2017/04/22 by Thanh Thoa Pham Thi, Joe Timoney, Thi, Thanh Thoa Pham +8
Computer Science · Engineering · Social Sciences · #Computers and Society (cs.CY) #FOS: Computer and information sciences #Transportation Planning and Optimization #Urban Transport and Accessibility #Urban and Freight Transport Logistics #cs.CY
paper · pdf · doi:10.48550/arxiv.1704.06802
GISRUK 2017
arxiv created 2017/04/22 · openalex publication_date 2017/04/22 · arxiv updated 2017/04/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Public bike renting is more and more popular in cities to incentivise a reduction in car journeys and to boost the use of green transportation alternatives. One of the challenges of this application is to effectively plan the resources usage. This paper presents some analysis of Dublin bike renting scheme based on statistics and data mining. It provides available bike patterns at the most interesting bike stations, that is, the busiest and the quietest stations. Consistency checking with new data reinforces confidence in the patterns obtained. Identifying available bike patterns helps to better address user needs such as organising the rebalancing of the bike numbers between stations in advance of demand.