Transportation Research Record: Journal of the Transportation Research Board

Official sources of cyclist safety data suffer from underreporting and bias. Crowdsourced safety data have the potential to supplement official sources and to provide new data on near-miss incidents. BikeMaps.org is a global online mapping tool that allows cyclists to record the location and details of near misses and collisions they experience. However, little is known about how the characteristics of near-miss and collision events compare. Further, the question remains whether the characteristics of crowdsourced collision data are similar to those of collision data captured by official insurance reports. The objectives of this study were twofold: (a) to assess similarities and differences in near misses and collisions reported to BikeMaps.org and (b) to assess similarities and differences in collisions reported to BikeMaps.org and to an official insurance data set. Logistic regression was used first to model the odds of crowdsourced near-miss reports as opposed to collision reports and then to model the odds of crowdsourced as opposed to official insurance collision reports, as a function of incident circumstances. The results indicated higher odds of crowdsourced reports of near misses than of crowdsourced collision reports for commute trips, interactions with motor vehicles, and in locations without bicycle-specific facilities. In addition, relative to insurance reports, crowdsourced collision reports were associated with peak traffic hours, nonintersection locations, and locations where bicycle facilities were present. These analyses indicated that crowdsourced collision data have potential to fill in gaps in reports to official collision sources and that crowdsourced near-miss reporting may be influenced by perceptions of risk.

Bikeshare systems with docking stations have gained popularity in cities throughout the United States—and have increased from six programs with 2,300 bikes in 2010 to 74 systems with 32,200 bikes in 2016. Even though bikeshare systems generate a wealth of data about bicycle checkout and check-in locations and times at docking stations, virtually nothing is known about routes and activities undertaken between checkout and check-in. Such information could greatly enhance expansion of bikeshare systems, placement of new docking stations, and location of new bike lanes and paths. In pursuit of such information, the District Department of Transportation, Washington, D.C., placed GPS trackers on 94 Capital Bikeshare (CaBi) bikes in the spring of 2015. On the basis of these data, this geographic information system analysis distinguished riders by type of CaBi membership, identified popular routes, analyzed bicycle infrastructure use, and examined stops and dwelling times at places of interest. Results showed strong differences in trip attributes between types of membership. Trips taken by short-term users were longer in distance, slower than long-term users’ trips, and concentrated in and around the National Mall, whereas long-term users’ trips were concentrated in mixed-use neighborhoods. Short-term users rode 12% of their miles on dedicated bicycle infrastructure, 61% in parks, and 27% on roadways with motorized traffic, whereas for long-term members the percentages were 33%, 17%, and 50%, respectively. On the basis of the routes taken in this study, potential locations were recommended for bicycle infrastructure improvements and new bikeshare stations.

This research investigated aggressive driver–bicyclist interactions. Individuals who identified themselves as both a driver and a bicyclist were asked about their behavior when they encountered a bicyclist on the road while they were driving a car. Open-ended survey responses were analyzed from individuals who reported a propensity for driving too closely to a bicyclist who they felt was not staying to the side of the road. The data were drawn from a snowball-sampled, online survey specifically targeted to elicit responses about rare (i.e., deviant or illegal) behaviors. Little research exists on why individuals would choose to intimidate a bicyclist while they were driving. Applicable theories from sociology and behavioral economics (i.e., theories of crime as social control and as altruistic punishment) were drawn on in this study to help understand why individuals might do so. This paper argues that aggressive driving behavior directed at bicyclists in the sample population could be characterized with two general themes: “teaching them a lesson” and “they had it coming.” In both cases, individuals deflected the blame for their aggressive behavior away from themselves. Instead, they cast themselves as serving a social good by teaching bicyclists how they should behave or by punishing bicyclists for behaving in ways with which the drivers disagreed. The study reported here was an initial step in an effort to identify testable hypotheses through qualitative methods to explain such behaviors and eventually to mitigate them. The intent is to inform actionable directions to address dangerous on-street interactions that act as barriers to a safe transportation system that accommodates all users.

