Bicycling crash characteristics: An in-depth crash investigation study

The aim of this study was to describe the crash characteristics and patient outcomes of a sample of patients admitted to hospital following bicycle crashes. Injured cyclists were recruited from the two major trauma services for the state of Victoria, Australia. Enrolled cyclists completed a structured interview, and injury details and patient outcomes were extracted from the Victorian State Trauma Registry (VSTR) and the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR). 186 cyclists consented to participate in the study. Crashes commonly occurred during daylight hours and in clear weather conditions. Two-thirds of crashes occurred on-road (69%) and were a combination of single cyclist-only events (56%) and multi-vehicle crashes (44%). Of the multi-vehicle crashes, a motor vehicle was the most common impact partner (72%) and distinct pre-crash directional interactions were observed between the cyclist and motor vehicle. Nearly a quarter of on-road crashes occurred when the cyclist was in a marked bicycle lane. Of the 31% of crashes that were not on-road, 28 (15%) occurred on bicycle paths and 29 (16%) occurred in other locations. Crashes on bicycle paths commonly occurred on shared bicycle and pedestrian paths (83%) and did not involve another person or vehicle. Other crash locations included mountain bike trails (39%), BMX parks (21%) and footpaths (18%). While differences in impact partners and crash characteristics were observed between crashes occurring on-road, on bicycle paths and in other locations, injury patterns and severity were similar. Most cyclists had returned to work at 6 months post-injury, however only a third of participants reported a complete functional recovery. Further research is required to develop targeted countermeasures to address the risk factors identified in this study.     

An epidemiological study of the risk of cycling in the dark: The role of visual perception,conspicuity and alcohol use

To curtail the rising numbers of cyclists seriously injured in road crashes, more insights are needed into the factors that contribute to these crashes. For instance, darkness is known to be associated with higher injury rates, but little is known about the relative influence of factors such as poor conspicuity, impaired perception and alcohol use among cyclists. To examine these factors, the present study analyzed the epidemiological crash data for three meteorological light conditions: daylight, late evening darkness and early morning darkness; for two crash types: crashes with (M-crashes) and without motorized traffic (NM-crashes); and for different age groups. The relative injury rates (injury risk per distance travelled in darkness corrected for daylight injury risks for each age group) confirmed findings from earlier studies that cycling in late evening darkness is associated with higher injury rates than cycling in daylight conditions. This is the case for both crash types with only small differences between the age groups suggesting that poor conspicuity (M-crashes) and impaired perception (NM-crashes) may play a role. In comparison to late evening darkness, relative injury rates in early morning darkness are much higher. This is the case for both crash types with large differences among the age groups, suggesting that in addition to the absence of daylight also age related risk factors are at play. Support for this hypothesis was found from the analyses of hospital records, showing that the proportion of seriously injured cyclists who have been drinking is highest in early morning darkness and has strongly increased over the last decades. These insights provide input for the selection of countermeasures such as improved lighting (both street and bicycle lights) and interventions targeting alcohol use among cyclists.     

Modeling motor vehicle crashes for street racers using zero-inflated models

Motor vehicle crashes are a leading cause of death for young people in the United States. Assessing which drivers are at a high risk of experiencing a crash is important for the implementation of traffic regulations. Illegal street racing has been associated with a high rate of motor vehicle crashes. In this study, we link Utah statewide driver license citations and motor vehicle crash data to evaluate the rate of crashes for drivers with street racing citations relative to other drivers. Using a zero-inflated negative binomial model we found that drivers with no citations are approximately three times more likely to be at zero risk of a crash compared to drivers with street racing citations. Moreover, among drivers at non-negligible risk of crash, cited street racers are more likely to be involved in a crash compared to drivers without citations or those cited for violations other than street racing. However, drivers with increased numbers of non-street-racing citations experience crash risks approaching those of the cited street racers.     

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.     

Fatality risk in motorcycle collisions with roadside objects in the United States

Motorcycle crashes with roadside objects often involve more than one impact event: typically involving a collision with the ground and another object. The objective of this study was to determine the fatality risk in these roadside object collisions when compared with crashes only involving a collision with the ground. The roadside objects analyzed included guardrails, concrete barriers, signs, utility poles, and trees. The Fatality Analysis Reporting System (FARS) database was used in conjunction with the General Estimates System (GES) to analyze fatality risk for motorcycle crashes from 2004 to 2008. The analysis was based upon over 3600 fatal motorcycle crashes with roadside objects. Collisions with roadside objects were found to have a higher fatality risk than collisions with either the ground or another motor vehicle. Based on the most harmful event reported in the crash, motorcycle collisions with guardrail were 7 times more likely to be fatal than collisions with the ground, and collisions with trees were almost 15 times more likely to be fatal than collisions with the ground. Additionally, the roadside object was reported as the most harmful event in the majority of the crashes in fatal two-event crashes involving a roadside object and a collision with the ground, with the exception of collisions with signage. From these analyses it was concluded that collisions with fixed objects are more harmful to motorcyclists than collisions with the ground.     

