Relationship of traffic fatality rates to maximum state speed limits

Objectives: The objective of this study was to examine the safety effects of increases in U.S. state maximum speed limits during the period 1993–2013.

Methods: Poisson regression was used to model state-by-state annual traffic fatality rates per mile of travel as a function of time, the unemployment rate, the percentage of the driving age population that was younger than 25, per capita alcohol consumption, and the maximum posted speed limit on any road in the state. Separate analyses were conducted for all roads, interstates and freeways, and all other roads.

Results: A 5 mph increase in the maximum state speed limit was associated with an 8% increase in fatality rates on interstates and freeways and a 4% increase on other roads. In total, there were an estimated 33,000 more traffic fatalities during the years 1995–2013 than would have been expected if maximum speed limits had not increased. In 2013 alone, there were approximately 1,900 additional deaths—500 on interstates/freeways and 1,400 on other roads.

Conclusions: There is a definite trend of increased fatality risk when speed limits are raised. As roadway sections with higher speed limits have become more ubiquitous, the increase in fatality risk has extended beyond these roadways. The increase in risk has been so great that it has now largely offset the beneficial effects of some other traffic safety strategies. State policy makers should keep this trade-off in mind when considering proposals to raise speed limits.     

Safe speed limits for a safe system: The relationship between speed limit and fatal crash rate for different crash types

Objective: The objective of this article is to provide empirical evidence for safe speed limits that will meet the objectives of the Safe System by examining the relationship between speed limit and injury severity for different crash types, using police-reported crash data.

Method: Police-reported crashes from 2 Australian jurisdictions were used to calculate a fatal crash rate by speed limit and crash type. Example safe speed limits were defined using threshold risk levels.

Results: A positive exponential relationship between speed limit and fatality rate was found. For an example fatality rate threshold of 1 in 100 crashes it was found that safe speed limits are 40 km/h for pedestrian crashes; 50 km/h for head-on crashes; 60 km/h for hit fixed object crashes; 80 km/h for right angle, right turn, and left road/rollover crashes; and 110 km/h or more for rear-end crashes.

Conclusions: The positive exponential relationship between speed limit and fatal crash rate is consistent with prior research into speed and crash risk. The results indicate that speed zones of 100 km/h or more only meet the objectives of the Safe System, with regard to fatal crashes, where all crash types except rear-end crashes are exceedingly rare, such as on a high standard restricted access highway with a safe roadside design.     

Pedestrian fatality and impact speed squared: Cloglog modeling from French national data

Objective: The present study estimates pedestrians' risk of death according to impact speed when hit by a passenger car in a frontal collision.

Methods: Data were coded for all fatal crashes in France in 2011 and for a random sample of 1/20th of all road injuries for the same year and weighted to take into account police underreporting of mild injury. A cloglog model was used to optimize risk adjustment for high collision speeds. The fit of the model on the data was also improved by using the square of the impact speed, which best matches the energy dissipated in the collision.

Results: Modeling clearly demonstrated that the risk of death was very close to 1 when impact speeds exceeded 80 km/h. For speeds less than 40 km/h, because data representative of all crashes resulting in injury were used, the estimated risk of death was fairly low. However, although the curve seemed deceptively flat below 50 km/h, the risk of death in fact rose 2-fold between 30 and 40 km/h and 6-fold between 30 and 50 km/h. For any given speed, the risk of death was much higher for more elderly subjects, especially those over 75 years of age. These results concern frontal crashes involving a passenger car. Collisions involving trucks are far less frequent, but half result in the pedestrian being run over, incurring greater mortality.

Conclusions: For impact speeds below 60 km/h, the shape of the curve relating probability of death to impact speed was very similar to those reported in recent rigorous studies. For higher impact speeds, the present model allows the curve to rise ever more steeply, giving a much better fit to observed data. The present results confirm that, when a pedestrian is struck by a car, impact speed is a major risk factor, thus providing a supplementary argument for strict speed limits in areas where pedestrians are highly exposed.     