Washington, D.C., has been a national leader in the adoption of innovative bicycle facilities. However, with much of the low-hanging fruit already plucked (i.e., bicycle facilities already in place), the District Department of Transportation (DOT) needed a mechanism to prioritize investments. Thus the District DOT developed a bicycle level of traffic stress (LTS) map as part of a Multimodal Congestion Management Study. Existing roadway information, combined with an innovative geographic information system approach, was used to create the map and to prioritize and expedite the collection of supplemental roadway information. The results confirmed existing perceptions about the availability of bicycle facilities in the District and identified previously unidentified gaps in the overall bicycle network. In addition, the methodology used to develop the LTS network map provided a proof-of-concept for other jurisdictions to use as they look to develop their own LTS network maps. With this information, the District DOT can now prioritize future bicycle infrastructure investments. It also has a mechanism to update the LTS map as additional data are collected and new facilities are constructed.

This research investigated the route choice behavior of cyclists in Toronto, Ontario, Canada, with data collected from a smartphone application deployed to many cyclists in the city. For the study, 4,556 cyclists registered and logged more than 30,000 commuting trips over 9 months. In addition to the time-stamped, second-by-second GPS readings on each trip, information on age, gender, and rider history was collected on a voluntary basis. Multinomial logit route choice models were estimated for the commuting cycling trips. The results revealed the critical importance of cycling facilities (e.g., bike lanes, cycling paths and trails) on cyclists’ route choice decisions, and provided valuable information for use in Toronto’s ongoing bicycle network planning.

As many cities are investing in street improvements or transportation infrastructure upgrades to provide better bike access or more complete bike networks, many practitioners, planners, and policy makers are seeking more conclusive evidence about the economic value of bike infrastructure and bike facilities. With the use of residential property values as indicators of consumer preferences for bicycle infrastructure, many scholars have shown the importance of green space and off-street bike trails as amenities valuable to property owners. However, empirical evidence on the relationship of on-street bike facilities and property values remains relatively inconsistent. The unique focus of this study was advanced bike facilities that represented higher levels of bike priority or bike infrastructure investments shown to be more desirable to a larger portion of the population. Through the separate estimation of ordinary least squares hedonic pricing models and spatial autoregressive hedonic models of single and multifamily properties, it was found that proximity to advanced bike facilities (measured by distance) had significant and positive effects on all property values, which highlighted household preferences for high-quality bike infrastructure. Furthermore, the study showed that the extensiveness of the bike network (measured by density) was a positive and statistically significant contributor to the prices for all property types, even after proximity was controlled for with respect to bike facilities and other property, neighborhood, and transaction characteristics. Finally, estimated coefficients were applied to assess the property value impacts of the Green Loop (i.e., the proposed Portland, Oregon, signature bike infrastructure concept), which illustrated the importance of considering the accessibility and the extensiveness of bike facility networks.

Urban transportation systems tend to operate most effectively when common expectations exist about all user travel behavior under various conditions. A wide range of behavior among cyclists presents a significant challenge to the achievement of safer and improved designs at intersections. In this research, cyclists were observed (i.e., through the use of video at fixed-camera locations) as they made left turns at six intersections in Toronto, Ontario, Canada. The intersections were classified into five types on the basis of their physical designs and operational characteristics. Cyclist behavior was assessed to determine the propensity to traverse the intersection legally, designated as “rule compliance.” Further, the analysis determined the likelihood that a cyclist would traverse an intersection in a path that was consistent with the design; this outcome was defined as “facility compliance.” The results revealed that the presence of bike boxes, two-phase lefts, and turning lanes with advanced green phases positively influenced cyclists by increasing the likelihood that left turns would be legal and consistent with the behavior intended through the design. The results also suggested that the highest rates of rule and facility compliance existed under the condition in which cyclists approached an intersection during a green signal. On the basis of the observations in the research, design recommendations were made to accommodate cyclists better and produce more consistent behavior and presumably to enhance safety.

Urban intensification is believed to result in a modal shift away from automobiles to more active forms of transportation. This study extended the understanding of bicycle mode choice and the influence of built form through an analysis of dwelling type, density, and mode choice. Apartment dwelling and active transportation are related to intensification, but an understanding of the impact of increased density on bicycling is muddied by the lack of isolation of cycling from walking in many studies and by the lack of controls for the confounding effects of dwelling type. This study examined the relationship between dwelling type and mode choice in Toronto, Ontario, Canada. In this study of 223,232 trips, 25 variables were controlled for, and multinomial logistic regression analysis was used to estimate relative risk ratios. Strong evidence was found that a trip that originated from an apartment-based household was less than half as likely to be taken by bicycle as a similar trip that originated from a house-based household in Toronto in 2011. Increased population density of the household location had a positive impact on the likelihood that a trip would be taken by walking and a negligible and uncertain impact on the likelihood that it would be taken by transit. However, increased population density had a negative impact on bicycling. Further analysis found that the negative impact of density did not seem to apply to those who lived in single detached housing but rather only to the likelihood that apartment and townhouse dwellers would cycle. Further research is required to identify the exact barriers to cycling that apartment dwellers experience.

