Identifying Left Behind Passengers at Subway Stations from Auto Fare Collection Data
With the rapid growth in transport demand, it has become a frequent occurrence that passengers are left behind especially during peak hours in subway, which has led to a significant reduction in the level of service. In this paper, we propose a left behind passengers identifying method based on Auto...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2022-01-01
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| Series: | Tehnički Vjesnik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/412460 |
| _version_ | 1827281973774647296 |
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| author | Lianghui Xie Zhenji Zhang Daqing Gong |
| author_facet | Lianghui Xie Zhenji Zhang Daqing Gong |
| author_sort | Lianghui Xie |
| collection | DOAJ |
| description | With the rapid growth in transport demand, it has become a frequent occurrence that passengers are left behind especially during peak hours in subway, which has led to a significant reduction in the level of service. In this paper, we propose a left behind passengers identifying method based on Automatic Fare Collection (AFC) and Automated Vehicle Location (AVL) data. Firstly, we choose the passengers with the limited deterministic information as the research objects; secondly, we propose a classification-based method for identifying left behind passengers by the probabilistic model; next, the accuracy and effectiveness of the proposed method is verified by the simulation experiment and the case of Beijing Subway. Ultimately, the proposed method will support research related to the operation, management and future development of subways. |
| first_indexed | 2024-04-24T09:10:14Z |
| format | Article |
| id | doaj.art-3267ff3695e74d86b2697689be68fc0a |
| institution | Directory Open Access Journal |
| issn | 1330-3651 1848-6339 |
| language | English |
| last_indexed | 2024-04-24T09:10:14Z |
| publishDate | 2022-01-01 |
| publisher | Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek |
| record_format | Article |
| series | Tehnički Vjesnik |
| spelling | doaj.art-3267ff3695e74d86b2697689be68fc0a2024-04-15T18:00:54ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in OsijekTehnički Vjesnik1330-36511848-63392022-01-012961949195510.17559/TV-20220903113056Identifying Left Behind Passengers at Subway Stations from Auto Fare Collection DataLianghui Xie0Zhenji Zhang1Daqing Gong2School of Economics and Management, Beijing Jiaotong University, No. 3 Shangyuancun, Haidian District, Beijing 100044, P. R. ChinaSchool of Economics and Management, Beijing Jiaotong University, No. 3 Shangyuancun, Haidian District, Beijing 100044, P. R. ChinaSchool of Economics and Management, Beijing Jiaotong University, No. 3 Shangyuancun, Haidian District, Beijing 100044, P. R. ChinaWith the rapid growth in transport demand, it has become a frequent occurrence that passengers are left behind especially during peak hours in subway, which has led to a significant reduction in the level of service. In this paper, we propose a left behind passengers identifying method based on Automatic Fare Collection (AFC) and Automated Vehicle Location (AVL) data. Firstly, we choose the passengers with the limited deterministic information as the research objects; secondly, we propose a classification-based method for identifying left behind passengers by the probabilistic model; next, the accuracy and effectiveness of the proposed method is verified by the simulation experiment and the case of Beijing Subway. Ultimately, the proposed method will support research related to the operation, management and future development of subways.https://hrcak.srce.hr/file/412460Automatic Fare Collection (AFC)left behindprobabilistic modelsubwaytemporal distribution |
| spellingShingle | Lianghui Xie Zhenji Zhang Daqing Gong Identifying Left Behind Passengers at Subway Stations from Auto Fare Collection Data Tehnički Vjesnik Automatic Fare Collection (AFC) left behind probabilistic model subway temporal distribution |
| title | Identifying Left Behind Passengers at Subway Stations from Auto Fare Collection Data |
| title_full | Identifying Left Behind Passengers at Subway Stations from Auto Fare Collection Data |
| title_fullStr | Identifying Left Behind Passengers at Subway Stations from Auto Fare Collection Data |
| title_full_unstemmed | Identifying Left Behind Passengers at Subway Stations from Auto Fare Collection Data |
| title_short | Identifying Left Behind Passengers at Subway Stations from Auto Fare Collection Data |
| title_sort | identifying left behind passengers at subway stations from auto fare collection data |
| topic | Automatic Fare Collection (AFC) left behind probabilistic model subway temporal distribution |
| url | https://hrcak.srce.hr/file/412460 |
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