Self-regulation of driving speed among distracted drivers: An application of driver behavioral adaptation theory

Objective: The adaptive behavior of mobile phone–distracted drivers has been a topic of much discussion in the recent literature. Both simulator and naturalistic studies suggest that distracted drivers generally select lower driving speeds; however, speed adaptation is not observed among all drivers, and the mechanisms of speed selection are not well understood. The aim of this research was to apply a driver behavioral adaptation model to investigate the speed adaptation of mobile phone–distracted drivers.

Methods: The speed selection behavior of drivers was observed in 3 phone conditions including baseline (no conversation) and hands-free and handheld phone conversations in a high-fidelity driving simulator. Speed adaptation in each phone condition was modeled as a function of secondary task demand and self-reported personal/psychological characteristics with a system of seemingly unrelated equations (SURE) accounting for potential correlations due to repeated measures experiment design.

Results: Speed adaptation is similar between hands-free and handheld phone conditions, but the predictors of speed adaptation vary across the phone conditions. Though perceived workload of secondary task demand, self-efficacy, attitude toward safety, and driver demographics were significant predictors of speed adaptation in the handheld condition, drivers' familiarity with the hands-free interface, attitude toward safety, and sensation seeking were significant predictors in the hands-free condition. Drivers who reported more positive safety attitudes selected lower driving speeds while using phones.

Conclusion: This research confirmed that behavioral adaptation models are suitable for explaining speed adaptation of mobile phone distracted drivers, and future research could be focused on further theoretical refinement.     

Effects of vehicle power on passenger vehicle speeds

Objectives: During the past 2 decades, there have been large increases in mean horsepower and the mean horsepower-to–vehicle weight ratio for all types of new passenger vehicles in the United States. This study examined the relationship between travel speeds and vehicle power, defined as horsepower per 100 pounds of vehicle weight.

Methods: Speed cameras measured travel speeds and photographed license plates and drivers of passenger vehicles traveling on roadways in Northern Virginia during daytime off-peak hours in spring 2013. The driver licensing agencies in the District of Columbia, Maryland, and Virginia provided vehicle information numbers (VINs) by matching license plate numbers with vehicle registration records and provided the age, gender, and ZIP code of the registered owner(s). VINs were decoded to obtain the curb weight and horsepower of vehicles. The study focused on 26,659 observed vehicles for which information on horsepower was available and the observed age and gender of drivers matched vehicle registration records. Log-linear regression estimated the effects of vehicle power on mean travel speeds, and logistic regression estimated the effects of vehicle power on the likelihood of a vehicle traveling over the speed limit and more than 10 mph over the limit.

Results: After controlling for driver characteristics, speed limit, vehicle type, and traffic volume, a 1-unit increase in vehicle power was associated with a 0.7% increase in mean speed, a 2.7% increase in the likelihood of a vehicle exceeding the speed limit by any amount, and an 11.6% increase in the likelihood of a vehicle exceeding the limit by 10 mph. All of these increases were highly significant.

Conclusions: Speeding persists as a major factor in crashes in the United States. There are indications that travel speeds have increased in recent years. The current findings suggest the trend toward substantially more powerful vehicles may be contributing to higher speeds. Given the strong association between travel speed and crash risk and crash severity, this is cause for concern.     

Perils of using speed zone data to assess real-world compliance to speed limits

Objective: Real-world driving studies, including those involving speeding alert devices and autonomous vehicles, can gauge an individual vehicle's speeding behavior by comparing measured speed with mapped speed zone data. However, there are complexities with developing and maintaining a database of mapped speed zones over a large geographic area that may lead to inaccuracies within the data set. When this approach is applied to large-scale real-world driving data or speeding alert device data to determine speeding behavior, these inaccuracies may result in invalid identification of speeding. We investigated speeding events based on service provider speed zone data.