Drugs related to motor vehicle crashes in northern European countries: a study of fatally injured drivers

The aim of this study was to find which drugs and drug combinations were most common in drivers who died, in particular, in single vehicle crashes where the responsibility for the crash would be referred to the driver killed. The study included all available blood samples from drivers, who died within 24 h of the accident, in the years 2001 and 2002 in the five Nordic countries (total population about 24 million inhabitants). The samples were analysed for more than 200 different drugs in addition to alcohol, using a similar analytical programme and cut-off limits in all countries. In three countries (Finland, Norway and Sweden) blood samples were available for more than 70% of the drivers, allowing representative prevalence data to be collected. 60% of the drivers in single vehicle crashes had alcohol and/or drug in their blood samples, compared with 30% of drivers killed in collisions with other vehicles. In single vehicle accidents, 66% of the drivers under 30 years of age had alcohol and/or drugs in their blood (alcohol only – 40%; drugs only – 12%; alcohol and drugs – 14%). The drugs found were mostly illicit drugs and psychoactive medicinal drugs with warning labels (in 57% and 58% respectively of the drivers under 30 with drugs present). Similar findings were obtained for drivers 30–49 years of age (63% with alcohol and/or drugs). In drivers aged 50 years and above, killed in single vehicle crashes (48% with alcohol and/or drugs) illicit drugs were found in only one case, and psychoactive medicinal drugs were detected less frequently than in younger age groups. In 75% of single vehicle crashes, the driver was under 50 years. Thus, the majority of accidents where the drivers must be considered responsible, occurred with drivers who had recently used alcohol, or drugs, alone or in combination. The drugs involved were often illicit and/or psychoactive drugs with warning labels. Therefore a large proportion of single vehicle accidents appear to be preventable, if more effective measures against driving after intake of alcohol and drugs can be implemented.     

Drugs related to motor vehicle crashes in northern European countries: A study of fatally injured drivers

The aim of this study was to find which drugs and drug combinations were most common in drivers who died, in particular, in single vehicle crashes where the responsibility for the crash would be referred to the driver killed. The study included all available blood samples from drivers, who died within 24 h of the accident, in the years 2001 and 2002 in the five Nordic countries (total population about 24 million inhabitants). The samples were analysed for more than 200 different drugs in addition to alcohol, using a similar analytical programme and cut-off limits in all countries. In three countries (Finland, Norway and Sweden) blood samples were available for more than 70% of the drivers, allowing representative prevalence data to be collected. 60% of the drivers in single vehicle crashes had alcohol and/or drug in their blood samples, compared with 30% of drivers killed in collisions with other vehicles. In single vehicle accidents, 66% of the drivers under 30 years of age had alcohol and/or drugs in their blood (alcohol only – 40%; drugs only – 12%; alcohol and drugs – 14%). The drugs found were mostly illicit drugs and psychoactive medicinal drugs with warning labels (in 57% and 58% respectively of the drivers under 30 with drugs present). Similar findings were obtained for drivers 30–49 years of age (63% with alcohol and/or drugs). In drivers aged 50 years and above, killed in single vehicle crashes (48% with alcohol and/or drugs) illicit drugs were found in only one case, and psychoactive medicinal drugs were detected less frequently than in younger age groups. In 75% of single vehicle crashes, the driver was under 50 years. Thus, the majority of accidents where the drivers must be considered responsible, occurred with drivers who had recently used alcohol, or drugs, alone or in combination. The drugs involved were often illicit and/or psychoactive drugs with warning labels. Therefore a large proportion of single vehicle accidents appear to be preventable, if more effective measures against driving after intake of alcohol and drugs can be implemented.     

