Examination of factors determining fault in two-vehicle motorcycle crashes

Near-crash risk identification and evaluation for takeout delivery motorcycles using roadside LiDAR

The proliferation of motorcycles in urban areas has raised concerns regarding traffic safety. However, traditional sensors struggle to obtain precise high-resolution trajectory data, which hinder the accurate identification and quantification of near-crash risks for takeout delivery motorcycles. To fill this gap, this study presents a novel approach utilizing roadside light detection and ranging (LiDAR) to identify and evaluate the risk of near crashes of takeout delivery motorcycles. First, a trajectory amendment method incorporating speed and steering angle was introduced to enhance the accuracy and continuity of the trajectory prediction. Second, a trajectory prediction method combining the steering intention and a repulsive force model was proposed for near-crash risk prediction. Subsequently, a near-crash identification method was developed that relied on the closest distance and risk radius. Finally, near-crash risk fields were constructed to quantify risk levels by leveraging velocity, position, and weight. The experimental results demonstrated 92.10 % accuracy in intention prediction, with mean absolute error (MAE) and root mean square error (RMSE) values of 0.53 m and 0.45 m, respectively. In addition to its higher accuracy, the proposed method makes it easier to quantify near-crash risk and supports a proactive approach for visualizing and analyzing traffic safety.

Predicting and factor analysis of rider injury severity in two-wheeled motorcycle and vehicle crash accidents based on an interpretable machine learning framework

OBJECTIVE

As one of the vulnerable road users in accidents, how to improve the two-wheeled motorcyclist's driving safety and reduce accident injury is a public health issue. Accurate identification of the factors influencing the severity of accidents is an important prerequisite for mitigating injury from crashes.

METHODS

Based on a vehicle and a two-wheeled motorcycle crash accident data from the China in-depth accident study database (CIDAS), this study uses the performance evaluation indicators of accuracy, precision, recall, F1-score, AUC, and the ROC curve. The classification and prediction performances of the six machine learning methods on the dataset are compared, and the LightGBM algorithm with the best performance is selected to model the accident injury severity of the motorcyclists. The SHAP method is used to extend the interpretability of the LightGBM model results. Based on the SHAP method, the importance, main effect, and the interaction effect of factors under each accident injury severity are quantitatively analyzed.

RESULTS

The model prediction accuracy is 92.6%, the F1-Score is 92.8%, and the AUC value is 0.986. The importance of factors varies with the accident injury severity of motorcyclists. The kilometers traveled per year by the driver, the throwing distance of the motorcyclist, and the road speed limit are the three most important factors. The motorcyclist is more likely to suffer fatal injuries when the throwing distance is >1,000 cm.

CONCLUSIONS

The prediction model of driver injury severity based on LightGBM algorithm has a good prediction performance. It can be used to analyze the influence factors of injury severity in two-wheeled motorcyclist accident by combining the model with SHAP method. These results could help the traffic management department to take measures to reduce accident injury of motorcyclists.

Addressing endogeneity between hazardous actions and motorcyclist injury severity by integrating generalized propensity score approach and instrumental variable model

Motorcyclist hazardous actions (e.g., particularly speed too fast or failing to stop in assured clear distance (ACD)) are commonly identified as risk factors that significantly impact the motorcyclist injury severity. However, endogenous effects resulting from motorcyclist hazardous actions have seldom been considered, which may cause the biased estimates. Specifically, two important sources of endogeneities (i.e., endogeneity arising from observed confounding factors and endogeneity caused by unobserved confounders) tend to yield a biased relationship between hazardous actions and motorcyclist injury severity. To jointly account for two sources of endogeneities and provide more robust estimates, the study tries to assess the effects of speed-too-fast and failing to stop in ACD on motorcyclist injury severity via a hybrid method by integrating the generalized propensity score approach with instrumental variable model. Specifically, we adopt a generalized propensity score matching method to reduce the endogeneity bias arising from observed confounders. Furthermore, the matched data are used to develop an instrumental variable model with random parameters to handle the endogeneity resulting from unobserved confounders and unobserved heterogeneity, which consists of random parameters binary logit models modelling the motorcyclist hazardous actions in the first stage and a random parameters logit model with heterogeneity in means modelling the motorcyclist injury severity in the second stage. The proposed approach is estimated based on Michigan motorcycle crash data from 2015 to 2018. Results suggest that alcohol use leads motorcyclists to engage in speed-too-fast, while alcohol use and signal control cause motorcyclists to be involved in failing to stop in ACD. Middle-aged and elderly motorcyclists, alcohol use, speed too fast, speed limit ≥50 mph, wet surface, and head-on/angle crashes significantly increase the injury severity of motorcyclists. Moreover, failing to stop in ACD produces a random parameter with heterogeneity in means, while intersection increases the mean effects of failing to stop in ACD on motorcyclist minor injury. These findings further provide insights for a better understanding of hazardous actions and motorcyclist injury severity via the impact analysis of various explanatory variables.

