Search Results (32)

Despite growing policy support for active travel, the fatality rate of vulnerable road users has remained persistently high in recent years, while the emergence of autonomous vehicles has further increased the complexity of mixed traffic environments. Interactions between cyclists and motorized vehicles are a major contributor to these fatalities, highlighting the urgent need for effective cyclist protection strategies. As one of the most widely adopted active transport modes, cycling safety cannot be assessed solely through crash statistics; understanding cyclists’ perceived safety is equally critical, as it reflects how infrastructure design and dynamic traffic conditions influence cycling behavior. In this study, we propose a cyclist safety perception framework that combines vision–language models with interpretable machine learning to analyze perceived safety in mixed traffic scenarios. A vision–language model is employed to generate semantic descriptions of traffic scenes, while an Explainable Boosting Machine quantifies both individual and interactive contributions of traffic-related features. By integrating visual information with road attributes extracted from OpenStreetMap, the proposed framework achieves a binary safety classification accuracy of 71% and a mean absolute error of 1.01 on a safety score scale ranging from 1 to 9. The results demonstrate the potential of combining multimodal perception and explainable models to support cyclist-centered safety assessment and inform sustainable and intelligent transportation system design. More specifically, the results show that protected cycling infrastructure is the most significant factor in improving perceived safety, whereas road construction has the opposite effect. Full article

Seatbelt use is well established as a life-saving measure. Nevertheless, many drivers and passengers continue to neglect seatbelt use. This study examines the risks associated with unrestrained occupants involved in motor vehicle crashes. Using data from the Fatality Analysis Reporting System from 2000 to 2018, the relative risk of fatal traffic accidents for unrestrained vehicle occupants in the United States was estimated using the maximum likelihood estimation method. The findings indicate that unrestrained passengers make up about 12% of all passengers on the road and face a roughly 4.3 times greater likelihood of fatality in severe crashes. Additionally, unrestrained drivers, whose higher risk profiles are linked not only to their lack of restraint but also to broader patterns of hazardous driving behavior, account for over 8% of all drivers and exhibit a risk approximately 5.4 times higher in causing fatal crashes compared to restrained drivers. The findings of this study reveal the prevalence and consequences of unrestrained vehicle occupants and supports ongoing efforts to promote seatbelt utilization and bolster road safety protocols. By doing so, we can alleviate the burden of preventable injuries and fatalities on individuals, families, and society at large, thus fostering a safer and more secure transportation environment for all. Full article

Motor vehicle crashes are a persistent cause of unintentional deaths in the United States. Scholarship on how manmade interventions and natural phenomena interact to effectuate such calamitous outcomes is longstanding. One manmade intervention of interest in the literature is daylight saving time (DST). Unfortunately, results on how the natural phenomena attributable to DST interact with driver behavior are inconsistent. To advance knowledge on DST-safety interactions, this study adopts a multilevel model approach to fatal motor vehicle crash outcomes in the contiguous United States. Results from a national analysis contextualize results from zonal analyses to unmask within- and between-time zone differences in DST-safety interactions. In the national analysis, motor vehicle crash fatalities decrease somewhat during DST (−0.10%). In the zonal analyses, motor vehicle crash fatalities decrease more so in the Central and Eastern time zones (−2.00% and −2.00%, respectively), but increase somewhat in the Pacific and Mountain time zones (+0.30%) during DST. The spatiotemporal context of the national analysis highlights specific policy implications from the zonal analyses to decrease the lethality of motor vehicle crashes. Specifically, interdictions to target alcohol and/or drug involvement in the northern latitudes of the Pacific and Mountain time zones during DST, the Central time zone at dawn or dusk before or after DST, and the northern latitudes in the Eastern time zone before or after DST are important. Generally, national DST-safety benefits mask zonal DST-safety costs in the Pacific and Mountain time zones. Full article

