The structure of spatial networks and communities in bicycle sharing systems.
ABSTRACT: Bicycle sharing systems exist in hundreds of cities around the world, with the aim of providing a form of public transport with the associated health and environmental benefits of cycling without the burden of private ownership and maintenance. Five cities have provided research data on the journeys (start and end time and location) taking place in their bicycle sharing system. In this paper, we employ visualization, descriptive statistics and spatial and network analysis tools to explore system usage in these cities, using techniques to investigate features specific to the unique geographies of each, and uncovering similarities between different systems. Journey displacement analysis demonstrates similar journey distances across the cities sampled, and the (out)strength rank curve for the top 50 stands in each city displays a similar scaling law for each. Community detection in the derived network can identify local pockets of use, and spatial network corrections provide the opportunity for insight above and beyond proximity/popularity correlations predicted by simple spatial interaction models.
Project description:INTRODUCTION:Bicycling is promoted as a transportation and population health strategy globally. Yet bicycling has low uptake in North America (1%-2% of trips) compared with European bicycling cities (15%-40% of trips) and shows marked sex and age trends. Safety concerns due to collisions with motor vehicles are primary barriers.To attract the broader population to bicycling, many cities are making investments in bicycle infrastructure. These interventions hold promise for improving population health given the potential for increased physical activity and improved safety, but such outcomes have been largely unstudied. In 2016, the City of Victoria, Canada, committed to build a connected network of infrastructure that separates bicycles from motor vehicles, designed to attract people of 'all ages and abilities' to bicycling.This natural experiment study examines the impacts of the City of Victoria's investment in a bicycle network on active travel and safety outcomes. The specific objectives are to (1) estimate changes in active travel, perceived safety and bicycle safety incidents; (2) analyse spatial inequities in access to bicycle infrastructure and safety incidents; and (3) assess health-related economic benefits. METHODS AND ANALYSIS:The study is in three Canadian cities (intervention: Victoria; comparison: Kelowna, Halifax). We will administer population-based surveys in 2016, 2018 and 2021 (1000 people/city). The primary outcome is the proportion of people reporting bicycling. Secondary outcomes are perceived safety and bicycle safety incidents. Spatial analyses will compare the distribution of bicycle infrastructure and bicycle safety incidents across neighbourhoods and across time. We will also calculate the economic benefits of bicycling using WHO's Health Economic Assessment Tool. ETHICS AND DISSEMINATION:This study received approval from the Simon Fraser University Office of Research Ethics (study no. 2016s0401). Findings will be disseminated via a website, presentations to stakeholders, at academic conferences and through peer-reviewed journal articles.
Project description:Understanding the influence of the built environment on human movement requires quantifying spatial structure in a general sense. Because of the difficulty of this task, studies of movement dynamics often ignore spatial heterogeneity and treat movement through journey lengths or distances alone. This study analyses public bicycle data from central London to reveal that, although journey distances, directions, and frequencies of occurrence are spatially variable, their relative spatial patterns remain largely constant, suggesting the influence of a fixed spatial template. A method is presented to describe this underlying space in terms of the relative orientation of movements toward, away from, and around locations of geographical or cultural significance. This produces two fields: one of convergence and one of divergence, which are able to accurately reconstruct the observed spatial variations in movement. These two fields also reveal categorical distinctions between shorter journeys merely serving diffusion away from significant locations, and longer journeys intentionally serving transport between spatially distinct centres of collective importance. Collective patterns of human movement are thus revealed to arise from a combination of both diffusive and directed movement, with aggregate statistics such as mean travel distances primarily determined by relative numbers of these two kinds of journeys.
