An Intelligent Route Guidance Strategy based on Congestion Type for ITS

Abstract

Traffic congestion is a severe challenge for intelligent transportation system (ITS). So far, if traffic congestion is perceived in a route, a common solution is searching for another congestion-free route. However, it is observed that not all congestions should be tackled with rerouting, since the extra overhead (e.g., extra travel time, extra fuel consumption, and extra CO2 emission) caused by certain congestions might be lower than that of re-routing. Against this backdrop, an intelligent route guidance strategy is proposed, in which vehicles will trade off the extra overhead of re-routing and that of waiting in congestion. Firstly, the perceived congestion is divided into four basic types. Then, the prediction method about the duration of each congestion type is formulated. Finally, the intelligent route planning mechanism is developed. Simulations demonstrate that the proposed strategy can reduce the travel time, fuel consumption, and CO2 emission for vehicles.