Article

Freedom from the Station: Spatial Equity in Access to Dockless Bike Share

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

Abstract

Background: Bike sharing systems have potential to substantially boost active transportation levels (and consequent physical and mental health) in urban populations. We explored equity of spatial access in a novel 'dockless' bike share system that does not that constrain bike pickup and drop-off locations to docking stations. Methods: Starting in July 2017, Seattle, Washington piloted a dockless bike share system that made 10,000 bikes available. We merged data on resident sociodemographic and economic characteristics from the American Community Survey about 93 defined neighborhoods with data about bike locations, bike idle time, and which neighborhoods operators rebalanced bikes to. We used mapping and descriptive statistics to compare access between neighborhoods along sociodemographic and economic lines. Results: With many bikes available, no neighborhood was consistently excluded from access. However, the average availability ranged from 3 bikes per day to 341 per day. Neighborhoods with more bikes had more college-educated residents (median 75% college-educated vs. 65%) and local community resources (median opportunity index score of 24 vs. 19), and higher incomes (median 83,202 vs. 71,296). Rebalancing destinations were strongly correlated with neighborhood demand (r=0.61). Conclusions: The overall scale of the dockless system ensured there was baseline access throughout Seattle. We observed modest inequities in access along sociodemographic lines, similar to prior findings in studies of docked bike share systems. Dockless bike share systems hold promise for offering equitable spatial access to bike sharing.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

... Dill and McNeil (2020) reviewed the literature on shared mobility and equity and found that the majority of bike-share studies show that lower income populations have lower accessibility and usage. Dockless bike-share and e-scooter-share, on the other hand, have not been analyzed as extensively (Shen et al., 2018;Guidon et al., 2019;Xu et al., 2019;Dill & McNeil, 2020) and studies have mainly focused on a single city (Luo et al., 2018;Shen et al., 2018;McKenzie, 2019;Mooney et al., 2019;Caspi et al., 2020;Li et al., 2020;Younes et al., 2020;. Shen et al. (2018) found that in Singapore, access to public transit, bike infrastructure and several other built environment factors are critical to increasing dockless ridership. ...
... Income and other socio-demographic variables have been analyzed in more recent studies (Caspi & Noland, 2019;Mooney et al., 2019;Caspi et al., 2020;Nasri et al., 2020). An opt-in survey found that e-scooter usage for Baltimore's Black/African American population is on par with the population ratio while for Washington D.C.'s Black/African American population e-scooter usage is less common than for White residents (NACTO, 2020). ...
... Surveys, unlike regression analyses, do not control for all other factors that could explain differences in usage. Mooney et al. (2019) found that neighborhoods in Seattle, WA with more educated residents had modestly more bikes. Another study surveyed Zurich, Switzerland residents and found that shared e-scooter users were more representative of the population (although still younger) than shared bike users, which suggests that escooters may contribute to transportation equity . ...
Article
Full-text available
We examine micromobility usage across four U.S. metropolitan areas, comprising over 3 million people. As micromobility increases in popularity and becomes incorporated in policies and city planning, it is important to understand how disadvantaged and underserved communities utilize shared micromobility options. Underserved communities typically have the lowest access to transportation options and thus, opportunities to jobs, health care, and food. While micromobility has the potential to increase opportunities in low-income areas, it is unclear how people in low-income and high minority areas use these options. Using publicly available API data, we analyze how e-scooters and e-bikes are employed in Los Angeles, Washington, D.C., Detroit, and Louisville. We find that the built environment had a strong impact on both the number of trips within a census block group (CBG) and the duration of those trips. Specifically, pedestrian friendly intersections (e.g. low-speed roads, bicycle and pedestrian trails) generated more trips than automobile oriented facilities. Presence of fixed transportation and percentage of households with one or less cars had a strong and positive impact on the number of trips. The proportion of minorities and percentage of low-wage employment in a CBG are both negatively associated with trips in all four cities. The results suggest that existing efforts to promote shared micromobility usage in minority and low-income communities may not be sufficient. Designing pedestrian and bicycle-oriented streets, increasing public outreach and promoting access, and enforcing equity zones could increase shared micromobility usage in low-income and minority areas.
... However, after offsetting the metro ridership, most of the land use types did not present significant associations with the BnR rate. This indicates the BnR rate is less influenced by land-use typesperhaps other unobserved socio-economic factors such as household car ownership and median income account more (Ji et al., 2017;Mooney et al., 2019). In addition, we found shared bikes around metro stations with more agricultural land exhibit significantly lower utilization rates and BnR rates. ...
... When increasing the fleet size fails to lead to an increase in bike utilization rate, the oversupplied and over-competing market may be established. Meanwhile, local governments should attach more importance to the equality, accessibility, and convenience of BnR services particularly in suburban areas seeing sustained demand (Hu et al., 2021b;Ji et al., 2018;Mooney et al., 2019;Qiao et al., 2021). ...
... Specifically, at metro stations in urban cores where shared bikes are oversupplied and highly accessible, regulating parking is more important than providing bikes. Suggested procedures include estimating real cycling demand and circulating redundant bikes to underserved areas, assigning geographically differentiated bike rack quotas to DBS operators, charging users for illegal parking, and giving credit points to users for returning bikes to designated parking locations (Mooney et al., 2019;Tu et al., 2019). At metro stations in middledensity areas, such as suburban areas with high population density, where BnR demand is unmet and negative externalities resulting from the oversupply of dockless bikes are mitigated, cultivating BnR habit via adequate supply of shared bikes is a win-win strategy to all participators. ...
Article
Dockless bikesharing (DBS) has been considered as a solution to the first and last mile problem of metro connectivity. Leveraging data covering all DBS programs in Shanghai, China, this study evaluated bike-and-ride (BnR) activities in DBS-metro systems via four metrics: BnR trip count, BnR rate, shared-bike utilization rate, and catchment size (85th percentile transfer distance). A set of generalized additive models considering marginal nonlinear interactions was fitted to examine associations between the four metrics and external environment, including land use, socio-demographics, roadway designs, transportation facilities, metro station features, and DBS operator features. Different buffer sizes measured by network distance were tested to check model robustness and find optimal buffers. Results showed that: 1) metro stations near the city center exhibited greater BnR trip count, higher BnR rate, lower shared-bike utilization rate, and smaller catchment size; 2) proportion of public and residential land suggested positive relationships with BnR trip count but lose their significances after offsetting metro ridership; 3) numbers of colleges, shopping malls, and carsharing stations presented positive relationships with both BnR trip count and BnR rate; 4) land use mix was significantly positively associated with BnR trip count only when buffer size was larger than 1.5 km; 5) regions with higher population density went from less BnR activities in the city center to more BnR activities in the suburbs; 6) Large DBS operators outperformed small ones in BnR trip count but not in bike utilization rate. Taken together, this study uncovers a spatially disproportionate and supply-demand unbalanced distribution of DBS resources, which could attenuate the efficiency and attractiveness of using DBS to BnR. DBS operators and local governments should evaluate DBS systems from multiple perspectives to avoid an oversupplied and over-competing market.
... The authors observed lower accessibility in Black and middle-income neighborhoods. Similarly, one study that focused on the City of Seattle showed greater bike availability in socioeconomically advantaged neighborhoods with higher median incomes and more college graduates (Mooney et al., 2019). ...
... These values are two or three times larger than those for low-income block groups. This finding is consistent with several previous studies of dockless micromobility systems which show that higher-income neighborhoods have greater micromobility availability (Mooney et al., 2019;Meng and Brown, 2021). ...
... In general, these results are consistent with the results discussed above regarding the availability indicators. These results further confirm the results of some earlier studies that show a lower level of accessibility to micromobility systems in disadvantaged block groups such as those with an EEA status, a low median household income, and a Black-majority population Mooney et al., 2019) ...
Preprint
Full-text available
Many cities around the world have introduced dockless micromobility services in recent years and witnessed their rapid growth. Shared dockless e-scooters have the potential to benefit neighborhoods that lack access to station-based bikeshare services, but they may also exacerbate the existing spatial disparities. While some studies have examined the equity of station-based bikeshare systems, limited knowledge is available regarding dockless e-scooter services. This study uses Washington DC as a case study, a city with both dockless e-scooter and station-based bikeshare systems, to conduct equity analysis of the two types of micromobility options. We develop an analytical framework to examine how dockless e-scooter and station-based bikeshare differ on a set of equity-related outcomes (i.e., availability, accessibility, usage, and idle time) across neighborhoods of different socioeconomic categories. Results reveal that dockless e-scooter services increase accessibility to shared micromobility options for disadvantaged neighborhoods but also widen the access gap across neighborhoods. Compared to bikeshare, shared e-scooters have a higher level of spatial accessibility overall due to greater supply; however, the greater supply largely leads to longer average idle time of shared e-scooters rather than a greater number of trips. Finally, it appears that the bikeshare system's equity program effectively promotes low-income use but e-scooters' equity programs do not. Our findings suggest that increasing vehicle supply alone would probably not lead to higher micromobility use in disadvantaged neighborhoods. Instead, policymakers should combine a variety of strategies such as promoting the enrollment of equity programs and reducing access barriers (e.g., smartphone and banking requirements) to micromobility services.
... Recent research suggests dockless service geographies are more equitable than docked. Mooney et al. (2019) examine the distribution of dockless shared bikes in Seattle, WA and find no distinction in neighborhoods by race/ethnicity, though higher-income and high-destination neighborhoods have more bikes. Another study conducted in Austin, TX shows that e-scooter use is not associated with neighborhood income level (Caspi et al., 2020). ...
... Thus, we cannot analyze the actual service geography of dockless systems in relatively low-density cities. Second, service geographies show the spatial coverage of micromobility services, but do not reveal the quantity or type of micromobility use in those areas, such as the exact vehicle supply or use frequency; omitting vehicle-level data may obfuscate uneven vehicle distribution as identified in other research (Mooney et al. (2019). Third, the data offer no insight into who uses micromobility vehicles. ...
