Crash histories,safety perceptions,and attitudes among Virginia bicyclists

IntroductionCycling injury and fatality rates are on the rise, yet there exists no comprehensive database for bicycle crash injury data.MethodWidely used for safety analysis, police crash report datasets are automobile-oriented and widely known to under-report bicycle crashes. This research is one attempt to address gaps in bicycle data in sources like police crash reports. A survey was developed and deployed to enhance the quality and quantity of available bicycle safety data in Virginia. The survey captures bicyclist attitudes and perceptions of safety as well as bicycle crash histories of respondents.ResultsThe results of this survey most notably show very high levels of under-reporting of bicycle crashes, with only 12% of the crashes recorded in this survey reported to police. Additionally, the results of this work show that lack of knowledge concerning bicycle laws is associated with lower levels of cycling confidence. Count model results predict that bicyclists who stop completely at traffic signals are 40% less likely to be involved in crashes compared to counterparts who sometimes stop at signals. In this dataset, suburban and urban roads with designated bike lanes had more favorable injury severity profiles, with lower percentages of severe and minor injury crashes compared to similar roads with a shared bike/automobile lane or no designated bike infrastructure.     

Exploring the severity of bicycle–vehicle crashes using latent class clustering approach in India

IntroductionBicyclists are vulnerable users in the shared asset like roadways. However, people still prefer to use bicycles for environmental, societal, and health benefits. In India, the bicycle plays a role in supporting the mobility to more people at lower cost and are often associated with the urban poor. Bicyclists represents one of the road user categories with highest risk of injuries and fatalities. According to the report by the Ministry of Road Transport and Highways (Accidents, 2017) in India, there is a sharp increase in the number of fatal victims for bicyclists in 2017 over 2016. The number of cyclists killed jumped from 2,585 in 2016 to 3,559 in 2017, a 37.7% increase. Method: Few studies have only investigated the crash risk perceived by the bicyclists while interacting with other road users. The present paper investigates the injury severity of bicyclists in bicycle-vehicle crashes that occurred in the state of Tamilnadu, India during the nine year period (2009–2017). The analyses demonstrate that dividing bicycle-vehicle collision data into five clusters helps in reducing the systematic heterogeneity present in the data and identify the hidden relationship between the injury severity levels of bicyclists and cyclists demographics, vehicle, environmental, temporal cause for the crashes. Results: Latent Class Clustering (LCC) approach was used in the present study as a preliminary tool for the segmentation of 9,978 crashes. Later, logistic regression analysis was used to identify the factors that influence bicycle crash severity for the whole dataset as well as for the clusters that were obtained from the LCC model. Results of this study show that combined use of both techniques reveals further information that wouldn’t be obtained without prior segmentation of the data. Few variables such as season, weather conditions, and light conditions were significant for certain clusters that were hidden in the whole dataset. This study can help domain experts or traffic safety researchers to segment traffic crashes and develop targeted countermeasures to mitigate injury severity.     

An in-depth analysis of self-reported cycling injuries in single and multiparty bicycle crashes in Denmark

Introduction: Cycling is one of the main forms of transportation in Denmark. However, while the number of traffic crash fatalities in the country has decreased over the past decade, the frequency of cyclists killed or seriously injured has increased. The high rate of serious injuries and fatalities associated with cycling emphasizes the increasing need for mitigating the severity of such crashes. Method: This study conducted an in-depth analysis of cyclist injury severity resulting from single and multiparty bicycle-involved crashes. Detailed information was collected using self-reporting data undertaken in Denmark for a 12-month period between 1 November 2012 and 31 October 2013. Separate multilevel logistic (MLL) regression models were applied to estimate cyclist injury severity for single and multiparty crashes. The goodness-of-fit measures favored the MLL models over the standard logistic models, capturing the intercorrelation among bicycle crashes that occurred in the same geographical area. Results: The results also showed that single bicycle-involved crashes resulted in more serious outcomes when compared to multiparty crashes. For both single and multiparty bicycle crash categories, non-urban areas were associated with more serious injury outcomes. For the single crashes, wet surface condition, autumn and summer seasons, evening and night periods, non-adverse weather conditions, cyclists aged between 45 and 64 years, male sex, riding for the purpose of work or educational activities, and bicycles with light turned-off were associated with severe injuries. For the multiparty crashes, intersections, bicycle paths, non-winter season, not being employed or retired, lower personal car ownership, and race bicycles were directly related to severe injury consequences. Practical Applications: The findings of this study demonstrated that the best way to promote cycling safety is the combination of improving the design and maintenance of cycling facilities, encouraging safe cycling behavior, and intensifying enforcement efforts.     

