Next Article in Journal
The Psychology of Harmony and Harmonization: Advancing the Perspectives for the Psychology of Sustainability and Sustainable Development
Next Article in Special Issue
Effects of Perceived Traffic Risks, Noise, and Exhaust Smells on Bicyclist Behaviour: An Economic Evaluation
Previous Article in Journal
Effect of Stakeholders-Oriented Behavior on the Performance of Sustainable Business
Open AccessArticle

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.
Sustainability 2018, 10(12), 4725; https://doi.org/10.3390/su10124725
Received: 6 December 2018 / Accepted: 10 December 2018 / Published: 11 December 2018
(This article belongs to the Special Issue Sustainable Transportation for Sustainable Cities)
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
Show Figures

Figure 1

MDPI and ACS Style

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. https://doi.org/10.3390/su10124725

AMA Style

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(12):4725. https://doi.org/10.3390/su10124725

Chicago/Turabian Style

Huang, Hainan; Lin, Yi; Weng, Jiancheng; Rong, Jian; Liu, Xiaoming. 2018. "Identification of Inelastic Subway Trips Based on Weekly Station Sequence Data: An Example from the Beijing Subway" Sustainability 10, no. 12: 4725. https://doi.org/10.3390/su10124725

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop