TY - Jour A2 - DeOña，罗西奥·奥 - 薛，永杰·奥 - 峰，瑞阿翠，少华AU - yu，ZI-2020 DA - 2020/12/19 TI - 交通状态演进趋势预测基于拥塞传播效果在多雨天气下SP - 8850123 VL - 2020 AB - 在多雨的天气中，准确的交通状况预测不仅可以帮助道路交通管理人员制定交通管理方法，还可以帮助旅行者设计旅行路线甚至调整旅行时间。In this paper, based on six-dimensional data (e.g., past and present spatiotemporal traffic status, road network structure, pavement type, water accumulation, and rainfall level), a fuzzy neural network (FNN) prediction system is proposed to predict traffic status. The traffic status evolution trend is related not only to the existing traffic but also to the new traffic demand. Therefore, the FNN prediction system designed includes offline and online parts using the data of the past and the day separately and avoids the forecast of new traffic demand. The fuzzy C-means clustering algorithm is applied to cluster traffic status data under similar rainy weather in the past to form an offline initial dataset, which is used to train FNN weight parameters. The online part uses real-time detection data and the parameters trained by the offline part to further predict the traffic status and returns the prediction errors to the offline part to correct the weight parameters to further improve prediction accuracy. Finally, the FNN prediction system is verified using real Beijing expressway network data. The verification results show that the prediction system can guarantee prediction accuracy and can be used to effectively identify traffic status. SN - 0197-6729 UR - https://doi.org/10.1155/2020/8850123 DO - 10.1155/2020/8850123 JF - Journal of Advanced Transportation PB - Hindawi KW - ER -