基于多源数据的城市交通空间规划策略研究——以浙江省诸暨市为例

Research on Urban Traffic Spatial Planning Strategies Based on Multi-Source Data:A Case of Zhuji City in Zhejiang Province

随着机动车数量的快速增长,由城市道路交通资源供需不均衡引起的交通拥堵越来越严重,缓解城市交通拥堵成为世界性难题。为提升交通状态判断的准确性,文章基于卡口和出租车两种数据,运用自适应加权平均融合路段行程速度估计模型,对多源数据进行融合。同时,运用模糊均值聚类算法(FCM)识别交通堵点,进而评估城市交通拥堵的时空分布。在此基础上,提出了区域城市用地规划与交通服务协同发展、公共交通优先发展和中心城区道路交叉口群优化的交通综合规划应对策略。最后,以诸暨市为例进行了实证研究。

With the rapid growth of motor vehicles,the traffic congestion caused by the imbalance between supply and demand of urban road traffic resources is becoming more and more serious.The alleviation of urban traffic congestion has become a world difficulty.In order to improve the accuracy of traffic status judgment,based on the data of bayonet and taxi,the multi-source data is fused by the adaptive weighted average fusion road segment speed estimation model in this paper.At the same time,the fuzzy average clustering algorithm(FCM)is used to identify traffic congestion.The spatial and temporal distribution of urban traffic congestion is further evaluated.On this basis,the comprehensive traffic planning and response strategies are proposed from the aspects of synergistic development of regional urban land use planning and transportation services,prioritization of public transportation and optimization of road intersection clusters in the central urban area.Finally,an empirical study was conducted in Zhuji City.