Effects of turning on and off red light cameras on fatal crashes in large U.S. cities

IntroductionThis study updates estimates of effects of activating red light cameras and offers a first look at effects of turning them off.MethodAmong 117 large U.S. cities with more than 200,000 residents in 2014, trends in citywide per capita rates of fatal red light running crashes and of all fatal crashes at signalized intersections were compared between 57 cities that initiated camera programs during 1992–2014 and 33 cities without cameras to examine effects of activating camera programs. Trends also were compared between 19 cities that removed cameras and 31 regionally matched cities with continuous camera programs to evaluate effects of terminating camera programs. Because several cities removed cameras during 2005–2008 and estimated effects might have been confounded by the subsequent economic downturn, primary analyses were limited to the 14 cities that removed cameras during 2010–2014 and 29 regionally matched cities with continuous camera programs. Poisson regression examined the relationship of activating and deactivating cameras with fatal crash rates.ResultsAfter controlling for temporal trends in annual fatal crash rates, population density, and unemployment rates, rates of fatal red light running crashes and of all fatal crashes at signalized intersections were 21% and 14% lower, respectively, in cities with cameras after cameras were turned on than would have been expected without cameras; 30% and 16% higher, respectively, in 14 cities that terminated cameras during 2010–2014 after cameras were terminated than expected had cameras remained; and 18% and 8% higher, respectively, in all 19 cities that removed cameras, but not significantly.ConclusionsThis study adds to the body of evidence that red light cameras can reduce the most serious crashes at signalized intersections, and is the first to demonstrate that removing cameras increases fatal crashes.Practical applicationsCommunities thinking about removing cameras should consider impacts to safety.     

The effect of speed limit reductions in urban areas on cyclists’ injuries in collisions with cars

Abstract

Objective: Impact speed is one of the most important factors explaining the severity of injuries to cyclists when they collide with passenger cars. To reduce injury severity (especially for vulnerable road users), since 2008, Swedish municipalities have the authority to lower the speed limit to 30 or 40?km/h in urban areas as appropriate. The aim of this study was to evaluate how this speed limit reduction has influenced the injury severity for cyclists in this type of collision.

Method: Data from 1,953 collisions between bicycles and passenger cars were collected using information from third-party-liability insurance claims from 2005 to 2017. The change of speed limit distribution, influenced by the reduction of speed limits in urban areas, where car-to-cyclist collisions occurred was studied. Following that, injury severity for cyclists was evaluated regarding collisions occurring in areas with different speed limits.

Results: The results show that, in collisions with cars, cyclists have a significantly lower risk of a moderate-to-fatal (MAIS 2+) injury when the speed limit is 30–40?km/h compared to 50–60?km/h. During the last decade, while the speed-limit has been lowered on many road-sections in urban areas from 50–60?km/h to 30–40?km/h the risk of a cyclist getting a MAIS 2+ injury decreased by 25%. In 2005 to 2011, 16% of the crashes happened on a road with a speed limit of 30–40?km/h; in 2016–2017, this percentage had increased to approximately 50%. Thus, in recent years more crashes occurred on roads with lower speed limits, and in these crashes, there was a lower risk of severe injuries to cyclists. Unfortunately, it was not possible to evaluate the risk of a crash for specific speed limits; since one limitation of this study was the lack of exposure data, nor do we know the impact speed or the actual speed of the vehicles.