Nowadays, the bicycle is seen as a sustainable and healthy substitute for the car in urban environments. The Netherlands is the leading country in bicycle use, especially in urban environments. Yet route choice models featuring inner-city travel that includes cyclists are lacking. This study estimated a cyclists’ route choice model for the inner city of Amsterdam, Netherlands, on the basis of 3,045 trips collected with GPS data. The main contribution of this study was the construction of the choice set with an empirical approach, which used only the observed trips in the data set to compose the choice alternatives. The findings suggested that cyclists were insensitive to separate cycle paths in Amsterdam, a city characterized by a dense cycle path network in which cycling was the most prominent mode of travel. In addition, cyclists were found to minimize travel distance and the number of intersections per kilometer. The impact of distance on route choice increased during the morning peak when schedule constraints were more prevalent. Furthermore, overlapping routes were more likely to be chosen by cyclists, everything else being the same.

The District of Columbia is enjoying rapid growth in cycling, evident through trends in census mode share data and in the presence of more cyclists out on the street. The District Department of Transportation (DOT) has spent significant resources in the past two decades to improve active transportation planning, outreach, and infrastructure delivery. These efforts have led to the District’s recognition as a cycling-friendly city. Now the District DOT is taking stock of what has been done to improve cycling thus far and to determine what to do next. The District DOT is starting to ask what is driving the growth in the cycling mode share. How can the District understand, nurture, and expand on that growth in the cycling mode share? This study explored underlying relationships in which the District’s cycling mode share was present. The analysis dug deeply by doing (a) a statistical analysis to identify key factors that influenced cycling and (b) a spatial analysis that defined trends in accessibility to cycling facilities and the mobility of the cycling network. Findings from this research will help inform District DOT planners on what policy, operational, outreach, and capital investment levers to consider as they continue to promote cycling in the District going forward.

This paper reports the experience of a bikeshare operation in Ningbo, China. For analysis of the characteristics of the system operation, system log data were collected for a month, and these data were supplemented by questionnaire data from 1,856 respondents. It was found that the Ningbo bikeshare operation, when compared with that of other cities, had a higher car substitution rate of 16.1% and a higher public bike usage rate of 3.7 trips per bike per day. Together, these contributed to a higher than average reduction in car travel of 756.0 km per bike per year. Although the system was successful in terms of reduced car travel and user satisfaction, it still suffered from the problem of rent–return imbalance, especially during the morning and afternoon peak travel hours. It was also found that rainy weather discouraged the use of public bikes. Moreover, the survey showed that 70% of bike riders took bikes as the sole mode to reach their destination and only 30% of them used bikes as a “last mile” means to transfer to other transit modes. This factor is in contrast to the initial expectation that public bikes would mainly fulfill the last mile demand. It is suggested that the bikeshare system should be well planned, designed, and operated to cope with the negative effects of the imbalance problem and rainy weather conditions. The aim of the bikeshare system may need to be repositioned from a last mile solution to an independent public transportation system that supplements metro, bus, and taxi systems.

As cities worldwide try to increase the adoption of the bicycle as a legitimate mode of urban transportation, the perception of danger plays a significant role in deterring potential new users. In a study conducted in Montreal, Quebec, Canada, bicycle users claimed to perceive intersections with bidirectional cycle tracks twice as negatively as they perceived either similar protected facilities midblock or intersections with painted bicycle lanes. This study aimed to understand this negative perception through a fine-grained analysis and observation of the interplay between infrastructure design and bicycle users’ behavior at these intersections. Researchers used the Desire Lines Analysis tool pioneered by Copenhagenize Design Company and developed recommendations and design interventions for two intersections with bidirectional facilities in the city of Montreal. Study results demonstrated that most users followed the prescribed routes of the street design through each intersection and shone light on users who did not—more than a quarter of users. The trajectories of bicycle users that were questionably legal resulted in observed conflicts at both bidirectional intersections. Conflicts were grouped into three major observed themes: counterflow interactions, priority confusion, and directional awareness. Recommendations made in this paper aim to address each one of these observed themes with appropriate designs that are choreographic, prioritized, and predictable for all road users. Planners, engineers, and urban designers can gain significant insight into best-practice bicycle infrastructure through techniques, such as desire lines analysis, that observe behavior and design accordingly.