Project description:Bike-sharing programs, with initiatives to increase bike use and improve accessibility of urban transit, have received increasing attention in growing number of cities across the world. The latest generation of bike-sharing systems has employed smart card technology that produces station-based data or trip-level data. This facilitates the studies of the practical use of these systems. However, few studies have paid attention to the changes in users and system usage over the years, as well as the impact of system expansion on its usage. Monitoring the changes of system usage over years enables the identification of system performance and can serve as an input for improving the location-allocation of stations. The objective of this study is to explore the impact of the expansion of a bicycle-sharing system on the usage of the system. This was conducted for a bicycle-sharing system in Zhongshan (China), using operational usage data of different years following system expansion. To this end, we performed statistical and spatial analyses to examine the changes in both users and system usage between before and after the system expansion. The findings show that there is a big variation in users and aggregate usage following the system expansion. However, the trend in spatial distribution of demand shows no substantial difference over the years, i.e. the same high-demand and low-demand areas appear. There are decreases in demand for some old stations over the years, which can be attributed to either the negative performance of the system or the competition of nearby new stations. Expanding the system not only extends the original users' ability to reach new areas but also attracts new users to use bike-sharing systems. In the conclusions, we present and discuss the findings, and offer recommendations for the further expansion of system.
Project description:OBJECTIVE: To determine whether the author's 20.9 lb (9.5 kg) carbon frame bicycle reduced commuting time compared with his 29.75 lb (13.5 kg) steel frame bicycle. DESIGN: Randomised trial. SETTING: Sheffield and Chesterfield, United Kingdom, between mid-January 2010 and mid-July 2010. PARTICIPANTS: One consultant in anaesthesia and intensive care. MAIN OUTCOME MEASURE: Total time to complete the 27 mile (43.5 kilometre) journey from Sheffield to Chesterfield Royal Hospital and back. RESULTS: The total distance travelled on the steel frame bicycle during the study period was 809 miles (1302 km) and on the carbon frame bicycle was 711 miles (1144 km). The difference in the mean journey time between the steel and carbon bicycles was 00:00:32 (hr:min:sec; 95% CI -00:03:34 to 00:02:30; P=0.72). CONCLUSIONS: A lighter bicycle did not lead to a detectable difference in commuting time. Cyclists may find it more cost effective to reduce their own weight rather than to purchase a lighter bicycle.
Project description:Bicycle lanes reduce real and perceived risks for bicycle vs. motor vehicle crashes, reducing the burden of traffic injuries and contributing to greater cycling participation. Previous research indicates that the effectiveness of bicycle lanes differs according to roadway characteristics, and that bicycle lane types are differentially associated with reduced crash risks. The aim of this study is to combine these perspectives and identify the types of on-road bicycle lanes that are associated with the greatest reductions in bicycle crashes given the presence of specific roadway characteristics. We compiled a cross sectional spatial dataset consisting of 32,444 intersection polygons and 57,285 street segment polygons representing the roadway network for inner Melbourne, Australia. The dependent measure was a dichotomous indicator for any bicycle crash (2014-2017). Independent measures were bicycle lanes (exclusive bicycle lanes, shared bicycle and parking lanes, marked wide kerbside lanes, and kerbside bicycle lanes) and other roadway characteristics (speed limit, bus routes, tram routes, bridges, one-way flow, traffic lane width). In Bayesian conditional autoregressive logit models, bicycle lanes of all types were associated with decreased crash odds where speeds were greater, bus routes and tram stops were present, and traffic lanes were narrower. Only exclusive bicycle lanes were associated with reduced crash odds (compared to the expected odds given the presence of the bicycle lane and the roadway conditions) in all these setting. The extent to which on-road bicycle lanes reduce crash risks depends on the bicycle lane type, the roadway conditions, and the combination of these two factors. Bicycle lanes that provide greater separation between cyclists and vehicular traffic are most consistently protective.
Project description: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.
Project description:<h4>Objectives</h4>To examine (1) the effect of new dock-less bicycle-sharing programmes on change in travel mode and (2) the correlates of change in travel mode.<h4>Design</h4>A retrospective natural experimental study.<h4>Setting</h4>12 neighbourhoods in Shanghai.<h4>Participants</h4>1265 respondents were recruited for a retrospective study in May 2017.<h4>Main outcome measures</h4>Prevalence of cycling before and after launch of dock-less bicycle-sharing programme.<h4>Results</h4>The proportion of participants cycling for transport increased from 33.3% prior to the launch of the bicycle-sharing programmes to 48.3% 1?year after the launch (p<0.001). Being in the age group of 30-49 years (OR 2.28; 95%?CI 1.30 to 4.00), living within the inner ring of the city (OR 2.27; 95%?CI 1.22 to 4.26), having dedicated bicycle lanes (OR 1.37, 95%?CI 1.12 to 1.68) and perceiving riding shared bicycles as fashionable (OR 1.46, 95%?CI 1.21 to 1.76) were positively associated with adopting cycling for transport. Access to a public transportation stop/station (OR 0.82, 95%?CI 0.67 to 0.99) was inversely correlated with adopting cycling for transport.<h4>Conclusions</h4>Dock-less bicycle sharing may promote bicycle use in a metropolitan setting. Findings from this study also highlight the importance of cycling-friendly built environments and cultural norms as facilitators of adopting cycling.
