A Novel Dynamic Dispatching Method for Bicycle-Sharing System
With the rapid development of sharing bicycles, unreasonable dispatching methods are likely to cause a series of issues, such as resource waste and traffic congestion in the city. In this paper, a new dynamic scheduling method is proposed, named Tri-G, so as to solve the above problems. First of all...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-02-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | http://www.mdpi.com/2220-9964/8/3/117 |
| _version_ | 1819042997127348224 |
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| author | Dianhui Mao Zhihao Hao Yalei Wang Shuting Fu |
| author_facet | Dianhui Mao Zhihao Hao Yalei Wang Shuting Fu |
| author_sort | Dianhui Mao |
| collection | DOAJ |
| description | With the rapid development of sharing bicycles, unreasonable dispatching methods are likely to cause a series of issues, such as resource waste and traffic congestion in the city. In this paper, a new dynamic scheduling method is proposed, named Tri-G, so as to solve the above problems. First of all, the whole visualization information of bike stations was built based on a Spatio-Temporal Graph (STG), then Gaussian Mixture Mode (GMM) was used to group individual stations into clusters according to their geographical locations and transition patterns, and the Gradient Boosting Regression Tree (GBRT) algorithm was adopted to predict the number of bikes inflow/outflow at each station in real time. This paper used New York’s bicycle commute data to build global STG visualization information to evaluate Tri-G. Finally, it is concluded that Tri-G is superior to the methods in control groups, which can be applied to various geographical scenarios. In addition, this paper also discovered some human mobility patterns as well as some rules, which are helpful for governments to improve urban planning. |
| first_indexed | 2024-12-21T09:49:46Z |
| format | Article |
| id | doaj.art-29f4203a18e64ab88a6ab76db5d704e9 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-12-21T09:49:46Z |
| publishDate | 2019-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-29f4203a18e64ab88a6ab76db5d704e92022-12-21T19:08:13ZengMDPI AGISPRS International Journal of Geo-Information2220-99642019-02-018311710.3390/ijgi8030117ijgi8030117A Novel Dynamic Dispatching Method for Bicycle-Sharing SystemDianhui Mao0Zhihao Hao1Yalei Wang2Shuting Fu3Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, ChinaBeijing Key Laboratory of Big Data Technology for Food Safety, School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, ChinaBeijing Key Laboratory of Big Data Technology for Food Safety, School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, ChinaBeijing Key Laboratory of Big Data Technology for Food Safety, School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, ChinaWith the rapid development of sharing bicycles, unreasonable dispatching methods are likely to cause a series of issues, such as resource waste and traffic congestion in the city. In this paper, a new dynamic scheduling method is proposed, named Tri-G, so as to solve the above problems. First of all, the whole visualization information of bike stations was built based on a Spatio-Temporal Graph (STG), then Gaussian Mixture Mode (GMM) was used to group individual stations into clusters according to their geographical locations and transition patterns, and the Gradient Boosting Regression Tree (GBRT) algorithm was adopted to predict the number of bikes inflow/outflow at each station in real time. This paper used New York’s bicycle commute data to build global STG visualization information to evaluate Tri-G. Finally, it is concluded that Tri-G is superior to the methods in control groups, which can be applied to various geographical scenarios. In addition, this paper also discovered some human mobility patterns as well as some rules, which are helpful for governments to improve urban planning.http://www.mdpi.com/2220-9964/8/3/117bike-sharingSpatio-Temporal Graphgaussian mixture modedispatching method |
| spellingShingle | Dianhui Mao Zhihao Hao Yalei Wang Shuting Fu A Novel Dynamic Dispatching Method for Bicycle-Sharing System ISPRS International Journal of Geo-Information bike-sharing Spatio-Temporal Graph gaussian mixture mode dispatching method |
| title | A Novel Dynamic Dispatching Method for Bicycle-Sharing System |
| title_full | A Novel Dynamic Dispatching Method for Bicycle-Sharing System |
| title_fullStr | A Novel Dynamic Dispatching Method for Bicycle-Sharing System |
| title_full_unstemmed | A Novel Dynamic Dispatching Method for Bicycle-Sharing System |
| title_short | A Novel Dynamic Dispatching Method for Bicycle-Sharing System |
| title_sort | novel dynamic dispatching method for bicycle sharing system |
| topic | bike-sharing Spatio-Temporal Graph gaussian mixture mode dispatching method |
| url | http://www.mdpi.com/2220-9964/8/3/117 |
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