The bicycle is an important part of the urban transportation system in China. Traditional research on bicycle levels of service concentrated on the cyclists’ perspective and neglected bicyclists’ particularity and diversity. The objectives of this research were to propose bicycle level-of-service (BLOS) models from the users’ perspective and to develop a new BLOS criterion on the basis of a new classification of persons. The key influential factors of BLOS were classified into three categories: safety, comfort, and air quality. The stepwise regression analysis was employed to develop the BLOS models on the basis of influential factors and volunteers’ ratings. To isolate the significant difference of the BLOS requirements, cyclists were divided into four groups: users with special requirements, attempters, frequent users, and enthusiasts. New BLOS criteria corresponding to the classification of cyclists and BLOS models were developed. Results showed that the nonmotorized vehicle lane width, the form of separation between motorized and nonmotorized vehicle lanes, moped speed, and proportion of roadside planting were the significant influential factors of the corresponding models. The fact that the developed BLOS models and classification criteria could improve cycling facilities proved to be quite applicable and reasonable. Results can be used to draw two classification maps of BLOS on the bike lanes of main roads in China as an example of an application. The results described in this paper can help decision makers find significant factors affecting cyclists’ satisfaction at road segments and determine the order of the improvements to be made in the nonmotorized vehicle lane.

Following global guidelines, several cities are investing in urban cycling. Cities are in different stages of cycling development and have adopted different approaches and packages of policies that are likely to be most effective at each stage. Urban cycling plans include investment in infrastructure, promotion, and education supporting the adoption of active modes for urban mobility. Some investments aim to meet current cyclists’ needs and others those of potential bicycle adopters. With respect to urban cyclists, several studies propose typologies, usually related to frequency, trip purpose, or motivation. This paper compares a set of cyclist typologies and the corresponding categorization methods and reviews 20 studies that considered different cyclists’ profiles. Most studies relied on expert judgment approaches or rule-based decisions; five considered multivariate analysis techniques for clustering groups, on the basis of data from surveys. Despite the variety of group categorizations, commonalities were found in most cases and divided cyclists into three main types: current cyclists (typically more proficient riders), potential cyclists (willing but not convinced), and noncyclists (unaware of or unwilling to shift to cycling). Dividing the population of potential cyclists into different typologies can better inform the different stages of planning for cycling infrastructure development by targeting more accurately the needs and requirements of different types of users. This is a key element in the management of a cycling network and cycling infrastructure, which are intended to be built on the basis of effective solutions and decisions to achieve desirable bicycle modal shares of regular trips.

Lessons derived from the urban experience of bicycling may not be broadly supportive of bicycling in rural, small, and low-density (RSLD) places because of differences in built environment, social, and political contexts. In this study, the hypothesis that bicycling was primarily an urban activity was investigated. Binary logistic regression was used to compare the frequency of bicycling and the population characteristics of bicyclists across urban and RSLD places. Multiple operational definitions of urban–rural continua were used to examine whether the results were sensitive to how RSLD places were defined. The data for bicycling were from the 2009 National Household Travel Survey, which was designed to represent the population of the United States. Bicycling was found to be primarily, but not exclusively, an urban activity. Moreover, women and youths were more likely to bicycle in RSLD places compared with urban places. These findings suggest that an urban perspective on bicycling could limit the success of initiatives aiming to increase the diversity of populations that bicycle. Developing a base of empirical knowledge of bicycling in RSLD places is a necessary step toward developing more inclusive and effective multimodal transportation strategies.

The past decade has seen increased public interest in sustainable transportation modes in the United States. However, there is a relative lack of guidance regarding standards and specifications for bicycle facilities compared with the highway mode. This project sought to address this deficiency through the investigation of alternative pavement markings for bicycle wayfinding and proper bicycle placement at signalized intersections as part of the federal Nonmotorized Transportation Pilot Program in Columbia, Missouri. This evaluation was accomplished with a bicycle simulator study and postsimulator survey with 27 participants. A network of 37 intersections with characteristics similar to intersections in Columbia was created with the ZouSim simulator. The survey included questions regarding bicycling habits and preferences for the alternative markings. For wayfinding, two alternative types of pavement markings and the signage recommended by the Manual on Uniform Traffic Control Devices (MUTCD) were evaluated. Both the survey and the simulator results indicated that the Type 2 wayfinding markings with a green circle performed better with respect to visibility and delineating the bicycle route. The bicycle placement portion of the study investigated three alternative types of markings as well as the MUTCD markings and signage to help riders position their bicycle at the correct location to receive a green signal. The bicycle placement results indicated that the Type 1 and Type 2 experimental detector markings resulted in the fewest number of missed detections, while the Type 1 marking was the preferred alternative of the survey participants.

