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论文类型：期刊论文
发表时间：2010-06-01
发表刊物：Journal of Computational Information Systems
收录刊物：EI、Scopus
卷号：6
期号：6
页面范围：2045-2052
ISSN号：15539105
摘要：To improve the veracity and practicality of traffic state estimation, a distributed cooperative algorithm is proposed in this paper. Firstly, a stochastic traffic flow distributed detection platform is introduced for this algorithm based on a binary proximity magnetic sensors network. Then, a generalized neural networks is used as the mainly part of this algorithm because of its better astringency and precision. At last, a number of real-data-based tests have been conducted to test the performance of the traffic state estimation. The results verified that the traffic state estimation model and algorithm enhanced the real-time traffic state estimation with high accuracy and solid robustness. Copyright ? 2010 Binary Information Press.