Empirical comparison of the effects of other party's vehicle type on motorcyclists' injury severity

Chouhan S.S., Kathuria A., Chalumuri R.S.

Se C., Champahom T., Wisutwattanasak P., Jomnonkwao S., Ratanavaraha V.

AbstractUpon detecting a crash impact, the vehicle restraint system locks the driver in place. However, external factors such as speeding, crash mechanisms, roadway attributes, vehicle type, and the surrounding environment typically contribute to the driver being jostled within the vehicle. As a result, it is crucial to model unrestrained and restrained drivers separately to reveal the true impact of the restraint system and other factors on driver injury severities. This paper aims to explore the differences in factors affecting injury severity for seatbelt-restrained and unrestrained drivers involved in speeding-related crashes while accounting for temporal instability in the investigation. Utilizing crash data from Thailand between 2012 and 2017, mixed logit models with heterogeneity in means and variances were employed to account for multi-layered unobserved heterogeneity. For restrained drivers, the risk of fatal or severe crashes was positively associated with factors such as male drivers, alcohol influence, flush/barrier median roadways, sloped roadways, vans, running off the roadway without roadside guardrails, and nighttime on unlit or lit roads. For unrestrained drivers, the likelihood of fatal or severe injuries increased in crashes involving older drivers, alcohol influence, raised or depressed median roadways, four-lane roadways, passenger cars, running off the roadway without roadside guardrails, and crashes occurring in rainy conditions. The out-of-sample prediction simulation results are particularly significant, as they show the maximum safety benefits achievable solely by using a vehicle's seatbelt system. Likelihood ratio test and predictive comparison findings highlight the considerable combined impact of temporal instability and the non-transferability of restrained and unrestrained driver injury severities across the periods studied. This finding also demonstrates a potential reduction in severe and fatal injury rates by simply replicating restrained driver conditions. The findings should be of value to policymakers, decision-makers, and highway engineers when developing potential countermeasures to improve driver safety and reduce the frequency of severe and fatal speeding-related single-vehicle crashes.

Yan X., He J., Zhang C., Wang C., Ye Y., Qin P.

Driving at nighttime may make drivers more likely to be involved in fatal crashes. To investigate the temporal instability and age differences of contributors determining different injury severity levels in nighttime crashes, this paper estimates three groups of random parameters logit models with heterogeneity in the means and variances (young/middle-age/old groups). Nighttime single-vehicle crashes in this study are gathered over four years in California, from January 1, 2014, to December 31, 2017, provided by Highway Safety Information System, including single-vehicle crashes occurring under dark, dawn, and dusk lighting conditions. Simultaneously, to investigate the temporal instability and transferability of nighttime crash severity relating to drivers of different ages, three disaggregate groups are defined: young drivers (15–29 years old), middle-age drivers (30–49 years old), old drivers (over 49 years old). Three injury-severity categories are determined as outcome variables: severe injury, minor injury, and no injury, while multiple factors are investigated as explanatory variables, including driver characteristics, vehicle characteristics, roadway characteristics, environmental characteristics, crash characteristics, and temporal characteristics. Two series of likelihood ratio tests are undertaken to unveil the contributors determining nighttime crash injury severities varying among drivers of different ages over time. Besides, the current study also compares the differences between out-of-sample and within-sample predictions. The results indicate the unstable direction of predictions across different age groups over time and underscore the necessity to adequately accommodate the temporal instability and age differences in accident prediction. More studies can be conducted to accommodate the self-selectivity issue and the out-of-sample prediction differences between using the parametric models and non-parametric models.

Se C., Champahom T., Jomnonkwao S., Wisutwattanasak P., Laphrom W., Ratanavaraha V.

Using motorcycle crash data from 2016 to 2019, this paper aims to uncover and compare the risk factors that influence the severity of motorcyclist injuries sustained in daytime and nighttime motorcycle crashes in Thailand. Mixed-ordered probit models with means and variances in heterogeneity were used to take into consideration unobserved heterogeneity. The temporal instability of risk factors was also extensively explored. The results show that male motorcyclists, speeding, fatigue, crashes in work zones, crashes on raised median roads, intersection-related crashes, crashes on wet roads, and crashes on unlit roads are all factors that are positively associated with the risk of death and serious injury in nighttime crashes. The presence of pillions, crashes on two-lane roads, crashes on depressed/flush median roads, crashes in rural areas, U-turn-related crashes, weekend crashes involving heavy vehicles, and head-on crashes are factors that were positively associated with risk of death and serious injury for both daytime and nighttime crashes. This study’s findings provide evidence that factors that influence motorcycle accidents during the daytime and nighttime vary significantly. Additionally, nighttime crashes typically carried a higher risk of fatalities or serious injuries compared to daytime crashes. A discussion of policy recommendations is also provided.

