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Simulation Optimization of Traffic Signal Control Parameters
LIN Yong,XU Zhao-xia,LI Shu-bin, DANG Wen-xiu
2010, 10(3):
42-49 .
To optimize the signal controller timing schemes in an regional traffic network, the recursive least square (RLS) algorithm and the simultaneous perturbation stochastic approximation (SPSA) algorithm are developed, which can utilize the surveillance flows to estimate the dynamic OD matrix input and calibrate the speed-density model parameters and saturation flow for each road segment in the DynaCHINA dynamic network traffic simulation and analysis system. By this approach, the network traffic states can be estimated accurately, such as the speed, density, flow, queue length, and so on, for each road segment of the network. Based on the reliable traffic estimation, the SPSA algorithm is proposed to adjust the signal controlling parameters in a network, including the signal cycles, offsets, and splits, so that the network performance index, such as average vehicle travel delay,queue lengths, intersection throughputs, and so on, can be optimized in a dynamic network traffic simulation system. From wide tests for actual network, it is concluded that the proposed method can obtain more accurate estimation of surveillance flows than that of Ashok K’s dynamic OD matrice and sensor flow estimation method, and it can also significantly reduce the average travel delay of vehicles across the network, in comparison with Synchro signal timing optimization software which is now widely used by traffic engineers. Furthermore, the proposed method can be extended to the application of more complicated and large area traffic networks.
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