Risk factors for causing road crashes involving cyclists: An application of a quasi-induced exposure method

A quasi-induced exposure approach was applied to the Spanish Register of Traffic Crashes to identify driver- and vehicle-related factors associated with the risk of causing a road crash involving a cyclist in Spain from 1993 to 2009. We analyzed 19,007 collisions between a bicycle and another vehicle in which only one of the drivers committed an infraction, and 13,540 records that included the group of non-infractor cyclists in the above collisions plus cyclists involved in single-bicycle crashes. Adjusted odds ratios were calculated for being responsible for each type of crash for each factor considered. Age from 10 to 19 years, male sex, alcohol or drug consumption and non-helmet use were cyclist-related variables associated with a higher risk of crash, whereas cycling more than 1 h increased only the risk of single crashes. Bicycles with brake defects and ridden by two occupants were also at higher risk of involvement in a crash, whereas light defects were associated only with collisions with another vehicle. For drivers of the other vehicle, age more than 60 years, alcohol, not using safety devices and nonprofessional drivers were at higher risk. The risk of colliding with a bicycle was higher for mopeds than for passenger cars.     

Bicycle crash casualties in a highly motorized city

The characteristics of bicycle crashes in cities where bicycles are a minor transport mode have received little attention in road safety research. However, the characteristics of these injury-inflicting bicycle crashes are expected to be very different from those happening in cities where cycling is generally considered as one of the major transport modes. Specifically, this study has the following three objectives: (1) to conduct the first scientific spatial analysis of bicycle crashes in Hong Kong; (2) to analyze the circumstances leading to bicycle crashes; and (3) to conduct an epidemiological study on injury patterns of cyclist casualties. Various spatial and statistical tools, including buffer analysis, chi-square tests, analysis-of-variance and binary logistic regression, are used to analyze the bicycle crashes in Hong Kong from 2005-2007. An important finding of this paper is that the bicycle safety problem has a clear spatial dimension. The crash circumstances in different parts of the city differed systematically. Furthermore, the findings suggest that initiatives to develop new cycle tracks and to encourage bicycles as a transport mode must be planned carefully with new infrastructure and policies to ensure the safety of cyclists.     

Risk factors for severe injury in cyclists involved in traffic crashes in Victoria,Australia

This study examines the impact of cyclist, road and crash characteristics on the injury severity of cyclists involved in traffic crashes reported to the police in Victoria, Australia between 2004 and 2008. Logistic regression analysis was carried out to identify predictors of severe injury (serious injury and fatality) in cyclist crashes reported to the police. There were 6432 cyclist crashes reported to the police in Victoria between 2004 and 2008 with 2181 (33.9%) resulting in severe injury of the cyclist involved. The multivariate analysis found that factors that increase the risk of severe injury in cyclists involved in traffic crashes were age (50 years and older), not wearing a helmet, riding in the dark on unlit roads, riding on roads zoned 70 km/h or above, on curved sections of the road, in rural locations and being involved in head-on collisions as well as off path crashes, which include losing control of vehicle, and on path crashes which include striking the door of a parked vehicle. While this study did not test effectiveness of preventative measures, policy makers should consider implementation of programs that address these risk factors including helmet programs and environmental modifications such as speed reduction on roads that are frequented by cyclists.     

On-road bicycle facilities and bicycle crashes in Iowa, 2007–2010

Purpose

An average of 611 deaths and over 47,000 bicyclists are injured in traffic-related crashes in the United States each year. Efforts to increase bicycle safety are needed to reduce and prevent injuries and fatalities, especially as trends indicate that ridership is increasing rapidly. The objective of this study was to evaluate the effect of bicycle-specific roadway facilities (e.g., signage and bicycle lanes) in reducing bicycle crashes.

Methods

We conducted a case site-control site study of 147 bicycle crash-sites identified from the Iowa Department of Transportation crash database from 2007 to 2010 and 147 matched non-crash sites. Control sites were randomly selected from intersections matched to case sites on neighborhood (census block group) and road classification (arterial, feeder, collector, etc.). We examined crash risk by any on-road bicycle facility present and by facility type (pavement markings--bicycle lanes and shared lane arrows, bicycle-specific signage, and the combination of markings and signage), controlling for bicycle volume, motor vehicle volume, street width, sidewalks, and traffic controls.