Do routes with lower doses of air pollution exist in real-world bicycling networks, and do bicyclists actually use those routes? Low-pollution-dose alternative routes for a sample of urban cycling trips were modeled and compared with shortest paths. Bicyclists’ actual route choices on the same trips were observed with the use of GPS data and compared with the low-dose and shortest paths alternatives. With use of past studies of pollution exposure levels and simplified ventilation rates, link-inhaled doses of air pollution were estimated. Findings suggest that a majority of trips have lower-dose alternatives to the shortest path, with a 12% average dose reduction. Cyclists tend to choose routes with pollution concentrations between those of shortest paths and minimum-dose routes, but they also travel considerably farther, leading to total inhaled doses that are higher than on either alternative route. People’s seeming avoidance of nontraffic factors such as hills, excess turns, and difficult intersections leads to longer than optimal detours from a pollution avoidance perspective. Bike paths and bike boulevards (traffic-calmed streets with bicycle priority), as well as denser street grids, appear to provide effective low-pollution alternatives, although such routes tend to encourage excess detours that can add to total inhaled dose. Bike lanes can draw cyclists onto more polluted routes in some circumstances, with poor pollution inhalation outcomes. Overall, excess doses did seem to be a common problem for this sample of cyclists on a real-world network. The study’s findings support policies that provide dense networks of attractive facilities that encourage cyclists to choose direct, lower-pollution routes.

The number of public bikeshare systems has been increasing rapidly across the United States over the past 5 to 10 years. To date, most academic research around bikeshare systems in the United States has focused on the logistics of planning and operationalizing successful systems. Investigations of system users and effects on the local community are less common, and studies that are focused on efforts to engage underserved communities in bikeshare systems are rarer still. This paper relies on a survey of representatives from 56 U.S. bikeshare systems to better understand and document current approaches toward serving low-income and minority populations. The survey asked about equity policies and metrics, the degree to which equity considerations affect a variety of system practices, what the existing barriers to utilizing bikeshare are for target populations, and what challenges the bikeshare system entity faces in addressing those barriers. Results indicate that nearly one in four bikeshare systems has written policies around equity; nearly half of bikeshare systems with more than 500 bikes have such policies. However, many more systems consider equity in various aspects of their systems. Equity considerations affected station siting, fee structure and payment systems, and promotion and marketing in a majority of systems (68%, 72%, and 57%, respectively), and operations and data collection and analysis, though to a lesser extent (42% each). Bikeshare systems reported cost, access, and outreach as the largest barriers to equity, in addition to overall funding and staff levels.

This research explored the relationship between level of traffic stress (LTS) and bikeshare ridership within the Capital Bikeshare (CB) network in Montgomery County, Maryland. Linear regression was used to build a model that could predict the relationship between bikeshare ridership and low-stress bicycle connections between stations, enhanced by various demographic and built environment variables that helped to define the regional context. Linear regression models were used to estimate total trips per year and to inform further studies that sought to increase ridership through improved bicycle facilities and environments. On the basis of the varying land uses within Montgomery County and the geography of CB stations in the county, two separate data sets were created to measure the ridership propensity within the northern part of the county around Rockville and Shady Grove and the southern part of the county around Bethesda and Silver Spring. The models illustrated the utility of LTS measures in identifying the effect of low-stress bicycle connections on bikeshare ridership. The models indicated that bikeshare station pairs that were connected by links with a higher percentage of low-stress facilities were correlated with higher bikeshare ridership. Station pairs that required a longer detour to achieve a low-stress route relative to a shortest-path route were correlated with lower bikeshare ridership. Application of the linear regression tool to estimate ridership on the basis of LTS and other context variables is transferable to other similar networks to draw conclusions about the relationship between quality bicycle connections and the level of bikeshare ridership.