The motion and coordination of autonomous vehicles have impact on the entire transportation process, i.e. on the motion of human-driven vehicles in the traffic network and on the performances of the traffic flow. In case of urban traffic networks, the coordination of autonomous vehicles in intersections has high importance.
The goal of the project is to develop learning-based and physical-based modeling and control methods on the interactions of autonomous vehicles in intersection scenarios, with which the global transportation performances can be guaranteed.
During the research centralized and distributed autonomous vehicle control design methods on urban traffic context are developed, with which predefined traffic flow, energy consumption and emission requirements can be effectively improved.