Results

A total of 11.6% of case sites and 15.0% of controls had an on-road bicycle facility. Case intersections had higher bicycle volume (3.52 vs. 3.34 per 30 min) and motor vehicle volume (248.77 vs. 205.76 per 30 min) than controls. Our results are suggestive that the presence of an on-road bicycle facility decreases crash risk by as much as 60% with a bicycle lane or shared lane arrow (OR = 0.40, 95% CI = 0.09–1.82) and 38% with bicycle-specific signage (OR = 0.62, 95% CI = 0.15–2.58).

Conclusions

Investments in bicycle-specific pavement markings and signage have been shown to be beneficial to traffic flow, and our results suggest that they may also reduce the number of bicycle-motor vehicle crashes and subsequent injuries and fatalities. As a relatively low-cost traffic feature, community considerations for further implementation of these facilities are justified.     

Cyclist safety on bicycle boulevards and parallel arterial routes in Berkeley,California

This study compares the safety of bicyclists riding on bicycle boulevards to those riding on parallel arterial routes in Berkeley, California. Literature on the impact of motor vehicle traffic characteristics on cyclist safety shows that high motor vehicle speeds and volumes and the presence of heavy vehicles are all detrimental to cyclist safety. This suggests that cyclists may be safer on side streets than on busy arterials. Bicycle boulevards—traffic-calmed side streets signed and improved for cyclist use—purport to offer cyclists a safer alternative to riding on arterials. Police-reported bicycle collision data and manually collected cyclist count data from bicycle boulevards and parallel arterial routes in Berkeley, California from 2003 to 2010 are used to test the hypothesis that Berkeley's bicycle boulevards have lower cyclist collision rates and a lower proportion of bicycle collisions resulting in severe injury. While no significant difference is found in the proportion of collisions that are severe, results show that collision rates on Berkeley's bicycle boulevards are two to eight times lower than those on parallel, adjacent arterial routes. The difference in collision rate is highly statistically significant, unlikely to be caused by any bias in the collision and count data, and cannot be easily explained away by self-selection or safety in numbers. Though the used dataset is limited and the study design is correlational, this study provides some evidence that Berkeley's bicycle boulevards are safer for cyclists than its parallel arterial routes. The results may be suggestive that, more generally, properly implemented bicycle boulevards can provide cyclists with a safer alternative to riding on arterials.     

Built environment effects on cyclist injury severity in automobile-involved bicycle crashes

This analysis uses a generalized ordered logit model and a generalized additive model to estimate the effects of built environment factors on cyclist injury severity in automobile-involved bicycle crashes, as well as to accommodate possible spatial dependence among crash locations. The sample is drawn from the Seattle Department of Transportation bicycle collision profiles. This study classifies the cyclist injury types as property damage only, possible injury, evident injury, and severe injury or fatality. Our modeling outcomes show that: (1) injury severity is negatively associated with employment density; (2) severe injury or fatality is negatively associated with land use mixture; (3) lower likelihood of injuries is observed for bicyclists wearing reflective clothing; (4) improving street lighting can decrease the likelihood of cyclist injuries; (5) posted speed limit is positively associated with the probability of evident injury and severe injury or fatality; (6) older cyclists appear to be more vulnerable to severe injury or fatality; and (7) cyclists are more likely to be severely injured when large vehicles are involved in crashes. One implication drawn from this study is that cities should increase land use mixture and development density, optimally lower posted speed limits on streets with both bikes and motor vehicles, and improve street lighting to promote bicycle safety. In addition, cyclists should be encouraged to wear reflective clothing.     