Article
Docked bike-share programs have proliferated worldwide, but studies find that the distribution of docked stations is geographically unequal. New dockless systems offer more flexibility compared to docked systems, but it remains unclear if dockless systems can address existing geographic inequities. This study examines all 32 US cities with both docked and dockless micromobility (bikeshare and e-scooter) programs and develops three service geography indicators to compare the geographic equity of docked versus dockless systems. We first use Lorenz curves and Gini indices to examine the overall spatial distribution of micromobility; we then use logistic and Tobit regressions to investigate how service geography corresponds to neighborhood characteristics. Results show that the distribution of docked systems is extremely unequal, and that dockless systems greatly reduce geographical inequalities relative to docked. Low-density areas and neighborhoods with low median household incomes, smaller shares of young people, and fewer zero-car households have limited micromobility service. Docked services are less prevalent in communities of color, and the implementation of dockless systems yields mixed outcomes for racial equity. Importantly, designated service areas do not always translate into available micromobility vehicles. Policymakers should use program design and performance metrics to address the mismatch between designated and actual service geographies and to ensure that micromobility services benefit marginalized communities.
... For example, research on the BIXI bike share program in Montreal, Canada showed that living within 250 meters of a bike share station significantly increased the likelihood of using bike share [25]. Two recent studies have examined correlates of dockless bike share use [20] and access [26]. An investigation of dockless bike share at a Texas university found that living off campus, lower class rank, current biking behavior, and confidence in biking were all positively correlated with bike share use [20]. ...
... An investigation of dockless bike share at a Texas university found that living off campus, lower class rank, current biking behavior, and confidence in biking were all positively correlated with bike share use [20]. Mooney and colleagues assessed spatial access to dockless bike share bikes during the first six months of a pilot program in Seattle and found that neighborhoods with above the median bike availability had higher median incomes, more college-educated residents, and more access to opportunity on average [26]. Despite the rapid growth in dockless bike share and scooter systems in the U.S. since 2017, station-based bike share still comprised 29% of all trips in 2019 [17]. ...
Article
Full-text available
Background Research on the influences on bike share use and potential favorable relationships between use and obesity is limited, particularly in the U.S. context. Therefore, the aims of this exploratory study were to examine correlates of awareness and use of Boston’s Bluebikes bike share system and assess the association between use and weight status. Methods Students, faculty, and staff (n = 256) at a public urban university completed an online survey that assessed sociodemographic, behavioral, and physical activity characteristics, Bluebikes awareness, and use of Bluebikes and personal bikes. Multivariable logistic regression models were estimated to examine associations between sociodemographic and behavioral factors and bike share awareness and use; and between use and overweight/obesity status. Results Respondents were mostly students (72.2%), female (69.1%), White (62.1%), and the mean age was 32.4±13.8 years. The percentage of respondents classified as aware of Bluebikes was 33.6% with only 12.9% reporting any use of the system. Living in a community where bike share stations were located (odds ratio (OR) = 2.01, 95% confidence interval (CI): 1.10, 3.67), personal bike ownership (OR = 2.27, 95% CI:1.27, 4.45), and not exclusively commuting to campus via car (OR = 3.19, 95% CI:1.63, 6.22) had significant positive associations with awareness. Living in a bike share community (OR = 2.34; 95% CI:1.04, 5.27) and personal bike ownership (OR = 3.09; 95% CI:1.27, 7.52) were positively associated with bike share use. Any reported use of Bluebikes was associated with 60% lower odds of being overweight/obese (OR = 0.40; 95% CI:0.17, 0.93). Conclusions Several environmental and behavioral variables, including access to stations and personal bicycle ownership, were significantly associated with Bluebikes awareness and use. Findings also suggest a potential benefit to bike share users in terms of maintaining a healthy weight, though further longitudinal studies are needed to rule out the possibility that more active and leaner individuals tend to use bike share more frequently.
... Various aspects of dockless bike-sharing systems have recently been studied, such as system usage (Lin et al., 2019;Shen et al., 2018), user profiles (Du & Cheng, 2018), accessibility and distribution of bicycles Mooney et al., 2019) and the implications of such systems for urban mobility (Li et al., 2019). Still, there is uncertainty about how dockless bike-sharing contributes to (possible) mode substitution. ...
... As the connection of traditional docked systems with public transit relies largely on the number of docks available, the pressure of drop-off restriction and space limitation around public transit stations is lower in a dockless system. In addition, dockless bike-sharing systems are often operated with a greater number of shared bikes than docked bike-sharing due to a lower requirement of economic and human resource input for docking stations (Mooney et al., 2019), which enables a larger availability of shared bicycles surrounding public transit stations (Mobike Global, Beijing Tsinghua Tongheng Planning and Design Institute, & China New Urbanization Research Institute, 2017). The improved experience at the end of rides and the higher availability of dockless shared bicycles can contribute to tighter integration with public transit, offering dockless bike-sharing as a "first-/ last-mile" trip option and meanwhile complementing the walking transfers in-between public transits . ...
Article
As a newly emerged bike-sharing system, dockless bike-sharing has the potential to positively influence urban mobility by encouraging active cycling and drawing users from car, public transit and walking. However, scant empirical research explores the extent to which dockless bike-sharing replaces other travel modes for different travel purposes. There is a lack of knowledge about how dockless bike-sharing users’ personal characteristics and neighborhood environment features influence their mode substitution behaviors. Using survey data collected from residents in Beijing and geodata of land use and public transit, we conduct four multinomial logistic models to explore potential mode-substitution behaviors influenced by dockless bike-sharing for four travel purposes: work or education commuting, sports and leisure, grocery shopping, and recreational activities such as shopping, eating and drinking. The results indicate that, for the majority of respondents, dockless bike-sharing systems potentially substitute for walking or public transit. In addition, our analysis of travel attitudes points out that dockless bike-sharing not only attracts bicycle lovers but also users with a preference or positive attitude toward other travel modes. The positive association between the length of bicycle paths and the likelihood of potentially replacing public transit or motorized vehicles by dockless bike-sharing also reveals that the cycling infrastructure of residential neighborhood could be an important facilitator for users of public transit and motorized vehicles to switch to dockless bike-sharing systems.
... In recent years, the possibility of geo-referenced data collection has opened doors for understanding human behaviour in urban contexts, such as pedestrian mobility [1], taxi services [2] and bike and scooter-sharing mobility [3]. In particular, bike-sharing services offer new opportunities for researchers to study human mobility by analyzing spatial patterns [4] and temporal patterns [5] of bike usage or by studying the effects of weather on bike-sharing services [6]. ...
... Recently, a number of studies have also investigated dockless bike-sharing systems [25], [26], [27]. The main emphasis is on analysing spatial patterns of such systems, as without stations, bicycles can be left anywhere in the city, which also raises the question of redistribution of bikes in particular during the weekdays [4], [28], [29]. These papers have focused mainly on the problem of redistribution of the bikes in different locations. ...
Preprint
Understanding human mobility in urban environments is of the utmost importance to manage traffic and for deploying new resources and services. In recent years, the problem is exacerbated due to rapid urbanization and climate changes. In an urban context, human mobility has many facets, and cycling represents one of the most eco-friendly and efficient/effective ways to move in touristic and historical cities. The main objective of this work is to study the cycling mobility within the city of Bologna, Italy. We used six months dataset that consists of 320,118 self-reported bike trips. In particular, we performed several descriptive analysis to understand spatial and temporal patterns of bike users for understanding popular roads, and most favorite points within the city. This analysis involved several other public datasets in order to explore variables that can possibly affect the cycling activity, such as weather, pollution, and events. The main results of this study indicate that bike usage is more correlated to temperature, and precipitation and has no correlation to wind speed and pollution. In addition, we also exploited various machine learning and deep learning approaches for predicting short-term trips in the near future (that is for the following 30, and 60 minutes), that could help local governmental agencies for urban planning. Our best model achieved an R square of 0.91, a Mean Absolute Error of 5.38 and a Root Mean Squared Error of 8.12 for the 30-minutes time interval.
... In every application of urban machine learning, prediction and modeling carries enormous risk of exacerbating inequity and opacity [21,42,43,49]. Building on recent advances in fair and explainable AI, we consider the interactions between accuracy, fairness, and explainability in urban applications. ...
... The raw data are collected tabular format, where each record/row contains the information of each taxi trip, including the longitude and latitude of the starting location. We considered the demand prediction problem, interpreting each record as an indicator of demand following Mooney et al. [43]. We processed the tabular data into raster format given the following steps: ...
Article
We consider the use of AI techniques to expand the coverage, access, and equity of urban data. We aim to enable holistic research on city dynamics, steering AI research attention away from profit-oriented, societally harmful applications (e.g., facial recognition) and toward foundational questions in mobility, participatory governance, and justice. By making available high-quality, multi-variate, cross-scale data for research, we aim to link the macrostudy of cities as complex systems with the reductionist view of cities as an assembly of independent prediction tasks. We identify four research areas in AI for cities as key enablers: interpolation and extrapolation of spatiotemporal data, using NLP techniques to model speech- and text-intensive governance activities, exploiting ontology modeling in learning tasks, and understanding the interaction of fairness and interpretability in sensitive contexts.
... In another study, Forest found that dockless E-scooter and bike-share riders in San Francisco were highly skewed to white, male, and high-income population and that private vendors did not deliver social equity by serving "communities of concern" adequately (Forest 2019). However, Mooney et al. (2019) conducted a case study on spatial access to the DBS program in Seattle and reached an opposite conclusion that the access was moderately equitable. They mapped out the equity scores in the region and found that although the standard demographic features of DBS-friendly neighborhoods were unsurprisingly well educated and wealthier, no communities were entirely excluded from the service and racial disparities were insignificant. ...
Article
This study revealed the inequitable societal impacts of E-scooters on disadvantaged populations. The study conducted a population distribution analysis to compare the use opportunities and space intrusion burdens of E-scooter sharing on four vulnerable population groups in Austin, Texas. Nearly all minority population experienced fewer E-scooter use opportunities. Ten percent of the minority population waited for a disproportionately longer time before a disturbance could be resolved. Ten percent of the low-income population were in a disadvantaged position in high opportunities and moderate burdens. Twenty percent of the physically disabled population faced more moderate-level burdens. The result did not show significant inequitable outcomes for the elderly population.
... A simulation study by [27] predicted that escooters would be a particularly strong alternative to private automobiles for trips between 0.5 and 2 miles. At the same time, studies show that (1) e-scooter trips replace mainly trips that could have been undertaken by walking or cycling [28]; (2) dockless micro-mobility solutions can cause (safety) conflicts with pedestrians and people with disabilities [6]; and (3) the spatial availability of the new offers could be determined merely by demand and therefore not be evenly distributed across the city but could be concentrated where the early adopters are living and traveling [29,30]. However, there are assumptions that micro-mobility modes, such as e-scooters, might have positive impacts on public transport use [31] and will not result in significant diversion from public transit on long-distance trips due to their higher relative cost on trips [27]. ...
