Chapter
Jun 29, 2020
13th Asia Pacific Transportation Development Conference

Analyzing and Modeling Post-Earthquake Emergency Traffic Demand

Publication: Resilience and Sustainable Transportation Systems

ABSTRACT

The earthquake emergency channel is an important disaster prevention and shock absorption infrastructure for the city and plays an important and fundamental role in the post-earthquake rescue work. Based on the urban actual seismic hazard, an improved four-step method and scenario construction method are used to establish a multi-scenario urban earthquake emergency access system. First, researchers conducted post-earthquake demand node analysis from emergency rescue, medical rescue, and material rescue. Then, based on the post-earthquake activity, the Dijstra shortest path algorithm and the original unit method are used to predict the traffic demand. Finally, based on the principle of near distribution and the principle of balanced distribution, four scenarios are constructed, which consider time, traffic demand, and bridge condition factors. The four scenarios are the shortest path model with intact bridge, the shortest path model with damaged bridge, the balanced distribution model of bridge, and the balanced distribution model of bridge damage. In order to verify the validity of the model, Beijing was selected as the research area, and the traffic demand allocation and result solving were carried out by means of the Beijing road network VISUM model. The road network results of the post-earthquake emergency channel under four scenarios were obtained. At the same time, combined with scenarios 1 and 3, the researchers recommended a comprehensive post-earthquake emergency access road network. The method proposed by the researcher is very operational, and the result can provide decision-making basis for the post-earthquake contingency planning of the urban transportation system. At the same time, the proposed method can provide theoretical reference for post-earthquake emergency channel planning in other cities.

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ACKNOWLEDGMENTS

This research was supported by the Fundamental Research Funds for the Central Universities of Ministry of Education of China (2019YJS107), National Natural Science Foundation of China (71501011), and Beijing Road Network VISUM Model from Beijing Transport Institute

REFERENCES

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Information & Authors

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Published In

Go to Resilience and Sustainable Transportation Systems
Resilience and Sustainable Transportation Systems
Pages: 166 - 175
Editors: Fengxiang Qiao, Ph.D., Texas Southern University, Yong Bai, Ph.D., Marquette University, Pei-Sung Lin, Ph.D., University of South Florida, Steven I Jy Chien, Ph.D., New Jersey Institute of Technology, Yongping Zhang, Ph.D., California State Polytechnic University, and Lin Zhu, Ph.D., Shanghai University of Engineering Science
ISBN (Online): 978-0-7844-8290-2

History

Published online: Jun 29, 2020

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Authors

Affiliations

Shengyou Wang [email protected]
Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, School of Traffic and Transportation, Beijing Jiaotong Univ., Beijing, Haidian District. E-mail: [email protected]
Zhihua Xiong
Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, School of Traffic and Transportation, Beijing Jiaotong Univ., Beijing, Haidian District
Shuling Wang [email protected]
Beijing Transport Institute, Rail Transit Dept., Fengtai District, Beijing. E-mail: [email protected]
Ying Hu
Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, School of Traffic and Transportation, Beijing Jiaotong Univ., Beijing, Haidian District; Beijing Transport Institute, Rail Transit Dept., Fengtai District, Beijing
Xiong Yang
Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, School of Traffic and Transportation, Beijing Jiaotong Univ., Beijing, Haidian District
Peiwen Chen [email protected]
China Urban Construction Design and Research Institute, Beijing. E-mail: [email protected]

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