Temporal Instability of Motorcycle Crash Fatalities on Local Roadways: A Random Parameters Approach with Heterogeneity in Means and Variances

Motorcycle accidents can impede sustainable development due to the high fatality rate associated with motorcycle riders, particularly in developing countries. Although there has been extensive research conducted on motorcycle accidents on highways, there is a limited understanding of the factors contributing to accidents involving the most commonly used motorcycles on local roads. This study aimed to identify the root causes of fatal motorcycle accidents on local roads. The contributing factors consist of four groups: rider characteristics, maneuvers prior to the crash, temporal and environmental characteristics, and road characteristics. The study employed random parameters logit models with unobserved heterogeneity in means and variances while also incorporating the temporal instability principle. The results revealed that the data related to motorcycle accidents on local roads between 2018 and 2020 exhibited temporal variation. Numerous variables were discovered to influence the means and variances of the unobserved factors that were identified as random parameters. Male riders, riders over 50 years old, foreign riders, and accidents that occurred at night with inadequate lighting were identified as the primary factors that increased the risk of fatalities. This paper presents a clear policy recommendation aimed at organizations and identifies the relevant stakeholders, including the Department of Land Transport, traffic police, local government organizations, and academic groups.

Modeling faults among mountainous highway fatal crash-involved drivers with different route familiarity levels

OBJECTIVE

With the constrained topography and road geometry, adverse weather conditions and restricted roadway facilities, mountainous highway crash rates and fatality rates are much higher. Considering the potential influence of driver's route familiarity level on driving behavior and fault assignment, this research investigates high- and low- route familiarity level drivers (HRF and LRF drivers) fault assignment in mountainous highway fatal crashes in Yunnan Province of China by examining factors of driver, crash/environment and pre-crash behaviors.

METHODS

Yunnan Province is famous for its tourism, and tourism can also bring in many drivers with low-route familiarity levels. Spatial distance away from residence-based method is used for identifying route familiarity levels of the drivers in this study. We employed two separate binary logistic regression models to investigate the effects of the explanatory variables on the likelihoods that the HRF or LRF drivers were at fault in the mountainous highway fatal crashes.

RESULTS

The results show that driver under alcohol influence, sharp turn, dawn/dusk and left turning are 4 common factors that significantly influence both HRF and LRF drivers' fault assignments. Factors including driver age, driver seatbelt use, weather condition, road type, section type, lighting condition and pre-crash behaviors have different or opposite influences on HRF and LRF drivers' fault assignments. HRF drivers are much easier to be distracted under the conditions that are without the need of extra attention. LRF drivers have much more difficulties in figuring out, responding to and making timely driving behavior adjustment to ensure their driving safety on the high-risk sections like tunnels, continuous long downhills and sharp turns. Street parking/backing and left turning of the LRF drivers are very serious problems on the mountainous highways in China.

CONCLUSIONS

There is a large difference of significant factors contributing to the fault assignment of HRF and LRF drivers in mountainous highway fatal crashes. Some more effective and targeted countermeasures are put forward for HRF and LRF drivers and transportation managers to improve mountainous highway traffic safety.

The Impact of Aging Drivers and Vehicles on the Injury Severity of Crash Victims

Against a general trend of increasing driver longevity, the injuries suffered by vehicle occupants in Spanish road traffic crashes are analyzed by the level of severity of their bodily injuries (BI). Generalized linear mixed models are applied to model the proportion of non-serious, serious, and fatal victims. The dependence between vehicles involved in the same crash is captured by including random effects. The effect of driver age and vehicle age and their interaction on the proportion of injured victims is analyzed. We find a nonlinear relationship between driver age and BI severity, with young and older drivers constituting the riskiest groups. In contrast, the expected severity of the crash increases linearly up to a vehicle age of 18 and remains constant thereafter at the highest level of BI severity. No interaction between the two variables is found. These results are especially relevant for countries such as Spain with increasing driver longevity and an aging car fleet.

Mid-term prediction of at-fault crash driver frequency using fusion deep learning with city-level traffic violation data

Traffic violations and improper driving are behaviors that primarily contribute to traffic crashes. This study aimed to develop effective approaches for predicting at-fault crash driver frequency using only city-level traffic enforcement predictors. A fusion deep learning approach combining a convolution neural network (CNN) and gated recurrent units (GRU) was developed to compare predictive performance with one econometric approach, two machine learning approaches, and another deep learning approach. The performance comparison was conducted for (1) at-fault crash driver frequency prediction tasks and (2) city-level crash risk prediction tasks. The proposed CNN-GRU achieved remarkable prediction accuracy and outperformed other approaches, while the other approaches also exhibited excellent performances. The results suggest that effective prediction approaches and appropriate traffic safety measures can be developed by considering both crash frequency and crash risk prediction tasks. In addition, the accumulated local effects (ALE) plot was utilized to investigate the contribution of each traffic enforcement activity on traffic safety in a scenario of multicollinearity among predictors. The ALE plot illustrated a complex nonlinear relationship between traffic enforcement predictors and the response variable. These findings can facilitate the development of traffic safety measures and serve as a good foundation for further investigations and utilization of traffic violation data.

