Methodology for Extracting Potential Customized Bus Routes Based on Bus Smart Card Data

Jing Li, Yongbo Lv, Jihui Ma and Qi Ouyang
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Jing Li: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Yongbo Lv: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Jihui Ma: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Qi Ouyang: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China

Energies, 2018, vol. 11, issue 9, 1-15

Abstract: To alleviate traffic congestion and traffic-related environmental pollution caused by the increasing numbers of private cars, public transport (PT) is highly recommended to travelers. However, there is an obvious contradiction between the diversification of travel demands and simplification of PT service. Customized bus (CB), as an innovative supplementary mode of PT service, aims to provide demand-responsive and direct transit service to travelers with similar travel demands. But how to obtain accurate travel demands? It is passive and limited to conducting online surveys, additionally inefficient and costly to investigate all the origin-destinations (ODs) aimlessly. This paper proposes a methodological framework of extracting potential CB routes from bus smart card data to provide references for CB planners to conduct purposeful and effective investigations. The framework consists of three processes: trip reconstruction, OD area division and CB route extraction. In the OD area division process, a novel two-step division model is built to divide bus stops into different areas. In the CB route extraction process, two spatial-temporal clustering procedures and one length constraint are implemented to cluster similar trips together. An improved density-based spatial clustering of application with noise (DBSCAN) algorithm is used to complete these procedures. In addition, a case study in Beijing is conducted to demonstrate the effectiveness of the proposed methodological framework and the resulting analysis provides useful references to CB planners in Beijing.

Keywords: public transport service; customized bus; route planning; bus smart card data; improved DBSCAN algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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