Railway capacity calculation in emergency using modified fuzzy random optimization methodology

Wang, L; An, M; Jia, L; Qin, Y

Abstract

Accurate estimated capacity of the railway section can provide reliable information to railway operators and engineers in decision-making, particularly, in an emergency situation. However, in an emergency, the optimization of capacity of a railway section is usually involved to study, for example, the characteristics of dynamic, fuzziness, randomness, and non-aftereffect properties. This paper presents a proposed capacity calculation method based on the modified fuzzy Markov chain (MFMC). In this method, the capacity of a railway section in an emergency can be expressed by a fuzzy random variable, which remains the randomness of capacity changing according to the impact of emergencies and the fuzziness of the driving behavior and other factors.Acase study of a high-speed line from Beijing to Shanghai is used to show the process of the proposed methods for optimization of section capacity calculation in an emergency.

Citation

Wang, L., An, M., Jia, L., & Qin, Y. (2019, October). Railway capacity calculation in emergency using modified fuzzy random optimization methodology. Presented at The 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2019, Changsha, China

• Presentation Conference Type: Other
• Conference Name: The 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2019
• Conference Location: Changsha, China
• Start Date: Oct 25, 2019
• End Date: Oct 27, 2019
• Acceptance Date: Jul 20, 2019
• Online Publication Date: Apr 2, 2020
• Publication Date: Apr 2, 2020
• Deposit Date: May 28, 2020
• Publicly Available Date: Apr 2, 2021
• Series Title: Lecture Notes in Electrical Engineering
• Series Number: 640
• Book Title: Proceedings of the 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2019 Rail Transportation Information Processing and Operational Management Technologies
• ISBN: 9789811529139-(print);-9789811529146-(online)
• DOI: https://doi.org/10.1007/978-981-15-2914-6_26
• Publisher URL: https://doi.org/10.1007/978-981-15-2914-6_26
• Related Public URLs: https://link.springer.com/book/10.1007/978-981-15-2914-6
• Additional Information: Event Type : Conference; Funders : NationalKey Research andDevelopment Program of China;National Natural Science Foundation of China; Projects : High Speed Rail Research;Railway Engineering; Grant Number: Grant No. 2016YFB1200401; Grant Number: Grant No. 71701010