Analyzing the Effects of Rainfall on Urban Traffic-Congestion Bottlenecks
Analyzing the Effects of Rainfall on Urban Traffic-Congestion Bottlenecks
复制标题
分析降雨对城市交通拥堵瓶颈的影响
DOI：
10.1109/jstars.2020.2966591
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发表时间：
2020
影响因子：
5.5
通讯作者：
Dai Liangyang
中科院分区：
文献类型：
--
作者：
Yao Yao;Wu Daiqiang;Hong Ye;Chen Dongsheng;Liang Zhaotang;Guan Qingfeng;Liang Xun;Dai Liangyang
地理空间大数据的发展使研究交通拥堵问题成为可能。特别是浮动车数据（FCD）非常适合它，因为FCD可以帮助预测交通拥堵瓶颈并提供相应的解决方案来解决交通问题。以往的研究已经讨论了降雨对道路速度的影响，但很少有研究集中在降雨对整个特大城市的交通拥堵瓶颈的空间分布和变化的影响。本文提出了一个索引计算和聚类（ICC）模型，集成PageRank和聚类算法的多个数据，包括降雨量数据，FCD，和OpenStreetMap数据。作为研究区域，我们选择了深圳，这是最大的发达城市在华南地区。结果显示，8：00-10：00、14：00-16：00和18：00-20：00是市民出行的三个高峰期。降雨后的道路速度在工作日和周末分别下降6.20%和2.37%，交通拥堵面积在工作日和周末分别增加23.53%和20.65%。此外，降雨对深圳平日交通状况的影响较周末更为显著。与传统的核密度分析方法相比，ICC模型能够更深入地了解城市交通拥堵区域，有助于政策制定者优化缓解策略。
The development of geospatial big data makes it possible to study traffic-congestion issues. In particular, floating car data (FCD) is very suitable for it because FCD can help predict traffic-congestion bottlenecks and provide corresponding solutions to address traffic problems. Previous studies have discussed the impacts of rainfall on road speeds, but few studies have focused on the impacts of rainfall on the spatial distribution and changes in traffic-congestion bottlenecks throughout a mega-city. This article proposes an index calculation and clustering (ICC) model by integrating PageRank and clustering algorithms from multisource data, including rainfall data, FCD, and OpenStreetMap data. As the study area, we selected Shenzhen, which is the largest developed city in South China. The results demonstrate three peak periods of citizen travel, namely, 8:00-10:00, 14:00-16:00, and 18:00-20:00. Road speeds after rainfall decrease by 6.20% on weekdays and by 2.37% on weekends, and traffic-congestion areas increase by 23.53% and 20.65% on weekdays and on weekends, respectively. In addition, rainfall causes more significant effects on traffic conditions on weekdays compared with on weekends in Shenzhen. Compared with a traditional kernel density analysis, the proposed ICC model can offer a more thorough understanding of urban traffic-congestion areas, which can help policy makers optimize alleviation strategies.