Conclusions: This study is an important follow-up on the implementation of measures that can influence bicycle safety. The insurance data used, made it possible to quantify a positive effect on injury severity for cyclists in passenger car-to-cyclist collisions when the speed limit was reduced in urban areas. Insurance claims cover collisions of all crash severity, so they include data covering all types of injuries—not just the most severe/fatal ones. This aspect is especially important in the speed intervals evaluated here, since moderate (MAIS 2) injuries are very frequent in lower-speed crashes and even these injuries can result in long-term consequences.     

Built environment effects on bike crash frequency and risk in Beijing

IntroductionBuilding a safe biking environment is crucial to encouraging bicycle use. In developed areas with higher density and more mixed land use, the built environment factors that pose a crash risk may vary. This study investigates the connection between biking risk factors and the compact built environment, using data for Beijing.MethodIn the context of China, this paper seeks to answer two research questions. First, what types of built environment factors are correlated with bike-automobile crash frequency and risk? Second, how do risk factors vary across different types of bikes? Poisson lognormal random effects models are employed to examine how land use and roadway design factors are associated with the bike-automobile crashes.ResultsThe main findings are: (1) bike-automobile crashes are more likely to occur in densely developed areas, which is characterized by higher population density, more mixed land use, denser roads and junctions, and more parking lots; (2) areas with greater ground transit are correlated with more bike-automobile crashes and higher risks of involving in collisions; (3) the percentages of wider streets show negative associations with bike crash frequency; (4) built environment factors cannot help explain factors contributing to motorcycle-automobile crashes.Practical ApplicationsIn China's dense urban context, important policy implications for bicycle safety improvement drawn from this study include: prioritizing safety programs in urban centers, applying safety improvements to areas with more ground transit, placing bike-automobile crash countermeasures at road junctions, and improving bicycle safety on narrower streets.     

E-bikers’ braking behavior: Results from a naturalistic cycling study

Abstract

Objective: The number of e-bike users has increased significantly over the past few years and with it the associated safety concerns. Because e-bikes are faster than conventional bicycles and more prone to be in conflict with road users, e-bikers may need to perform avoidance maneuvers more frequently. Braking is the most common avoidance maneuver but is also a complex and critical task in emergency situations, because cyclists must reduce speed quickly without losing balance. The aim of this study is to understand the braking strategies of e-bikers in real-world traffic environments and to assess their road safety implications. This article investigates (1) how cyclists on e-bikes use front and rear brakes during routine cycling and (2) whether this behavior changes during unexpected conflicts with other road users.

Methods: Naturalistic data were collected from 6 regular bicycle riders who each rode e-bikes during a period of 2 weeks, for a total of 32.5?h of data. Braking events were identified and characterized through a combined analysis of brake pressure at each wheel, velocity, and longitudinal acceleration. Furthermore, the braking patterns obtained during unexpected events were compared with braking patterns during routine cycling.

Results: In the majority of braking events during routine cycling, cyclists used only one brake at a time, favoring one of the 2 brakes according to a personal pre-established pattern. However, the favored brake varied among cyclists: 66% favored the rear brake and 16% the front brake. Only 16% of the cyclists showed no clear preference, variously using rear brake, front brake, or combined braking (both brakes at the same time), suggesting that the selection of which brake to use depended on the characteristics of the specific scenario experienced by the cyclist rather than on a personal preference. In unexpected conflicts, generally requiring a larger deceleration, combined braking became more prevalent for most of the cyclists; still, when combined braking was not applied, cyclists continued to use the favored brake of routine cycling. Kinematic analysis revealed that, when larger decelerations were required, cyclists more frequently used combined braking instead of single braking.