Identification of factors influencing severity of motorcycle crashes in Dhaka, Bangladesh using binary logistic regression model

Dhaka, the capital and megacity of the developing country Bangladesh, has experienced a sharp rise in motorcycle users in the last decade, especially after the introduction of ridesharing services. Therefore, the morbidity and mortality rates of motorcycle crash injuries have also increased and become one of the major safety concerns. However, there is scant empirical evidence on motorcycle crash severity in the context of developing countries. Hence, this study was conducted to identify the factors that influenced the severity of motorcycle crashes in Dhaka. A binary logistic regression model was developed using motorcycle crash data of Dhaka over the period of 2006-2015 to identify the contributing factors of motorcycle crash severity. The model output showed that eleven factors significantly increased the probability of fatal motorcycle crashes. These factors were crashes occurring on weekends, during the rainy season, during dawn and night period, at non-intersections, on straight and flat roads, on highways, hit pedestrian type crashes, crashes involving motorcycles with no defect, crashes with heavier vehicles, crashes involving motorcyclists not wearing helmets, and drivers with alcohol suspicion. These findings would help to formulate prevention strategies to reduce the injury severity of motorcycle crashes in the developing countries.

Motorcycle-related trauma:effects of age and site of injuries on mortality. A single-center, retrospective study

Background

Motorcyclists are often victims of road traffic incidents. Though elderly patients seem to have worse survival outcomes and sustain more severe injuries than younger patients, concordance in the literature for this does not exist. The aim of the study is to evaluate the impact of age and injury severity on the mortality of patients undergoing motorcycle trauma.

Methods

Data of 1725 patients consecutively admitted to our Trauma Center were selected from 2002 to 2016 and retrospectively analyzed. The sample was divided into three age groups: ≤ 17 years, 18–54 years, and ≥ 55 years. Mortality rates were analyzed for the overall population and patients with Injury Severity Score (ISS) ≥ 25. Differences in survival among age groups were evaluated with log-rank test, and multivariate logistic regression models were created to identify independent predictors of mortality.

Results

A lower survival rate was detected in patients older than 55 years (83.6% vs 94.7%, p = 0.049) and in those sustaining critical injuries (ISS ≥ 25, 61% vs 83%, p = 0.021). Age (p = 0.027, OR 1.03), ISS (p < 0.001, OR 1.09), and Revised Trauma Score (RTS) (p < 0.001, OR 0.47) resulted as independent predictors of death. Multivariate analysis identified head (p < 0.001, OR 2.04), chest (p < 0.001, OR 1.54), abdominal (p < 0.001, OR 1.37), and pelvic (p = 0.014, OR 1.26) injuries as independent risk factors related to mortality as well. Compared to the theoretical probability of survival, patients of all age groups showed a survival advantage when managed at a level I trauma center.

Conclusions

We detected anatomical injury distributions and mortality rates among three age groups. Patients aging more than 55 years had an increased risk of death, with a prevalence of severe chest injuries, while younger patients sustained more severe head trauma. Age represented an independent predictor of death. Management of these patients at a level I trauma center may lead to improved outcomes.

Examining correlations between motorcyclist's conspicuity, apparel related factors and injury severity score: Evidence from new motorcycle crash causation study

Motorcyclists are vulnerable road users at a particularly high risk of serious injury or death when involved in a crash. In order to evaluate key risk factors in motorcycle crashes, this study quantifies how different "policy-sensitive" factors correlate with injury severity, while controlling for rider and crash specific factors as well as other observed/unobserved factors. The study analyzes data from 321 motorcycle injury crashes from a comprehensive US DOT FHWA's Motorcycle Crash Causation Study (MCCS). These were all non-fatal injury crashes that are representative of the vast majority (82%) of motorcycle crashes. An anatomical injury severity scoring system, termed as Injury Severity Score (ISS), is analyzed providing an overall score by accounting for the possibility of multiple injuries to different body parts of a rider. An ISS ranges from 1 to 75, averaging at 10.32 for this sample (above 9 is considered serious injury), with a spike at 1 (very minor injury). Preliminary cross-tabulation analysis mapped ISS to the Abbreviated Injury Scale (AIS) injury classification and examined the strength of associations between the two. While the study finds a strong correlation between AIS and ISS classification (Kendall's tau of 0.911), significant contrasts are observed in that, when compared to ISS, AIS tends to underestimate the severity of an injury sustained by a rider. For modeling, fixed and random parameter Tobit modeling frameworks were used in a corner-solution setting to account for the left-tail spike in the distribution of ISS and to account for unobserved heterogeneity. The developed random parameters Tobit framework additionally accounts for the interactive effects of key risk factors, allowing for possible correlations among random parameters. A correlated random parameter Tobit model significantly out-performed the uncorrelated random parameter Tobit and fixed parameter Tobit models. While controlling for various other factors, we found that motorcycle-specific shoes and retroreflective upper body clothing correlate with lower ISS on-average by 5.94 and 1.88 units respectively. Riders with only partial helmet coverage on-average sustained more severe injuries, whereas, riders with acceptable helmet fit had lower ISS Methodologically, not only do the individual effects of several key risk factors vary significantly across observations in the form of random parameters, but the interactions between unobserved factors characterizing random parameters significantly influence the injury severity score as well. The implications of the findings are discussed.