Roadway mortality increased during COVID-19, reversing a multi-decade downward trend. The Fatality Analysis Reporting System (FARS) was used to examine contributing factors pre-COVID-19 and in the COVID-19 era using the five pillars of the Safe System framework: (1) road users; (2) vehicles; (3) roadways; (4) speed; and (5) post-crash care. Two study time periods were matched to control for seasonality differences pre-COVID-19 (n = 1725, 1 April 2018–31 December 2019) and in the COVID-19 era (n = 2010, 1 April 2020–31 December 2021) with a three-month buffer period between the two time frames excluded. Four of the five pillars of the safe system had road safety indicators that worsened during the pandemic. Mortality was 19.7% higher for motor vehicle occupants and 45.1% higher for riders of motorized two-wheeled vehicles. In adjusted analyses, failure to use safety equipment (safety belts/helmets) was associated with 44% higher mortality. Two road user groups, non-motorized bicyclists and pedestrians, did not contribute significantly to higher mortality. Urban roadway crashes were higher compared to rural crashes. Additional scientific inquiry into factors associated with COVID-19-era mortality using the Safe System framework yielded important scientific insights to inform prevention efforts. Motorized two-wheeled vehicles contribute disproportionately to pandemic-era higher mortality and constitute an emerging road safety issue that deserves further attention. Full article

Traffic crashes significantly contribute to global fatalities, particularly in urban areas, highlighting the need to evaluate the relationship between urban environments and traffic safety. This study extends former spatial modeling frameworks by drawing paths between global models, including spatial lag (SLM), and spatial error (SEM), and local models, including geographically weighted regression (GWR), multi-scale geographically weighted regression (MGWR), and multi-scale geographically weighted regression with spatially lagged dependent variable (MGWRL). Utilizing the proposed framework, this study analyzes severe traffic crashes in relation to urban built environments using various spatial regression models within Leon County, Florida. According to the results, SLM outperforms OLS, SEM, and GWR models. Local models with lagged dependent variables outperform both the global and generic versions of the local models in all performance measures, whereas MGWR and MGWRL outperform GWR and GWRL. Local models performed better than global models, showing spatial non-stationarity; so, the relationship between the dependent and independent variables varies over space. The better performance of models with lagged dependent variables signifies that the spatial distribution of severe crashes is correlated. Finally, the better performance of multi-scale local models than classical local models indicates varying influences of independent variables with different bandwidths. According to the MGWRL model, census block groups close to the urban area with higher population, higher education level, and lower car ownership rates have lower crash rates. On the contrary, motor vehicle percentage for commuting is found to have a negative association with severe crash rate, which suggests the locality of the mentioned associations. Full article

Human factors play a huge role in road traffic safety. Research has found that a huge proportion of traffic crashes occur due to some form of human error. Improving road user behavior has been the major strategy that has been emphasized for improving road traffic safety. Meanwhile, despite the training efforts, and testing for drivers, the global status of road traffic safety is alarming. This research highlights the seriousness of human factors on road traffic safety and provides actionable strategies to greatly reduce the negative impact of human factors on road traffic safety. Motor vehicle safety data that were made available online by the U.S. Bureau of Transportation Statistics were reviewed to evaluate the severity of traffic collisions. To evaluate the extent of human factors in motor vehicle traffic fatalities, data for Canadian motor vehicle traffic collision statistics were reviewed. The study confirms that human factors (such as driver distraction, fatigue, driving under the influence of drugs and alcohol etc.) play a huge role in road traffic fatalities. The need for a reasonable degree of automation to help reduce the impacts of human factors on road safety and recommendations aimed at providing widespread support for a reasonable degree of automation systems in driving tasks are presented. Actionable strategies that can be implemented by policymakers to reduce global road traffic fatalities are also presented. Full article