Conclusions: The results provide new insights into the behavior of cyclists on e-bikes and may provide support in the development of safety measures including guidelines and best practices for optimal brake use. The results may also inform the design of braking systems intended to reduce the complexity of the braking operation.     

Analysis of bicycle crashes in Sweden involving injuries with high risk of health loss

Objective: The objectives of the present article were to (a) describe the main characteristics of bicycle crashes with regard to the road environment, crash opponent, cyclist, and crash dynamics; (b) compare individuals who describe their health after the crash as declined with those who describe their health as not affected; and (c) compare the number of injured cyclists who describe their health as declined after the crash with the predicted number of permanent medical impairments within the same population.

Methods: A sample of individuals with specific injury diagnoses was drawn from the Swedish Traffic Accident Data Acquisition (STRADA) database (n?=?2,678). A survey form was used to collect additional information about the crash and the health-related outcomes. The predicted number of impaired individuals was calculated by accumulating the risk for all individuals to sustain at least a 1% permanent medical impairment, based on the injured body region and injury severity.

Results: Nine hundred forty-seven individuals (36%) responded, of whom 44% reported declined health after the crash. The majority (68%) were injured in single bicycle crashes, 17% in collisions with motor vehicles, and 11% in collisions with another cyclist or pedestrian. Most single bicycle crashes related to loss of control (46%), mainly due to skidding on winter surface conditions (14%), followed by loss of control during braking (6%). There was no significant difference in crash distribution comparing all crashes with crashes among people with declined health. The predicted number of impaired individuals (n?=?427) corresponded well with the number of individuals self-reporting declined health (n?=?421).

Conclusions: The types of crashes leading to health loss do not substantially differ from those that do not result in health loss. Two thirds of injuries leading to health loss occur in single bicycle crashes. In addition to separating cyclists from motorized traffic, other preventive strategies are needed.     

The potential of vehicle and road infrastructure interventions in fatal bicyclist accidents on Swedish roads—What can in-depth studies tell us?

Abstract

Objective: The objective of this article is to describe the characteristics of fatal crashes with bicyclists on Swedish roads in rural and urban areas and to investigate the potential of bicycle helmets and different vehicle and road infrastructure interventions to prevent them. The study has a comprehensive approach to provide road authorities and vehicle manufacturers with recommendations for future priorities.

Methods: The Swedish Transport Administration’s (STA) in-depth database of fatal crashes was used for case-by-case analysis of fatal cycling accidents (2006–2016) on rural (n?=?82) and urban (n?=?102) roads. The database consists of information from the police, medical journals, autopsy reports, accident analyses performed by STA, and witness statements. The potential of helmet use and various vehicle and road infrastructure safety interventions was determined retrospectively for each case by analyzing the chain of events leading to the fatality. The potential of vehicle safety countermeasures was analyzed based on prognoses on their implementation rates in the Swedish vehicle fleet.

Results: The most common accident scenario on rural roads was that the bicyclist was struck while cycling along the side of the road. On urban roads, the majority of accidents occurred in intersections. Most accidents involved a passenger car, but heavy trucks were also common, especially in urban areas. Most accidents occurred in daylight conditions (73%). Almost half (46%) of nonhelmeted bicyclists would have survived with a helmet. It was assessed that nearly 60% of the fatal accidents could be addressed by advanced vehicle safety technologies, especially autonomous emergency braking with the ability to detect bicyclists. With regard to interventions in the road infrastructure, separated paths for bicyclists and bicycle crossings with speed calming measures were found to have the greatest safety potential. Results indicated that 91% of fatally injured bicyclists could potentially be saved with known techniques. However, it will take a long time for such technologies to be widespread.

Conclusions: The majority of fatally injured bicyclists studied could potentially be saved with known techniques. A speedy implementation of important vehicle safety systems is recommended. A fast introduction of effective interventions in the road infrastructure is also necessary, preferably with a plan for prioritization.     