Trends and patterns in fatal US motorcycle crashes, 2000-2016

Objective: To investigate trends of motorcyclist fatalities and identify at-risk populations by motorcyclist demographics and crash characteristics. Methods: We used the Fatality Analysis Reporting System (FARS) database (2000-2016) to track fatality rate trends, which were quantified by using Poisson mixed-effects regression models comparing 2000-2001 and 2007-2008, as well as 2009-2010 and 2015-2016. Results: The overall fatality rate per 100,000 population increased from 2000 to 2016, defined by two trend lines-before and after the economic recession in 2008-2009. The overall fatality rate ratio between 2000-2001 and 2007-2008 was 1.60 [95% Confidence Interval (CI): 1.51-1.70], and between 2009-2010 and 2015-2016 was 1.09 (95% CI: 1.02-1.18). Fatality rates increased among all age groups, particularly for motorcyclists aged 60 and older. Those aged 18-29 had the highest fatality rates overall. Age-and-sex standardized state fatality rates were consistently highest in Wyoming, South Dakota, and South Carolina and lowest in Massachusetts, New York and New Jersey. Conclusion: Motorcycle fatality rates increased overall and across all age groups between 2000 and 2016. Fatalities for the oldest riders showed the steadiest increasing trends. Results highlight the continued public health burden of motorcyclist fatalities and, by extension, the importance of improving motorcycle safety.

A heterogeneity based case-control analysis of motorcyclist's injury crashes: Evidence from motorcycle crash causation study

The main objective of this study is to quantify how different "policy-sensitive" factors are associated with risk of motorcycle injury crashes, while controlling for rider-specific, psycho-physiological, and other observed/unobserved factors. The analysis utilizes data from a matched case-control design collected through the FHWA's Motorcycle Crash Causation Study. In particular, 351 cases (motorcyclists involved in injury crashes) are analyzed vis-à-vis similarly-at-risk 702 matched controls (motorcyclists not involved in crashes). Unlike traditional conditional estimation of relative risks, the paper presents heterogeneity based statistical analysis that accounts for the possibility of both within and between matched case-control variations. Overall, the correlations between key risk factors and injury crash propensity exhibit significant observed and unobserved heterogeneity. The results of best-fit random parameters logit model with heterogeneity-in-means show that riders with partial helmet coverage (U.S. DOT compliant helmets with partial coverage, least intrusive covering only the top half of the cranium) have a significantly lower risk of injury crash involvement. Lack of motorcycle rider conspicuity captured by dark (red) upper body clothing is associated with significantly higher injury crash risk (odds ratio 3.87, 95% CI: 1.63, 9.61). Importantly, a rider's motorcycle-oriented lower clothing (e.g., cannot easily get stuck in the machinery) significantly lowers the odds of injury crash involvement. Regarding the effectiveness of training, formal motorcycle driving training in recent years was associated with lower injury crash propensity. Finally, riders with less sleep prior to crash/interview exhibited 1.97 times higher odds of crash involvement compared to riders who had more than 5 h of sleep. Methodologically, the conclusion is that the correlations of several rider, exposure, apparel, and riding history related factors with crash risk are not homogeneous and in fact vary in magnitude as well as direction. The study results indicate the need to develop appropriate countermeasures, such as refresher motorcycle training courses, prevention of sleep-deprived/fatigued riding, and riding under the influence of alcohol and drugs.

Factors contributing to motorcycle fatal crashes on National Highways in India

This study analyses fatal crash patterns, and identifies the risk factors contributing to motorcycle versus non-motorcycle fatal crashes using binomial logistic regression on two-, four- and six-lane National Highways (NHs) in India utilizing police fatal crash data. The distribution of victims' mode by striking vehicles shows that percentage share of striking vehicles (truck) against the victims' vehicles (motorcycle) is 44%, 52% and 37% on two-lane NH-8, four-lane NH-24 and six-lane NH-1, respectively. Nine explanatory variables pertaining to fatal crash, victim, roadway and environment are considered for the model (using combined data of cited three NHs). The results of the logistic regression model (motorcycle versus non-motorcycle fatal crashes) show that for variable 'collision type', likelihood of occurrence of 'rear-end', 'sideswipe' and 'head-on' fatal crashes are 42-times, 35-times and 25-times more than 'hit pedestrian' respectively. Similarly, for variable 'number of vehicle', likelihood is thrice as 'single-vehicle' than 'two or more vehicles'; and, for variable 'number of lane', probability is more on 'two-lane' NH-8 than 'four-lane' NH-24. Based on the study results, it is recommended to upgrade two-lane (undivided carriageway) to four-lane (divided carriageway) NHs to reduce 'head-on' collision.

Are automatic systems the future of motorcycle safety? A novel methodology to prioritize potential safety solutions based on their projected effectiveness

OBJECTIVE

Motorcycle riders are involved in significantly more crashes per kilometer driven than passenger car drivers. Nonetheless, the development and implementation of motorcycle safety systems lags far behind that of passenger cars. This research addresses the identification of the most effective motorcycle safety solutions in the context of different countries.

METHODS

A knowledge-based system of motorcycle safety (KBMS) was developed to assess the potential for various safety solutions to mitigate or avoid motorcycle crashes. First, a set of 26 common crash scenarios was identified from the analysis of multiple crash databases. Second, the relative effectiveness of 10 safety solutions was assessed for the 26 crash scenarios by a panel of experts. Third, relevant information about crashes was used to weigh the importance of each crash scenario in the region studied. The KBMS method was applied with an Italian database, with a total of more than 1 million motorcycle crashes in the period 2000-2012.

