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交通拥堵与经济背景:危机期间和危机后时期交通出行时间的时空模式变化

Traffic congestion and economic context: changes of spatiotemporal patterns of traffic travel times during crisis and post-crisis periods.

作者信息

Moyano Amparo, Stępniak Marcin, Moya-Gómez Borja, García-Palomares Juan Carlos

机构信息

Department of Civil Engineering, Universidad de Castilla-La Mancha (UCLM), Avda, Camilo José Cela s/n, 13071 Ciudad Real, Spain.

Transport, Infrastructure and Territory Research Group (T-GIS), Department of Geography, Universidad Complutense de Madrid (UCM), C/ Profesor Aranguren s/n, 28040 Madrid, Spain.

出版信息

Transportation (Amst). 2021;48(6):3301-3324. doi: 10.1007/s11116-021-10170-y. Epub 2021 Jan 26.

DOI:10.1007/s11116-021-10170-y
PMID:33518830
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7836352/
Abstract

This paper aims to evaluate the impacts of the economic context on traffic congestion and its consequential effects on private vehicle accessibility. We conduct a long-term analysis of spatiotemporal traffic congestion patterns in Madrid (Spain), comparing two urban realms: the 2008 economic crisis and the following post-crisis situation. We apply TomTom Speed Profiles data to assess daily variations in traffic congestion and their changes between both periods, and Twitter data to capture spatial patterns of the daily pulse of the city. Increased traffic, a by-product of economic recovery, resulted in higher congestion, particularly during peak hours. Nevertheless, these changes are spatially uneven. In the city core, an increase in congestion is relatively temporally homogeneous, while in the peripheral suburban zones, there has been only a marginal increase in travel times. On the other hand, in the urban outskirts, increased traffic congestion is more severe but visibly different between north and south. These differences have strong social connotations: over 40% of the population experienced a dramatic increase in travel times (more than 25%) during peak hours. Moreover, low-income groups are more likely to live in the more affected southern districts, suffering most the negative consequences of increased congestion.

摘要

本文旨在评估经济环境对交通拥堵的影响及其对私家车可达性的相应影响。我们对西班牙马德里的时空交通拥堵模式进行了长期分析,比较了两个城市区域:2008年经济危机时期和随后的危机后情况。我们应用TomTom速度剖面数据来评估交通拥堵的每日变化以及两个时期之间的变化,并利用推特数据来捕捉城市每日脉动的空间模式。交通量增加作为经济复苏的一个副产品,导致了更严重的拥堵,尤其是在高峰时段。然而,这些变化在空间上并不均匀。在城市核心区,拥堵增加在时间上相对较为均匀,而在周边郊区,出行时间仅有小幅增加。另一方面,在城市郊区,交通拥堵加剧更为严重,但南北之间存在明显差异。这些差异具有强烈的社会内涵:超过40%的人口在高峰时段出行时间大幅增加(超过25%)。此外,低收入群体更有可能居住在受影响更大的南部地区,遭受拥堵加剧带来的负面影响最大。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa6/7836352/b2490bd1a029/11116_2021_10170_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa6/7836352/4b5443fdea54/11116_2021_10170_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa6/7836352/b71afca00337/11116_2021_10170_Fig4_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa6/7836352/607cd5115ef0/11116_2021_10170_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa6/7836352/b2490bd1a029/11116_2021_10170_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa6/7836352/4b5443fdea54/11116_2021_10170_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa6/7836352/b4021273d93e/11116_2021_10170_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa6/7836352/01f788fe77dd/11116_2021_10170_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa6/7836352/b71afca00337/11116_2021_10170_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa6/7836352/9c5d2f0557cc/11116_2021_10170_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa6/7836352/a3936fa6da01/11116_2021_10170_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa6/7836352/607cd5115ef0/11116_2021_10170_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffa6/7836352/b2490bd1a029/11116_2021_10170_Fig8_HTML.jpg

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