Dataset Information

Statistical patterns of human mobility in emerging Bicycle Sharing Systems.

ABSTRACT: The emerging Bicycle Sharing System (BSS) provides a new social microscope that allows us to "photograph" the main aspects of the society and to create a comprehensive picture of human mobility behavior in this new medium. BSS has been deployed in many major cities around the world as a short-distance trip supplement for public transportations and private vehicles. A unique value of the bike flow data generated by these BSSs is to understand the human mobility in a short-distance trip. This understanding of the population on short-distance trip is lacking, limiting our capacity in management and operation of BSSs. Many existing operations research and management methods for BSS impose assumptions that emphasize statistical simplicity and homogeneity. Therefore, a deep understanding of the statistical patterns embedded in the bike flow data is an urgent and overriding issue to inform decision-makings for a variety of problems including traffic prediction, station placement, bike reallocation, and anomaly detection. In this paper, we aim to conduct a comprehensive analysis of the bike flow data using two large datasets collected in Chicago and Hangzhou over months. Our analysis reveals intrinsic structures of the bike flow data and regularities in both spatial and temporal scales such as a community structure and a taxonomy of the eigen-bike-flows.

SUBMITTER: Chang X

PROVIDER: S-EPMC5854355 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Statistical patterns of human mobility in emerging Bicycle Sharing Systems.

Chang Xiangyu X Shen Jingzhou J Lu Xiaoling X Huang Shuai S

PloS one 20180315 3

The emerging Bicycle Sharing System (BSS) provides a new social microscope that allows us to "photograph" the main aspects of the society and to create a comprehensive picture of human mobility behavior in this new medium. BSS has been deployed in many major cities around the world as a short-distance trip supplement for public transportations and private vehicles. A unique value of the bike flow data generated by these BSSs is to understand the human mobility in a short-distance trip. This unde ...[more]

PMID: 29543832

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Project description:ObjectiveTo model the impacts of the bicycle sharing system in London on the health of its users.DesignHealth impact modelling and evaluation, using a stochastic simulation model.SettingCentral and inner London, England.Data sourcesTotal population operational registration and usage data for the London cycle hire scheme (collected April 2011-March 2012), surveys of cycle hire users (collected 2011), and London data on travel, physical activity, road traffic collisions, and particulate air pollution (PM2.5, (collected 2005-12).Participants578,607 users of the London cycle hire scheme, aged 14 years and over, with an estimated 78% of travel time accounted for by users younger than 45 years.Main outcome measuresChange in lifelong disability adjusted life years (DALYs) based on one year impacts on incidence of disease and injury, modelled through medium term changes in physical activity, road traffic injuries, and exposure to air pollution.ResultsOver the year examined the users made 7.4 million cycle hire trips (estimated 71% of cycling time by men). These trips would mostly otherwise have been made on foot (31%) or by public transport (47%). To date there has been a trend towards fewer fatalities and injuries than expected on cycle hire bicycles. Using these observed injury rates, the population benefits from the cycle hire scheme substantially outweighed harms (net change -72 DALYs (95% credible interval -110 to -43) among men using cycle hire per accounting year; -15 (-42 to -6) among women; note that negative DALYs represent a health benefit). When we modelled cycle hire injury rates as being equal to background rates for all cycling in central London, these benefits were smaller and there was no evidence of a benefit among women (change -49 DALYs (-88 to -17) among men; -1 DALY (-27 to 12) among women). This sex difference largely reflected higher road collision fatality rates for female cyclists. At older ages the modelled benefits of cycling were much larger than the harms. Using background injury rates in the youngest age group (15 to 29 years), the medium term benefits and harms were both comparatively small and potentially negative.ConclusionLondon's bicycle sharing system has positive health impacts overall, but these benefits are clearer for men than for women and for older users than for younger users. The potential benefits of cycling may not currently apply to all groups in all settings.

Project description:BackgroundPublic bicycle share programs in many cities are used by a small segment of the population. To better understand the market for public bicycle share, this study examined the socio-demographic and transportation characteristics of current, potential, and unlikely users of a public bicycle share program and identified specific motivators and deterrents to public bicycle share use.MethodsWe used cross-sectional data from a 2017 Vancouver public bicycle share (Mobi by Shaw Go) member survey (n = 1272) and a 2017 population-based survey of Vancouver residents (n = 792). We categorized non-users from the population survey as either potential or unlikely users based on their stated interest in using public bicycle share within the next year. We used descriptive statistics to compare the demographic and transportation characteristics of current users to non-users, and multiple logistic regression to compare the profiles of potential and unlikely users.ResultsPublic bicycle share users in Vancouver tended to be male, employed, and have higher educations and incomes as compared to non-users, and were more likely to use active modes of transportation. The vast majority of non-users (74%) thought the public bicycle share program was a good idea for Vancouver. Of the non-users, 23% were identified as potential users. Potential users tended to be younger, have lower incomes, and were more likely to use public transit for their main mode of transportation, as compared to current and unlikely users. The most common motivators among potential users related to health benefits, not owning a bicycle, and stations near their home or destination. The deterrents among unlikely users were a preference for riding their own bicycle, perceived inconvenience compared to other modes, bad weather, and traffic. Cost was a deterrent to one-fifth of unlikely users, notable given they tended to have lower incomes than current users.ConclusionFindings can help inform targeted marketing and outreach to increase public bicycle share uptake in the population.

Dataset Information

Statistical patterns of human mobility in emerging Bicycle Sharing Systems.

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Statistical patterns of human mobility in emerging Bicycle Sharing Systems.

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