vehicles to prevent the optimization problem to become infeasible when sensors give noisy measurements.
Centralized MPC for autonomous intersection crossing
01.11.2016
1669159 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch