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城市交通弹性评估框架:纳入拼车影响。

A Framework for Assessing Resilience in Urban Mobility: Incorporating Impact of Ridesharing.

机构信息

Jiangsu Key Laboratory of Urban ITS, Southeast University, 2 Dongnandaxue Rd, Nanjing 211189, China.

Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, 2 Dongnandaxue Rd, Nanjing 211189, China.

出版信息

Int J Environ Res Public Health. 2022 Aug 30;19(17):10801. doi: 10.3390/ijerph191710801.

DOI:10.3390/ijerph191710801
PMID:36078535
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9518447/
Abstract

To a certain degree, the resilience of the transportation system expresses the safety of the transportation system, because it reflects the ability of the system to maintain its function in the face of disturbance events. In the current research, the assessment of the resilience of urban mobility is attractive and challenging. Apart from this, the concept of green mobility has been popular in recent years. As a representative way of shared mobility, the implementation of ridesharing will affect the level of urban mobility resilience to a certain extent. In this paper, we use a data low-intensity method to evaluate the urban traffic resilience under the circumstance of restricted car use. In addition, we incorporate the impact of ridesharing services. The research in this paper can be regarded as an evaluation framework, which can help policy makers and relevant operators to grasp the overall resilience characteristics of cities in emergencies, identify weak sectors, and formulate the best response plan. This method has been successfully applied to two cities in China, demonstrating its potential for practice. Finally, we also explored the relationship between urban traffic resilience and the pattern of population distribution. The analysis shows that population density has an impact on the level of transportation resilience. And the incorporation of ridesharing will bring an obvious increment in resilience of most areas.

摘要

在一定程度上,交通系统的恢复力反映了交通系统的安全性,因为它反映了系统在面对干扰事件时保持其功能的能力。在当前的研究中,城市机动性的恢复力评估具有吸引力和挑战性。除此之外,绿色机动性的概念近年来也很流行。作为共享机动性的一种代表性方式,拼车的实施将在一定程度上影响城市机动性恢复力的水平。在本文中,我们使用数据低强度方法来评估在限制汽车使用的情况下城市交通的恢复力。此外,我们还纳入了拼车服务的影响。本文的研究可以被视为一个评估框架,可以帮助政策制定者和相关运营商在紧急情况下掌握城市的整体恢复力特征,识别薄弱环节,并制定最佳应对计划。该方法已成功应用于中国的两个城市,证明了其在实践中的潜力。最后,我们还探讨了城市交通恢复力与人口分布模式之间的关系。分析表明,人口密度对交通恢复力水平有影响。而拼车的加入将使大多数地区的恢复力明显提高。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/fc86d3b8cf7e/ijerph-19-10801-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/c270a522b7c5/ijerph-19-10801-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/2ad31e1710bf/ijerph-19-10801-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/ae2de678890a/ijerph-19-10801-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/f785c04d7b0b/ijerph-19-10801-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/25911f15304e/ijerph-19-10801-g005a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/9cd6814cd04b/ijerph-19-10801-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/1e6b24ee7465/ijerph-19-10801-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/47ae8b88090c/ijerph-19-10801-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/d4008968fc59/ijerph-19-10801-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/4c254acb8d4b/ijerph-19-10801-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/348678e6f3d5/ijerph-19-10801-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/c9de38b22657/ijerph-19-10801-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/fc86d3b8cf7e/ijerph-19-10801-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/c270a522b7c5/ijerph-19-10801-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/2ad31e1710bf/ijerph-19-10801-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/ae2de678890a/ijerph-19-10801-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/f785c04d7b0b/ijerph-19-10801-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/25911f15304e/ijerph-19-10801-g005a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/9cd6814cd04b/ijerph-19-10801-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/1e6b24ee7465/ijerph-19-10801-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/47ae8b88090c/ijerph-19-10801-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/d4008968fc59/ijerph-19-10801-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/4c254acb8d4b/ijerph-19-10801-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/348678e6f3d5/ijerph-19-10801-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/c9de38b22657/ijerph-19-10801-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd16/9518447/fc86d3b8cf7e/ijerph-19-10801-g013.jpg

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本文引用的文献

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Estimation of the shared mobility demand based on the daily regularity of the urban mobility and the similarity of individual trips.基于城市出行的日常规律性和个体出行的相似性估算共享出行需求。
PLoS One. 2020 Sep 17;15(9):e0238143. doi: 10.1371/journal.pone.0238143. eCollection 2020.
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