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  • 标题:Unraveling reaction-diffusion-like dynamics in urban congestion propagation: Insights from a large-scale road network
  • 本地全文:下载
  • 作者:Leonardo Bellocchi ; Nikolas Geroliminis
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2020
  • 卷号:10
  • 期号:1
  • 页码:1-11
  • DOI:10.1038/s41598-020-61486-1
  • 出版社:Springer Nature
  • 摘要:We study the dynamical process of congestion formation for large-scale urban networks by exploring a unique dataset of taxi movements in a megacity. We develop a dynamic model based on a reaction and a diffusion term that properly reproduces the cascade phenomena of traffic. The interaction of these two terms brings the values of the speeds on road network in self-organized patterns and it reveals an elegant physical law that reproduces the dynamics of congestion with very few parameters. The results presented show a promising match with an available real data set of link speeds estimated from more than 40 millions of GPS coordinates per day of about 20,000 taxis in Shenzhen, China.
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