Teenage driver crash incidence and factors influencing crash injury by rurality

BackgroundPrevious research has identified teenage drivers as having an increased risk for motor-vehicle crash injury compared with older drivers, and rural roads as having increased crash severity compared with urban roads. Few studies have examined incidence and characteristics of teen driver-involved crashes on rural and urban roads.MethodsAll crashes involving a driver aged 10 through 18 were identified from the Iowa Department of Transportation crash data from 2002 through 2008. Rates of overall crashes and fatal or severe injury crashes were calculated for urban, suburban, rural, and remote rural areas. The distribution of driver and crash characteristics were compared between rural and urban crashes. Logistic regression was used to identify driver and crash characteristics associated with increased odds of fatal or severe injury among urban and rural crashes.ResultsFor younger teen drivers (age 10 through 15), overall crash rates were higher for more rural areas, although for older teen drivers (age 16 through 18) the overall crash rates were lower for rural areas. Rural teen crashes were nearly five times more likely to lead to a fatal or severe injury crash than urban teen crashes. Rural crashes were more likely to involve single vehicles, be late at night, involve a failure to yield the right-of-way and crossing the center divider.ConclusionsIntervention programs to increase safe teen driving in rural areas need to address specific risk factors associated with rural roadways.Impact on IndustryTeen crashes cause lost work time for teen workers as well as their parents. Industries such as safety, health care, and insurance have a vested interest in enhanced vehicle safety, and these efforts should address risks and injury differentials in urban and rural roadways.     

The use and risk of portable electronic devices while cycling among different age groups

Introduction: In the Netherlands, a survey was set up to monitor the extent of the use of portable, electronic devices while cycling amongst different age groups of cyclists and to estimate the possible consequences for safety. Method: The main research questions concerned age differences in the self-reported use of electronic devices while cycling, self-reported crash involvement and risk, and self-reported compensatory behaviour. Teen cyclists (12–17 years) and young adult cyclists (18–34 years) were more frequent users, and also more indiscriminate users of portable devices while cycling than middle-aged and older adult cyclists (35–49 years; 50 + years). Results: After statistical correction for influences on crash risk of urbanization level, weekly time spent cycling, and cycling in more demanding traffic situations, the odds of being involved in a bicycle crash were estimated to be higher for teen cyclists and young adult cyclists who used electronic devices on every trip compared to same age groups cyclists who never used these devices. For middle-aged and older adult cyclists, the use of portable electronic devices was not a significant predictor of bicycle crashes, but frequency of cycling in demanding traffic situations was. Possible implications for education or legal measures are discussed. Impact on Industry: Results may inform researchers, policy makers, and cyclists themselves. Educational campaigns may use risk information to warn young cyclists about risk of device use while cycling.     

The unintended impact of helmet use on bicyclists’ risk-taking behaviors

Introduction: Safety is a critical factor in promoting sustainable urban non-motorized travel modes like bicycles. Helmets have shown to be effective in reducing injury severity in bicycle crashes, however, their effects on bicyclists’ behaviors still requires deeper understanding, especially amid the emerging trend of using shared bicycles. Risk compensation effects suggest that bicyclists may offset perceived gains in safety from wearing a helmet by increasing risk-taking behaviors. A better understanding of these compensation effects can be useful in assessing various bicycle safety related programs. Method: Using a sample of 131 bicyclists from the San Francisco Bay area, this research studies how bicyclists respond with respect to risk-taking behaviors under various urban-street conditions, as a function of helmet use. Study participants were each shown 12 videos, shot in Berkeley, California, from the perspective of a bicyclist riding behind another bicyclist. A fractional factorial experiment design was used to systematically vary contextual attributes (e.g., speed, bike lane facilities, on-street parking, passing vehicles) across the videos. After each video, participants were asked to indicate if they would overtake the bicyclist in the video. With the help of data adaptive estimation techniques, targeted maximum likelihood estimation (TMLE) was applied to estimate the average risk difference between helmeted users and non-users, controlling for self-selection effects. Individual-based nonparametric bootstrap was performed to assess the uncertainty associated with the estimator. Results: Our findings suggest, on average, individuals more likely to wear a helmet are 15.6% more likely to undertake a risky overtaking maneuver. Practical Applications: This study doesn’t try to oppose mandatory helmet laws, but rather serves as a cautionary warning that road safety programs may need to consider strategies in which unintended impact of bicycle helmet use can be mitigated. Moreover, our findings also provide additional evaluation component when it comes to the cost-benefit assessment of helmet-related laws.     

