一种智能交通响应式车流车道控制系统

Proceedings of VNIS '93 - Vehicle Navigation and Information Systems Conference Pub Date : 1993-10-12 DOI:10.1109/VNIS.1993.585610

W. Zhou, P. Livolsi, E. Miska, H. Zhang, J. Wu, D. Yang

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引用次数: 17

摘要

介绍了针对大温哥华南部乔治梅西隧道开发的一种智能自学习动态最优车流控制系统。开发了一个程序，以便准确估计实时交通需求。采用模糊建模算法对在线流量数据进行排序，确定最佳匹配模式。利用自学习机制对预测需求进行增量修改。提出了一种基于预测需求在线计算最优逆流调度的优化算法。两种交通方式的总延误是最小的。

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An intelligent traffic responsive contraflow lane control system

An intelligent-self learning dynamic optimal contraflow lane control system developed for the George Massey Tunnel in southern Greater Vancouver is introduced. A program was developed to permit the accurate estimation of realtime traffic demands. Online traffic data are sorted by a fuzzy modeling algorithm to identify the best matching pattern. A self learning mechanism is utilized to modify the predicted demand incrementally. An optimization algorithm is developed for online calculation of the optimal contraflow schedule based on the predicted demand. The total delay of both traffic approaches is minimized.

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Proceedings of VNIS '93 - Vehicle Navigation and Information Systems Conference

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