Project description:We conducted individual and ecologic analyses of prospectively collected data from 839 injured bicyclists who collided with motorized vehicles and presented to Bellevue Hospital, an urban Level-1 trauma center in New York City, from December 2008 to August 2014. Variables included demographics, scene information, rider behaviors, bicycle route availability, and whether the collision occurred before the road segment was converted to a bicycle route. We used negative binomial modeling to assess the risk of injury occurrence following bicycle path or lane implementation. We dichotomized U.S. National Trauma Data Bank Injury Severity Scores (ISS) into none/mild (0-8) versus moderate, severe, or critical (>8) and used adjusted multivariable logistic regression to model the association of ISS with collision proximity to sharrows (i.e., bicycle lanes designated for sharing with cars), painted bicycle lanes, or physically protected paths. Negative binomial modeling of monthly counts, while adjusting for pedestrian activity, revealed that physically protected paths were associated with 23% fewer injuries. Painted bicycle lanes reduced injury risk by nearly 90% (IDR 0.09, 95% CI 0.02-0.33). Holding all else equal, compared to no bicycle route, a bicycle injury nearby sharrows was nearly twice as likely to be moderate, severe, or critical (adjusted odds ratio 1.94; 95% confidence interval (CI) 0.91-4.15). Painted bicycle lanes and physically protected paths were 1.52 (95% CI 0.85-2.71) and 1.66 (95% CI 0.85-3.22) times as likely to be associated with more than mild injury respectively.
Project description:OBJECTIVE: To estimate the risks and benefits to health of travel by bicycle, using a bicycle sharing scheme, compared with travel by car in an urban environment. DESIGN: Health impact assessment study. SETTING: Public bicycle sharing initiative, Bicing, in Barcelona, Spain. PARTICIPANTS: 181,982 Bicing subscribers. Main outcomes measures The primary outcome measure was all cause mortality for the three domains of physical activity, air pollution (exposure to particulate matter <2.5 µm), and road traffic incidents. The secondary outcome was change in levels of carbon dioxide emissions. RESULTS: Compared with car users the estimated annual change in mortality of the Barcelona residents using Bicing (n = 181,982) was 0.03 deaths from road traffic incidents and 0.13 deaths from air pollution. As a result of physical activity, 12.46 deaths were avoided (benefit:risk ratio 77). The annual number of deaths avoided was 12.28. As a result of journeys by Bicing, annual carbon dioxide emissions were reduced by an estimated 9,062,344 kg. CONCLUSIONS: Public bicycle sharing initiatives such as Bicing in Barcelona have greater benefits than risks to health and reduce carbon dioxide emissions.
Project description:Bicycle sharing systems are increasingly popular around the world and have the potential to increase the visibility of people cycling in everyday clothing. This may in turn help normalise the image of cycling, and reduce perceptions that cycling is 'risky' or 'only for sporty people'. This paper sought to compare the use of specialist cycling clothing between users of the London bicycle sharing system (LBSS) and cyclists using personal bicycles. To do this, we observed 3594 people on bicycles at 35 randomly-selected locations across central and inner London. The 592 LBSS users were much less likely to wear helmets (16% vs. 64% among personal-bicycle cyclists), high-visibility clothes (11% vs. 35%) and sports clothes (2% vs. 25%). In total, 79% of LBSS users wore none of these types of specialist cycling clothing, as compared to only 30% of personal-bicycle cyclists. This was true of male and female LBSS cyclists alike (all <i>p</i>>0.25 for interaction). We conclude that bicycle sharing systems may not only encourage cycling directly, by providing bicycles to rent, but also indirectly, by increasing the number and diversity of cycling 'role models' visible.