RESULTS

When applied to the Italian context, the KBMS suggested that automatic systems designed to compensate for riders' or drivers' errors of commission or omission are the potentially most effective safety solution. The KBMS method showed an effective way to compare the potential of various safety solutions, through a scored list with the expected effectiveness of each safety solution for the region to which the crash data belong. A comparison of our results with a previous study that attempted a systematic prioritization of safety systems for motorcycles (PISa project) showed an encouraging agreement.

CONCLUSIONS

Current results revealed that automatic systems have the greatest potential to improve motorcycle safety. Accumulating and encoding expertise in crash analysis from a range of disciplines into a scalable and reusable analytical tool, as proposed with the use of KBMS, has the potential to guide research and development of effective safety systems. As the expert assessment of the crash scenarios is decoupled from the regional crash database, the expert assessment may be reutilized, thereby allowing rapid reanalysis when new crash data become available. In addition, the KBMS methodology has potential application to injury forecasting, driver/rider training strategies, and redesign of existing road infrastructure.

Motorcycle-related hospitalizations of the elderly

Background

To investigate the injury pattern, mechanisms, severity, and mortality of the elderly hospitalized for treatment of trauma following motorcycle accidents.

Methods

Motorcycle-related hospitalization of 994 elderly and 5078 adult patients from the 16,548 hospitalized patients registered in the Trauma Registry System between January 1, 2009 and December 31, 2013.

Results

The motorcycle-related elderly trauma patients had higher injury severity, less favorable outcomes, higher proportion of patients admitted to the intensive care unit (ICU), prolonged hospital and ICU stays and higher mortality than those adult motorcycle riders. It also revealed that a significant percentage of elderly motorcycle riders do not wear a helmet. Compared to patients who had worn a helmet, patients who had not worn a helmet had a lower first Glasgow Coma Scale (GCS) score, and a greater percentage presented with unconscious status (GCS score ≤8), had sustained subdural hematoma, subarachnoid hemorrhage, cerebral contusion, severe injury (injury severity score 16–24 and ≥25), had longer hospital stay and higher mortality, and had required admission to the ICU.

Conclusions

Elderly motorcycle riders tend to present with a higher injury severity, worse outcome, and a bodily injury pattern differing from that of adult motorcycle riders, indicating the need to emphasize use of protective equipment, especially helmets, to reduce their rate and severity of injury.

Differences between the sexes in motorcycle-related injuries and fatalities at a Taiwanese level I trauma center

Background

Female patients present with unique physiological and behavioral characteristics compared to male patients. The aim of this study was to investigate and compare the injury patterns, injury characteristics, and mortality of male and female patients hospitalized for treatment of motorcycle accident-related trauma in a level I trauma center.

Methods

Retrospective analysis of motorcycle-related injuries from the Trauma Registry System was performed to identify and compare 4028 male and 2919 female patients hospitalized for treatment between January 1, 2009 and December 31, 2013.

Results

The female patients were younger, less often drunken, more often wore helmets, were transported by emergency medical services, and arrived at the emergency department between 7 a.m. and 5 p.m. compared to male patients. Analysis of Abbreviated Injury Scale scores revealed that female patients sustained significantly higher rates of injuries to the extremities, but lower rates of injuries to the head/neck, face, and thorax than male patients did. Female patients had a significant lower Injury Severity Score (ISS) and adjusted odds ratio of in-hospital mortality (AOR 0.83, 95% CI: 0.83–0.86) after adjustment by ISS. However, the logistic regression analysis of propensity score-matched patients with adjusted confounders including helmet-wearing status and alcohol intoxication revealed that the gender did not significantly influence mortality (OR 0.82, 95% CI 0.47–1.43; p = 0.475), implying the an associated risky behaviors may attribute to the difference of odds of mortality between the male and female patients. In addition, a significantly fewer female patients were admitted to the intensive care unit (ICU), and female patients had a significantly shorter hospital and ICU length of stay.

Conclusion

Female motorcycle riders have different injury characteristics, lower ISS and in-hospital mortality, and present with a bodily injury pattern that differs from that of male motorcycle riders.

Level of evidence

Epidemiologic study, level III.

Do Young Drivers Become Safer After Being Involved in a Collision?

As drivers age, their risk of being involved in a car collision decreases. The present study investigated if this trend is due, in part, to some risky drivers having a collision early in their driving lives and subsequently reducing their risky driving after that negative experience. Accelerometers and video cameras were installed in the vehicles of 16- to 17-year-old drivers ( N = 254), allowing coders to measure the number of g-force events (i.e., events in which a threshold acceleration level was exceeded) per 1,000 miles and the number of collisions. Among the 41 participants who experienced a severe collision, the rate of g-force events dropped significantly in the 1st month after the collision, remained unchanged for the 2nd month, and increased significantly in the 3rd month. There were no changes in the rate of g-force events at comparable time points for the drivers not involved in a collision. Being involved in a collision led to a decrease in risky driving, but this may have been a temporary effect.

Examination of factors associated with use rates after transition from a universal to partial motorcycle helmet use law

OBJECTIVES

Motorcycle riders account for a disproportionately high number of traffic injuries and fatalities compared to occupants of other vehicle types. Though research has demonstrated the benefits of helmet use in preventing serious and fatal injuries in the event of a crash, helmet use has remained relatively stable in the United States, where the most recent national estimates show a 64% use rate. Use rates have been markedly lower among those states that do not have a universal helmet law for all riders. In 2012, the state of Michigan repealed its longstanding mandatory helmet use law. In order to gain insights as to the effects of this legislative change, a study was conducted to examine short-term changes in helmet use and identify factors associated with use rates.