Age and gender patterns in motor vehicle crash injuries: importance of type of crash and occupant role

To evaluate the interaction of gender, age, type of crash, and occupant role in motor vehicle crash injuries leading to hospitalization, we analyzed 1997 Wisconsin hospital discharge data for patients with primary E-code diagnoses of motor vehicle injuries. The overall ratio of males to females (M/F ratio) hospitalized for motor vehicle crash injuries was 1.33 (95% confidence interval (CI): 1.26-1.41). The M/F ratio varied by type of crash and differed for passengers and drivers. For injuries sustained in collisions between vehicles, the M/F ratio was 0.96 (95% CI: 0.87-1.05); in loss of control accidents the M/F ratio was 1.95 (95% CI: 1.76-2.17). Within each type of crash, the M/F ratio for drivers was similar to that for the entire type; the M/F ratio for passengers was about half of the type total. Expressed as rates of hospitalization per 100,000 people in the general population, hospitalizations of drivers in collisions with another motor vehicle increased steeply in males, but not in females, beginning at about age 70. For drivers in loss of control crashes, male rates exceeded female rates in all age groups, with peaks in the groups 15-24 and 85-89. For passengers, injury rates from collisions with other motor vehicles were greater for females, especially in the elderly, and injury rates from loss of control crashes were similar for both genders, with peaks at 15-24 and 85-94. The higher fatality of men in loss of control motor vehicle crashes, compared to women, suggests an important area for further investigation.     

The effects of age,gender, and crash types on drivers’ injury-related health care costs

There are many studies that evaluate the effects of age, gender, and crash types on crash related injury severity. However, few studies investigate the effects of those crash factors on the crash related health care costs for drivers that are transported to hospital. The purpose of this study is to examine the relationships between drivers’ age, gender, and the crash types, as well as other crash characteristics (e.g., not wearing a seatbelt, weather condition, and fatigued driving), on the crash related health care costs. The South Carolina Crash Outcome Data Evaluation System (SC CODES) from 2005 to 2007 was used to construct six separate hierarchical linear regression models based on drivers’ age and gender. The results suggest that older drivers have higher health care costs than younger drivers and male drivers tend to have higher health care costs than female drivers in the same age group. Overall, single vehicle crashes had the highest health care costs for all drivers. For males older than 64-years old sideswipe crashes are as costly as single vehicle crashes. In general, not wearing a seatbelt, airbag deployment, and speeding were found to be associated with higher health care costs. Distraction-related crashes are more likely to be associated with lower health care costs in most cases. Furthermore this study highlights the value of considering drivers in subgroups, as some factors have different effects on health care costs in different driver groups. Developing an understanding of longer term outcomes of crashes and their characteristics can lead to improvements in vehicle technology, educational materials, and interventions to reduce crash-related health care costs.     

The effect of distractions on the crash types of teenage drivers

Teenage drivers are overrepresented in crashes when compared to middle-aged drivers. Driver distraction is becoming a greater concern among this group as in-vehicle devices, opportunities for distractions, and teenage drivers' willingness to engage in these activities increase. The objective of this study was to determine how different distraction factors impact the crash types that are common among teenage drivers. A multinomial logit model was developed to predict the likelihood that a driver will be involved in one of three common crash types: an angular collision with a moving vehicle, a rear-end collision with a moving lead vehicle, and a collision with a fixed object. These crashes were evaluated in terms of four driver distraction categories: cognitive, cell phone related, in-vehicle, and passenger-related distractions. Different driver distractions have varying effects on teenage drivers' crash involvement. Teenage drivers that were distracted at an intersection by passengers or cognitively were more likely to be involved in rear-end and angular collisions when compared to fixed-object collisions. In-vehicle distractions resulted in a greater likelihood of a collision with a fixed object when compared to angular collisions. Cell phone distractions resulted in a higher likelihood of rear-end collision. The results from this study need to be evaluated with caution due to the limited number of distraction related cases available in the U.S. GES crash database. Implications for identifying and improving the reporting of driver distraction related factors are therefore discussed.     

The prevalence of alcohol, cannabinoids, benzodiazepines and stimulants amongst injured drivers and their role in driver culpability: part ii: the relationship between drug prevalence and drug concentration, and driver culpability