Article
Full-text available
Electric scooter sharing (e-scooter sharing) is a new urban micro-mobility service that is expected to shape individual urban mobility. The introduction of e-scooter sharing systems poses challenging questions for cities and transportation planners regarding their effects on their transportation system. This study addresses the question concerning the strategies which are applied for the introduction of e-scooter sharing systems in different operation areas in Germany. An interview study with 21 stakeholders with different backgrounds (local transport authorities, public transport providers, e-scooter sharing operators, municipalities, associations, planning offices and consulting companies, and other mobility providers) was conducted to reflect upon the introduction of e-scooter sharing systems in Germany and stakeholders’ involvement in planning. The qualitative content analysis provides insights into the stakeholders’ assessment of the introduction process and thus contributes to a multi-perspective understanding on the topic. Derived hypotheses and recommendations further contribute to knowledge sharing and learning from experience. The paper concludes with a description of three introduction styles: protective, pro-active, and laissez-faire.
... A study [7] has indeed shown that every additional meter of walking to a shared bike decreases a user's likelihood of using a bike by 0.194% for short distances (≤ 300m) and 1.307% for long distances (> 300m), implying that a user walking a distance > 500m for reaching the closest bike is highly unlikely to use the system. Moreover, if bikes are well distributed all over the service area, the spatial equity improves since the benefits of the service are not a prerogative of just some zones (e.g., city center) [14]. Assume the service area to be split into zones (e.g., quadrants) where the diameter of each zone is considered a reasonable walking distance (e.g., ≤ 500m): then, the desired goal is that each zone has a sufficient number of bikes. ...
Preprint
Full-text available
A free-floating bike-sharing system (FFBSS) is a dockless rental system where an individual can borrow a bike and returns it everywhere, within the service area. To improve the rental service, available bikes should be distributed over the entire service area: a customer leaving from any position is then more likely to find a near bike and then to use the service. Moreover, spreading bikes among the entire service area increases urban spatial equity since the benefits of FFBSS are not a prerogative of just a few zones. For guaranteeing such distribution, the FFBSS operator can use vans to manually relocate bikes, but it incurs high economic and environmental costs. We propose a novel approach that exploits the existing bike flows generated by customers to distribute bikes. More specifically, by envisioning the problem as an Influence Maximization problem, we show that it is possible to position batches of bikes on a small number of zones, and then the daily use of FFBSS will efficiently spread these bikes on a large area. We show that detecting these areas is NP-complete, but there exists a simple and efficient $1-1/e$ approximation algorithm; our approach is then evaluated on a dataset of rides from the free-floating bike-sharing system of the city of Padova.
... Carleton and Porter (2018) conducted a needs gap analysis while Sharma et al. (2020) compared group means. Both studies divided the area into subregions corresponding to traffic analysis zones (the geographic unit of analysis). For shared mobility systems, the availability or density of vehicles in an area is often used as a service quality metric.Mooney et al. (2019) used the number of bikes available ...
Preprint
Full-text available
Big data can help government agencies better make equity-related decisions in transportation systems. However, the lack of disaggregated big data is an obstacle to inform policy actions. In this paper, we review data sources that can be used to investigate transportation equity. Following the general three-step framework for transportation equity outcomes analysis, we categorized the identified data sources into a taxonomy with four broad data categories: population data, transportation infrastructure data, mobility data, and other data (facility data, traffic accident data, traffic-related air pollution data). Sources to collect these four types of data for the United States were identified. Representative studies from the literature were reviewed to reveal how data collected from the identified sources have been or could be used to characterize transportation outcomes equity. Here we call for efforts to construct a transportation equity big data library, specifying the associated technological, epistemological, methodological, and political challenges. This paper will offer an important reference where government agencies and transportation researchers can seek data to improve transportation equity.
... In assessing the environmental determinants of dockless bike trip generation over four months in Singapore, Xu et al. (2019) echoed the prior findings, noting that grid cells with higher residential and employment densities, greater land use mix, more robust road and bike network infrastructure, and better access to public transit stations generated more demand; with transit station proximity appearing to be a first-mile facilitator rather than a last-mile solution. Finally, Mooney et al. (2019) investigated the spatial equity of dockless bike access during a six-month pilot program-with Lime as one of three operators-in Seattle, Washington. Their study findings did not detect significant racial or ethnic disparities regarding dockless bike access but noted that neighborhoods with greater bike availability and shorter idle times between bike rentals tended to have households with higher median incomes and more college-educated residents. ...
Article
Full-text available
The introduction and proliferation of privately-operated dockless bikeshare systems across North America has caught many public planning agencies, who seek evidence to recognize the extent of dockless bikeshare adoption in their communities and its impact on existing transportation systems, by surprise. In this study, we investigate systemwide travel patterns during the first 18 months of a dockless bikeshare program in the Greater Boston region. Specifically, by identifying neighborhood-level predictors of dockless bike access and usage, this study offers insights into the spatial equity-related impacts of this promising active mobility option in Boston’s suburbs, which have limited access to the region’s decade-old public dock-based system. Utilizing spatiotemporal route-level data provided by the sole dockless system operator to model bikeshare trip generation and duration, this study finds that neighborhoods with a higher share of renter-occupied housing and historically disadvantaged populations had less access to dockless bikes while also exhibiting higher rates of bike usage. We conclude that this undesirable finding may be addressed by implementing safeguard policies such as an equitable dockless bikeshare rebalancing scheme.
... This kind of spatial disparity was also found in dockless bike-share systems in other cities. For example, Mooney et al. (2019) investigated the spatial equity of access to dockless share bikes and found that higher-income neighborhoods tended to have higher availability of dockless bikes in Seattle, US. Another possible reason could be the presence of a higher percentage of unbanked households in Chicago compared to Austin (7.4 % vs 4.5 %). ...
Article
The rapid popularity growth of shared e-scooters creates the necessity of understanding the determinants of shared e-scooter usage. This paper estimates the impacts of temporal variables (weather data, weekday/weekend, and gasoline prices) and time-invariant variables (socio-demographic, built environment, and neighborhood characteristics) on the shared e-scooter demand by using four months (June 2019- October 2019) period of data from the shared e-scooter pilot program in Chicago. The study employs a random-effects negative binomial (RENB) model that effectively models shared e-scooter trip origin and destination count data with over-dispersion while capturing serial autocorrelation in the data. Results of temporal variables indicate that shared e-scooter demand is higher on days when the average temperature is higher, wind speed is lower, there is less precipitation (rain), weekly gasoline prices are higher, and during the weekend. Results related to time-invariant variables indicate that densely populated areas with higher median income, mixed land use, more parks and open spaces, public bike-sharing stations, higher parking rates, and fewer crime rates generate a higher number of e-scooter trips. Moreover, census tracts with a higher number of zero-car households and workers commuting by public transit generate more shared e-scooter trips. On the other hand, results reveal mixed relationships between shared e-scooter demand and public transportation supply variables. This study's findings will help planners and policymakers make decisions and policies related to shared e-scooter services.
... Other studies have investigated the determining factors of bikeshare usage using historical trip data (Noland et al., 2016;An et al., 2019), showing the significant effects of weather factors (El-Assi et al., 2015;Younes et al., 2020). Mooney et al. (2019) explored equity of spatial access to DBS, while Shen et al. (2018) investigated the impact of fleet size on the usage of dockless bikes in Singapore, finding that precipitations, statistically, appear to have a significant negative impact on the number of rides while extreme temperatures (>87.8°F) were not significant. Hosseinzadeh et al. (2021) analyzed more than 400,000 e-scooter trips in Louisville, KY exploring how factors relating to demographics, density, diversity, design, urbanism scores, distance to transit and other transportation-related variables influence escooter usage. ...
Article
Electric micromobility systems such as e-bikes and e-scooters represent sustainable mobility options especially for specific classes of travelled distances. Moreover, the coverage and accessibility of transit services can be expanded through the implementation and promotion of these systems. Therefore, transport engineering is dealing with the development of new tools to support the forecast of the potential demand both for door-to-door trips and its integration with transit. With respect to these incoming research challenges, the paper proposes a methodology to investigate private mobility through floating car data (FCD) to identify the potential demand that can be shifted from cars to electric micromobility (e-micromobility) systems while also exploring the opportunity to increase transit usage. The benefits of such methodology have been evaluated on a real large test case, i.e. Rome (Italy), through an FCD dataset of about 240,000 monitored vehicles. The developed methodology is parametric and, thus, it can be easily transferred to other city contexts taking into consideration the compatibility of the local network infrastructures and the micromobility solutions. In Rome, it was estimated that the potential demand for e-micromobility can reach a maximum value of about 20% of weekday-trips, while about 10% of the morning peak trips could potentially be interested in a multimodal trip (i.e. mass transit services and e-micromobility for the access/egress). Results can be adopted by local authorities, transport companies and electric mobility providers to optimize infrastructural measures or the location of shared e-scooters and e-bikes to increase potential e-micromobility demand, as well as to increase the number of multimodal mobility options. Keywords: Micromobility; Sustainable travel modes; E-scooters; E-bikes; Floating car data; Modal shift; Transit network coverage https://www.sciencedirect.com/science/article/pii/S0965856422000088
... In cycling equity analysis specifically, studies have been carried out on the interaction between the provision of bicycle infrastructure, the place of residence and employment, and the income levels of both advantaged and disadvantaged population groups (6)(7)(8)(9)(10)(11). The majority of such studies have focused on access to bicycle infrastructure or cycling facilities, including bicycle sharing systems (BSS) and dock-less bicycle sharing systems (DBSS), or access to destinations by bicycle (12)(13)(14)(15). ...
Article
Full-text available
Ensuring equity is considered in all types of decision making, including with respect to cycling provision, is important. Studies have investigated equity in relation to provision of cycling infrastructure and facilities. However, identifying other factors that need consideration in cycling equity is important. This study explored the impact of cycling infrastructure provision on individual perceptions of cycling infrastructure in relation to sociodemographic characteristics in Auckland, New Zealand. The results indicated that bicycle lane availability did not significantly influence perceptions of cycling infrastructure; however, ethnicity and whether a person was a regular cyclist did. Among noncyclists and potential cyclists, ethnicity was the only factor found to significantly influence perceptions of cycling infrastructure. Māori, the indigenous people of New Zealand, and Pacific Islanders rated the provision of cycling infrastructure higher than others for the same level of bicycle infrastructure in their community. Whereas Māori had the highest percentage of potential cyclists among all ethnicities, Pacific Islanders had the highest percentage of noncyclists (64.9%), the lowest percentage of potential cyclists, and one of the lowest percentages of regular cyclists. The study showed that cycling provision perceptions were more affected by factors like ethnicity, education, and bicycle user type than objective measures of bicycle infrastructure. Following the capabilities approach of justice, this study suggests that equitable provision of cycling infrastructure may not lead to an equitable cycling environment. To achieve this, interpersonal and intrapersonal indicators such as ethnicity and community-related factors must also be considered to encourage and empower all population groups to cycle.