Methods: We compared service provider speed zone data (Speed Alert by Smart Car Technologies Pty Ltd., Ultimo, NSW, Australia) against a second set of speed zone data (Google Maps Application Programming Interface [API] mapped speed zones).

Results: We found a systematic error in the zones where speed limits of 50–60 km/h, typical of local roads, were allocated to high-speed motorways, which produced false speed limits in the speed zone database. The result was detection of false-positive high-range speeding. Through comparison of the service provider speed zone data against a second set of speed zone data, we were able to identify and eliminate data most affected by this systematic error, thereby establishing a data set of speeding events with a high level of sensitivity (a true positive rate of 92% or 6,412/6,960).

Conclusions: Mapped speed zones can be a source of error in real-world driving when examining vehicle speed. We explored the types of inaccuracies found within speed zone data and recommend that a second set of speed zone data be utilized when investigating speeding behavior or developing mapped speed zone data to minimize inaccuracy in estimates of speeding.     

Investigating factors influencing drivers' speed selection behavior under reduced visibility conditions

Objective: Driving speed is a major concern for driving safety under reduced visibility conditions. Many factors affect speed selection in low visibility, but few studies have been conducted examining drivers' characteristics, particularly in China. The present study aimed to investigate the correlation between drivers' demographic information, driving ability, and speed choice in low-visibility conditions using a sample of Chinese drivers.

Methods: A self-designed driving ability scale was used to assess driving ability in reduced visibility conditions. The reliability and validity of 306 gathered questionnaires were examined in this article, and a structural equation model (SEM) was built to explore the predictors of drivers' speed selection behavior under reduced visibility conditions and to measure the relationships between various factors.

Results: Age and driving experience have no direct relationship to speed selection behavior in reduced visibility, but the frequency of using expressways and annual mileage are significantly related to the speed on roads that have a speed restriction of 80 or 120 km/h. Under reduced visibility conditions, driving ability has a significant effect on speed selection behavior, and driving skill (DS) is the most influential on speed selection behavior on roads with a speed limit of 120 km/h; otherwise, the effect of risk perception (RP) does not differ by speed choice on 3 roads with different speed limits. Driving speed in good weather also has a positive influence on speed selection behavior in low visibility.

Conclusion: Driving ability is directly associated with speed selection in reduced visibility conditions, and some demographic data indirectly influence speed selection. This study provides useful recommendations for drivers' training programs to reduce casualties from accidents in low-visibility conditions.     

Perceived enjoyment,concentration, intention,and speed violation behavior: Using flow theory and theory of planned behavior

Objective: Road accidents are an important public health concern, and speeding is a major contributor. Although flow theory (FLT) is a valid model for understanding behavior, currently the nature of the roles and interplay of FLT constructs within the theory of planned behavior (TPB) framework when attempting to explain the determinants of motivations for intention to speed and speeding behavior of car drivers is not yet known. The study aims to synthesize TPB and FLT in explaining drivers of advanced vehicles intentions to speed and speed violation behaviors and evaluate factors that are critical for explaining intention and behavior.

Method: The hypothesized model was validated using a sample collected from 354 fully licensed drivers of advanced vehicles, involving 278 males and 76 females on 2 occasions separated by a 3-month interval. During the first of the 2 occasions, participants completed questionnaire measures of TPB and FLT variables. Three months later, participants' speed violation behaviors were assessed.

Results: The study observed a significant positive relationship between the constructs. The proposed model accounted for 51 and 45% of the variance in intention to speed and speed violation behavior, respectively. The independent predictors of intention were enjoyment, attitude, and subjective norm. The independent predictors of speed violation behavior were enjoyment, concentration, intention, and perceived behavioral control.

Conclusions: The findings suggest that safety interventions for preventing speed violation behaviors should be aimed at underlying beliefs influencing the speeding behaviors of drivers of advanced vehicles. Furthermore, perceived enjoyment is of equal importance to driver's intention, influencing speed violation behavior.     

