Multi-View Interactive Visual Exploration of Individual Association for Public Transportation Passengers
More and more people in mega cities are choosing to travel by public transportation due to its convenience and punctuality. It is widely acknowledged that there may be some potential associations between passengers. Their travel behavior may be working together, shopping together, or even some abnor...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-01-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/2/628 |
| _version_ | 1818301060279697408 |
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| author | Di Lv Yong Zhang Jiongbin Lin Peiyuan Wan Yongli Hu |
| author_facet | Di Lv Yong Zhang Jiongbin Lin Peiyuan Wan Yongli Hu |
| author_sort | Di Lv |
| collection | DOAJ |
| description | More and more people in mega cities are choosing to travel by public transportation due to its convenience and punctuality. It is widely acknowledged that there may be some potential associations between passengers. Their travel behavior may be working together, shopping together, or even some abnormal behaviors, such as stealing or begging. Thus, analyzing association between passengers is very important for management departments. It is very helpful to make operational plans, provide better services to passengers and ensure public transport safety. In order to quickly explore the association between passengers, we propose a multi-view interactive exploration method that provides five interactive views: passenger 3D travel trajectory view, passenger travel time pixel matrix view, passenger origin-destination chord view, passenger travel vehicle bubble chart view and passenger 2D travel trajectory view. It can explore the associated passengers from multiple aspects such as travel trajectory, travel area, travel time, and vehicles used for travel. Using Beijing public transportation data, the experimental results verified that our method can effectively explore the association between passengers and deduce the relationship. |
| first_indexed | 2024-12-13T05:17:00Z |
| format | Article |
| id | doaj.art-7d6f51e8696f4b189a77c817de831f3c |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-12-13T05:17:00Z |
| publishDate | 2020-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-7d6f51e8696f4b189a77c817de831f3c2022-12-21T23:58:24ZengMDPI AGApplied Sciences2076-34172020-01-0110262810.3390/app10020628app10020628Multi-View Interactive Visual Exploration of Individual Association for Public Transportation PassengersDi Lv0Yong Zhang1Jiongbin Lin2Peiyuan Wan3Yongli Hu4Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Faculty of Information Technology, Beijing University of Technology, No.100, Pingleyuan, Chaoyang District, Beijing 100124, ChinaBeijing Key Laboratory of Multimedia and Intelligent Software Technology, Faculty of Information Technology, Beijing University of Technology, No.100, Pingleyuan, Chaoyang District, Beijing 100124, ChinaBeijing Key Laboratory of Multimedia and Intelligent Software Technology, Faculty of Information Technology, Beijing University of Technology, No.100, Pingleyuan, Chaoyang District, Beijing 100124, ChinaFaculty of Information Technology, Beijing University of Technology, No.100, Pingleyuan, Chaoyang District, Beijing 100124, ChinaBeijing Key Laboratory of Multimedia and Intelligent Software Technology, Faculty of Information Technology, Beijing University of Technology, No.100, Pingleyuan, Chaoyang District, Beijing 100124, ChinaMore and more people in mega cities are choosing to travel by public transportation due to its convenience and punctuality. It is widely acknowledged that there may be some potential associations between passengers. Their travel behavior may be working together, shopping together, or even some abnormal behaviors, such as stealing or begging. Thus, analyzing association between passengers is very important for management departments. It is very helpful to make operational plans, provide better services to passengers and ensure public transport safety. In order to quickly explore the association between passengers, we propose a multi-view interactive exploration method that provides five interactive views: passenger 3D travel trajectory view, passenger travel time pixel matrix view, passenger origin-destination chord view, passenger travel vehicle bubble chart view and passenger 2D travel trajectory view. It can explore the associated passengers from multiple aspects such as travel trajectory, travel area, travel time, and vehicles used for travel. Using Beijing public transportation data, the experimental results verified that our method can effectively explore the association between passengers and deduce the relationship.https://www.mdpi.com/2076-3417/10/2/628visual analyticspublic transportationic card dataassociated passengerinteractive visualisation |
| spellingShingle | Di Lv Yong Zhang Jiongbin Lin Peiyuan Wan Yongli Hu Multi-View Interactive Visual Exploration of Individual Association for Public Transportation Passengers Applied Sciences visual analytics public transportation ic card data associated passenger interactive visualisation |
| title | Multi-View Interactive Visual Exploration of Individual Association for Public Transportation Passengers |
| title_full | Multi-View Interactive Visual Exploration of Individual Association for Public Transportation Passengers |
| title_fullStr | Multi-View Interactive Visual Exploration of Individual Association for Public Transportation Passengers |
| title_full_unstemmed | Multi-View Interactive Visual Exploration of Individual Association for Public Transportation Passengers |
| title_short | Multi-View Interactive Visual Exploration of Individual Association for Public Transportation Passengers |
| title_sort | multi view interactive visual exploration of individual association for public transportation passengers |
| topic | visual analytics public transportation ic card data associated passenger interactive visualisation |
| url | https://www.mdpi.com/2076-3417/10/2/628 |
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