Motor vehicle crashes (MVCs) are the leading cause of fatal work-related injuries in the United States. Research assessing sociodemographic risk disparities for work-related MVCs is limited, yet structural and systemic inequities at work and during commutes likely contribute to disproportionate MVC risk. This paper summarizes the literature on risk disparities for work-related MVCs by sociodemographic and employment characteristics and identifies worker populations that have been largely excluded from previous research. The social–ecological model is used as a framework to identify potential causes of disparities at five levels—individual, interpersonal, organizational, community, and public policy. Expanded data collection and analyses of work-related MVCs are needed to understand and reduce disparities for pedestrian workers, workers from historically marginalized communities, workers with overlapping vulnerabilities, and workers not adequately covered by employer policies and safety regulations. In addition, there is a need for more data on commuting-related MVCs in the United States. Inadequate access to transportation, which disproportionately affects marginalized populations, may make travel to and from work less safe and limit individuals’ access to employment. Identifying and remedying inequities in work-related MVCs, whether during the day or while commuting, will require the efforts of industry and multiple public sectors, including public health, transportation, and labor. Full article

Due to the number of severe traffic collisions involving motorcycles, a comprehensive investigation is required to determine their causes. This study analyzed Texas crash data from 2017 to 2021 to determine who was at fault and how various factors affect the frequency and severity of motorcycle collisions. Moreover, the study tried to identify high-risk sites for motorcycle crashes. Utilizing bivariate analysis and logistic regression models, the study investigated the individual and combined effects of several variables. Heat maps and hotspot analyses were used to identify locations with a high incidence of both minor and severe motorcycle crashes. The survey showed that dangerous speed, inattention, lane departure, and failing to surrender the right-of-way at a stop sign or during a left turn were the leading causes of motorcycle crashes. When a motorcyclist was at fault, the likelihood of severe collisions was much higher. The study revealed numerous elements as strong predictors of catastrophic motorcycle crashes, including higher speed limits, poor illumination, darkness during the weekend, dividers or designated lanes as the principal road traffic control, an increased age of the primary crash victim, and the lack of a helmet. The concentration of motorcycle collisions was found to be relatively high in city cores, whereas clusters of severe motorcycle collisions were detected on road segments beyond city limits. This study recommends implementing reduced speed limits on high-risk segments, mandating helmet use, prioritizing resource allocation to high-risk locations, launching educational campaigns to promote safer driving practices and the use of protective gear, and inspecting existing conditions as well as the road geometry of high-risk locations to reduce the incidence and severity of motorcycle crashes. Full article

Although the risks faced by passengers in near-side lateral collisions are understood, and despite the presence of side airbags for injury prevention, passengers involved in far-side lateral collisions also suffer serious and fatal injuries. The objective of this study was to determine the independent predictive factors of fatality of motor vehicle passengers involved in far-side lateral collisions. Using 2010 records from the National Automotive Sampling System/Crashworthiness Data System (NASS/CDS), we selected 86 fatal and 325 non-fatal passengers with an Abbreviated Injury Scale (AIS) score of 2 or more. The background and injury severity of the passengers and collision characteristics were compared between the two groups. In a multivariable logistic regression analysis, variables independently associated with fatalities were female sex (Ref, male) (odds ratio [OR], 0.396), age (OR, 1.029), body mass index (OR, 1.057), total delta-V (OR, 1.031), head AIS score (OR, 1.679), chest AIS score (OR, 1.330), and abdomen AIS score (OR, 1.294). This is the first report to determine factors affecting fatality in passengers involved in far-side lateral collisions. Improving the safety of the vehicle interior, such as by including additional seatbelt systems or a side airbag that deploys between seats, might help to avoid fatalities, and reduce injury severity. Full article