... These works have used the GPS records generated by the systems themselves, which store the history of the origins and destinations of the trips made by users. The data collected from the GPS systems installed in the shared mobility vehicles have been used to analyze the accessibility offered by these new systems [16], spatiotemporal patterns of use [17][18][19], and models for predicating demand and customer segmentation [20]. ...
Article
Full-text available
Moped-style scooters are one of the most popular systems of micro-mobility. They are undoubtedly good for the city, as they promote forms of environmentally-friendly mobility, in which flexibility helps prevent traffic build-up in the urban centers where they operate. However, their increasing numbers are also generating conflicts as a result of the bad behavior of users, their unwarranted use in public spaces, and above all their parking. This paper proposes a methodology for finding parking spaces for shared motorcycle services using Geographic information system (GIS) location-allocation models and Global Positioning System (GPS) data. We used the center of Madrid and data from the company Muving (one of the city’s main operators) for our case study. As well as finding the location of parking spaces for motorbikes, our analysis examines how the varying distribution of demand over the course of the day affects the demand allocated to parking spaces. The results demonstrate how reserving a relatively small number of parking spaces for scooters makes it possible to capture over 70% of journeys in the catchment area. The daily variations in the distribution of demand slightly reduce the efficiency of the network of parking spaces in the morning and increase it at night, when demand is strongly focused on the most central areas.
... According to Gu et al. (2019), in the context of China, DBS users tend to be young and college-educated, and the gender gap is nearly nonexistent. In Seattle's DBS program, no neighborhood was consistently excluded from access to the system, although the spatial equity analysis of Mooney et al. (2019) revealed that neighborhoods with higher proportion of college-educated, highincome residents, and more community resources had more bikes. The researchers measured bike idle times and quantified neighborhood access to the DBS by computing the average number of bikes available per resident per day. ...
Article
A case study is presented of a dockless e-scooter rental service (MDES) in Mayagüez, Puerto Rico, a city within the understudied Latin American region. MDES trip data were used to examine the spatiotemporal patterns of e-scooter trips in the city, while survey data was collected to explore the characteristics of MDES users and nonusers, as well as the factors that influenced their demand for MDES trips. In addition, this study proposes a network-based approach to evaluate the level of spatial access and equity of dockless micromobility vehicles. Three measures are proposed to quantify spatial access at the level of locations (i.e., network nodes) as a function of the distance of each location to each e-scooter. As illustrated in the MDES case, the measures can be used to examine spatial access at the service area-, zonal-, building-, and point-levels, and to compute spatial access inequality indexes. The survey analysis indicated that female respondents were 1.7 times less likely to use MDES than males and that young populations groups more than two times more likely to be MDES users than the reference population group. The survey analysis also revealed that cost, safety, and built environment concerns were the main barriers to the use of MDES, and that the primary reasons for using the service were parking problems and traffic congestion. Among other things, the spatiotemporal analysis of the MDES trips data shows that 78% of trips started and ended at the city’s main university, that a significant proportion of trips were linked to neighborhoods with a high concentration of university students, and that demand for e-scooter trips dropped drastically when the university was not in session. The analysis of the MDES data revealed marked differences in spatial access within and between zones in the study region. On average, daily Atkinson inequality index values, which were computed using the proposed spatial access indicators, ranged from 0.45 to 0.80, which points to an unequal spatial access to MDES. The paper closes by discussing applications of the proposed methodology for the design of policies aimed at minimizing inequality in spatial access to dockless micromobility services.
... They found that more bikes were available in neighborhoods with higher incomes, higher educational attainment, and local community resources. Similarly, to previous docked bike-sharing system studies, they noted modest access inequality across sociodemographic lines [52]. Despite numerous studies on bike-sharing systems, there has been limited analysis of shared e-scooter systems and equity. ...
Article
Full-text available
In recent years, cities around the world have launched various micromobility programs to offer more convenient and efficient mobility options that make transit networks more accessible. However, the question of whether micromobility services are accessible to and equitably distributed amongst all populations still remains unanswered. In this study, we investigate the spatial accessibility of disadvantaged communities, such as racial and ethnic minorities, low-income populations, and transit-dependent populations, to scooter and bike services. The ultimate goal of this study is to examine associations between the level of access to bikes and scooters and the racial and social characteristics of communities throughout the City of Austin, Texas. To achieve this goal, first, equity analysis with a Lorenz curve was performed to understand how bike and scooter accessibility is distributed among the population. Then, both Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models were generated to explore factors associated with bike and scooter accessibility. The analysis of the residuals showed more consistent results in the GWR models than in the OLS models. The equity analysis with the Lorenz curve conducted herein reveals extreme inequity in access to micromobility services. Almost 80 percent of residents have no access to bikes and scooters. Access is even worse for transit-dependent people when compared to the general population. The regression models further revealed that areas with a higher proportion of Black residents were less likely to have access to both bikes and scooters, yet positive associations were found for both bike and scooter accessibility and low-income populations. Increased understanding of spatial access to bikes and scooters can support ongoing efforts to deliver equitable transportation systems, improve transportation alternatives for disadvantaged populations, and support future policy actions related to bike and scooter services.
... Dockless shared bicycles provide residents with more convenient services due to their stop-on-ride, flexibility, ease of use and low price. However, there are also many factors that are not conducive to the development of urban transportation, such as disorderly parking and the imbalance between supply and demand (16)(17)(18). These problems might decrease the opportunity and willingness of the public to use shared bicycles, but they have occurred in almost every city where shared bicycles are deployed in Asia, Europe and the Americas, including Beijing, Shanghai and Nanjing in China (17,19,20). ...
Article
Full-text available
Shared bicycles are currently widely welcomed by the public due to their flexibility and convenience; they also help reduce chemical emissions and improve public health by encouraging people to engage in physical activities. However, during their development process, the imbalance between the supply and demand of shared bicycles has restricted the public's willingness to use them. Thus, it is necessary to forecast the demand for shared bicycles in different urban regions. This article presents a prediction model called QPSO-LSTM for the origin and destination (OD) distribution of shared bicycles by combining long short-term memory (LSTM) and quantum particle swarm optimization (QPSO). LSTM is a special type of recurrent neural network (RNN) that solves the long-term dependence problem existing in the general RNN, and is suitable for processing and predicting important events with very long intervals and delays in time series. QPSO is an important swarm intelligence algorithm that solves the optimization problem by simulating the process of birds searching for food. In the QPSO-LSTM model, LSTM is applied to predict the OD numbers. QPSO is used to optimize the LSTM for a problem involving a large number of hyperparameters, and the optimal combination of hyperparameters is quickly determined. Taking Nanjing as an example, the prediction model is applied to two typical areas, and the number of bicycles needed per hour in a future day is predicted. QPSO-LSTM can effectively learn the cycle regularity of the change in bicycle OD quantity. Finally, the QPSO-LSTM model is compared with the autoregressive integrated moving average model (ARIMA), back propagation (BP), and recurrent neural networks (RNNs). This shows that the QPSO-LSTM prediction result is more accurate.
... However, a dockless bike-sharing system has greater accessibility parameters for users. In combination with the application, it is easy to find the free bike close by [12]. On the other hand, in such a system it is harder to maintenance bikes, because an operator needs to reach all of them in different locations. ...
Chapter
Bike-sharing systems are a popular and widespread mobility tool all over the world. The introduction of such system could bring a large amount of benefits for city or region: starting from the promotion of cycling as a mode of transport and finishing with the improvement of image of this city or region. Though there is a lot of advices as well as guidelines concerning the system introduction, unfortunately, there are less research works with the practical application concerning problems of their operations. In this chapter the performance of station-based bike-sharing systems and its evaluation are discussed by using quite basic parameters. Application of the proposed approach was demonstrated on the example of the system in Krakow, Poland.
... Dockless programs are more accessible to lower-income communities. The dockless programs focus less on higher educated and higher income neighborhoods [19]. Likely, this is because it costs to buy and maintain the program. ...
... Availability of shared mobility facilities: The realtime information about nearby shared mobility services of each user is important for evaluating the availability of free-float bike-sharing or ridesourcing service for the user. Specifically, availiability of shared mobility facilities as an indicator of the supply can be calculated in different ways, such as the inverse of the idle time (number of vehicles per day in an area) and the time rate in which there is at least one vehicle available in a buffer (61,62). In addition, the ''ratio of the number of bicycles available to the station capacity'' or the ''ratio of the number bicycles available to the distance to the bike rack'' are used as a proxy for station-based bike-sharing service (34,54). ...
Article
Full-text available
Although metro systems are established in many Asian cities including Chengdu, they have yet to cover every corner of a city. Understanding the transfer behavior of passengers can provide insight into achieving efficient and sustainable urban transport systems. Combining shared mobility programs with metro to improve the weaknesses of traditional feeder modes is viewed as the most promising line of business in sustainable transportation for the near future. Therefore, this study aims to compre- hend the factors affecting the usage regularity of shared mobility by deepening the knowledge on endogenous and exogenous effects, and integrating two modes, namely bike-sharing and ridesourcing. Two systems are cross-compared, first in respect of their travel characteristics. Then, a binary logistic model is employed to capture the influences of trip characteristics and travel environment characteristics on their usage frequency. Researchers found that trip distance is significantly associated with users’ mode options, indicating that bike-sharing and ridesourcing mainly serve short-distance and long-distance transfer users, respectively, although some users may be confused which feeder mode to choose for the journeys of 2 km to 4 km. There were also meteorological and temporal influences, with the competition and complementation of multiple shared mobility feeder modes being likely to change under extreme weather conditions, during peak hours, or on weekends. Besides, metro-shared mobility users value the accessibility of two kinds of transport service, which is affected by the metro station and its surrounding built environment. This study and the proposed policy implications are helpful for embracing a sustainable mobility design from general optimum.
... Coined as "shared micromobility," shared fleets of small, usually station-free and electrified personal vehicles available for travels within a relatively small area are at the forefront of car-free transportation innovation (Shaheen and Cohen, 2019). By providing car-free travel options like scootershare, researchers argued that shared micromobility could improve accessibility to destinations for a broader range of transport participants, especially the carless population (Caspi et al., 2020;Jacques, 2019;Mooney et al., 2019;Smith and Schwieterman, 2018). ...
