Performance studies of a network adaptive traffic control algorithm via simulation model

A complete optimal formulation of a network traffic control scheme with embedded traffic flow models (platoon dispersion) in the form of arc-flows in a time-expanded network is presented here. The integer-linear network-programming formulation is solved using a modified network simplex and branch and bound scheme. The results of comparing the solutions to other actuated controls are discussed here. The model formulation is an integer-linear program, and does not assume fixed cycle lengths or phase sequences. It assumes full information on external inputs, but can be incorporated in a sensor-based environment, as well as in a feedback control framework. The integer-linear program formulation may not be efficiently solved with standard simplex and branch and bound techniques. We discuss network programming formulations to handle the linear platoon dispersion equations and the integer constraints at the intersections. A special purpose network simplex algorithm For fast solution is also mentioned. The control strategies generated by these optimization models were compared with those derived from conventional signal timing models, using the TRAF-NETSIM microscopic simulation model. It was found that the optimization models successfully produced optimal signal timing plans for the various signalized intersections including simulated and real-world networks. The proposed optimization models consistently outperformed the conventional signal control methods with respect to system delay objective.