Higher-order cycling skills among 11- to 13-year-old cyclists and relationships with cycling experience,risky behavior,crashes and self-assessed skill

IntroductionIn the Netherlands, young cyclists are extremely vulnerable in traffic, which may partly be due to their still underdeveloped higher-order cycling skill. So far, knowledge on their actual level of skill is lacking. Using a computerized test battery mimicking real-life risky traffic conditions, this study assessed the level of higher-order cycling skill in children 11 and 12 years of age and tested the hypothesis that these skills show caveats. Furthermore, factors potentially influencing the development and impact of these skills were studied, such as cycling experience, risky road behavior, crash involvement, and self-assessed skill.MethodA total of 335 students (49% female) completed computerized tests on hazard perception, gap acceptance, blind spot strategies, and priority decisions in traffic, and completed questionnaires on cycling experience, risky cycling behavior, crashes, and self-assessment of cycling skill.ResultsOn the hazard perception test, one-third of the participants missed at least half of the number of hazards. They made errors in about 50% of the priority decisions, accepted critical gaps when crossing the road, and conversely rejected safe gaps; only 1% of the participants identified all blind spots of a truck correctly, while 69% made unsafe decisions when interacting with trucks in traffic scenarios. Overall, in complex traffic situations performance was worse than in simple ones. The hypothesis of lack of skills was therefore accepted. However, the study failed to demonstrate consistent relationships between subtest performance and cycling experience, risky behavior, crashes, and self-assessed skill, which weakens the theoretical assumptions concerning the subtests.ConclusionsThe results suggest that children at the end of primary school are still lacking elementary skills for safe cycling, calling for measures to accelerate skill development.Practical applicationsTest batteries are essential tools for systematically monitoring skill development in cyclists, evaluating education programs, and for guiding the development of effective road safety education. The next step is the validation of such batteries.     

Effects of red light camera enforcement on fatal crashes in large U.S. cities

Objective

To estimate the effects of red light camera enforcement on per capita fatal crash rates at intersections with signal lights.

Methods

From the 99 large U.S. cities with more than 200,000 residents in 2008, 14 cities were identified with red light camera enforcement programs for all of 2004-2008 but not at any time during 1992-1996, and 48 cities were identified without camera programs during either period. Analyses compared the citywide per capita rate of fatal red light running crashes and the citywide per capita rate of all fatal crashes at signalized intersections during the two study periods, and rate changes then were compared for cities with and without cameras programs. Poisson regression was used to model crash rates as a function of red light camera enforcement, land area, and population density.

Results

The average annual rate of fatal red light running crashes declined for both study groups, but the decline was larger for cities with red light camera enforcement programs than for cities without camera programs (35% vs. 14%). The average annual rate of all fatal crashes at signalized intersections decreased by 14% for cities with camera programs and increased slightly (2%) for cities without cameras. After controlling for population density and land area, the rate of fatal red light running crashes during 2004-2008 for cities with camera programs was an estimated 24% lower than what would have been expected without cameras. The rate of all fatal crashes at signalized intersections during 2004-2008 for cities with camera programs was an estimated 17% lower than what would have been expected without cameras.

