基于道路交通指数大数据的上海市主城区交通拥堵特征研究
Analysis on Traffic Congestion of Shanghai Central City Based on Road Transportation Index Big Data
邹 伟
上海市城市规划设计研究院 信息服务中心 助理工程师，硕士
摘要: 采用道路交通指数大数据，从全局均值、均值时间分布、层次聚类及区域空间等相关角度对上海市主城区的交通拥堵状况进行了系列特征分析。上海市主城区各个区域的交通拥堵主要表现为“畅通”及“较畅通”状态，少数呈现“拥挤”状态；在工作日存在“早晚高峰”的双峰现象，休息日则呈现长时单峰特点；位于外环边及沿江等区域则呈现较弱的相关关系，表明这些区域的交通网络有待改善及提升，或者表现出独特的交通出行模式。提出了上海市主城区交通拥堵特征及其可能形成原因，助力于上海市新一轮总体规划。
Abstract: From the point of global mean, mean time distribution, hierarchical clustering and regional spatial correlation, this research uses big data to analyze condition of traffic jams in downtown Shanghai. The results show that most of the 68 areas in downtown Shanghai are unblocked or some and few areas are under crowded condition. The traffic in downtown has a phenomenon of bimodal distribution in workdays, while in weekends there is a longstanding unimodal distribution. In addition, some areas beside the outer ring or along the river have different features. It shows that the transportation network remains to be improving. This research gives suggestions on traffic jams and provides references for Shanghai Master Plan (2015—2040).
关键词：交通拥堵、道路交通指数、大数据、层次聚类、皮尔逊相关
Keyword: Traffic congestion，Road transportation index，Big data， Hierarchical clustering ，Pearson correlation
中图分类号：TU981
文献标识码: A
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