Coping with non-recurring congestion with distributed hybrid routing strategy

In case of congestion drivers typically select an alternative route on the basis of the shortest travel time principle. However, if drivers are informed with the same traffic conditions, their routing decisions can create a new congestion on the alternative route. The simplest method to reduce the risk of such an event has drivers choose another route with a certain probability associated with the latest reported travel time on the route. Nevertheless, this method has two drawbacks. Firstly, it is efficient only during the congestion period. Secondly, it presumes that some drivers select a route which is not optimal from their point of view. In this paper we demonstrate that these drawbacks can be eliminated when a hybrid approach is used. That is, an in-vehicle system detects a period when capacity of a route is reduced, and only then it requests drivers to follow the probabilistic approach. Otherwise the conventional shortest-time principle is applied. Each vehicle acts as a traffic sensor, and travel times are disseminated by means of connected vehicle technology. In addition, a simple road user charging mechanism is used to motivate free-riders to select routes contributing to system optimum. System evaluation is carried out using realistic network (NS-3) and traffic (SUMO) simulations and a two-route example.