Analyzing pedestrian crash injury severity under different weather conditions

Objective: Pedestrians are the most vulnerable road users due to the lack of mass, speed, and protection compared to other types of road users. Adverse weather conditions may reduce road friction and visibility and thus increase crash risk. There is limited evidence and considerable discrepancy with regard to impacts of weather conditions on injury severity in the literature. This article investigated factors affecting pedestrian injury severity level under different weather conditions based on a publicly available accident database in Great Britain.

Method: Accident data from Great Britain that are publicly available through the STATS19 database were analyzed. Factors associated with pedestrian, driver, and environment were investigated using a novel approach that combines a classification and regression tree with random forest approach.

Results: Significant severity predictors under fine weather conditions from the models included speed limits, pedestrian age, light conditions, and vehicle maneuver. Under adverse weather conditions, the significant predictors were pedestrian age, vehicle maneuver, and speed limit.

Conclusions: Elderly pedestrians are associated with higher pedestrian injury severities. Higher speed limits increase pedestrian injury severity. Based on the research findings, recommendations are provided to improve pedestrian safety.     

Reducing the risk of rear-end collisions with infrastructure-to-vehicle (I2V) integration of variable speed limit control and adaptive cruise control system

Objective: Adaptive cruise control (ACC) has been investigated recently to explore ways to increase traffic capacity, stabilize traffic flow, and improve traffic safety. However, researchers seldom have studied the integration of ACC and roadside control methods such as the variable speed limit (VSL) to improve safety. The primary objective of this study was to develop an infrastructure-to-vehicle (I2V) integrated system that incorporated both ACC and VSL to reduce rear-end collision risks on freeways.

Methods: The intelligent driver model was firstly modified to simulate ACC behavior and then the VSL strategy used in this article was introduced. Next, the I2V system was proposed to integrate the 2 advanced techniques, ACC and VSL. Four scenarios of no control, VSL only, ACC only, and the I2V system were tested in simulation experiments. Time exposed time to collision (TET) and time integrated time to collision (TIT), 2 surrogate safety measures derived from time to collision (TTC), were used to evaluate safety issues associated with rear-end collisions. The total travel times of each scenario were also compared.

Results: The simulation results indicated that both the VSL-only and ACC-only methods had a positive impact on reducing the TET and TIT values (reduced by 53.0 and 58.6% and 59.0 and 65.3%, respectively). The I2V system combined the advantages of both ACC and VSL to achieve the most safety benefits (reduced by 71.5 and 77.3%, respectively). Sensitivity analysis of the TTC threshold also showed that the I2V system obtained the largest safety benefits with all of the TTC threshold values. The impact of different market penetration rates of ACC vehicles in I2V system indicated that safety benefits increase with an increase in ACC proportions.

Conclusions: Compared to VSL-only and ACC-only scenarios, this integrated I2V system is more effective in reducing rear-end collision risks. The findings of this study provide useful information for traffic agencies to implement novel techniques to improve safety on freeways.     

Transport company safety climate—The impact on truck driver behavior and crash involvement

Objective: The present study investigated the relationships between safety climate and driving behavior and crash involvement.

Methods: A total of 339 company-employed truck drivers completed a questionnaire that measured their perceptions of safety climate, crash record, speed choice, and aberrant driving behaviors (errors, lapses, and violations).

Results: Although there was no direct relationship between the drivers' perceptions of safety climate and crash involvement, safety climate was a significant predictor of engagement in risky driving behaviors, which were in turn predictive of crash involvement.

Conclusions: This research shows that safety climate may offer an important starting point for interventions aimed at reducing risky driving behavior and thus fewer vehicle collisions.     

Risk factors affecting the severity of traffic accidents at Shanghai river-crossing tunnel

Objective: With increasing traffic volume and urban development, increasing numbers of underground tunnels have been constructed to relieve conflict between strained land and heavy traffic. However, as more long tunnels are constructed, tunnel traffic safety is becoming increasingly serious. Thus, it is necessary to acquire their implications and impacts. This study examined 4,539 traffic accidents that have occurred in 14 Shanghai river-crossing tunnels for the period 2011–2012 and analyze the correlation between potential factors and accident injury severity.