Blood samples from 2,500 injured drivers were analysed for alcohol, cannabinoids (measured by the presence of THC), benzodiazepines and stimulants. The relationship between the prevalence and concentration of drugs and the culpability of the driver was examined using an objective method for assessing culpability. There were no significant differences between males and females with respect to culpability. However, there was a relationship between age and culpability: drivers under 26 years and over 60 years were more likely to be culpable. Drivers who tested positive for alcohol only, benzodiazepines only and the combinations of alcohol and THC and alcohol and benzodiazepines were significantly more likely to be culpable for the crash compared with the drug-free group. Conversely, a lower percentage of drivers who only tested positive for THC were culpable for the crash compared with drug-free drivers. This difference was not statistically significant. For car drivers in single-vehicle crashes, the majority of drivers were judged culpable irrespective of drug use. In multiple-vehicle crashes, car drivers testing positive for alcohol only or benzodiazepines only were more likely to be culpable for the crash compared with drug-free drivers. For motorcycle riders in both single- and multiple-vehicle crashes, there were no significant differences between the drug-positive and drug-free groups. A higher percentage of drug-free riders in multiple-vehicle crashes were culpable compared with riders who only tested positive for THC, but this difference was not statistically significant. There was a significant concentration-dependent relationship between alcohol and culpability: as blood alcohol concentration increased, so did the percentage of culpable drivers. When THC was used alone, there was no significant increase in culpability. For those drivers with benzodiazepines at therapeutic concentrations and above, there was a significant increase in culpability. The relationship between stimulants and culpability was not significant, although a higher proportion of stimulant-positive drivers were culpable compared with drug-free drivers. The combinations of alcohol and THC, and alcohol and benzodiazepines also produced a significant increase in culpability, but this increase was not significantly greater than that produced by alcohol alone.     

Drug and alcohol use among drivers admitted to a Level-1 trauma center

The purpose of this research was to determine the incidence and prevalence of drug use, alcohol use, and the combination of drug and alcohol use among motor vehicle crash (MVC) victims admitted to a Level-1 trauma center. In a 90-day study, nearly two-thirds of trauma center admissions were victims of motor vehicle crashes. Blood and urine was collected from 168 MVC victims of whom 108 were identified as the driver in the crash. Toxicology results indicated that 65.7% of drivers tested positive for either commonly abused drugs or alcohol. More than half of the drivers tested positive for drugs (50.9%) other than alcohol, with one in four drivers testing positive for marijuana use. About one-third of those using drugs had also been drinking, but alcohol was detected in only 30.6% of all injured drivers. Within the total MVC patient pool, passenger drug/alcohol use was equivalent to the driver population; however, injured pedestrians had higher rates of alcohol only than other MVC victims. There were no significant differences in drug and alcohol use between MVCs and trauma admissions of other causes. Of the patients with positive toxicology results, less than half (42%) were referred for evaluation for substance abuse disorders.     

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.     

Driver injury severity: an application of ordered probit models

This paper describes the use of ordered probit models to examine the risk of different injury levels sustained under all crash types, two-vehicle crashes, and single-vehicle crashes. The results suggest that pickups and sport utility vehicles are less safe than passenger cars under single-vehicle crash conditions. In two-vehicle crashes, however, these vehicle types are associated with less severe injuries for their drivers and more severe injuries for occupants of their collision partners. Other conclusions also are presented; for example. the results indicate that males and younger drivers in newer vehicles at lower speeds sustain less severe injuries.     

Driver injury severity outcome analysis in rural interstate highway crashes: a two-level Bayesian logistic regression interpretation

There is a high potential of severe injury outcomes in traffic crashes on rural interstate highways due to the significant amount of high speed traffic on these corridors. Hierarchical Bayesian models are capable of incorporating between-crash variance and within-crash correlations into traffic crash data analysis and are increasingly utilized in traffic crash severity analysis. This paper applies a hierarchical Bayesian logistic model to examine the significant factors at crash and vehicle/driver levels and their heterogeneous impacts on driver injury severity in rural interstate highway crashes. Analysis results indicate that the majority of the total variance is induced by the between-crash variance, showing the appropriateness of the utilized hierarchical modeling approach. Three crash-level variables and six vehicle/driver-level variables are found significant in predicting driver injury severities: road curve, maximum vehicle damage in a crash, number of vehicles in a crash, wet road surface, vehicle type, driver age, driver gender, driver seatbelt use and driver alcohol or drug involvement. Among these variables, road curve, functional and disabled vehicle damage in crash, single-vehicle crashes, female drivers, senior drivers, motorcycles and driver alcohol or drug involvement tend to increase the odds of drivers being incapably injured or killed in rural interstate crashes, while wet road surface, male drivers and driver seatbelt use are more likely to decrease the probability of severe driver injuries. The developed methodology and estimation results provide insightful understanding of the internal mechanism of rural interstate crashes and beneficial references for developing effective countermeasures for rural interstate crash prevention.     