The safety of electrically assisted bicycles compared to classic bicycles

Use of electrically assisted bicycles with a maximum speed of 25 km/h is rapidly increasing. This growth has been particularly rapid in the Netherlands, yet very little research has been conducted to assess the road safety implications. This case–control study compares the likelihood of crashes for which treatment at an emergency department is needed and injury consequences for electric bicycles to classic bicycles in the Netherlands among users of 16 years and older. Data were gathered through a survey of victims treated at emergency departments. Additionally, a survey of cyclists without any known crash experience, drawn from a panel of the Dutch population acted as a control sample. Logistic regression analysis is used to compare the risk of crashes with electric and classical bicycles requiring treatment at an emergency department. Among the victims treated at an emergency department we compared those being hospitalized to those being send home after the treatment at the emergency department to compare the injury consequences between electric and classical bicycle victims. The results suggest that, after controlling for age, gender and amount of bicycle use, electric bicycle users are more likely to be involved in a crash that requires treatment at an emergency department due to a crash. Crashes with electric bicycles are about equally severe as crashes with classic bicycles. We advise further research to develop policies to minimize the risk and maximize the health benefits for users of electric bicycles.     

Road factors and bicycle-motor vehicle crashes at unsignalized priority intersections

In this study, the safety of cyclists at unsignalized priority intersections within built-up areas is investigated. The study focuses on the link between the characteristics of priority intersection design and bicycle–motor vehicle (BMV) crashes. Across 540 intersections that are involved in the study, the police recorded 339 failure-to-yield crashes with cyclists in four years. These BMV crashes are classified into two types based on the movements of the involved motorists and cyclists:

• • 

  type I: through bicycle related collisions where the cyclist has right of way (i.e. bicycle on the priority road);

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  type II: through motor vehicle related collisions where the motorist has right of way (i.e. motorist on the priority road).

The probability of each crash type was related to its relative flows and to independent variables using negative binomial regression. The results show that more type I crashes occur at intersections with two-way bicycle tracks, well marked, and reddish coloured bicycle crossings. Type I crashes are negatively related to the presence of raised bicycle crossings (e.g. on a speed hump) and other speed reducing measures. The accident probability is also decreased at intersections where the cycle track approaches are deflected between 2 and 5 m away from the main carriageway. No significant relationships are found between type II crashes and road factors such as the presence of a raised median.     

Incidence, severity and correlates of bicycling injuries in a sample of cyclists in Queensland, Australia

Bicycle injuries, particularly those resulting from single bicycle crashes, are underreported in both police and hospital records. Data on cyclist characteristics and crash circumstances are also often lacking. As a result, the ability to develop comprehensive injury prevention policies is hampered. The aim of this study was to examine the incidence, severity, cyclist characteristics, and crash circumstances associated with cycling injuries in a sample of cyclists in Queensland, Australia. A cross-sectional study of Queensland cyclists was conducted in 2009. Respondents (n = 2056) completed an online survey about their cycling experiences, including cycling injuries. Logistic regression modelling was used to examine the associations between demographic and cycling behaviour variables with experiencing cycling injuries in the past year, and, separately, with serious cycling injuries requiring a trip to a hospital. Twenty-seven percent of respondents (n = 545) reported injuries, and 6% (n = 114) reported serious injuries. In multivariable modelling, reporting an injury was more likely for respondents who had cycled <5 years, compared to ≥10 years (p < 0.005); cycled for competition (p = 0.01); or experienced harassment from motor vehicle occupants (p < 0.001). There were no gender differences in injury incidence, and respondents who cycled for transport did not have an increased risk of injury. Reporting a serious injury was more likely for those whose injury involved other road users (p < 0.03). Along with environmental and behavioural approaches for reducing collisions and near-collisions with motor vehicles, interventions that improve the design and maintenance of cycling infrastructure, increase cyclists’ skills, and encourage safe cycling behaviours and bicycle maintenance will also be important for reducing the overall incidence of cycling injuries.     

Selecting exposure measures in crash rate prediction for two-lane highway segments

A critical part of any risk assessment is identifying how to represent exposure to the risk involved. Recent research shows that the relationship between crash count and traffic volume is non-linear; consequently, a simple crash rate computed as the ratio of crash count to volume is not proper for comparing the safety of sites with different traffic volumes. To solve this problem, we describe a new approach for relating traffic volume and crash incidence. Specifically, we disaggregate crashes into four types: (1) single-vehicle, (2) multi-vehicle same direction, (3) multi-vehicle opposite direction, and (4) multi-vehicle intersecting, and define candidate exposure measures for each that we hypothesize will be linear with respect to each crash type. This paper describes initial investigation using crash and physical characteristics data for highway segments in Michigan from the Highway Safety Information System (HSIS). We use zero-inflated-Poisson (ZIP) modeling to estimate models for predicting counts for each of the above crash types as a function of the daily volume, segment length, speed limit and roadway width. We found that the relationship between crashes and the daily volume (AADT) is non-linear and varies by crash type, and is significantly different from the relationship between crashes and segment length for all crash types. Our research will provide information to improve accuracy of crash predictions and, thus, facilitate more meaningful comparison of the safety record of seemingly similar highway locations.     