Methods: An ordered logit model was developed to examine the correlation between potential factors and accident injury severity.

Results: Results show that increased injury severity is associated with male drivers, drivers aged 65 years or older, accident time from midnight to dawn, weekends, wet road surface, goods vehicles, 3 or more vehicles, 4 or more lanes, middle speed limits (50–79 km/h), zone 3, extra-long tunnels (over 3,000 m), and maximum longitudinal gradient.

Conclusions: This article aims to provide useful information for engineers to develop interventions and countermeasures to improve tunnel safety in China.     

Survey regarding the 0.05 blood alcohol concentration limit for driving in the United States

Background: On May 14, 2013, the National Transportation Safety Board (NTSB) proposed that states lower the blood alcohol concentration (BAC) illegal limit from 0.08 to 0.05 g/dL (also referred to as the 0.08 law and the 0.05 limit, respectively). In March 2017, this recommendation was signed into law in the State of Utah.

Objective: The objective of this survey is to investigate perceptions regarding enforcement of the 0.05 g/dL BAC limit.

Method: Opinions of law enforcement officers, prosecutors, and defense attorneys were obtained through a series of questionnaires and focus groups.

Results: Survey data were collected from 32 law enforcement officers, 20 prosecutors, and 4 defense attorneys. The participants rated the usefulness of the NHTSA's driving while intoxicated (DWI) driving cues lower for the 0.05 limit than for the 0.08 law. Some of the participants believed that training would be needed in regard to sobriety testing under the 0.05 limit. Participants also stated that adequately preparing for prosecution of drunk drivers would be more difficult under the 0.05 limit. In addition, it was believed that drunk driving cases are more likely to be withdrawn and fewer plea agreements and guilty pleas are likely under the 0.05 limit. Prosecutors were concerned that the 0.05 limit would result in poorly investigated cases and overburden the court system. Defense attorneys were concerned about the social and economic costs of a 0.05 limit.

Discussion: Overall, it appears that the 0.05 limit is viewed as enforceable and it will save lives; however, the usefulness of the NHTSA DWI Detection Guide and of the standardized field sobriety tests need to be established for lower BACs, and efforts must be made to educate people regarding the relationship between BAC and impairment and impairment and driving with the risk of injury and death.

Conclusion: Though the 0.05 limit offers promise in saving lives, the following issues associated with changing the limit to 0.05 need to be resolved prior to implementation: Validating the sobriety tests for the 0.05 limit; if needed, modifying the sobriety tests to make them effective and valid at the 0.05 limit; and training law enforcement personnel and educating the public regarding the 0.05 limit.     

Pelvic restraint cushion sled test evaluation of pelvic forward motion

Objective: This study was designed to evaluate the performance of a pelvic restraint cushion (PRC), a submarining countermeasure that deploys under the thighs when a crash is detected in order to block the forward motion of the pelvis.

Methods: Sled tests approximating low- and high-speed frontal impacts were conducted with 4 female postmortem human subjects (PMHS) restrained by a lap and shoulder belt in the right front passenger seat. The subjects were tested with and without a PRC.

Results: The PRC is effective in reducing forward motion of the PMHS pelvis and reduces the risk of injury due to lap belt loading in a high-speed frontal crash.

Conclusions: Although small sample size limits the utility of the study's findings, the results suggest that the PRC can limit pelvic forward motion and that pelvic injury due to PRC deployment is not likely.     

Using negative emotional feedback to modify risky behavior of young moped riders

Objective: The aim of this research was to investigate whether the use of messages with negative emotional content is effective in promoting safe behavior of moped riders and how exactly these messages modulate rider behavior.

Methods: Participants received negative feedback when performing risky behaviors using a computer task. The effectiveness of this treatment was subsequently tested in a riding simulator.