METHODS

A statewide direct observation survey was conducted 1 year after the transition from a universal helmet law to a partial helmet law. A random parameters logistic regression model was estimated to identify motorcyclist, roadway, and environmental characteristics associated with helmet use. This modeling framework accounts for both intravehicle correlation (between riders and passengers on the same motorcycle) as well as unobserved heterogeneity across riders due to important unobserved factors.

RESULTS

Helmet use was shown to vary across demographic segments of the motorcyclist population. Use rates were higher among Caucasian riders, as well as among those age 60 and above. No significant difference was observed between male and female riders. Use was also found to vary geographically, temporally, and with respect to various environmental characteristics. Geographically, helmet use rates tended to be correlated with historical restraint use trends, which may be reflective of riding environment and general differences in the riding population. To this end, rates were also highly variable based upon the type of motorcycle and whether the motorcyclist was wearing high-visibility gear.

CONCLUSIONS

The study results demonstrate the short-term reduction in helmet use following transition from a universal to partial motorcycle helmet law. The reduction in use is somewhat less pronounced than has been experienced in other states, which may be reflective of general differences among Michigan motorcyclists because the state has also generally exhibited higher use rates of seat belts and other forms of occupant protection. The study results also highlight potential target areas for subsequent education and public awareness initiatives aimed at increasing helmet use.

Exploratory field trial of motorcycle autonomous emergency braking (MAEB): Considerations on the acceptability of unexpected automatic decelerations

OBJECTIVE

Autonomous emergency braking (AEB) acts to slow down a vehicle when an unavoidable impending collision is detected. In addition to documented benefits when applied to passenger cars, AEB has also shown potential when applied to motorcycles (MAEB). However, the feasibility of MAEB as practically applied to motorcycles in the real world is not well understood.

METHODS

In this study we performed a field trial involving 16 riders on a test motorcycle subjected to automatic decelerations, thus simulating MAEB activation. The tests were conducted along a rectilinear path at nominal speed of 40 km/h and with mean deceleration of 0.15 g (15% of full braking) deployed at random times. Riders were also exposed to one final undeclared brake activation with the aim of providing genuinely unexpected automatic braking events.

RESULTS

Participants were consistently able to manage automatic decelerations of the vehicle with minor to moderate effort. Results of undeclared activations were consistent with those of standard runs.

CONCLUSIONS

This study demonstrated the feasibility of a moderate automatic deceleration in a scenario of motorcycle travelling in a straight path, supporting the notion that the application of AEB on motorcycles is practicable. Furthermore, the proposed field trial can be used as a reference for future regulation or consumer tests in order to address safety and acceptability of unexpected automatic decelerations on a motorcycle.

A comparison of contributing effects on 2-vehicle alcohol-related crashes between impaired and nonimpaired operators

OBJECTIVE

Driving under the influence of alcohol is a crime that places the lives of all motorists in danger. Though it is a largely preventable act, impaired driving has accounted for 31 to 38% of fatal crashes across the country over the last decade. When an impaired operator crashes his or her vehicle, there is often a second unit, of which the operator is not impaired, involved in the crash.

METHODS

This research looks at approximately 14,000 2-unit crashes involving an impaired operator in the State of Ohio from 2008 through 2012. The research is focused on determining the effects of crash and operator characteristics in 2-unit alcohol-related crashes through the use of 2 mixed logit models.

RESULTS

It is found that several factors have similar effects on the injury severities of both the impaired and nonimpaired operators, including head-on crashes, the use of seat belts, and the deployment of airbags. There are, however, several factors that affect the 2 operators differently. It is found that the impaired operator's injury severity is based on the type and, more important, the size of the vehicle he or she is driving, the roadway geometry, and the speed of the vehicle driven by the nonimpaired operator. The nonimpaired operator is equally affected by the speed of the impaired vehicle as much as his or her own speed, and the nonimpaired operator's injury severity is virtually independent of the type of vehicle being driven.

CONCLUSIONS

Researchers may disseminate the results to community groups such as Mothers Against Drunk Driving and Safe Communities to increase awareness of the dangers of drunk driving in an effort to reduce the number of alcohol-related crashes.

Observation of motorcycle helmet use rates in Michigan after partial repeal of the universal motorcycle helmet law

Motorcycle crashes result in a significant health burden, including many fatal injuries and serious non-fatal head injuries. Helmets are highly effective in preventing such trauma, and jurisdictions that require helmet use of all motorcyclists have higher rates of helmet use and lower rates of head injuries among motorcyclists. The current study examines helmet use and characteristics of helmeted operators and their riding conditions in Michigan, following a weakening of the state's universal motorcycle helmet use law in April 2012. Data on police-reported crashes occurring during 2012-14 and from a stratified roadside observational survey undertaken in Southeast Michigan during May-September 2014 were used to estimate statewide helmet use rates. Observed helmet use was more common among operators of sports motorcycles, on freeways, and in the morning, and least common among operators of cruisers, on minor arterials, and in the afternoon. The rate of helmet use across the state was estimated at 75%, adjusted for roadway type, motorcycle class, and time of day. Similarly, the helmet use rate found from examination of crash records was 73%. In the observation survey, 47% of operators wore jackets, 94% wore long pants, 54% wore boots, and 80% wore gloves. Protective clothing of jackets and gloves was most often worn by sport motorcycle operators and long pants and boots most often by riders of touring motorcycles. Findings highlight the much lower rate of helmet use in Michigan compared with states that have a universal helmet use law, although the rate is higher than observed in many states with partial helmet laws. Targeted interventions aimed at specific groups of motorcyclists and situations where helmet use rates are particularly low should be considered to increase helmet use.

