Abstract

Advanced traffic management is a cost-effective option to reduce total delay, fuel consumption and air pollution in urban networks. Nevertheless, Adaptive Signal Control, the most advanced scheme for real-time traffic responsive operations, is still not widely used due to inadequate sensor systems and the deficiencies in the control algorithms. A novel traffic data system was recently proposed at UC Irvine named the “Persistent Traffic Cookies” (PTC) system, in which the routes traveled by the vehicles are recorded onboard and read using short-range wireless communication among vehicles and roadside devices. An advantage of this system is that there is no requirement of massive central databases and data processing of all possible vehicles in the network. The accumulated travel data is distributed across vehicles. The trip behavior inferred in the day-by-day data is used to predict individual paths and aggregated across vehicles for traffic prediction in dynamic network traffic control. This research develops traffic control schemes that use path-based data systems like PTC. Initially, methods are presented to generate the required path-based input variables such as turning flows and travel times. Two main aspects are addressed. One is a systematic approach to define spatial boundaries of subnetworks for area-control using observed traffic dynamics, the path flow between signalized intersections being used as the criterion for control dependency. The second focus is to provide network-level signal optimization, based on a decentralized control scheme yielding indirect signal coordination optimized for delay with no explicit bandwidth maximization. The local optimization uses a Dynamic Programming approach using the predicted arrival flows modeled via link traffic platoon dispersion. Optimal signal indications are found for small time steps (currently 5 seconds) within the control horizon, essentially resulting in a “cycle-less” operation. A modified rolling horizon scheme is applied, incorporating a proper calculation of the salvage cost of left-over queue after the horizon. Signal coordination is indirectly achieved and the feedback among signal decisions lead to an iterative approach. The schemes are evaluated with a microscopic simulation study of a real-world network. The results showed that the scheme reduces the total delays in the network in comparison to the Actuated Signal Control already installed in the network. It is also seen that the modified rolling horizon method with salvage cost considerations performs better than the more conventional methods.