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Sustainability 2018, 10(12), 4725; https://doi.org/10.3390/su10124725

Identification of Inelastic Subway Trips Based on Weekly Station Sequence Data: An Example from the Beijing Subway

1
Key Lab of Traffic Engineering, Beijing University of Technology, Beijing 100124, China
2
College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou 350002, China
3
National Key Laboratory of Fundamental Science on Synthetic Vision, Sichuan University, Chengdu 610065, China
*
Authors to whom correspondence should be addressed.
Received: 6 December 2018 / Accepted: 10 December 2018 / Published: 11 December 2018
(This article belongs to the Special Issue Sustainable Transportation for Sustainable Cities)
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Abstract

Urban rail transit has become an indispensable option for Beijing residents. Subway inelastic users (SIUs) are the main component among all users. Understanding the proportion of SIUs and their characteristics is important in developing service promotions and helpful for subway agencies in making marketing policies. This paper proposes a novel and simple identification process for identifying regular subway inelastic trips (SITs) in order to distinguish SITs and non-SITs and extract their characteristics. Weekly station sequence (WSS) is selected as the data-based format, principles of SIUs are discussed and chosen, and the framework of SIT identification is applied to a large weekly sample from the Beijing Subway. A revealed preference (RP) survey and results analysis are undertaken to estimate the performance of the proposed methods. The RP survey validation shows that accuracy reaches as high as 94%, and the distribution analysis of SITs and their origin-destinations (ODs) indicate that the SIT characteristics extracted are consistent with the situation in Beijing. The proportion of SIUs is stable on workdays and is more than 80% during rush hour. The efforts described in this paper can provide subway managers with a useful and convenient method to understand the characteristics of subway passengers and the performance of a subway system. View Full-Text
Keywords: Subway inelastic users (SIUs); subway inelastic trips (SITs); weekly station sequence (WSS); travel behavior; smart card data Subway inelastic users (SIUs); subway inelastic trips (SITs); weekly station sequence (WSS); travel behavior; smart card data
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Huang, H.; Lin, Y.; Weng, J.; Rong, J.; Liu, X. Identification of Inelastic Subway Trips Based on Weekly Station Sequence Data: An Example from the Beijing Subway. Sustainability 2018, 10, 4725.

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