Self-reported risk behaviors among offender motorcyclists in Ahvaz City

Introduction

Road traffic accidents are among the most critical public health issues. Many people die on the roads each day and tens of millions sustain nonfatal injuries. The aim of this study is to describe the high-risk behaviors of motorcyclists in which police had to confiscate their motorcycles.

Methods

This cross-sectional study was carried out on 240 motorcyclists in Iran from December 2010 to February 2011. A researcher-created questionnaire was used to collect data on self-reported high-risk behaviors, including passing the crossroads without considering the traffic light, refusing to wear a helmet, performing stunts in the street, and driving in the opposite direction. The collected data was descriptively analyzed.

Results

The mean age of motorcyclists was 29.3 years (SD=8.26). Twenty-six percent (n=62) of the participants did not have a motorcycle driver’s license. The analysis of risk behaviors showed that 60.8% (n=146) of the motorcycle drivers usually passed crossroads without considering the traffic light and 20.8% (n=50) performed stunts in the street.

Conclusions

This study indicates that the prevalence of high-risk behaviors among motorcyclists is significant. Health education interventions may inhibit these behaviors, thus reducing the risk of injuries.

Modeling the effect of operator and passenger characteristics on the fatality risk of motorcycle crashes

BACKGROUND

In Iran more than 25% of crash fatalities belong to motorcycle operators and passengers in the recent years, from which about 20% are related to passenger fatalities.

METHODS

The aim of this study was to investigate the motorcycle operator and passenger characteristics as well as other contributory factors that may affect the fatality risk of motorcyclists involved in traffic crashes. To this end, motorcycle crash data between 2009 and 2012 was extracted from Iran traffic crash database and a logistic regression analysis was performed to obtain odds ratio estimates for each of the study variables.

RESULTS

The fatality risk of motorcyclists has a direct relationship with the number of pillion passengers carried. Results also indicate that the amount of increase in the likelihood of having a fatality in a motorcycles crash is considerably higher when the operator is accompanied by a male passenger of the same age. Furthermore, results showed that if the crash is occurred in the darkness, on curves, in rural areas and on highways, then the crash would be more likely to be fatal. Moreover, the head-on collisions, older operators, unlicensed operators and not using a safety helmet were found to increase the likelihood of a fatality in a motorcycle crash.

CONCLUSIONS

Preventative measures such as, imposing stricter rules regarding safety helmet usage and confining the number of pillion passengers to one, might be implemented to reduce the fatality risk in motorcycle crashes. In addition, more appropriate infrastructures for penalizing offending motorcyclists could also reduce the frequency of law violations such as not wearing helmet or riding without motorcycle license, which in turn, would result into a reduction in the fatality risk of motorcycle crashes.

Motorcycle-related hospitalization of adolescents in a Level I trauma center in southern Taiwan: a cross-sectional study

Background

The aim of this study was to investigate and compare the injury pattern, mechanisms, severity, and mortality of adolescents and adults hospitalized for treatment of trauma following motorcycle accidents in a Level I trauma center.

Methods

Detailed data regarding patients aged 13–19 years (adolescents) and aged 30–50 years (adults) who had sustained trauma due to a motorcycle accident were retrieved from the Trauma Registry System between January 1, 2009 and December 31, 2012. The Pearson’s chi-squared test, Fisher’s exact test, or the independent Student’s t-test were performed to compare the adolescent and adult motorcyclists and to compare the motorcycle drivers and motorcycle pillion.

Results

Analysis of Abbreviated Injury Scale (AIS) scores revealed that the adolescent patients had sustained higher rates of facial, abdominal, and hepatic injury and of cranial, mandibular, and femoral fracture but lower rates of thorax and extremity injury; hemothorax; and rib, scapular, clavicle, and humeral fracture compared to the adults. No significant differences were found between the adolescents and adults regarding Injury Severity Score (ISS), New Injury Severity Score (NISS), Trauma-Injury Severity Score (TRISS), mortality, length of hospital stay, or intensive care unit (ICU) admission rate. A significantly greater percentage of adolescents compared to adults were found not to have worn a helmet. Motorcycle riders who had not worn a helmet were found to have a significantly lower first Glasgow Coma Scale (GCS) score, and a significantly higher percentage was found to present with unconscious status, head and neck injury, and cranial fracture compared to those who had worn a helmet.

Conclusion

Adolescent motorcycle riders comprise a major population of patients hospitalized for treatment of trauma. This population tends to present with a higher injury severity compared to other hospitalized trauma patients and a bodily injury pattern differing from that of adult motorcycle riders, indicating the need to emphasize use of protective equipment, especially helmets, to reduce their rate and severity of injury.