Se C., Champahom T., Jomnonkwao S., Kronprasert N., Ratanavaraha V.

• Determinants of motorcyclist injury severities are studied. • Random parameters logit models with heterogeneity in means and variances are estimated. • Significant differences between weekday, weekend and holiday motorcyclist injury severities are observed. • Factors affecting motorcyclist injury severities have changed over time. • Temporal shift and nontransferability of theses crash types are confirmed by out-of-sample prediction. This paper examines the differences between weekday, weekend, and holiday crashes on the severity of motorcyclist injury using four-year motorcycle crash data in Thailand from 2016-2019. While also considering the temporal stability assessment of significant factors, this study adopted a random parameters logit model with possible heterogeneity in means and variances to account for unobserved heterogeneity. Three levels of motorcyclist injury severity were considered including minor injury, severe injury, and fatal injury. Two series of likelihood ratio tests clearly indicated nontransferability between weekday, weekend, and holiday crashes and substantial temporal instability over the four-year study period. Findings also revealed many statistically significant factors that affect motorcyclist injury severity probabilities in various time-of-year and yearly models. In addition, the prediction comparison results (using out-of-sample prediction simulation) clearly illustrated substantial differences between weekday, weekend, and holiday motorcyclist injury severity probabilities, and substantial changes in each injury predicted probabilities over time. This paper highlights the importance of accounting for day-of-week and holiday transferability and temporal instability with unobserved effects in determinants that affect motorcyclist injury severity. Through nontransferability and temporal instability, the findings provide valuable knowledge for practitioners, researchers, institutions, and decision-makers to enhance highway safety, specifically motorcyclist safety, and facilitate the development of more effective motorcycle crash injury mitigation policies.

Wang C., Ijaz M., Chen F., Zhang Y., Cheng J., Zahid M.

• Differences in factors contributing to injury severity in male and female non-helmet wearing motorcyclist crashes were investigated over a three-year period. • Statistically significant temporal instability and non-transferability of contributors determining male and female non-helmet wearing motorcyclist crashes were revealed. • Out-of-sample prediction was conducted to further examine the temporal instability and non-transferability. With rapid growth in motorcycle use and relatively low helmet-wearing usage rates, injuries and fatalities resulting from motorcycle crashes in Pakistan are a critical concern. To investigate possible temporal instability and differences in the factors that determine resulting injury severities between male and female non-helmet wearing motorcyclists, this study estimated male and female injury severity models using a random parameter logit approach with heterogeneity in means and variances. Motorcycle crash data between 2017 and 2019 from Rawalpindi, Pakistan, were used for the model estimation. With four possible crash injury severity outcomes (injury, minor injury, severe injury, and fatal injury), a wide variety of explanatory variables were considered, including the characteristics of riders, vehicles, roadways, environments, crashes, and temporal considerations. Temporal shifts in the effects of explanatory variables were confirmed using a series of likelihood ratio tests. While the effects of several explanatory variables are relatively temporally stable, those of most variables vary considerably across the years. In addition, out-of-sample simulations underscore the temporal shifts from year to year and the differences between male and female motorcyclist-injury severity. The findings suggest that factors such as effective enforcement countermeasures and relevant educational campaigns can be implemented to reduce injury severity. The statistically significant differences between male and female non-helmeted injury severity models underscore the importance of policies that separately target male and female motorcycle rider safety.

Saini H.K., Chouhan S.S., Kathuria A.

