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A compositional modeling and performance evaluation technique for traffic control systems based on Stochastic Timed Petri Nets (STPN's) is presented. We use STPN's to specify traffic and traffic control at an intersection and use a random distribution model to model the motion of vehicles in a road segment between any two consecutive intersections. A traffic control system is thus modeled as a composition of individual intersection models and segment random distribution models. A technique is presented to incrementally evaluate the system's performance by analyzing intersections separately according to a carefully selected order. The analysis technique conforms to the accepted practice of transportation research. Compared to existing Petri net models of traffic control systems, our technique dramatically reduces the complexity of analysis.
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Wang et al. (2000) studied this question.
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