Dynamic route planning in vehicular networks based on future travel estimation

Abstract

Traffic congestion wastes time, energy, and causes pollution. In this paper, We propose an application taking advantage of vehicular communications, namely dynamic route planning. In dynamic route planning, the route from a travel origin to its destination, instead of being statically determined at the travel starting time, is periodically recomputed according to real-time traffic information. Estimating future travel time is indeed central to the dynamic route planning problem. Since knowing future travel times cannot be achieved, a major challenge its estimation. In this paper, we consider three estimates for the future travel time: the latest travel time heuristic commonly used in the literature, an improvement of the latest travel time heuristic, and a novel approach based on exploiting the observed correlation between vehicle density in a road segment and travel time. We show through accurate simulation that all these heuristics are able to considerably improve traffic efficiency, with up to 60% traveling time reduction with respect to the case of the static route planning. Among the considered heuristics, the one based on vehicle density is consistently outperforming the others, especially in presence of traffic build up/decongestion situations (e.g., accidents).