Dynamic Models for traffic prediction and control

network traffic assignment/ equilibrium models have been widely used for transportation planning. For traffic management one is interested on how traffic pattern change dynamically since equilibrium cannot be reached instantaneously. Many models propagate flows through a network using link flows and independent turning probabilities (ITP) at nodes. route trajectories ate the spatial-temporal realizations of vehicle route flow demands. this article proposes a mesoscopic simulation platform where route flows are propageted through the network and dynamic trajectories are computed. furthermore a model is presented for estimating temporal route flow demands when real time data is available. finally, a traffic signal control optimizer based on the mesoscopic model and a gradient search to optimize given performance index and the approach may be used for on-line traffic signal control.

کلیدواژه ها:

network traffic models ، mesoscopic simulation ، traffic signal control