Feedback and iterative routing strategies for freeway networks

The paper considers route guidance in complex freeway networks. With the aid of the simulation tool METANET, feedback routing strategies of bang-bang, P, PI, and LQI types are designed and tested. The influence of various factors such as compliance rate, demands, OD, incidents, and control interval length is carefully investigated. Moreover, an iterative strategy with perfect prediction is designed to deliver the best achievable results as a reference solution to compare with the feedback routing results. Simulation results indicate that feedback routing strategies based on the real-time measurement of instantaneous travel times and iterative strategies based on experienced travel times can efficiently equalize experienced travel times along the alternative routes within the network. Furthermore, the feedback routing controllers work robustly in many perturbed situations, while the open-loop iterative strategy is critically deficient in robustness