Road accidents are the main leading cause of death, and more than half of people killed in road accidents are motorcyclists, pedestrians, and bicyclists. In developing countries, the share of motorcycles is very high in the traffic stream, which results in an increased number of accidents. Nonetheless, a high share of motorcycles and risky riding behavior of motorcyclists raise notable threats to other road users as well as themselves. Segregating motorcycles from the main traffic stream by providing an Exclusive MotorCycle Lane (EMCL) is reported as one of the strategies to improve motorcyclist's safety and overall road safety. Although EMCLs are successfully running in some Asian countries like Malaysia, Taiwan, and Indonesia, and have reported reducing motorcycle accidents, existing literature related to such lanes is limited and lacks combined contemplation of various design factors. Therefore, a systematic review of studies related to EMCL was carried out in the present paper using the PRISMA approach. The review was majorly divided into the following three categories viz., geometric design elements of EMCL, motorcyclist's flow characteristics on EMCL, and traffic control measures for EMCL to highlight the research lacunas in this field. The present study aims to cast light on the need for specific geometric design standards for EMCL and to assess the safety impact of segregating motorcyclists from other mixed traffic. The review highlights that the design standards for EMCL should be based on the motorcycle's characteristics, as it varies from other vehicle categories in terms of riding behavior and the physical properties of the motorcycle. • EMCL is one of the strategies to reduce motorcycle accidents and improve rider's safety. • A systematic review of evidence from 23 studies of EMCL was conducted using the PRISMA approach. • Geometric design standards and capacity considerations of EMCL are reviewed. • Future research directions to improve the effectiveness of EMCL.

Thongnak N., Kanitpong K., Saitoh T., Lubbe N.

Motorcycle crashes are documented in Thailand's national records but are underreported and lacking detail. In-depth motorcycle crash data, collected by Thailand Accident Research Center (TARC), contains a smaller number of motorcycle crashes but more detail. However, to draw conclusions at a national level, representativeness of the TARC in-depth data is currently unknown, and the correction of sampling biases may be required. In this study, the Capture-recapture method was used to examine the underreporting in the national crash data (from the government insurance company). It was found that 69% of fatal and 70% of non-fatal injuries were underreported, respectively. The in-depth crash data was found to be biased. The weighting methods post-stratification and iterative proportional fitting were applied to compensate for the bias and are shown to improve the representativeness of the in-depth motorcycle crash data. Weighted in-depth crash data appears to be suitable to draw conclusions on motorcyclist safety in Thailand. • This study is to check the representativeness of in-depth motorcycle crash data. • This study is to find weighting methods that can improve the representativeness of in-depth motorcycle crash data. • It was found that 69% of fatal and 70% of non-fatal injuries were underreported, respectively. • The weighting methods were applied to improve the representativeness of the in-depth motorcycle crash data. • Weighted in-depth crash data appears to be suitable to draw conclusions on motorcyclist safety in Thailand.

Yan X., He J., Wu G., Zhang C., Wang C., Ye Y.

• Studied rural overturned and hit-fixed-object crashes caused by speeding driving. • Revealed temporal shifts and non-transferability of these two types of crashes. • Utilized correlated random parameters models with the heterogeneity in the means. • Conducted a comparison between out-of-sample and within-sample prediction. Overturned crashes are associated with a disproportionate number of severe injuries and fatalities, while hit-fixed-object crashes are acknowledged as the most frequent single-vehicle crashes. To investigate the temporal stability and differences of contributing factors determining different injury severity levels in overturned and hit-fixed-object crashes on rural roads accompanied by speeding driving, this paper estimates two groups of correlated random parameters logit models with heterogeneity in the means (one group relating to overturned crashes and the other relating to hit-fixed-object crashes). Three injury-severity categories are determined as outcome variables: severe injury, minor injury and no injury, while multiple factors are investigated as explanatory variables including driver, vehicle, roadway, environmental, and crash characteristics. The overall temporal instability and non-transferability between overturned and hit-fixed-object crashes are captured through likelihood ratio tests. Marginal effects are adopted to further exhibit temporal variations of the explanatory variables. Despite the overall temporal instability, some variables still present relative temporal stability such as alcohol, truck, aggressive driving, vehicle age (>14 years old), and speed limit (

Wang C., Chen F., Zhang Y., Wang S., Yu B., Cheng J.

