Demand and Congestion in Multiplex Transportation Networks

Urban transportation systems are multimodal, sociotechnical systems; however, while their multimodal aspect has received extensive attention in recent literature on multiplex networks, their sociotechnical aspect has been largely neglected. We present the first study of an urban transportation syste...

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Bibliographic Details
Published in:PloS one 2016-09, Vol.11 (9), p.e0161738-e0161738
Main Authors: Chodrow, Philip S, Al-Awwad, Zeyad, Jiang, Shan, González, Marta C
Format: Article
Language:English
Subjects:
Analysis
Biology and Life Sciences
Case studies
Cellular telephones
Cities
Commuting
Computer and Information Sciences
Dynamic structural analysis
Earth Sciences
Ecology and Environmental Sciences
Engineering
Engineering and Technology
Environmental engineering
Impact analysis
Infrastructure
Local transit
Medicine and Health Sciences
Multiplexing
Network analysis
Open source software
Social Sciences
Source code
Traffic assignment
Traffic congestion
Traffic speed
Transportation industry
Transportation networks
Transportation systems
Travel
Travel demand
Urban areas
Urban transportation
Walking
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Summary:Urban transportation systems are multimodal, sociotechnical systems; however, while their multimodal aspect has received extensive attention in recent literature on multiplex networks, their sociotechnical aspect has been largely neglected. We present the first study of an urban transportation system using multiplex network analysis and validated Origin-Destination travel demand, with Riyadh's planned metro as a case study. We develop methods for analyzing the impact of additional transportation layers on existing dynamics, and show that demand structure plays key quantitative and qualitative roles. There exist fundamental geometrical limits to the metro's impact on traffic dynamics, and the bulk of environmental accrue at metro speeds only slightly faster than those planned. We develop a simple model for informing the use of additional, "feeder" layers to maximize reductions in global congestion. Our techniques are computationally practical, easily extensible to arbitrary transportation layers with complex transfer logic, and implementable in open-source software.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0161738