Results: The results demonstrated how riders receiving negative feedback had a lower number of traffic accidents than a control group. The reduction in accidents was accompanied by a set of changes in the riding behavior. We observed a lower average speed and greater respect for speed limits. Furthermore, analysis of the steering wheel variance, throttle variance, and average braking force provided evidence for a more even and homogenous riding style. This greater abidance of traffic regulations and friendlier riding style could explain some of the causes behind the reduction in accidents.

Conclusions: The use of negative emotional feedback in driving schools or advanced rider assistance systems could enhance riding performance, making riders aware of unsafe practices and helping them to establish more accurate riding habits. Moreover, the combination of riding simulators and feedback—for example, in the training of novice riders and traffic offenders—could be an efficient tool to improve their hazard perception skills and promote safer behaviors.     

Identifying factors affecting the safety of mid-block bicycle lanes considering mixed 2-wheeled traffic flow

Objective: Electric bikes (e-bikes) have been one of the fastest growing trip modes in Southeast Asia over the past 2 decades. The increasing popularity of e-bikes raised some safety concerns regarding urban transport systems. The primary objective of this study was to identify whether and how the generalized linear regression model (GLM) could be used to relate cyclists' safety with various contributing factors when riding in a mid-block bike lane. The types of 2-wheeled vehicles in the study included bicycle-style electric bicycles (BSEBs), scooter-style electric bicycles (SSEBs), and regular bicycles (RBs).

Methods: Traffic conflict technology was applied as a surrogate measure to evaluate the safety of 2-wheeled vehicles. The safety performance model was developed by adopting a generalized linear regression model for relating the frequency of rear-end conflicts between e-bikes and regular bikes to the operating speeds of BSEBs, SSEBs, and RBs in mid-block bike lanes.

Results: The frequency of rear-end conflicts between e-bikes and bikes increased with an increase in the operating speeds of e-bikes and the volume of e-bikes and bikes and decreased with an increase in the width of bike lanes. The large speed difference between e-bikes and bikes increased the frequency of rear-end conflicts between e-bikes and bikes in mid-block bike lanes. A 1% increase in the average operating speed of e-bikes would increase the expected number of rear-end conflicts between e-bikes and bikes by 1.48%. A 1% increase in the speed difference between e-bikes and bikes would increase the expected number of rear-end conflicts between e-bikes/bikes by 0.16%.

Conclusions: The conflict frequency in mid-block bike lanes can be modeled using generalized linear regression models. The factors that significantly affected the frequency of rear-end conflicts included the operating speeds of e-bikes, the speed difference between e-bikes and regular bikes, the volume of e-bikes, the volume of bikes, and the width of bike lanes. The safety performance model can help better understand the causes of crash occurrences in mid-block bike lanes.     

Features of fatal injuries in older cyclists in vehicle–bicycle accidents in Japan

Objective: The purpose of this study was to identify and better understand the features of fatal injuries in cyclists aged 75 years and over involved in collisions with either hood- or van-type vehicles.

Methods: This study investigated the fatal injuries of cyclists aged 75 years old and over by analyzing accident data. We focused on the body regions to which the fatal injury occurred using vehicle–bicycle accident data from the Institute for Traffic Accident Research and Data Analysis (ITARDA) in Japan. Using data from 2009 to 2013, we examined the frequency of fatally injured body region by gender, age, and actual vehicle travel speed. We investigated any significant differences in distributions of fatal injuries by body region for cyclists aged 75 years and over using chi-square tests to compare with cyclists in other age groups. We also investigated the cause of fatal head injuries, such as impact with a road surface or vehicle.

Results: The results indicated that head injuries were the most common cause of fatalities among the study group. At low vehicle travel speeds for both hood- and van-type vehicles, fatalities were most likely to be the result of head impacts against the road surface.

The percentage of fatalities following hip injuries was significantly higher for cyclists aged 75 years and over than for those aged 65–74 or 13–59 in impacts with hood-type vehicles. It was also higher for women than men in the over-75 age group in impacts with these vehicles.