• Differences in rear-end and non-rear-end crashes are explored over a three-year period. • Statistically significant temporal instability was observed in both rear-end and non-rear-end crashes and the implications are evaluated. • Several targeted countermeasures were provided for preventing rear-end and non-rear-end crashes. Rear-end crashes have become a serious global issue, with increasing injuries and fatalities accounting for massive property loss. The purpose of this study is to investigate the variation in the influence of factors affecting injury severity in rear-end and non-rear-end crashes and the change in impact degree over time. Using the three-year crash data of the Beijing–Shanghai Expressway from 2017 to 2019, the heterogeneity and temporal stability of contributing factors affecting rear-end and non-rear-end crashes were investigated through a group of random parameter logit models with unobserved heterogeneity in means and variances. Then, the temporal stability and transferability of the models were evaluated using likelihood ratio tests. Moreover, the marginal effects were calculated to explore the temporal stability and potential heterogeneity of the contributing variables from year to year. Using four possible injury severity outcomes, namely, fatal injury, severe injury, minor injury, and no injury, a wide variety of possible factors significantly affecting injury severity outcomes including environmental, temporal, spatial, traffic, speed, geometric, and sight distance characteristics were analyzed. Considerable differences were observed in the rear-end and non-rear-end crashes, and the contributing factors indicated statistically significant temporal instability in both crashes over the three-year period. This study can be of value in promoting highway safety aimed at rear-end and non-rear-end crashes and developing suitable safety countermeasures.

Peng Z., Wang Y., Truong L.T.

• A hypothesized four-level structure for triggering taxi crashes was validated. • Individual and combined effects of various factors were identified. • Sleep problems tend to have a greater effect on driving behaviors than fatigue. • The combination of long working hours, sleep problems, and aggressive behaviors resulted in the worst consequence. • Valuable suggestions were provided for the different factors affecting taxi crashes. This study aims to investigate the individual and combined effects of working conditions, physical and mental conditions, and risky driving behaviors on taxi crashes in China. A total of 2,391 taxi drivers from four Chinese cities were invited to participate in a cross-sectional questionnaire survey. The questionnaire collected information on the demographic characteristics, working conditions, physical and mental conditions, risky driving behaviors, and crash frequency of taxi drivers. A Bayesian network (BN) model was developed to explore taxi crashes’ contributing effects. The modelling results showed that the constructed BN model has a reasonable structure and good predictive performance. Eight factors (i.e., driving violations, driving errors, aggressive behaviors, sleep problems, fatigue, age, working hours, and management fees) have significant effects on taxi crashes. Sleep problems showed greater effects on driving behaviors than driver fatigue. The combination of long working hours, sleep problems, and aggressive behaviors would lead to the highest probability of taxi crashes. These results can provide valuable suggestions for the order of safety measures to be taken in response to different risk factors affecting taxi crashes, and are particularly important for the government and industry to make optimal decisions for improving the taxi industry’s safety performance.

Islam M.

Work-zone related crashes in Florida are increasing steadily in recent years. With such growing concern, work-zone is recognized in Florida Strategic Highway Safety Plan. The severity and complexity of motorcycle crashes in work-zones is critically important and worth investigating. However, the resulting effect of work-zone on motorcyclists' injuries in work-zone crashes is not fully understood. The purpose of study is to identify the contributing factors of motorcyclists' injury severity sustained in the work-zone crashes in Florida. Recognizing the relatively higher risk of motorcyclists in work-zones with respective to non-work-zones, this study further uncovers the contributing factors for single- and multi-vehicle motorcycle crashes in Florida work-zones. This study investigated motorcyclists' injury severity applying random parameter multinomial logit with possible heterogeneity in means and variances of the random parameters for single-motorcycle and multi-vehicle motorcycle crashes. This study utilizes the Crash Analysis Reporting (CAR) system in Florida over a period of five years from 2012 to 2016 (inclusive). The model result indicates a complex relationship between dark condition, old-aged motorcyclist (50–65), requirement and absence of endorsement, partial ejection, straight roadway segment, shoulder width (up to 1.22 m (4 ft), and 2.74–3.66 m (9–12 ft), urban interstate, activity area, and lane closure and work on shoulder-median work-zone types. The effect of work-zone on single-motorcycle crashes tends to have much more in resulting injury severities relative to multi-vehicle motorcycle crashes. It is more important to investigate the injury severity by single- and multi-vehicle crashes involving motorcycles in work-zones. These risk factors identified in the study are expected to provide more insights for the countermeasures specific to engineering (roadway design) and policy (motorcycle training), which can be considered to improve motorcycle safety in Florida. • Motorcycle crashes in Florida work zones are analyzed with mixed logit with heterogeneity in means and variances. • Injury severity of single- and multi-motorcycle crashes in work zones is analyzed with the unobserved heterogeneity. • Injury severity analysis for single- and multi-motorcycle crashes in work zones are conducted separately. • Targeted safety countermeasures for motorcycle safety in work zones are proposed.

