Research on Evaluation and Optimization Strategy of Road Traffic Resilience

DOI

10.2991/978-94-6463-610-9_27How to use a DOI?

Keywords

urban road traffic; Traffic resilience evaluation; Hierarchical analysis; Grey relational analysis

Abstract

In recent years, urban road traffic is frequently affected by various abnormal events, which not only damage the traffic facilities, but also have an impact on the operation of social economy. Therefore, it has become an important research direction to explore the resilience of urban road traffic, identify its influencing factors, and analyze the advantages and disadvantages of urban traffic resilience. This paper takes Beijing and Shanghai as the research objects, uses analytic hierarchy process (AHP) to construct the urban road traffic resilience evaluation index system, obtains the index data from 2017 to 2021, and evaluates the urban road traffic resilience according to the index weights by using the grey relational degree model. The main research content is the evaluation of urban road traffic resilience, the exploration of influencing factors and the optimization strategy. The results show that road traffic resilience in Beijing and Shanghai is closely related to each index.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Kai Wang
AU  - Aihua Fan
AU  - Kefeng Wang
PY  - 2024
DA  - 2024/12/16
TI  - Research on Evaluation and Optimization Strategy of Road Traffic Resilience
BT  - Proceedings of the 2024 International Conference on Rail Transit and Transportation (ICRTT 2024)
PB  - Atlantis Press
SP  - 237
EP  - 243
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-610-9_27
DO  - 10.2991/978-94-6463-610-9_27
ID  - Wang2024
ER  -