Author:
Serok Nimrod,Havlin Shlomo,Blumenfeld Lieberthal Efrat
Abstract
AbstractThe increasing urbanization in the last decades results in significant growth in urban traffic congestion around the world. This leads to enormous time people spent on roads and thus significant money waste and air pollution. Here, we present a novel methodology for identification, cost evaluation, and thus, prioritization of congestion origins, i.e., their bottlenecks. The presented work is based on network analysis of the entire road network from a global point of view. We identify and prioritize traffic bottlenecks based on big data of traffic speed retrieved in near-real-time. Our approach highlights the bottlenecks that have the most significant effect on the global urban traffic flow. We follow the evolution of every traffic congestion in the entire urban network and rank all the congestions, based on the cost they cause (in Vehicle Hours units). We show that the macro-stability that represents the seeming regularity of traffic load both in time and space, overshadows the existence of meso-dynamics, where the bottlenecks that create these congestions usually do not reappear on different days or hours. Thus, our method enables to identify in near-real-time both recurrent and nonrecurrent congestions and their sources.
Funder
Center for Innovative Transportation
European Union's Horizon 2020 research and innovation programme
Publisher
Springer Science and Business Media LLC
Reference48 articles.
1. Helbing, D. A section-based queueing-theoretical traffic model for congestion and travel time analysis in networks. J. Phys. A Math. Gen. 36, L593 (2003).
2. Batty, M. The size, scale, and shape of cities. Science 319, 769 (2008).
3. Schrank, D., Lomax, T. Urban mobility report 2009 (2009).
4. Barthélemy, M. Spatial networks. Phys. Rep. 499, 1–101 (2011).
5. Pishue, B. US traffic hot spots: Measuring the impact of congestion in the United States. (2017).
Cited by
9 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献