Online Traffic Light Control through Gradient Estimation Using Stochastic Fluid Models
نویسندگان
چکیده
In this paper, we consider the problem of dynamically regulating the timing of traffic light controllers in busy cities. We use a Stochastic Fluid Model (SFM) to model the dynamics of the queues formed at an intersection. Based on this model, we derive gradients of the queue lengths with respect to the green/red light lengths within a signal cycle. We report preliminary numerical results comparing the performance of the estimates with finite-difference and smoothed perturbation analysis estimates. Then all estimators are used to optimize the traffic system via Stochastic Approximation. Copyright c ©2005 IFAC
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تاریخ انتشار 2005