Resumen
Technology applications like Advanced Traveler Information Systems (ATIS) would enable the travelers to take pre-travel decisions related to the route, mode or time of travel. This aids as a viable and efficient solution strategy for congestion problems. The present study explores the potential scope of macroscopic continuum models with appropriate flux function (fundamental q-k diagram) to cater ATIS applications. The classical Lighthill, Whitham and Richards (LWR) model is used with bi-regime flux functions for traffic state prediction and travel times at different arrival times of vehicles are estimated using a dynamic macro-model based travel time prediction algorithm. The overall effects of blockage in terms of travel time for two hypothetical scenarios are quantified and the results agree well with those obtained from micro-simulation. The proposed framework is promising as it opens up a larger scope for integrating more refined modules of higher order models and high resolution numerical schemes into it, thus bridging the gap between traffic flow theory and its applications.