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Using flow analysis of bike-sharing system for finding spatiotemporal mobility patterns in Kuopio city region
There have been an increasing number of studies related to analyzing bike-sharing systems (BSS) in the recent years. In this article a method for finding interesting interstation routes and doing temporal analysis for them is portrayed. Analyzing flows between stations supports both planning of new...
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Main Authors: | , , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
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Summary: | There have been an increasing number of studies related to analyzing bike-sharing systems (BSS) in the recent years. In this article a method for finding interesting interstation routes and doing temporal analysis for them is portrayed. Analyzing flows between stations supports both planning of new station locations and improving biking infrastructure. It also gives information about mobility patterns of citizens. Data for this analysis is from Kuopio city's BSS for four seasons from 2019 to 2022. Kuopio's BSS is a hybrid fourth generation system with e-bikes, virtual stations, mobile passes and limited free-floating bike area. BSS first came to Kuopio in May of 2019 and by the end of 2022 there were 350 e-bikes and 41 stations in use. Dataset for years from 2019 to 2022 consists of total 1 180 494 rows of trip data of which 913 995 are trips between stations. This dataset is published freely available. The analysis concentrates to find out spatiotemporal flow patterns between stations and temporal activity patterns of each station. For singular route analysis two data visualization types were enough to give sufficient overview. Flow maps were used for identifying these routes of interest and getting general idea of spatiotemporal traffic flows. The results of this analysis can be used for further improvement of city's biking infrastructure to better serve mobility needs of citizens. |
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ISSN: | 2687-8860 |
DOI: | 10.1109/ISC257844.2023.10293575 |