Lots of cities have developed a bike sharing system, but how to deploy a bike sharing system reasonably is urgent issue in the cities like Kunming. A knowledge based on these factors that re-balancing on a bike sharing system will work on to support cities to design an efficient service bike sharing system while decreasing re-balancing costs. We collect traffic-zone-level bike sharing usage data in Kunming, analyze the bike sharing time-variation and daily variation characteristics of arrivals and departures. Especially, we built multiple regression model to quantify effect of socio-demographic characteristics and land-use characteristics on time-variation and daily variation characteristics of arrivals and departures. We then define the absolute value of arrivals minus departures as balance index, and develop a binary logit model to estimate the influence of socio-demographic characteristics, land-use characteristics, and public transit characteristics on re-balancing. The results provide a basis for the re-balancing of a bike sharing system.
Study on Bike Sharing Rebalancing: Evidence from Kunming
13th Asia Pacific Transportation Development Conference ; 2020 ; Shanghai, China (Conference Cancelled)
2020-06-29
Conference paper
Electronic Resource
English
Study on Bike Sharing Rebalancing: Evidence from Kunming
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