Temporal-spatial characteristics analysis of shared bikes travel based on multi-source data

Jie Lin; Xianyu Wu; Songmei Xie

doi:10.1117/12.2619769

22 December 2021 Temporal-spatial characteristics analysis of shared bikes travel based on multi-source data

Jie Lin, Xianyu Wu, Songmei Xie

Proceedings Volume 12058, Fifth International Conference on Traffic Engineering and Transportation System (ICTETS 2021); 120584Z (2021) https://doi.org/10.1117/12.2619769
Event: 5th International Conference on Traffic Engineering and Transportation System (ICTETS 2021), 2021, Chongqing, China

Abstract

As the commutes of urban residents are concentrated in time and unidirectional in space, there is often a mismatch between supply and demand in the operation of shared bikes. In order to solve the problem of supply and demand imbalance of shared bikes, based on the travel order data and parking sites data of shared bikes, combined with land use property data, statistical methods and ArcMap software are used to analyze temporal-spatial characteristics of shared bikes. The results show that the use of shared bikes has obvious temporal-spatial regularity. Firstly, there is an obvious difference in the usage characteristics of shared bikes on weekdays and non-weekdays. The hourly distribution of cycling volume on weekdays shows an M-shaped distribution, and there is an peak phenomenon in the morning and evening. Secondly, hotspots of shared bikes are mostly distributed in public transportation stations, residential areas and commercial office areas. Thirdly, the demand for shared bikes in different functional areas has different rules. Therefore, the travel characteristics analysis of shared bikes can provide reference for the operating enterprises to understand the demand characteristics of shared bikes, and realize the refinement and dynamic management of shared bikes.

Citation Download Citation

Jie Lin, Xianyu Wu, and Songmei Xie "Temporal-spatial characteristics analysis of shared bikes travel based on multi-source data", Proc. SPIE 12058, Fifth International Conference on Traffic Engineering and Transportation System (ICTETS 2021), 120584Z (22 December 2021); https://doi.org/10.1117/12.2619769

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