Conclusions

Red light camera enforcement programs were associated with a statistically significant reduction in the citywide rate of fatal red light running crashes and a smaller but still significant reduction in the rate of all fatal crashes at signalized intersections.

Impact on Industry

The study adds to the large body of evidence that red light camera enforcement can prevent the most serious crashes. Communities seeking to reduce crashes at intersections should consider this evidence.     

Bicyclist injury severity in traffic crashes: A spatial approach for geo-referenced crash data to uncover non-stationary correlates

Introduction: Bicyclists are among vulnerable road users with their safety a key concern. This study generates new knowledge about their safety by applying a spatial modeling approach to uncover non-stationary correlates of bicyclist injury severity in traffic crashes. Method: The approach is Geographically Weighted Ordinal Logistic Regression (GWOLR), extended from the regular Ordered Logistic Regression (OLR) by incorporating the spatial perspective of traffic crashes. The GWOLR modeling approach allows the relationships between injury severity and its contributing factors to vary across the spatial domain, to account for the spatial heterogeneity. This approach makes use of geo-referenced data. This study explored more than 7,000 geo-referenced bicycle--motor-vehicle crashes in North Carolina. Results: This study performed a series of non-stationarity tests to identify local relationships that vary substantially across the spatial domain. These local relationships are related to the bicyclist (bicyclist age, bicyclist behavior, bicyclist intoxication, bicycle direction, bicycle position), motorist (driver age, driver intoxication, driver behavior, vehicle speed, vehicle type) and traffic (traffic volume). Conclusions: Results from the regular OLR are in general consistent with previous findings. For example, an increased bicyclist injury severity is associated with older bicyclists, bicyclist being intoxicated, and higher motor-vehicle speeds. Results from the GWOLR show local (rather than global) relationships between contributing factors and bicyclist injury severity. Practical Applications: Researchers and practitioners may use GWOLR to prioritize cycling safety countermeasures for specific regions. For example, GWOLR modeling estimates in the study highlighted the west part (from Charlotte to Asheville) of North Carolina for increased bicyclist injury severity due to the intoxication of road users including both bicyclists and drivers. Therefore, if a countermeasure is concerned with the road user intoxication, there may be a priority for the region from Charlotte to Asheville (relative to other areas in North Carolina).     

An analysis of cyclists’ speed at combined pedestrian and cycle paths

Abstract

Objective: In Sweden, cyclists, pedestrians, and moped riders share the space on combined pedestrian and cycle paths, and their speeds may differ greatly. Both actual speed and speed differences can potentially influence the number of accidents on the shared paths. As a starting point, this article studies the speed component and how cyclists’ speed varies at pedestrian and cycle paths depending on the day, week, and year; road user composition; and road design.

Methods: Three data sources were used: Existing measurements of cycle speed and flow in 3 different Swedish municipalities, Eskilstuna (1 site, January–December 2015), Linköping (6 sites, 4?weeks in September–October 2015), and Stockholm (10 sites, 1–5?days in August–September 2015); complementary measurements of cycle speed and flow in Linköping (4 sites, 1–10?days in August–September 2016) and Stockholm (1 site, only part of 2?days in August 2016) were also conducted within the project, in addition to roadside observations of bicycle types at the 5 new sites.

Results: The average speed of cyclists on the paths varied between 12.5 and 26.5?km/h. As expected, the lower average speeds were found in uphill directions, near intersections, and on paths with high pedestrian flows. The higher speeds were found in downhill directions and on commuter routes. In all, 70%–95% of road users observed on pedestrian and cycle paths were cyclists, and 5%–30% were pedestrians. The most common type of bicycle was a comfort bike, followed by a trekking bike. Electric-assisted bicycles and racer bikes occurred at all sites, with proportions of 1%–10% and 1%–15%, respectively. The 2 sites with the highest proportion of electric-assisted bicycles and racer bicycles also had the highest average speeds. The differences in average speed throughout the day, week, and year could only be assessed at one of the sites. Only small differences were found, with the most noticeable being that the average speed was lower in January and February (13.8?km/h) compared to the rest of the year (15.3–16.1?km/h). The average speed was also lower during daytime (14.7?km/h) than during other parts of the day (15.4–15.8?km/h).