How similar are two-unit bicycle and motorcycle crashes?

This paper explores the similarities and differences between bicycle and motorcycle crashes with other motor vehicles. If similar treatments can be effective for both bicycle and motorcycle crashes, then greater benefits in terms of crash costs saved may be possible for the same investment in treatments. To reduce the biases associated with under-reporting of these crashes to police, property damage and minor injury crashes were excluded. The most common crash type for both bicycles (31.1%) and motorcycles (24.5%) was intersection from adjacent approaches. Drivers of other vehicles were coded most at fault in the majority of two-unit bicycle (57.0%) and motorcycle crashes (62.7%). The crash types, patterns of fault and factors affecting fault were generally similar for bicycle and motorcycle crashes. This confirms the need to combat the factors contributing to failure of other drivers to yield right of way to two-wheelers, and suggest that some of these actions should prove beneficial to the safety of both motorized and non-motorized two-wheelers. In contrast, child bicyclists were more often at fault, particularly in crashes involving a vehicle leaving the driveway or footpath. The greater reporting of violations by riders and drivers in motorcycle crashes also deserves further investigation.     

Characteristics of bicycle crashes in an adolescent population in Flanders (Belgium)

IntroductionIn regions where transportation is mainly motorized, air pollution and traffic congestion are rife. Active transportation such as cycling might be a solution but safety is a major concern. An efficient science based safety policy is needed. The aim of this paper is to analyze in depth the bicycle crash causes and characteristics in an adolescent population (14–18 yr).MethodsBy using questionnaires for self-reported bicycle crashes, bicycle crash data were collected from insurance companies (January 2014–June 2015) and from schools (November 2013–March 2014). Six bicycle crash causes were predefined and possible differences between schools and insurance companies were analyzed.ResultsEighty-six school and 78 insurance registered crashes were analyzed. “Distraction of the cyclist” and “third party crossing a bicycle path failing to see the cyclist” are the main causes of bicycle crashes (both 29%). Bad (maintained) infrastructure accounted for 21% of the crash causes. Bicycle crashes reported at insurance companies needed significantly more medical attention and led to high absenteeism (57% at least one day of absenteeism). Only 21% of the bicycle crashes reported at insurance companies were also reported in the official police database.ConclusionThe human factor was the main cause accounting for 79% of the crashes. Bicycle crashes involving a car accounted for 42% and single bicycle crashes accounted for 31% of the total number of crashes. From the bicycle crashes registered at insurance companies 21% was also registered in official police statistics. A combination of information, education and changing the bicycle specific environment might reduce the consequences of human errors more efficiently.     

Is the three-foot bicycle passing law working in Baltimore,Maryland?

Maryland (MD) recently became one of fourteen states in the United States to enact a traffic law requiring motor vehicles to pass bicyclists at a distance of greater than three feet. To our knowledge, motorist compliance with the law has never been assessed. This study measured the distance between overtaking motor vehicles and cyclists [e.g. vehicle passing distance (VPD)], to develop baseline metrics for tracking implementation of the three-foot passing law in Baltimore, MD and to assess risk factors for dangerous passes. During September and October 2011, cyclists (n = 5) measured VPD using a previously published video technique ( Parkin and Meyers, 2010). Cyclists logged a total of 10.8 h of video footage and 586 vehicle passes on 34 bicycle commuting trips. The average trip lasted 19.5 ± 4.9 min and cyclists were passed on average 17.2 ± 11.8 times per trip. VPDs of three feet or less were common when cycling in standard lanes (17%; 78 of 451 passes) and lanes with a shared lane marking (e.g. sharrows) (23%; 11 of 47 passes). No passes of three feet or less occurred in bicycle lanes (0 of 88 passes). A multiple linear regression model was created, which explained 26% of the variability in VPD. Significant model variables were lane width, bicycle infrastructure, cyclist identity, and street identity. Interventions, such as driver education, signage, enforcement, and bicycle infrastructure changes are needed to influence driving behavior in Baltimore to increase motorist compliance with the three-foot law.     