A case study analysis to examine motorcycle crashes in Bogota, Colombia

INTRODUCTION

Contributory factors to motorcycle crashes vary among populations depending on several aspects such as the users' profiles, the composition and density of traffic, and the infrastructure features. A better understanding of local motorcycle crashes can be reached in those places where a comprehensive analysis is performed. This paper presents the results obtained from a case study analysis of 400 police records of accidents involving motorcycles in Bogota.

METHOD

To achieve a deeper level of understanding of how these accidents occur, we propose a systemic approach that uses available crash data. The methodology is inspired by accident prototypical scenarios, a tool for analysis developed in France.

RESULTS

When grouping cases we identified three categories: solo motorcycle accidents, motorcyclist and pedestrian accidents, and accidents involving a motorcycle and another vehicle. Within these categories we undertook in-depth analyses of 32 groups of accidents obtaining valuable information to better comprehend motorcyclists' road crashes in a local context. Recurrent contributory factors in the groups of accidents include: inexperienced motorcyclists, wide urban roads that incite speeding and risky overtaking maneuvers, flowing urban roads that encourage high speed and increased interaction between vehicles, and lack of infrastructure maintenance.

PRACTICAL APPLICATIONS

The results obtained are a valuable asset to define measures that will be conveniently adapted to the group of accident on which we want to act. The methodology exposed in this paper is applicable to the study of road crashes that involve all types of actors, not only the motorcyclists, and in contexts different than those presented in Bogota.

Alcohol-related hospitalizations of adult motorcycle riders

Objective

To provide an overview of the demographic characteristics of adult motorcycle riders with alcohol-related hospitalizations.

Methods

Data obtained from the Trauma Registry System were retrospectively reviewed for trauma admissions at a level I trauma center between January 1, 2009 and December 31, 2013. Out of 16,548 registered patients, detailed information was retrieved regarding 1,430 (8.64%) adult motorcycle riders who underwent a blood alcohol concentration (BAC) test. A BAC level of 50 mg/dL was defined as the cut-off value for alcohol intoxication.

Results

In this study, alcohol consumption was more frequently noted among male motorcycle riders, those aged 30–49 years, those who had arrived at the hospital in the evening or during the night, and those who did not wear a helmet. Alcohol consumption was associated with a lower percentage of sustained severe injury (injury severity score ≥25) and lower frequencies of specific body injuries, including cerebral contusion (0.6; 95% confidence interval [CI] = 0.42–0.80), lung contusion (0.5; 95% CI = 0.24–0.90), lumbar vertebral fracture (0.1; 95% CI = 0.01–0.80), humeral fracture (0.5; 95% CI = 0.27–0.90), and radial fracture (0.6; 95% CI = 0.40–0.89). In addition, alcohol-intoxicated motorcycle riders who wore helmets had significantly lower frequencies of cranial fracture (0.4; 95% CI = 0.29–0.67), epidural hematoma (0.5; 95% CI = 0.29–0.79), subdural hematoma (0.4; 95% CI = 0.28–0.64), subarachnoid hemorrhage (0.5; 95% CI = 0.32–0.72), and cerebral contusion (0.4; 95% CI = 0.25–0.78).

Conclusions

Motorcycle riders who consumed alcohol presented different characteristics and bodily injury patterns relative to sober patients, suggesting the importance of helmet use to decrease head injuries in alcohol-intoxicated riders.

A review of powered-two-wheeler behaviour and safety

Powered-two-wheelers (PTWs) constitute a very vulnerable type of road users. The notable increase in their share in traffic and the high risk of severe accident occurrence raise the need for further research. However, current research on PTW safety is not as extensive as for other road users (passenger cars, etc.). Consequently, the objective of this research is to provide a critical review of research on Power-Two-Wheeler behaviour and safety with regard to data collection, methods of analysis and contributory factors, and discuss the needs for further research. Both macroscopic analyses (accident frequency, accident rates and severity) and microscopic analyses (PTW rider behaviour, interaction with other motorised traffic) are examined and discussed in this paper. The research gaps and the needs for future research are identified, discussed and put in a broad framework. When the interactions between behaviour, accident frequency/rates and severity are co-considered and co-investigated with the various contributory factors (riders, other users, road and traffic environment, vehicles), the accident and injury causes as well as the related solutions are better identified.

A mixed logit analysis of two-vehicle crash severities involving a motorcycle

Using motorcycle crash data for Iowa from 2001 to 2008, this paper estimates a mixed logit model to investigate the factors that affect crash severity outcomes in a collision between a motorcycle and another vehicle. These include crash-specific factors (such as manner of collision, motorcycle rider and non-motorcycle driver and vehicle actions), roadway and environmental conditions, location and time, motorcycle rider and non-motorcycle driver and vehicle attributes. The methodological approach allows the parameters to vary across observations as opposed to a single parameter representing all observations. Our results showed non-uniform effects of rear-end collisions on minor injury crashes, as well as of the roadway speed limit greater or equal to 55mph, the type of area (urban), the riding season (summer) and motorcyclist's gender on low severity crashes. We also found significant effects of the roadway surface condition, clear vision (not obscured by moving vehicles, trees, buildings, or other), light conditions, speed limit, and helmet use on severe injury outcomes.

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.