Optimal routing for automated highway systems

We present a routing guidance approach that can be used in Automated Highway Systems (AHS). We consider automated highway systems in which intelligent vehicles organised in platoons drive to their destination, controlled by a hierarchical control framework. In this framework there are roadside controllers that provide speed and lane allocation instructions to the platoons. These roadside controllers typically manage single stretches of highways. A collection of highways is then supervised by so-called area controllers that mainly take care of the route guidance instructions for the platoons and that also coordinate the various roadside controllers in their area. In this paper we focus on the optimal route choice control problem for the area controllers. In general, this problem is a nonlinear integer optimisation problem with high computational requirements, which makes the problem intractable in practice. Therefore, we first propose a simplified but fast simulation model to describe the flows of platoons in the network. Next, we show that the optimal route choice control problem can be approximated by a mixed-integer linear problem. Later, we describe a new METANET-like model to describe the flow of platoons in the AHS. With a simple case study we illustrate that both approaches result in a balanced trade-off between optimality and computational efficiency. Highlights: > We consider efficient route guidance control for platoons of autonomous vehicles. > The first control approach we propose is based on mixed-integer linear programming. > The second approach uses real-valued nonlinear programming. > Both provide a balanced trade-off between optimality and computational efficiency.