Conclusions: The relationship between bicycle type and measured speed was not entirely clear, but the results suggest that paths with higher proportions of electric and racer bicycles have higher average speeds. There also appears to be a connection between average speed and the width of the distribution; that is, the higher the average speed, the wider the speed distribution. More research is needed on how speed levels and speed variance affect accident risk.     

Are you an ambitious cyclist? Results of the cyclist profile questionnaire in Germany

Abstract

Objective: A number of studies have already grouped cyclists according to different aspects of their mobility behavior. This could be used e.g., to improve the bicycle infrastructure planning, to detect critical spots and, to reduce obstacles for cycling. This wide, preexisting, range of cyclist typologies usually concentrates on one or two influence factors and differs, content-wise, in both factors used, as well as, methodically. Based on existing cyclist typologies we extracted all possible influence factors to integrate them in one single questionnaire. The objective of this study, using an empirical, based approach, is to compare this typology of cyclists with existing ones, integrating all known influence factors of recent studies.

Methods: To address these issues, we conducted a Germany-wide online survey on cycling behavior, covering all relevant aspects we derived from both literature and especially, former cyclist typology studies including: social factors; the impact of environmental, individual; and route factors; as well as motives. The main goal was to identify distinct types of cyclists, and describe them as detailed as possible. The heterogeneous sample included a total of 10,294 responses.

Results: Using factor and cluster analyses, a multidimensional typology with four groups of cyclists was derived which were interpreted as: ambitious, functional, pragmatic, and passionate cyclists. In addition, socio-economic factors, cyclist’s motivation, and crash history were analyzed.

Conclusion: The results produced by grouping different characteristics of cyclists can lead to policy recommendations or communal bicycle traffic planning. Policy planners can estimate reactions of the different types on interventions and adjust their decisions which can serve to support already passionate cyclists or, encourage normally under-represented infrequent cyclists to cycle more. The extent of perceived safety plays here an important role in the classification, e.g., the handling of high-risk areas for crashes.     

Using CyclePhilly data to assess wrong-way riding of cyclists in Philadelphia

ProblemThe increasing use of smartphones and low cost GPS have provided new sources for collecting data and using them to explain travel behavior. This study aims to use data collected from a smartphone application (CyclePhilly) to explain wrong-way riding behavior of cyclists on one-way segments to help better identify the demographic and network factors influencing the wrong-way riding decision making.MethodsThe data used in this study consist of two different sources: (a) Route trips data downloaded from the CyclePhilly Website contained trips detailed up to segment level, collected from May 2014 to April 2016 (12,202 trips by 300 unique users); and (b) Open Street Maps (OSM). Using ArcGIS, we calculate detour routes for each wrong way segment. We then built a mixed logistic regression model to identify the trip and riders' characteristics affecting wrong-way riding behavior. Next, we explore the characteristics of road facilities associated with wrong-way riding behavior.Results and discussionOnly 2.7% of travel distance is wrong-way, yet 42% of trips include a wrong-way segment. Commute trips have a higher chance of wrong-way riding. The longer the trips also include more wrong-way riding. Segments with higher detour ratios (ratio of distance with a detour to the wrong-way distance) are found to be associated with more wrong-way behavior. Compared to roads with no bike lane, roads with sharrow markings and buffered bike lane discourage wrong way riding.Practical applicationsThis study proposes new methods that can be adapted to use naturalistic and probe data and analyze city-wide aberrant riders' behavior. These help planners and engineers choose between various types of bike infrastructure. Wrong-way riding is one application that can be investigated, but probe bicycle datasets provide unprecedented resolution and volume of data that will allow for more sophisticated safety and planning analyses.