Dynamic Routing using Real-time ITS Information

On-time delivery is a key performance measure for dispatching and routing of freight vehicles in just-in-time (JIT) manufacturing environments. Growing travel time delays and variability, attributable to increasing congestion in transportation networks, are negatively impacting the efficiency of JIT logistics operations. Recurrent congestion is one of the primary reasons for delivery delay and variability. In this study, we propose a stochastic dynamic programming formulation for dynamic routing of vehicles in non-stationary stochastic networks subject to recurrent congestion. Results are very promising when the algorithms are tested in a simulated network of Southeast-Michigan freeways using historical Intelligent Transportation Systems (ITS) data.