Online control of signalized networks using the Cell Transmission Model

Adaptive Traffic Control Systems (ATCS) aim at the improvement of traffic flow in terms of delay, number of stops, travel time etc. in urban networks under the regime of traffic signal control. Well known ATCS are SCOOT, SCATS, BALANCE and MOTION to name only a few. Lately the Cell Transmission Model (CTM) attracted some attention in the context of traffic signal control. It can be used to model the effects of different signal settings. Based on the CTM a prototype of a new ATCS has been developed. It can handle urban sub-networks with several interconnected signalized intersections. Every 15 minutes it adapts and optimizes signal plans and coordination patterns to the currently estimated traffic demand in the network. In a first step the upcoming traffic demand is forecasted and estimated. Based on this demand cycle length and green splits are adjusted. Finally, offsets are optimized by using the CTM in combination with Genetic Algorithms and a second alternative approach named Sequential Enumeration. The emphasis of this paper is on the offset optimization and the performance of the new ATCS which has been investigated in a microsimulation study.