Some old-order Anabaptist communities rely on animal-drawn vehicles for transportation and farm work. This research examines reports involving horse-drawn vehicles found in the AgInjuryNews dataset, which provides a publicly accessible collection of agricultural injury reports primarily gathered from news media. The goals of this research are to characterize the reports and to compare results with previous research to assess the utility of using AgInjuryNews to examine horse-drawn vehicle incidents. A total of 38 reports representing 83 victims were identified. Chi-square tests comparing victim and incident traits for fatal and nonfatal injuries were significant for the victim’s role in the incident, vehicle type, presence of a motor vehicle, rear-ending by a motor vehicle, spooked horses, a victim being run over or struck by a vehicle, and a victim being ejected or falling from a vehicle. Additional analysis of incidents involving horse-drawn farm equipment showed that a significantly higher proportion of off-road incidents were fatal compared to on-road incidents. The proportion of fatal injuries in the AgInjuryNews dataset was approximately 10 times higher than observed in a study using Pennsylvania Department of Transportation (DOT) data. Compared to previous research, the AgInjuryNews reports contained a higher proportion of incidents where a motor vehicle rear-ended a horse-drawn vehicle, and fewer cases of horse-drawn vehicles being struck by motor vehicles while crossing or entering a main road and making left turns. Reports of buggy crashes found in AgInjuryNews differed from those found in a Nexis Uni search in that the bulk of the articles from Nexis Uni referred to cases involving criminal charges for impaired driving or hit-and-run crashes. While it is evident that the reports included in the sample are incidents that media sources find compelling rather than comprehensive injury surveillance, it is possible to gain new insights using the AgInjuryNews reports. Full article

Fatal, pedestrian-involved, motor vehicle collisions are increasing in the United States yet remain lower in rural states such as West Virginia. This study’s purpose was to investigate the overall risk factors of pedestrian fatalities by rurality and sex in West Virginia. Data were obtained from the Fatality Analysis Reporting System. The fatality had to occur within West Virginia between 1 January 2009 and 31 December 2019. Risk factors of rural vs. urban and male vs. female crashes were determined using multivariable logistic regression models. Clustering of crash locations was analyzed using kernel density estimation and Ripley’s K. Among the 254 fatalities, most victims were male (70%). Most crashes occurred at night (76%), on highways (73%), on level (71%), non-curved (84%), dry (82%) roads during fair weather conditions (82%). Nearly 34% of the victims tested positive for alcohol. Men were 2.5 times as likely to be hit in a rural area (OR = 2.5; 95% CI 1.2, 5.4), on curved roads, and 57% less likely (OR = 0.43; 95% CI 0.2, 0.9) to test positive for drugs compared to women. Crash characteristics, including location, were similar between the sexes. As many risk factors were modifiable behaviors, public health interventions to ensure pedestrian safety may be necessary. Full article

Recent years have witnessed an increasing number of electric bicycles on the roads and a rise in the number of road crashes involving e-bicyclists. There are various causes of road crashes involving e-bicyclists. Out of the total number of fatalities in traffic, bicyclists account for 9% in the Republic of Serbia. Road crashes occurring when motor vehicles overtake bicyclists make up 13% of the total number of road crashes involving bicyclists. Having in mind the above-mentioned, an experimental study has been conducted in order to analyze whether the use of helmets and reflective vests, different vehicle categories, and the speed of electric bicycles affect the lateral distance when overtaking e-bicycles. This research analyzed the lateral distance of 1228 vehicles overtaking an e-bicyclist. There are statistically significant differences in the lateral distance when overtaking an e-bicycle regarding helmet use, different vehicle categories overtaking the e-bicycle, and different speeds of the e-bicycle. The results showed that a faster speed of an e-bicycle led to a shorter lateral distance when overtaking it and that SUV drivers (along with motorcycle drivers) had the shortest lateral distance when overtaking e-bicycles. Full article