Article
Shared micromobility programs, including dockless electric scooter-share (E-scooter), are popular in many U.S. cities, and with their adoption brings the hope that they may uphold better car-free accessibility. However, few studies provide clear answers to what activities drive its travel demand or whether it could actually generate more visiting activities. To fill this gap, we conducted a spatiotemporal similarity analysis between E-scooter use and visit patterns to leisure facilities. We find that E-scooter use is significantly correlated with daily dining and drinking, shopping, and recreational activities, in that order. Moreover, we find higher scooter-visit correlation clusters in downtown and university campus areas. We then used the Difference-in-Differences approach to examine if E-scooter use can generate more visiting activities. Surprisingly, the results show that E-scooter use is insignificant to the overall visit increase.
... Zhou et al. (2018) found that dockless bikesharing services had caused a modal shift, decreasing metro ridership in Shanghai, China. Mooney et al. (2019) found that although the shared dockless bike program in Seattle had promising spatial equity characteristics in the region, neighborhoods with more educated residents had slightly more bikes. ...
Technical Report
Full-text available
Active transportation can play an important role in promoting more physically active and positive public health outcomes. While walking and biking provide significant physical health benefits, their modal share remains low. As a new form of micromobility service, shared e-scooters can enhance the suite of options available in cities to promote active transportation and fill in the gaps when walking or biking are not preferred. Although e-scooters show potential as a mode of transportation, it is unclear whether people will adopt the technology for everyday use. Furthermore, shared micromobility (e.g., electric scooters) is gaining attention as a complementary mode to public transit and is expected to offer a solution to access/egress for public transit. However, few studies have analyzed integrated usage of shared e-scooters and public transit systems while using panel data to measure spatial and temporal characteristics. This study aims to examine the adoption and frequency of shared e-scooter usage and provide policy implementation. To do so, the researchers launched a survey in the Chicago region in late 2020 and collected a rich data set that includes residents’ sociodemographic details and frequency of shared e-scooter use. To characterize the frequency, the researchers used an ordered probit structure. The findings show that respondents who are male, low income, Millennials and Generation Z, or do not have a vehicle are associated with a higher frequency of shared e-scooter use. Furthermore, this study utilizes shared e-scooter trips for a 35-day measurement period from 10 shared e-scooter operators in Chicago, where the researchers used a random-parameter negative binomial modeling approach to analyze panel effects. The findings highlight the critical role of spatial and temporal characteristics in the integration of shared e-scooters with transit.
... Beyond increasing the number of docking stations, they must be distributed equitably. Additionally, dockless bikes, or free-floating bikes, which do not require stations, have been proposed as an approach to addressing inequities in bikeshare access and are associated with greater bike use [22]. These bikes offer the advantage of being more easily redistributed to meet demand during public health crises and other times of social vulnerability. ...
Article
Black, Latinx, and Indigenous people have contracted the SARS-CoV-2 virus and died of COVID-19 at higher rates than White people. Individuals rated public transit, taxis, and ride-hailing as the modes of transportation putting them at greatest risk of COVID-19 infection. Cycling may thus be an attractive alternative for commuting. Amid the increase in bikeshare usage during the early months of the pandemic, bikeshare companies made changes to membership requirements to increase accessibility, targeting especially essential workers. Essential workers in the United States are disproportionately Black and Latinx, underpaid, and reliant on public transit to commute to work. We document changes made by bikeshare companies, including benefits to various groups of essential workers, and we discuss such changes in the context of longstanding racial disparities in bikeshare access. While well intended, the arbitrary delineation in eligibility for such benefits by class of essential workers unwittingly curtailed access for many who may have benefited most. Given that equity in bikeshare is an important tool to improve access to safe transportation, critical changes in the distribution, accessibility, and usability of bikeshare networks is essential. Bikeshare companies, city planners, and policy makers should collaborate with community-based bike advocates to implement changes, as vocalized by those most in need of alternative forms of transportation.
... The growth of MSS has been reflected in emerging literature over the past few years, focusing on different aspects of MSS including technical (e.g., Ji et al., 2014; and operational issues (e.g., Caggiani et al., 2019;Mooney et al., 2019), health benefits (e.g., Trivedi et al., 2019;Woodcock et al., 2014), safety concerns (e.g., Friedman et al., 2016;Zanotto and Winters, 2017), and impact on traffic (e.g., Jensen et al., 2010;Zacharias, 2002). Additionally, there is a considerable number of studies that aim to understand the MSS user behaviour and related attitudes and responses by exploring their influencing factors. ...
Article
In light of the Micromobility Sharing Systems (MSS) boom, specifically bike and scooter sharing, related academic studies have grown accordingly in the last few years. However, contributions are scattered, particularly regarding the knowledge about the user of these systems. This article provides a systematic review of the studied factors influencing MSS user behaviour and offers insights for future research. An inclusive search of the Web of Science and Scopus databases was performed to identify related literature. The final analysis included 203 articles that met the eligibility criteria. The findings were organised into three main groups that aggregate 25 factors influencing MSS user behavioural responses: (i) temporal, spatial and weather-related factors, (ii) system-related factors and (iii) user-related factors. The review uncovered several neglected factors, as well as theoretical and methodological gaps in the literature. Based on that, the study suggests directions for future studies including researching the emotional influences and outcomes of MSS use, considering environmental beliefs and behaviours in the MSS context, examining negative behaviours and negative assessments of MSS use, and consolidating the use of theoretical frameworks.
Article
Many cities around the world have adopted dockless bike-sharing programs with the hope that this new service could enhance last-mile public transit connections. However, our understanding of the travel patterns using dockless bike sharing is still limited. To advance the knowledge on the new service, this study investigates mobility patterns of dockless bike sharing in Singapore using a four-month dataset. An exploratory spatiotemporal analysis is conducted to show daily travel patterns, while community detection of networks is used to explore the spatial clusters emerged from cycling behaviors. A series of Poisson regression models are then estimated to characterize the generation, attraction and resistance factors of bike trips in different periods of a day. The proposed regression model, which considers built environment factors of origin and destination simultaneously, is proved to be effective in deciphering mobility. The empirical findings shed light on policy implications in sustainable transportation planning.
Article
Full-text available
Dockless bike sharing plays an important role in residents’ daily travel, traffic congestion, and air pollution. Recently, urban greenness has been proven to be associated with bike sharing usage around metro stations using a global model. However, their spatial associations and bike sharing usage on public holidays have seldom been explored in previous studies. In this study, urban greenness was obtained objectively using eye-level greenness with street-view images by deep learning segmentation and overhead view greenness from the normalized difference vegetation index (NDVI). Geographically weighted regression (GWR) was applied to fill the research gap by exploring the spatially varying association between dockless bike sharing usage on weekdays, weekends, and holidays, and urban greenness indicators as well as other built environment factors. The results showed that eye-level greenness was positively associated with bike sharing usage on weekdays, weekends, and holidays. Overhead-view greenness was found to be negatively related to bike usage on weekends and holidays, and insignificant on weekdays. Therefore, to promote bike sharing usage and build a cycling-friendly environment, the study suggests that the relevant urban planner should pay more attention to eye-level greenness exposure along secondary roads rather than the NDVI. Most importantly, planning implications varying across the study area during different days were proposed based on GWR results. For example, the improvement of eye-level greenness might effectively promote bike usage in northeastern and southern Futian districts and western Nanshan on weekdays. It also helps promote bike usage in Futian and Luohu districts on weekends, and in southern Futian and southeastern Nanshan districts on holidays.
Article
Full-text available
Most bike-sharing systems in cities aim to maximize demand, an approach that tends to inadvertently favor wealthier neighborhoods. Therefore, we developed a heuristic and data-mining-based method to weigh both Demand And/oR Equity (DARE) in the station distribution and allocation process of planning bike-sharing. Equity is measured using a deprivation index and the potential demand is estimated using structural equation models via the built and social environment. The DARE method was applied first to the BSS service area in Munich, Germany, and then, to the area surrounding Munich, demonstrating the method’s transferability. Incorporating equity resulted in disadvantaged areas being better served by bike-sharing stations while favoring ridership (demand) tended to cluster stations in the wealthier city center. This method allows decision-makers to build scenarios for allocating infrastructure based on their desired fairness criterion, and can also be applied to other shared modes or public transport.
Article
Bicycle Sharing Schemes (BSS) are re-emerging as promising components of urban mobility solutions worldwide. However, the lack of consistent collaboration strategies between different actors and institutions, which have been tested in a wide range of cities and contexts regarding their design, tender, operation and expansion, raises significant social and governance implications. Urban transport features as a melting pot for diverse policy objectives, ranging from business model innovation, public tendering, and accessibility increase to the equity and social justice agenda. By employing a Multi-Level Perspective (MLP) framework and by introducing alluvial diagrams and circular dendrograms to BSS planning through a mixed-methods approach, this article illustrates an innovative tool in managing BSS in the context of the Global South. The strength of such diagrams has been underestimated to date since they can be particularly useful for public and private urban transport planners and policy-makers. Visualising user flows in such a manner, particularly in near-live time, may offer valuable insight on the operational challenges of BSS. Findings of the cross-sectional survey in Santiago de Chile confirm that maintenance is significant for user satisfaction levels. Furthermore, decisions regarding BSS expansion and modification could be based on such analysis and diagrams due to the precise identification of both the busiest and those under-represented BSS stations based on revealed preferences.
Article
Since the early modern age, the development of various means of transit has contributed to a dramatic improvement in quality of life. However, in past decades (particularly in urban environments), the simultaneous utilization of mobility options has resulted in poor air quality, traffic congestion, and a lack of parking. To solve these problems without imposing severe restrictions on personal mobility, alternatives to cars powered by internal combustion engines are necessary (see “Summary”).
Article
Shared dockless e-scooters are a popular micro-mobility solution in the US. However, e-scooters have raised equity concerns about lack of accessibility by low-income residents. Related work on the role of income on e-scooter use is limited, and mostly focused on non-causal approaches and surveys that can only point to non-causal relationships between e-scooter use and income. Causal analyses have been extensively used in other fields of research providing a framework to identify root causes that can point to actionable tasks. We propose a causal framework to carry out causality analyses of the effects of low income on shared dockless e-scooter use, and we discuss results and implications for four cities in the US. We propound that the proposed framework can be used to analyze the income-based imbalances shared dockless e-scooter companies incur in, and might serve as a tool to encourage changes that push for higher equity and inclusion.