Conclusions: For cyclists aged 75 years and over, wearing a helmet may be helpful to prevent head injuries in vehicle-to-cyclist accidents. It may also be helpful to introduce some safety measures to prevent hip injuries, given the higher level of fatalities following hip injury among all cyclists aged 75 and over, particularly women.     

Identifying risky drivers with simulated driving

Objective: The present study aimed to examine whether high-risk drivers differ from low-risk drivers in driving behavior in a simulated environment.

Method: The 2 risk groups including 36 drivers (18 males and 18 females) performed driving tasks in a simulated environment. The simulated driving behaviors are compared between the 2 risk groups.

Results: The high-risk drivers drove much faster and exhibited larger offsets of the steering wheel than did the low-risk drivers in events without incidents. Additionally, the high-risk drivers used turn signals and horns less frequently than the low-risk drivers.

Conclusions: The present study revealed that the high-risk group differed from the low-risk group in driving behavior in a simulated environment. These results also suggest that simulated driving tasks might be useful tools for the evaluation of drivers’ potential risks.     

Analyzing injury severity factors at highway railway grade crossing accidents involving vulnerable road users: A comparative study

Objective: The main objective of this study is to identify the main factors associated with injury severity of vulnerable road users (VRUs) involved in accidents at highway railroad grade crossings (HRGCs) using data mining techniques.

Methods: This article applies an ordered probit model, association rules, and classification and regression tree (CART) algorithms to the U.S. Federal Railroad Administration's (FRA) HRGC accident database for the period 2007–2013 to identify VRU injury severity factors at HRGCs.

Results: The results show that train speed is a key factor influencing injury severity. Further analysis illustrated that the presence of illumination does not reduce the severity of accidents for high-speed trains. In addition, there is a greater propensity toward fatal accidents for elderly road users compared to younger individuals. Interestingly, at night, injury accidents involving female road users are more severe compared to those involving males.

Conclusions: The ordered probit model was the primary technique, and CART and association rules act as the supporter and identifier of interactions between variables. All 3 algorithms' results consistently show that the most influential accident factors are train speed, VRU age, and gender. The findings of this research could be applied for identifying high-risk hotspots and developing cost-effective countermeasures targeting VRUs at HRGCs.     

Risk factors for motorcycle loss-of-control crashes

Objective: The present article identifies and assesses the effect of critical factors on the risk of motorcycle loss-of-control (LOC) crashes.

Method: Data come from a French project on road crashes, which include all fatal road crashes and a random sample of 1/20th of nonfatal crashes in France in 2011, based on police reports. A case–control study was carried out on a sample of 903 crashes for 444 LOC motorcycle riders (case) and 470 non-LOC and nonresponsible motorcycle riders (control). The sample was weighted due to the randomization of nonfatal crashes. Missing values were imputed using multiple imputation.

Results: Road alignment and surface conditions, human factors, and motorcycle type played important roles in motorcycle LOC crashes. Riding in a curve was associated with a 3-fold greater risk of losing control of motorcycle than riding in a straight line. Poor road adhesion significantly increased the risk of losing control; the risk increased more than 20-fold when deteriorated road adhesion was encountered unexpectedly, due to loose gravel, ice, oil, bumps, road marking, metal plates, etc. For motorcyclists, riding with a positive blood alcohol concentration (over or equal to the legal limit of 0.5 g/L) was very dangerous, often resulting in losing control. The risk of LOC crash varied for different types of motorcycle: Riders of roadsters and sports bikes were more likely to have an LOC crash greater than that of riders of basic or touring motorcycles. In addition, LOC risk increased with speed; a model using the square of the traveling speed showed better fit than one using speed itself.

Conclusion: The LOC crash factors related to riders, vehicles, and road infrastructure identified here were expected but were rarely identified and taken simultaneously into account in previous studies. They could be targeted by countermeasures to improve motorcyclist safety.