Stochastic system modeling and optimal control of incident-induced traffic congestion

Incident-induced traffic congestion is a critical issue in formulating urban traffic congestion problems, and also a major cause that contributes to the invalidity of traffic signal control. This paper presents a prototype of real-time local signal control method, and explores its applicability in alleviating incident-induced traffic congestion on the roadway between two adjacent intersections for incident management. The architecture includes two major parts: (1) formulating time-varying lane traffic state variables and control variables under conditions of lane-blocking incidents with a discrete-time non-linear stochastic model, and (2) developing a real-time control algorithm for predicting dynamically control variables. To generate efficiently traffic data used in model tests, we employed the Paramics microscopic traffic simulator, which is developed to model and analyze ITS traffic flow conditions. According to the measures of two proposed space-based incident-impact indexes, the preliminary test results indicate the superiority of the proposed real-time signal control method in comparison with fixed-time signal control modes which are currently used at the study site. We do expect that this study can stimulate research on incident management, and extend to network-wide incident-responsive traffic control for the development of advanced traffic management systems.