Study to short-term flow estimation at intersection base on genetic neural networks

Authors:
Zhina Zhou;Shi Zhongke;Yingfeng Li
Affiliations:
Northwestern Polytechnical University, Xi'an, China;Northwestern Polytechnical University, Xi'an, China;Northwestern Polytechnical University, Xi'an, China
Venue:
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Year:
2009

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Abstract

The traffic flow data is the foundation of the transportation management and control. Inevitably there is data loss in traffic parameters acquisitions, so it needs traffic flow estimation to complete the traffic flow information when the data loss is serious. Proper estimation of traffic flow is an essential component of advanced management of dynamic traffic networks. The genetic nerve-network is developed, combined the nerve network and the genetic algorithm together, to estimate the short-term traffic volume. According to the experiment result, the method is effective to estimate traffic flow in the short term at intersection.