Explaining two-lane highway crash rates using land use and hourly exposure

This paper describes the estimation of Poisson regression models for predicting both single and multi-vehicle highway crash rates as a function of traffic density and land use, as well as ambient light conditions and time of day. The study focuses on seventeen rural, two-lane highway segments, each one-half mile in length with varying land use patterns and where actual hourly exposure values are available in the form of observed traffic counts. Land-use effects are represented by the number of driveways of various types on each segment. Hourly exposure is represented for single-vehicle crashes as the total vehicle miles traveled and volume/capacity ratio; for multi-vehicle crashes it is the product of the hourly volumes on the main highway and the roads intersecting it along the study segment. For single-vehicle crashes, the following variables were found to be significant, with a positive or negative effect as noted: daytime (06:00–19:00 h, negative effect), the natural log of the segment volume/capacity ratio (negative), percent of the segment with no passing zones (positive), shoulder width (positive), number of intersections (negative), and driveways (mixed effects by type). Good multi-vehicle crash prediction models had quite different variables: daylight conditions from 10:00–15:00 and 15:00–19:00 h (positive), number of intersections (negative), and driveways (positive for all types). The results show that traffic intensity explains differences in crash rates even when controlling for time of day and light conditions, and that these effects are quite different for single and multi-vehicle crashes. Suggestions for future research are also given.     

Toronto bicycle commuter safety rates

This analysis uses data from a survey of Toronto commuter cyclists that collected information regarding accident history as well as regular commute route to work or school. By relating the route information of the 1196 respondents to facility attributes in a Geographic Information System (GIS), defensible estimates of travel exposure on roads, off-road paths and sidewalks were developed. The rate of collision on off-road paths and sidewalks was lower than for roads. The relative rates for falls and injuries suggest these events are least common on-road followed by off-road paths, and finally most common on sidewalks. The rate of major injuries, an injury that required medical attention, was greatest on sidewalks and the difference between paths and sidewalks was negligible. These rates suggest a need for detailed analysis of sidewalk and off-road path bicycle safety. The absolute event rates per bicycle kilometer were found to be between 26 and 68 times higher than similar rates for automobile travel, re-confirming the urgent bicycle safety crisis. Examination of rates for sub-groups of cyclists suggest that experience is an important factor in bicycle safety. The same survey conducted in Ottawa, Canada found event rates much lower than Toronto. This result may confirm urban form, traffic levels and attitude do affect bicycle safety. The analysis also demonstrates a successful method to quantify bicycle travel exposure information and should be considered for further use as complement to other existing techniques.     

Bayesian estimation of hourly exposure functions by crash type and time of day

The study describes an investigation of the relationship between crash occurrence and hourly volume counts for small samples of highway segments from two states: Michigan and Connecticut. We used a hierarchical Bayesian framework to fit binary regression models for predicting crash occurrence for each of four crash types: (1) single-vehicle, (2) multi-vehicle same direction, (3) multi-vehicle opposite direction, and (4) multi-vehicle intersecting direction, as a function of the hourly volume, segment length, speed limit and pavement width. The results reveal how the relationship between crashes and hourly volume varies by time of day, thus improving the accuracy of crash occurrence predictions. The results show that even accounting for time of day, the disaggregate exposure measure – hourly volume – is indeed non-linear for each of the four crash types. This implies that at any time of day, the crash occurrence is not proportional to the hourly volume. These findings help us to further understand the relationship between crash occurrence and hourly volume, segment length and other risk factors, and facilitate more meaningful comparisons of the safety record of seemingly similar highway locations.     

A simple method for identifying and correcting crash problems on urban arterial streets

Urban arterials by their nature carry heavy traffic volumes and generate large numbers of motor vehicle crashes. The present study involved review of police crash reports to identify precrash events and driver actions for a sample of crashes on urban arterials and describes a method for reducing such crashes based on analyses of collision patterns and identification of locations with excessive numbers of crashes of a particular type. Police-reported crash data were obtained for three urban arterials in the Washington, DC metropolitan area. A total of 2013 crash reports were analyzed. Seven crash types accounted for nearly 90% of these reports. On each arterial studied, several locations with excessive numbers of crashes of a particular type were identified, and corresponding engineering countermeasures were recommended. Differences between the approach employed in this study and traditional blackspot analyses are discussed.     