Article
Full-text available
Bike-sharing is known as a sustainable form of transportation. This travel mode is able to tackle the “last mile” transit issue and deliver financial, well-being, and low-carbon lifestyle advantages to users. To date, many studies have analysed the influence of various factors, including built environments, on bike-sharing ridership. However, no study has exclusively synthesised these findings regarding the association between built-environment attributes and bike-sharing ridership. Thus, in this study, a systematic literature review was conducted on 39 eligible studies. These studies were assessed with respect to (1) bike-sharing usage, (2) studies’ geographical distribution, (3) data collection and analysis method, and (4) built environment factor type. Most studies were carried out in the US and Chinese cities. Variables associated with diversity, density, and distance to public transport stations and public transport infrastructure were frequently employed by the studies reviewed. It was found that BS stations with an average capacity of 24.63 docks and street network systems with an average length of 12.57 km of cycling lanes had a significant impact on the bike-sharing ridership. The findings of these studies were combined, and a series of recommendations were proposed based on them for bike-sharing service providers and researchers in academia. The findings of this evaluation can help practitioners and scholars understand the important built environment elements that influence bike-sharing ridership. Knowledge in this field will enable bike-sharing service providers to direct their resources sufficiently to enhance the more essential aspects of bike-sharing users’ satisfaction.
Article
This paper aims to identify the main sociopsychological factors that individuals perceive as affecting their intention to adopt electric (e−)micromobility. Drawing from modal choice theory, the factors are classified into functional (money, time, and other convenience values) and non-functional (emotional, social, and epistemic values). Following a PRISMA systematic literature review of 67 papers, we observed the reported influence of several functional and non-functional factors over the decision on whether to use an e-micromobility mode of transport. Results indicate that non-functional factors such as environmental concern, innovativeness, and belonging can be even more influential for individuals than traditional functional factors such as speed, cost, and time savings. Users seem to perceive these services as socially beneficial, contributing to improved livability, equity of access, and diversity of choice. The present review contributes to our understanding of the complexity of modal choice, and the importance of accounting for the sociopsychological factors influencing user decisions regarding micromobility. Our findings can help improve the strategies and policies supporting e-micromobility adoption.
Article
Full-text available
Today, the number of cities implementing bike-share programs is remarkably increasing. One of the critical elements of implementing a successful bike-share program is integrating it with other transportation modes such as bus and metro and extending its coverage in high-density residential and employment areas to encourage more demand. In this study, we utilize a GIS-based method to visualize the spatial distribution of bike-share stations using the location-allocation problem, using the Capital bike-share program in Washington D.C. metropolitan areas as a study area. We chose Washington D.C. as it was one of the first cities in the United States that launched a bike-share program and currently has one of the largest bike-share systems across the country. The location-allocation problem, including Target Market Share (TMS) and Maximize Coverage and Minimize Facility (MCMF), is considered to analyze the accessibility of promoting transit modes with bike-share systems across the District of Columbia. Location-allocation models are investigated to determine the potential bike station locations accessible to the maximum population and within a 300-meters buffer around public transit stations (e.g., bus, metro). The results show that the bike-share system in Washington D.C. is more accessible for transit users as an access/egress mode. At the same time, in areas farther away from downtown D.C., docking stations are more distanced apart and offer less coverage, especially in residential-only areas. Finally, our methodology can potentially be utilized for optimal station location allocation in any other city where maximum exposure is required.
Article
Shared micromobility services have undergone rapid growth in cities throughout the world, including expansions in bike sharing and e-scooter sharing services. Shared micromobility provides a potential complement to public transit by accommodating first and last-mile trips. I analyze detailed data on shared, dockless bikes and e-scooters from Seattle, Washington. I find micromobility vehicles cluster near Seattle's rail transit stations. During the study period, Seattle expanded its rail system into a new section of the city. I use the system expansion as a natural experiment to provide evidence of complementarity between shared micromobility and public transit. Using a differencein-difference strategy I find that, after a new light rail station opened, the flow of new micromobility vehicles increased significantly within a 5 min walking radius of the station. I provide causal evidence that local rail transit increases the use of dockless micromobility vehicles.
Article
Full-text available
Over the last two years, we have witnessed the ever-fast growth of micro-mobility services (e.g., e-bikes and e-scooters), which brings both challenges and innovations to the traditional urban transportation systems. For example, they provide an opportunity to better address the “last mile” problem due to their convenience, flexibility and zero emission. As such, it is essential to understand why and how urban dwellers use these micro-mobility services across space and time. In this paper, we aim to understand spatiotemporal trip purposes of urban micro-mobility through the lens of dockless e-scooter user behavior. We first develop a spatiotemporal topic modeling method to infer the underlying trip purpose of dockless e-scooter usage. Then, using Washington, D.C. as a case study, we apply the model to a dataset including 83,002 valid user trips together with 19,370 POI venues and land use land cover data to systematically explore the trip purposes of micro-mobility across space and time in the city. The results confirm a set of uncovered 100 Trips Topics as an informative and effective proxy of the spatiotemporal trip purposes of micro-mobility users. The findings in this paper provide important insights for city authorities and dockless e-scooter companies into more sustainable urban transportation planning and more efficient vehicle fleet reallocation in future smart cities.
Article
Cities worldwide are developing and implementing strategies to promote the bicycle as a viable and competitive mobility option, to foster the development of resilient, livable, accessible, inclusive, and low-carbon societies. Nevertheless, empirical evidence has shown that equity issues have been far less addressed during bicycle planning and decision-making processes, regardless of the importance of the social dimension within the sustainable mobility policy. Therefore, to explore the distributional impacts of bicycle-related benefits in cities around the globe, this article delves into the current literature encompassing distributive justice frameworks and equity-oriented assessments. Our review revealed that often the distributional effects of bicycle planning are context-dependent, with projects and investments targeting central, advantaged, and wealthy areas of cities. Quantitative assessments identified that bicycle benefits such as infrastructure coverage, cycling trips, accessibility, and health gains are unevenly distributed in cities, not addressing the needs of disadvantaged and vulnerable population groups. Moreover, despite the current predominance of quantitative frameworks to examine the equity impacts of cycling, a considerable increase in qualitative and alternative approaches has been observed, including the role of bicycle advocacy, individual characteristics, and institutional perspectives in the distributive process. Whereas empirical evidence suggests that bicycle planning and decision-making processes often overlook equity issues, this article discusses methodological strengths and limitations and future research pathways to support planners, politicians, and practitioners toward more equitable approaches.
Chapter
The socioeconomically disadvantaged have much to gain from cycling uptake, as they are most likely to suffer transport disadvantage and be less physically active. This chapter reviews research on “cycling and socioeconomic disadvantage” from two different perspectives: (1) socioeconomic inequalities in cycling levels and (2) spatial inequalities in the provision of cycling facilities. We found evidence of variable relationships between socioeconomic disadvantage and cycling levels. In European “high-cycling” countries, all income groups seem to cycle with minor variations. In Western “low-cycling” countries such as the UK, Canada, and Australia, middle- and high-income groups tend to cycle more. By contrast, in the US, slightly higher levels of cycling among low-income groups or no significant differences were found. In South America, there is a consistent negative association between income and cycling. Education was found positively associated with cycling in Europe, North America, and Oceania, but negatively in South America. Most studies found that disadvantaged populations have lower access to cycling networks and particularly to docked-based Bike Share Schemes (BSS). Dockless BSS may, however, help to reduce geographical inequalities relative to BSS. These results lead to the conclusion that socioeconomic inequalities in cycling should receive greater consideration in research into cycling uptake and in practice, at design, implementation, and monitoring stages of interventions to enable cycling uptake. Further work is needed in a range of areas relating to cycling and socioeconomic disadvantage, including research from both perspectives—socioeconomic inequalities in cycling levels and spatial inequalities in the provision of cycling facilities—in middle- and low-income countries, new methods to reliably assess spatial inequalities in the provision of cycling facilities, more insight into trends in inequalities, and in-depth analysis of the barriers to cycling among disadvantaged populations.
Article
The rapid rise of digital platform-based transportation services over the past decade has begun to transform urban mobility. Fleets of dockless bicycles and scooters – or ‘micromobility’– represent the newest horizon of investment, particularly in the United States. Micromobility platforms launch rapidly, with minimal public planning or funding and no fixed infrastructure, using inexpensive, GPS-connected vehicles stored in public space. These platforms represent a deepening of the neoliberalisation of transport, in which infrastructural properties emerge biopolitically from the dynamics of private platforms. This article examines public debates over the regulation of micromobility platforms in Austin, Texas, in early 2018. Drawing on interviews with city officials and bikesharing professionals, observation of public meetings and GIS analysis of usage data, we argue that conflicts we observed over new micromobility platforms – specifically ‘clutter’, equity in geographic coverage and data privacy – obscured the deeper political economy of platformisation and the austerity that limited the effectiveness of the existing public station-based bikeshare system. In Austin, the search for ‘innovative’ micromobility transportation at no public cost resulted in the further erosion of the underfunded public system. We argue that despite their flexible, low-carbon image, existing micromobility platforms in the United States largely exploit rather than address inadequacies of urban transport.
Article
Since the early 2000s, academic research on equity and justice has become an increasingly integral component of transportation planning and policy-making. Less research, however, has focused specifically on the intersection of equity, justice, and active transportation (i.e. cycling and walking). This Viewpoint builds on some of the key concerns and barriers associated with active transportation for disadvantaged groups, especially but not exclusively in relation to planning culture and processes, policing, harassment and racism, and gentrification and displacement. We investigate how issues of equity and justice can worsen the conditions that often prevent or diminish one’s capability or desire to engage in active transportation. By providing a better understanding of the deep intersectionalities of equity, justice, and the physical and social barriers to active transportation, our hope is that this Viewpoint helps to improve how such barriers can be recognised and overcome, and the opportunities for change can be understood, centred, and implemented at the policy and planning level.