Despite an observed daytime front-seat seat belt use that exceeds 90%, nearly half of motor vehicle occupants who die in New York State (NYS) each year are not wearing a seat belt. Crash outcomes were examined by occupant, vehicle, environmental and traffic enforcement patterns related to the annual Click It or Ticket high visibility seat belt enforcement campaign. Three periods of enforcement were examined: pre-enforcement, peri-enforcement (during/immediately after), and post-enforcement. Of the 14.4 million traffic citations, 713,990 (5.0%) were seat belt violations. Relative risk with 95% CI was assessed using deaths from the Fatality Analysis Reporting System (FARS) and SAS Glimmix 9.4 software. Mortality was lower peri-enforcement (32.9%) compared to pre- (40.9%) or post-enforcement (37.1%) (p < 0.001) and tended to be elevated in low enforcement response areas (43.6%). Fatalities were 30% lower (0.7, 95% CI 0.6–0.9) during peri-enforcement in models adjusted for demographics, law coverage, enforcement response, rural, weekend, impairment, speeding, and vehicle type. Adjusted mortality was higher in rural (1.9, 1.6–2.6), alcohol-involved (1.8, 1.4–2.9), and speeding-involved (2.0, 1.7–2.5) crashes. Peri-enforcement alcohol- and speed-involved fatalities tended to be lower in restrained, unrestrained and occupants missing belt status. The finding of lower mortality in both belted and unbelted occupant’s peri-enforcement—in the context of fewer fatal speed and alcohol-involved crashes—suggests that the mechanism(s) through which high visibility seat belt enforcement lowers mortality is through impacting multiple risky driving behaviors. Full article

Motor vehicle crashes (MVC) cause over three million people to be nonfatally injured each year in the United States alone. We investigated trends and patterns in prescription opioid usage among nonfatal MVC injuries in 50 states in the US and the District of Columbia from 2014 to 2018. All emergency department visits for an MVC event (N = 142,204) were identified from the IBM^® MarketScan^® Databases. Using log-binomial regression models, we investigated whether the prevalence of prescription opioids in MVC injuries varied temporally, spatially, or by enrollees’ characteristics. Adjusting for age, relationship to the primary beneficiary, employment status, geographic region, and residence in metropolitan statistical area, the prevalence decreased by 5% (95% CI: 2–8%) in 2015, 18% (95% CI: 15–20%) in 2016, 31% (95% CI: 28–33%) in 2017, and 49% (95% CI: 46–51%) in 2018, compared to 2014. Moreover, the prevalence decreased by 28% (95% CI: 26–29%) after the publication of the CDC Guidelines for Prescribing Opioids for Chronic Pain. Spatial variations were observed in the prevalence and temporal trend of prevalence. The decreasing trend in the prevalence of prescription opioids in MVC is consistent with the decrease in the dispensing rate of opioids and the percentage of high-dosage opioids in the study population. Full article

When traffic collisions occur on urban expressways, the consequences, including injuries, the loss of lives, and damage to properties, are more serious. However, the existing research on the severity of expressway traffic collisions has not been deeply explored. The purpose of this research was to investigate how various factors affect the severity of urban expressway collisions. The severity of urban expressway collisions was set as the dependent variable, which could be divided into three categories: slight collisions, severe collisions, and fatal collisions. Ten variables, including individual characteristics, collision characteristics, and road environment conditions, were selected as independent factors. Based on 975 valid urban expressway collisions, an ordered logistic regression model was established to evaluate the impacts of influence factors on the severity of these crashes. The results show that gender, collision modality, road pavement conditions, road surface conditions, and visibility are significant factors that affect the severity of urban expressway collisions. Females were more likely to be involved in more severe urban expressway collisions than males. For collisions involving pedestrians and non-motorized vehicles, the risk of more severe injury was 7.508 times higher than that associated with vehicle–vehicle collisions. The probability of more severe collisions on urban expressways with poor pavement conditions and wet surface conditions is greater than that on urban expressways with good pavement conditions and dry surface conditions. In addition, as visibility increases, the probability of more severe collisions on urban expressways gradually decreases. These results provide more effective strategies to reduce casualties as a result of urban expressway collisions. Full article