Road environment, crash type and hospitalisation of bicyclists and motorcyclists presented to emergency departments in Western Australia

Emergency presentations by bicyclists and motorcyclists are often the result from a fall or non-motor vehicle collision that occurred in off-road locations. Consequently, they are unlikely to be captured by police records. If the injury is not severe enough to warrant hospitalisation, they will also not be captured by the hospital admission system. To ascertain the nature and type of these crash events, a 6-month prospective study was undertaken of bicyclists and motorcyclists who presented to emergency departments in Perth, Western Australia, due to involvement in a crash or non-motor vehicle collision. Of the 330 eligible presentations, 151 bicyclists and 104 motorcyclists agreed to participate in a structured interview, representing a response rate of 77.3%. Among them, 120 (79%) bicyclists and 71 (68%) motorcyclists had a fall or non-motor vehicle collision, and many of the crashes (88 (58%) and 47 (45%), respectively) occurred off-road. Moreover, 26.5% of bicyclist and 62.5% of motorcyclist presentations led to hospital admissions. Multivariate logistic regression analysis further showed that the crash location and road type affected hospitalisation for both groups. Although, crashes occurring in rural areas contributed 14% of the events overall, their adjusted risk of hospitalisation increased five times when compared to metropolitan locations. Crash preventive measures targeting rural areas should be considered to further improve the safety of bicyclists and motorcyclists.     

Macroscopic modeling of pedestrian and bicycle crashes: A cross-comparison of estimation methods

The paper presents a cross-comparison of different estimation methods to model pedestrian and bicycle crashes. The study contributes to macro level safety studies by providing further methodological and empirical evidence on the various factors that influence the frequency of pedestrian and bicycle crashes at the planning level. Random parameter negative binomial (RPNB) models are estimated to explore the effects of various planning factors associated with total, serious injury and minor injury crashes while accounting for unobserved heterogeneity. Results of the RPNB models were compared with the results of a non-spatial negative binomial (NB) model and a Poisson-Gamma-CAR model. Key findings are, (1) the RPNB model performed best with the lowest mean absolute deviation, mean squared predicted error and Akaiki information criterion measures and (2) signs of estimated parameters are consistent if these variables are significant in models with the same response variables. We found that vehicle kilometers traveled (VKT), population, percentage of commuters cycling or walking to work, and percentage of households without motor vehicles have a significant and positive correlation with the number of pedestrian and bicycle crashes. Mixed land use is also found to have a positive association with the number of pedestrian and bicycle crashes. Results have planning and policy implications aimed at encouraging the use of sustainable modes of transportation while ensuring the safety of pedestrians and cyclist.     

Contribution of exposure,risk of crash and fatality to explain age- and sex-related differences in traffic-related cyclist mortality rates

This study was designed to quantify the percent contribution of exposure, risk of collision and fatality rate to the association of age and sex with the mortality rates among cyclists in Spain, and to track the changes in these contributions with time. Data were analyzed for 50,042 cyclists involved in road crashes in Spain from 1993 to 2011, and also for a subset of 13,119 non-infractor cyclists involved in collisions with a vehicle whose driver committed an infraction (used as a proxy sample of all cyclists on the road). We used decomposition and quasi-induced exposure methods to obtain the percent contributions of these three components to the mortality rate ratios for each age and sex group compared to males aged 25–34 years. Death rates increased with age, and the main component of this increase was fatality (around 70%). Among younger cyclists, however, the main component of increased death rates was risk of a collision. Males had higher death rates than females in every age group: this rate increased from 6.4 in the 5–14 year old group to 18.8 in the 65–79 year old group. Exposure, the main component of this increase, ranged between 70% and 90% in all age categories, although the fatality component also contributed to this increase. The contributions of exposure, risk of crash and fatality to cyclist death rates were strongly associated with age and sex. Young male cyclists were a high-risk group because all three components tended to increase their mortality rate.