Methodology for Extracting Potential Customized Bus Routes Based on Bus Smart Card Data
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 se...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-08-01
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| Series: | Energies |
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| Online Access: | http://www.mdpi.com/1996-1073/11/9/2224 |
| _version_ | 1817995048341471232 |
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| author | Jing Li Yongbo Lv Jihui Ma Qi Ouyang |
| author_facet | Jing Li Yongbo Lv Jihui Ma Qi Ouyang |
| author_sort | Jing Li |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-14T02:00:05Z |
| format | Article |
| id | doaj.art-6e7cc6f64893416e97bdb93566349b10 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-14T02:00:05Z |
| publishDate | 2018-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-6e7cc6f64893416e97bdb93566349b102022-12-22T02:18:51ZengMDPI AGEnergies1996-10732018-08-01119222410.3390/en11092224en11092224Methodology for Extracting Potential Customized Bus Routes Based on Bus Smart Card DataJing Li0Yongbo Lv1Jihui Ma2Qi Ouyang3School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaTo 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.http://www.mdpi.com/1996-1073/11/9/2224public transport servicecustomized busroute planningbus smart card dataimproved DBSCAN algorithm |
| spellingShingle | Jing Li Yongbo Lv Jihui Ma Qi Ouyang Methodology for Extracting Potential Customized Bus Routes Based on Bus Smart Card Data Energies public transport service customized bus route planning bus smart card data improved DBSCAN algorithm |
| title | Methodology for Extracting Potential Customized Bus Routes Based on Bus Smart Card Data |
| title_full | Methodology for Extracting Potential Customized Bus Routes Based on Bus Smart Card Data |
| title_fullStr | Methodology for Extracting Potential Customized Bus Routes Based on Bus Smart Card Data |
| title_full_unstemmed | Methodology for Extracting Potential Customized Bus Routes Based on Bus Smart Card Data |
| title_short | Methodology for Extracting Potential Customized Bus Routes Based on Bus Smart Card Data |
| title_sort | methodology for extracting potential customized bus routes based on bus smart card data |
| topic | public transport service customized bus route planning bus smart card data improved DBSCAN algorithm |
| url | http://www.mdpi.com/1996-1073/11/9/2224 |
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