Se C., Champahom T., Jomnonkwao S., Ratanavaraha V.

In Thailand, the motorcyclist mortality rate is steadily on the rise and remains a serious concern for highway administrators and burden on both economic and local people. Using motorcycle-crash data in Thailand from 2016 to 2019, this study empirically employed and compared the Artificial Neural Networks (ANN) model and random parameters binary probit model with heterogeneity in means and variances (RPBPHM) to explore the effects of a wide range of associated risk characteristics on the severity outcomes of the motorcyclist. Study results revealed that probabilities of injury or fatal crash increase for crashes that involve male riders, riding with pillion, speeding, improper overtaking, riders under influence of alcohol, fatigue riders, undivided road and so on. The probability of non-injury crash increases for crashes on main or frontage traffic lane, four-lane road, concrete road, during rain, involving collision with other motorcycles, rear-end crashes, sideswipe crashes, single-motorcycle crashes and crashes within urban areas. The RPBPHM models were found to outperform the ANN model (quadratic support vector machine) in all performance metrics. The findings could potentially assist policymaker, safety professionals, practitioners, trainers, government agencies or highway designers in future planning and serve as guidance for mitigation policies directed at safety improvement for motorcyclists.

Alnawmasi N., Mannering F.

• Impacts of speed limits increases on the likelihood and severity of crashes is assessed. • Random parameters crash count and injury severity models are estimated before and after speed limit increase. • Temporal shifts in the effects of explanatory variables complicate the assessment of speed limit increases. • The overall effects of the speed limit are modest with only a significant increase in likelihood of rollover crashes. In recent years, US States have raised their maximum interstate speed limits from 70 mi/h to 75 mi/h, 80 mi/h and even 85 mi/h. However, understanding the effect that these higher speed limits have had on the frequency and severity of crashes using traditional before and after analyses has been difficult due to possible temporal shifts in driver behavior, and potential changes in vehicle safety technology and highway safety features. Using multi-year data from before and after higher speed limits were instituted on Kansas freeways, random parameters models of crash frequency and resulting injury severity were estimated. Regarding the frequency of crashes, the findings showed that the higher speed limits did not have a significant effect in the mean number of crashes on the 253 studied roadway segments. For injury severity, model-estimation results in one- and two-vehicle crashes show that the factors affecting driver-injury severities have changed before and after the speed limit increase, but changes were also observed in the years before the speed limit increases and the years after. However, using pre-speed-limit-increase model estimation results to predict post-speed-limit-increase injury-severity distributions it was found that the aggregate effect of the changing influences of explanatory variables on average injury severities was relatively small. While the injury-severity estimation results make it difficult to attribute any temporal shifts in parameter values to the increased speed limit, there was a significant increase in the probability of rollover crashes that suggests the higher speed limits may have had some contributory effect on injury severities in single-vehicle crashes.

Alnawmasi N., Mannering F.

• Changes in distracted driver injury severities are analyzed. • Random parameters and latent class models are estimated. • Statistically significant temporal shifts in parameter estimates are found. • Out-of-sample simulations are conducted to predict injury probabilities. • Simulations show distracted driving injuries have become less severe over time. This study explores temporal shifts in the effects of explanatory variables on the injury severity outcomes of crashes involving distracted driving. Using data from distracted driving crashes on Kansas State highways over a four-year period (from 2014 to 2017 inclusive), separate yearly models of driver-injury severities (with possible outcomes of severe injury, minor injury, and no injury) were estimated using two alternate modeling approaches to account for possible unobserved heterogeneity: a latent-class multinomial logit with class probability functions and a random parameters logit with possible heterogeneity in the means and variances of random parameters. Likelihood ratio tests were conducted to determine if model parameter estimates have shifted over time. A wide range of variables were found to statistically influence driver-injury severities and the findings show that were statistically significant temporal shifts in parameter estimates in both the random parameters and latent class modeling approaches. These shifts are likely the result of changes in driver behavior, improvements in vehicle and highway safety features, changes in communication technologies, and other temporally shifting trends. However, while out-of-sample simulations show that the two modeling approaches both indicate that distracted driving crashes have become less severe over time, the alternate approaches produced substantially different injury-severity predictions, suggesting the need for future research to explore how unobserved heterogeneity can best be modeled in temporal contexts.