Robustness of Intelligent Vehicular Rerouting Towards Non-Ideal Communication Delay

One of the main goals of Intelligent Transport Systems (ITSs) is to optimize traffic flow for the sake of saving fuel, decreasing travel time and/or reducing congestion. In order to achieve this goal, most of the numerous approaches from literature require some kind of information exchange between vehicles and the environment. Vehicles on the one hand need to provide data containing predicates, such as current velocity, position or route destination. On the other hand, a router needs a functional communication infrastructure to contribute route guidance to vehicles which are affected by traffic jams. However, variable delay or complete message loss can influence the rerouting performance significantly, since either route advices could fail to reach their recipient, or the supposed knowledge of the road conditions could be outdated. The delay requirements of various routers may be divergent, and therefore we propose two delay models which are independent of the underlying communication standard. Furthermore, this paper evaluates the existing PCMA* routing algorithm concerning its performance with varying delays and message loss probabilities by applying the introduced delay models in microscopic traffic simulations. We define constraints of both the delay and message loss probability which are required to achieve certain improvements ensuing from intelligent rerouting. The results further reveal a high robustness of the algorithm with regard to delays and message loss probabilities, which expresses itself by similarly low achieved average vehicle travel times for a large amount of the investigated simulation setups.