Examining driver injury severity outcomes in rural non-interstate roadway crashes using a hierarchical ordered logit model

Rural non-interstate crashes induce a significant amount of severe injuries and fatalities. Examination of such injury patterns and the associated contributing factors is of practical importance. Taking into account the ordinal nature of injury severity levels and the hierarchical feature of crash data, this study employs a hierarchical ordered logit model to examine the significant factors in predicting driver injury severities in rural non-interstate crashes based on two-year New Mexico crash records. Bayesian inference is utilized in model estimation procedure and 95% Bayesian Credible Interval (BCI) is applied to testing variable significance. An ordinary ordered logit model omitting the between-crash variance effect is evaluated as well for model performance comparison. Results indicate that the model employed in this study outperforms ordinary ordered logit model in model fit and parameter estimation. Variables regarding crash features, environment conditions, and driver and vehicle characteristics are found to have significant influence on the predictions of driver injury severities in rural non-interstate crashes. Factors such as road segments far from intersection, wet road surface condition, collision with animals, heavy vehicle drivers, male drivers and driver seatbelt used tend to induce less severe driver injury outcomes than the factors such as multiple-vehicle crashes, severe vehicle damage in a crash, motorcyclists, females, senior drivers, driver with alcohol or drug impairment, and other major collision types. Research limitations regarding crash data and model assumptions are also discussed. Overall, this research provides reasonable results and insight in developing effective road safety measures for crash injury severity reduction and prevention.     

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.     

A logistic model of the effects of roadway, environmental, vehicle, crash and driver characteristics on hit-and-run crashes

Leaving the scene of a crash without reporting it is an offence in most countries and many studies have been devoted to improving ways to identify hit-and-run vehicles and the drivers involved. However, relatively few studies have been conducted on identifying factors that contribute to the decision to run after the crash. This study identifies the factors that are associated with the likelihood of hit-and-run crashes including driver characteristics, vehicle types, crash characteristics, roadway features and environmental characteristics. Using a logistic regression model to delineate hit-and-run crashes from nonhit-and-run crashes, this study found that drivers were more likely to run when crashes occurred at night, on a bridge and flyover, bend, straight road and near shop houses; involved two vehicles, two-wheel vehicles and vehicles from neighboring countries; and when the driver was a male, minority, and aged between 45 and 69. On the other hand, collisions involving right turn and U-turn maneuvers, and occurring on undivided roads were less likely to be hit-and-run crashes.     

Exploring precrash maneuvers using classification trees and random forests

Taking evasive actions vis-à-vis critical traffic situations impending to motor vehicle crashes endows drivers an opportunity to avoid the crash occurrence or at least diminish its severity. This study explores the drivers, vehicles, and environments’ characteristics associated with crash avoidance maneuvers (i.e., evasive actions or no evasive actions). Rear-end collisions, head-on collisions, and angle collisions are analyzed separately using decision trees and the significance of the variables on the binary response variable (evasive actions or no evasive actions) is determined. Moreover, the random forests method is employed to rank the importance of the drivers/vehicles/environments characteristics on crash avoidance maneuvers. According to the exploratory analyses’ results, drivers’ visibility obstruction, drivers’ physical impairment, drivers’ distraction are associated with crash avoidance maneuvers in all three types of accidents. Moreover, speed limit is associated with rear-end collisions’ avoidance maneuvers and vehicle type is correlated with head-on collisions and angle collisions’ avoidance maneuvers. It is recommended that future research investigates further the explored trends (e.g., physically impaired drivers, visibility obstruction) using driving simulators which may help in legislative initiatives and in-vehicle technology recommendations.     

Motor vehicle-bicycle crashes in Beijing: irregular maneuvers, crash patterns, and injury severity

This research presents a comprehensive analysis of motor vehicle–bicycle crashes using 4 years of reported crash data (2004–2007) in Beijing. The interrelationship of irregular maneuvers, crash patterns and bicyclist injury severity are investigated by controlling for a variety of risk factors related to bicyclist demographics, roadway geometric design, road environment, etc.Results show that different irregular maneuvers are correlated with a number of risk factors at different roadway locations such as the bicyclist age and gender, weather and traffic condition. Furthermore, angle collisions are the leading pattern of motor vehicle–bicycle crashes, and different irregular maneuvers may lead to some specific crash patterns such as head-on or rear-end crashes. Orthokinetic scrape is more likely to result in running over bicyclists, which may lead to more severe injury. Moreover, bicyclist injury severity level could be elevated by specific crash patterns and risk factors including head-on and angle collisions, occurrence of running over bicyclists, night without streetlight, roads without median/division, higher speed limit, heavy vehicle involvement and older bicyclists.This study suggests installation of median, division between roadway and bikeway, and improvement of illumination on road segments. Reduced speed limit is also recommended at roadway locations with high bicycle traffic volume. Furthermore, it may be necessary to develop safety campaigns aimed at male, teenage and older bicyclists.