Article
Bike share programs (BSPs), which are a form of public transportation service that makes bicycles available for shared use on a short-term basis, have developed dramatically. As a new mode of BSP, dockless shared bikes (DSBs) are receiving increasingly more attention. Unlike the existing research on DSBs which concentrates on demand forecasting, static and dynamic repositioning, and transportation planning optimization, the present research focuses on the parking status, which is a unique characteristic of DSBs that is not relevant for station-based shared bikes. The results of a field study and a laboratory study revealed that consumers would have higher (lower) willingness to use upright (fallen) DSBs since they would consider fallen status as a signal of high risk. The effect is so strong that it occurs even for DSBs that are picked up while being observed by the consumer. In addition, the joint effect of motor fluency is also discussed. Our findings contribute to the literature on DSBs, risk perception, and motor fluency and provide insights into understanding consumers' decision-making process in choosing DSBs, optimizing the system efficiently and accurately, saving unnecessary costs, and decreasing environmental impacts.
Conference Paper
Significant new technological developments in transport are already part of our urban landscape, helped by trends in the globalisation of economic activities. Acknowledging that technology is a facilitator of key changes in urban mobility, this thesis examines the institutional context in which a new transport technology is deployed, highlighting concerns not only about possible failures of an ‘enabling state’, but also about the ‘enabling environment’ as a central policy issue. This perspective provides a suitable space to further discuss the increasing governance hybridity in deploying new technologies in transport, acknowledging that the balance of power appears to be shifting. This research seeks to analyse the role of decision-making processes in triggering transformative adaptations that account for a mobility justice transition towards more equitable and inclusive mobility landscapes. Empirically, the thesis presents a case study promoting utility cycling via the deployment of an inter-comunal Bicycle Sharing Scheme, comprising 14 comunas in Santiago, Chile’s capital city, a fragmented metropolitan area with high socio-spatial inequalities. This research approach combines quantitative and qualitative methods of data gathering and analysis. A survey of 343 current bike-hire users at the busiest stations in order to gauge the perceived benefits of such deployment was complemented by interviews with key decision-makers and direct observations of operational logistics in the field. Business model innovation and public tendering processes provided valuable insights into the decision-making process as a subject of analysis. Findings suggest that a mobility justice transition is a relational matter. Indeed, inter-governmental agreements and collaborative actions were crucial in challenging patterns of socio-spatial inequality and proved to be a transformative strategy for change. However, prospects for a radical transition towards greater mobility justice are mixed. In conclusion, partnerships supporting niche-innovations operate within norms, values and practices, which are socially and culturally conditioned, and systematically shaped by the actions of society. Unfolding this rationale and ‘working through’ tensions and synergies towards the search for a common interest on the basis of transparency, collaboration, trust and deliberation, there is potential for setting out a mobility justice transition pathway.
Article
Public bicycle share programs (PBSPs) can play a role in advancing transportation equity if they make bicycling more accessible to disadvantaged populations. In Ontario, Hamilton Bike Share expanded their program in 2018 by adding twelve “equity” stations with the explicit objective of increasing access for under-serviced neighborhoods. In this case study, we investigate differentials in accessibility to stations using a balanced floating catchment area approach and compare accessibility with and without the equity stations. We analyze population interpolated to small cells to better reflect walking to a station and conduct a sensitivity analysis at several walking time thresholds. We then reaggregate the estimated accessibility by income groups for further analysis. Our findings indicate that equity stations increased accessibility for the serviced population at every threshold examined, but the increase was relatively modest especially for population in the bottom 20% of median total household income.
Article
Bike Sharing Systems (BSS) have gained popularity all over the world. BSS success requires efficient location of stations and the rebalancing of the network, both of which depend on predicted demand and flows between stations. Therefore, predicting BSS demand is essential to optimize logistic operations, as well as network reliability and availability. The present work develops statistical models to predict the hourly origin-destination demand in the Lisbon BSS network. Models predict the number of trips that will occur between an origin station and a destination station (OD pair) at a certain hour, as well as the duration of such trips. This study also examines the effect of several explaining variables, including the weather, intermodality effects, effects of station location close to different types of points of interest and the time/hour effect. These effects were all tested using different statistical models, including the Generalized Linear Models (GLM) and zero-augmented ones: the hurdle model and the zero-inflated model. The hurdle model showed the best fit to the data and several explaining variables exhibited statistical significant effects. A discussion on the potential logistic and policy impacts of such findings is also provided, so that BSS network design and operations can incorporate them within the urban mobility system policy.
Article
Public–private transportation megaprojects such as toll roads and rail networks have received attention as expressions of neoliberal urban development processes, but what we call “mesoscale” mobility infrastructures have become increasingly common in the United States. Such infrastructures are large enough to have systemic qualities (e.g., fixed nodes, instrumented networks, and operational requirements) and complex institutional arrangements but small enough in cost and impact that they do not systemically transform urbanization patterns. In this article, we analyze one such mesoscale infrastructure system, bicycle sharing, across three urban regions in the United States: Austin, Texas, Philadelphia, and the San Francisco Bay Area. We argue that bicycle sharing systems in the United States have three key features: (1) widespread expectations of fiscal self-sufficiency restrict their geographical reach to urban centers; (2) they largely follow existing patterns of racialized uneven development, leading to major service gaps; and (3) their implementation involves contingent institutional configurations that create modest openings for steering them in more equitable directions. At the same time, newer venture capital–funded “dockless” competitors have exploited the coverage gaps of station-based bike sharing without departing from their basic market-driven logic. Mesoscale infrastructural experimentation is increasingly central to efforts to increase mobility options in the United States but, when implemented within existing urban political economies, tends to produce scales of infrastructure that are at odds with more substantive forms of mobility justice.
Article
Better transportation and medical service systems contribute to urban sustainable development. Dock-less bike-sharing system (DLBS) is an innovative, sustainable, and flexible travel mode that has been a worldwide spread. This paper addresses a pioneer research aims to explore the characteristics of DLBS usage in outpatient trips and its impacts on travelers’ mode choice behavior. The data sources include the survey at Beijing Friendship Hospital and the trip data from a DLBS company. The research results show that DLBS has evidently decreased the private bike usage by over one third and become a replacement. It is also an important feeder mode for public transport service to the medical service. Among 1,348 DLBS usage in outpatient trips, more than 40% trip transactions are connecting the hospital and public transport stations. Over 70% travelers ride DLBS only in a single trip while having other activity purpose after leaving the hospital. Multinomial Logit (MNL) model is used to investigate the factors that influence the DLBS daily usage. Education and online payment have positive affect. This study can be extended to DLBS usage in other trips with similar characteristics such as appointment-based, short-duration, and multiple activities.
Article
Full-text available
Public bicycle share users are predominantly Caucasian, employed, and have higher incomes and education levels, as compared to the general population. This has prompted bicycle share operators and researchers to increasingly consider equity in bicycle share program access and uptake. The location of bicycle share docking stations has been cited as a major barrier to uptake among lower socioeconomic groups. This study aimed to assess spatial access to bicycle share programs in Canadian cities by comparing the socioeconomic characteristics of dissemination areas inside and outside the bicycle share service areas. We obtained locations of bicycle share stations for the five existing programs in Canada: Vancouver, Hamilton, Toronto, Ottawa-Gatineau, and Montréal. We used the material component of the Pampalon Deprivation Index (2011) as a measure of socioeconomic status for each dissemination area, calculating city-specific quintiles. We compared the distribution of deprivation for dissemination areas inside the bicycle share service area, compared with outside the service area. We found that advantaged areas have better access to bicycle share infrastructure in Vancouver, Toronto, Ottawa-Gatineau, and Montréal, and conversely, that disadvantaged areas have better access in Hamilton. This analysis indicates that in most cities, substantial effort is needed to expand service areas to disadvantaged areas in order to increase spatial access for lower socioeconomic populations.
Technical Report
Full-text available
Research over the past several decades has made it increasingly clear that livable communities are inextricably linked with the provision of opportunities for active and/or non-motorized transportation; i.e., walking, cycling and their variants. An emerging phenomena that is working within the broader movement of active transportation is public bicycle sharing systems (BSS). Such systems have grown considerably in the US in recent years and, in some cases, are dramatically changing the ecology of urban transport. Alongside celebrations of the early successes of US BSS, have been criticisms that these systems have not been adequately integrated into lower-income communities; a pattern that mirrors (motorized) transportation injustices-both past and present-that have burdened lower-income while simultaneously advantaging middle to higher-income communities. And while diverse communities are embracing non-motorized transportation, there is valid concern that traditionally underserved populations will again be marginalized or unable to share in the full benefits of existing and future bicycle- and pedestrian-oriented infrastructure including BSS. This research explores the spatial arrangements and allocations of US BSS and examines the extent to which lower-income communities experience differential access to bike-sharing infrastructure. Spatial regression models are employed to examine the degree to which race, ethnicity and/or economic hardship explain variations in the distribution of bike-sharing stations.
Article
Full-text available
The number of cities offering bikeshare has increased rapidly, from just a handful in the late 1990s to over 800 currently. This paper provides a review of recent bikeshare literature. Several themes have begun to emerge from studies examining bikeshare. Convenience is the major motivator for bikeshare use. Financial savings has been found to motivate those on a low income and the distance one lives from a docking station is an important predictor for bikeshare membership. In a range of countries, it has been found that just under 50% of bikeshare members use the system less than once a month. Men use bikeshare more than women, but the imbalance is not as dramatic as private bike riding (at least in low cycling countries). Commuting is the most common trip purpose for annual members. Users are less likely than private cyclists to wear helmets, but in countries with mandatory helmet legislation, usage levels have suffered. Bikeshare users appear less likely to be injured than private bike riders. Future directions include integration with e-bikes, GPS (global positioning system), dockless systems and improved public transport integration. Greater research is required to quantify the impacts of bikeshare, in terms of mode choice, emissions, congestion and health.
Article
Full-text available
Despite the popularity of bike sharing, there is a lack of evidence on existing schemes and whether they achieved their objectives. This paper is concerned with identifying and critically interpreting the available evidence on bike sharing to date, on both impacts and processes of implementation and operation. The existing evidence suggests that bike sharing can increase cycling levels but needs complementary pro-cycling measures and wider support to sustainable urban mobility to thrive. Whilst predominantly enabling commuting, bike sharing allows users to undertake other key economic, social and leisure activities. Benefits include improved health, increased transport choice and convenience, reduced travel times and costs, and improved travel experience. These benefits are unequally distributed, since users are typically male, younger and in more advantaged socio-economic positions than average. There is no evidence that bike sharing significantly reduces traffic congestion, carbon emissions and pollution. From a process perspective, bike sharing can be delivered through multiple governance models. A key challenge to operation is network rebalancing, while facilitating factors include partnership working and inclusive scheme promotion. The paper suggests directions for future research and concludes that high-quality monitoring impact/process data, systematically and consistently collected, as well as innovative and inclusive evaluation methods are needed.
