Preliminary Results of a Spatial Analysis of Dublin City’s Bike Rental Scheme

We present some initial observations on the usage and flow patterns of the DublinBikes (DB) bicycle rental scheme across Dublin city. In September 2009 Dublin City in conjunction with outdoor advertising company JC Decaux made 450 bicycles publicly available from 40 locations around the city in a scheme called DublinBikes (DB). Cycling, as a commuting mode forms an important part of the Irish Government's Transport policy for Ireland up to 2020 stating that "a culture of cycling will be developed by 2020 to envisage around 160,000 people cycling for their daily commute, up from 35,000 in 2006"(DOT, 2009). We follow Froehlich et al (2008) who find usage patterns from these bike rental schemes can "infer cultural and geographical aspects of the city and predict future bike station usage behaviour" when combined with geographical information and local knowledge. Data captured on DB and presented in this paper covers the period of September 20th 2009 to February 15th 2010 inclusive

Preliminary Results of a Spatial Analysis of Dublin City’s Bike Rental Scheme

We present some initial observations on the usage and flow patterns of the DublinBikes (DB) bicycle rental scheme across Dublin city. In September 2009 Dublin City in conjunction with outdoor advertising company JC Decaux made 450 bicycles publicly available from 40 locations around the city in a scheme called DublinBikes (DB). Cycling, as a commuting mode forms an important part of the Irish Government's Transport policy for Ireland up to 2020 stating that "a culture of cycling will be developed by 2020 to envisage around 160,000 people cycling for their daily commute, up from 35,000 in 2006"(DOT, 2009). We follow Froehlich et al (2008) who find usage patterns from these bike rental schemes can "infer cultural and geographical aspects of the city and predict future bike station usage behaviour" when combined with geographical information and local knowledge. Data captured on DB and presented in this paper covers the period of September 20th 2009 to February 15th 2010 inclusive

Visualizing the dynamics of London's bicycle hire scheme

Visualizing flows between origins and destinations can be straightforward when dealing with small numbers of journeys or simple geographies. Representing flows as lines embedded in geographic space has commonly been used to map transport flows, especially when geographic patterns are important as they are when characterising cities or managing transportation. However, for larger numbers of flows, this approach requires careful design to avoid problems of occlusion, salience bias and information overload. Driven by the requirements identified by users and managers of the London Bicycle Hire scheme we present three methods of representation of bicycle hire use and travel patterns. Flow maps with curved flow symbols are used to show overviews in flow structures. Gridded views of docking station location that preserve geographic relationships are used to explore docking station status over space and time in a graphically efficient manner. Origin-Destination maps that visualise the OD matrix directly while maintaining geographic context are used to provide visual details on demand. We use these approaches to identify changes in travel behaviour over space and time, to aid station rebalancing and to provide a framework for incorporating travel modelling and simulation

Spatiotemporal Mining of BSS Data for Characterising Seasonal Urban Mobility Dynamics

Digital traces of individual mobility can be revealed from the origin-destination sensing systems of BSS (Bicycle Sharing System). This record enables wide analysis of human mobility traits in urban area including pattern, trend, and anomalies. This study investigates and compares trip history of BSS open data from two cities, London and New York, along a year period with respect to annual weather data as explanatory factors. This aims to get insights about seasonal urban mobility dynamics both temporally and spatially. Results show that, for both cities, there are differences as well as similarities of temporal correlation level between riding behaviour of BSS users and hour of the day, day of the week, season, and local weather. Practically, the most correlated factor can be further considered and used as predictive features. Meanwhile, the proposed spatial analysis shows the positive bikes imbalance occurs in the morning, mostly at inner stations because of inward flow, and vice versa. This spatial extent can be used for redistribution purpose, specifically in order to provide enough resources at the highly visited stations before peak time occurs

UNDERSTANDING USAGE OF PUBLIC BIKE SHARING SYSTEM : CITI BIKE AS AN EXAMPLE

In recent years, bike sharing systems ushered in the explosive growth. The growth of bike sharing systems brings both health benefits and environmental benefits.This study is a data analysis project that investigate the usage pattern of bike sharing system using Citi Bike open source data. This study provide a demand prediction and gender prediction model. Also, this study studied the influence of weather and date on the demand of bike usage, and compare the characteristic usage pattern of two different gender group. With the comparison on usage of NY taxi, this study analysis when people prefer Citi Bike and verify that Citi Bike can be an ideal alternative transportation to taxis.Master of Science in Information Scienc

The characteristics of bike-sharing usage:case study in Zhongshan, China

Public bike systems have grown in popularity and are expanding rapidly across cities worldwide. Such systems provide access to pickup and drop-off public bikes at numerous bike stations for free or for an affordable fee and aim at increasing bike use and extending the accessibility of traditional public transport systems. A variety of studies have examined the characteristics of bike-sharing systems, mostly in American and European cities and with a focus on user demographics. The objective of this study is to investigate the general characteristics of system usage, in terms of system efficiency, trip characteristics and bike activity patterns, for Zhongshan’s public bike system during a five-month period. The findings show that the system is not very efficient based on usage metrics which are low compared to successful systems in other countries. Demand is relatively high in city centre zones due to high population and activity density. However, there is no clear direction of inbound or outbound trips in rush hours. This may be attributed not only to mixed land use patterns throughout the city, but also to the fact that most trips are local trips over short distance. This could indicate that public bike trips are mainly substitute for walking trips rather than for car or PT trips. On the outskirts, demand and system efficiency are low, indicating that location allocation of stations needs adjustment. In the conclusions, we discuss how these findings can be used for improving the system