Article
Full-text available
The emergence of portable global positioning system (GPS) receivers over the last 10 years has provided researchers with a means to objectively assess spatial position in free-living conditions. However, the use of GPS in free-living conditions is not without challenges and the aim of this study was to test the dynamic accuracy of a portable GPS device under real-world environmental conditions, for four modes of transport, and using three data collection intervals. We selected four routes on different bearings, passing through a variation of environmental conditions in the City of Copenhagen, Denmark, to test the dynamic accuracy of the Qstarz BT-Q1000XT GPS device. Each route consisted of a walk, bicycle, and vehicle lane in each direction. The actual width of each walking, cycling, and vehicle lane was digitized as accurately as possible using ultra-high-resolution aerial photographs as background. For each trip, we calculated the percentage that actually fell within the lane polygon, and within the 2.5, 5, and 10 m buffers respectively, as well as the mean and median error in meters. Our results showed that 49.6% of all ≈68,000 GPS points fell within 2.5 m of the expected location, 78.7% fell within 10 m and the median error was 2.9 m. The median error during walking trips was 3.9, 2.0 m for bicycle trips, 1.5 m for bus, and 0.5 m for car. The different area types showed considerable variation in the median error: 0.7 m in open areas, 2.6 m in half-open areas, and 5.2 m in urban canyons. The dynamic spatial accuracy of the tested device is not perfect, but we feel that it is within acceptable limits for larger population studies. Longer recording periods, for a larger population are likely to reduce the potentially negative effects of measurement inaccuracy. Furthermore, special care should be taken when the environment in which the study takes place could compromise the GPS signal.
Article
Full-text available
Growing concerns over global motorization and climate change have led to increasing interest in sustainable transportation alternatives, such as bikesharing (the shared use of a bicycle fleet). Since 1965, bikesharing has grown across the globe on four continents including: Europe, North America, South America, and Asia (including Australia). Today, there are approximately 100 bikesharing programs operating in an estimated 125 cities around the world with over 139,300 bicycles. Bikesharing’s evolution is categorized into three generations: 1) White Bikes (or Free Bike Systems); 2) Coin-Deposit Systems; and 3) IT-Based Systems. In this paper, the authors propose a fourth-generation: “Demand-Responsive, Multi-Modal Systems.†A range of existing bikesharing business models (e.g., advertising) and lessons learned are discussed including: 1) bicycle theft and vandalism; 2) bicycle redistribution; 3) information systems (e.g., real-time information); 4) insurance and liability concerns; and 5) pre-launch considerations. While limited in number, several studies have documented bikesharing’s social and environmental benefits including reduced auto use, increased bicycle use, and a growing awareness of bikesharing as a daily mobility option. Despite bikesharing’s ongoing growth, obstacles and uncertainty remain, including: future demand; safety; sustainability of business models; limited cycling infrastructure; challenges to integrating with public transportation systems; technology costs; and user convenience (e.g., limited height adjustment on bicycles, lack of cargo space, and exposure to weather conditions). In the future, more research is needed to better understand bikesharing’s impacts, operations, and business models in light of its reported growth and benefits.
Article
"Complete Streets" policies require transportation engineers to make provisions for pedestrians, cyclists and transit users. These policies may make bicycling safer for individual cyclists while increasing overall bicycle fatalities if more individuals cycle due to improved infrastructure. We merged county-level records of Complete Streets policies with Fatality Analysis Reporting System counts of cyclist fatalities occurring between January 2000 and December 2015. Because comprehensive county cycling estimates were not available, we used bicycle commute estimates from the American Community Survey and US Census as a proxy for the cycling population, and limited analysis to 183 counties (accounting for over half the US population) for which cycle commute estimates were consistently non-zero. We used G-computation to estimate the effect of policies on overall cyclist fatalities while also accounting for potential policy effects on the size of the cycling population. Over 16 years, 5,254 cyclists died in these counties, representing 34 fatalities per 100,000 cyclist-years. We estimated that Complete Streets policies made cycling safer, averting 0.6 fatalities per 100,000 cyclist-years (95% CI: 0.3, 1.0) by encouraging a 2.4% increase in cycling and a 0.7% increase in cyclist fatalities. G-computation is a useful tool for understanding policy impact on risk and exposure.
Article
Free-floating bike sharing (FFBS) is an innovative bike sharing model. FFBS saves on start-up cost, in comparison to station-based bike sharing (SBBS), by avoiding construction of expensive docking stations and kiosk machines. FFBS prevents bike theft and offers significant opportunities for smart management by tracking bikes in real-time with built-in GPS. However, like SBBS, the success of FFBS depends on the efficiency of its rebalancing operations to serve the maximal demand as possible. Bicycle rebalancing refers to the reestablishment of the number of bikes at sites to desired quantities by using a fleet of vehicles transporting the bicycles. Static rebalancing for SBBS is a challenging combinatorial optimization problem. FFBS takes it a step further, with an increase in the scale of the problem. This article is the first effort in a series of studies of FFBS planning and management, tackling static rebalancing with single and multiple vehicles. We present a Novel Mixed Integer Linear Program for solving the Static Complete Rebalancing Problem. The proposed formulation, can not only handle single as well as multiple vehicles, but also allows for multiple visits to a node by the same vehicle. We present a hybrid nested large neighborhood search with variable neighborhood descent algorithm, which is both effective and efficient in solving static complete rebalancing problems for large-scale bike sharing programs. Computational experiments were carried out on the 1 Commodity Pickup and Delivery Traveling Salesman Problem (1-PDTSP) instances used previously in the literature and on three new sets of instances, two (one real-life and one general) based on Share-A-Bull Bikes (SABB) FFBS program recently launched at the Tampa campus of University of South Florida and the other based on Divvy SBBS in Chicago. Computational experiments on the 1-PDTSP instances demonstrate that the proposed algorithm outperforms a tabu search algorithm and is highly competitive with exact algorithms previously reported in the literature for solving static rebalancing problems in SBSS. Computational experiments on the SABB and Divvy instances, demonstrate that the proposed algorithm is able to deal with the increase in scale of the static rebalancing problem pertaining to both FFBS and SBBS, while deriving high-quality solutions in a reasonable amount of CPU time.
Article
Objectives: To investigate accuracy of distance measures computed from Global Positioning System (GPS) points in New York City. Methods: We performed structured walks along urban streets carrying Globalsat DG-100 GPS Data Logger devices in highest and lowest quartiles of building height and tree canopy cover. We used ArcGIS version 10.1 to select walks and compute the straight-line distance (Geographic Information System-measured) and sum of distances between consecutive GPS waypoints (GPS-measured) for each walk. Results: GPS distance overestimates were associated with building height (median overestimate = 97% for high vs 14% for low building height) and to a lesser extent tree canopy (43% for high vs 28% for low tree canopy). Conclusions: Algorithms using distances between successive GPS points to infer speed or travel mode may misclassify trips differentially by context. Researchers studying urban spaces may prefer alternative mode identification techniques. (Am J Public Health. Published online ahead of print February 18, 2016: e1-e3. doi:10.2105/AJPH.2015.303036).
Free Floating Bike Share Pilot Evaluation Report
  • City Of Seattle
City of Seattle, 2018. Free Floating Bike Share Pilot Evaluation Report. Seattle, WA. Available online at: https://www.seattle.gov/Documents/Departments/SDOT/BikeProgram/2017BikeShareEvaluati onReport.pdf City of Seattle, 2016. Seattle 2035 Equity Analysis. Seattle, WA. Available online at: https://www.seattle.gov/Documents/Departments/OPCD/OngoingInitiatives/SeattlesCompreh ensivePlan/2035EquityAnalysisSummary.pdf
Can Seattle's New Bike Share Succeed Where Pronto Failed
  • D Kroman
Kroman, D. 2018. Can Seattle's New Bike Share Succeed Where Pronto Failed. Crosscut.
Modes Less Traveled: Bicycling and Walking to Work in the United States
  • B Mckenzie
McKenzie, B., 2014. Modes Less Traveled: Bicycling and Walking to Work in the United States, 2008-2012. US Department of Commerce, Economics and Statistics Administration, US Census Bureau. Washington, DC. Available online at: https://www2.census.gov/library/publications/2014/acs/acs-25.pdf
Bike Share in the US
NACTO (National Association of City Transportation Officials), 2018. Bike Share in the US: 2017. New York, NY. Available at: https://nacto.org/bike-share-statistics-2017/.
Empirical analysis of munich's free-floating bike sharing system: Gps-booking data and customer survey among bikesharing users
  • S Reiss
  • F Paul
  • K Bogenberger
Reiss, S., Paul, F., Bogenberger, K., 2015. Empirical analysis of munich's free-floating bike sharing system: Gps-booking data and customer survey among bikesharing users. In: Transportation Research Board 94th Annual Meeting (No. 15-3741).
Public Bikesharing in North America: Early Operator and User Understanding, MTI-11-19
  • S A Shaheen
Shaheen, S.A., 2012. Public Bikesharing in North America: Early Operator and User Understanding, MTI-11-19. San Jose, CA. Available online at: https://transweb.sjsu.edu/sites/default/files/1029-public-bikesharing-understanding-earlyoperators-users.pdf
Public Bikesharing in North America During a Period of Rapid Expansion: Understanding Business Models, Industry Trends & User Impacts
  • S A Shaheen
  • E W Martin
  • A P Cohen
  • N D Chan
  • M Pogodzinski
Shaheen, S.A., Martin, E.W., Cohen, A.P., Chan, N.D., Pogodzinski, M., 2014. Public Bikesharing in North America During a Period of Rapid Expansion: Understanding Business Models, Industry Trends & User Impacts, MTI-12-29. San Jose, CA. Available online at:
China's Innovative Smartbike Sharing Startups Are Hitting Obstacles At Home And Abroad
  • B Sin
Sin, B., 2017. China's Innovative Smartbike Sharing Startups Are Hitting Obstacles At Home And Abroad. Forbes. Jersey City, NJ. Available online at: https://www.forbes.com/sites/bensin/2017/04/05/chinas-innovative-station-less-bike-shareshit-obstacles-at-home-and-abroad/.
Quantifying the equity of bikeshare access in US cities
  • J Ursaki
  • L Aultman-Hall
Ursaki, J., Aultman-Hall, L., 2016. Quantifying the equity of bikeshare access in US cities. UVM TRC Report 15-011. Burlington, VT. Available online at: https://www.uvm.edu/sites/default/files/media/TRC_Report_15-011.pdf