Crash Involvement Research Articles

Is a Driver's history of drunk driving and other traffic offenses linked to subsequent drunk driving and traffic crashes? A case study of Taiwan.

Crashes involving alcohol-impaired driving or driving under influence (DUI) are more likely to increase crash probability and severity. Many countries have adopted increasingly stringent policies in curbing DUI. Nevertheless, more and more studies show that while the total number of DUIs has reduced as a whole, DUI recidivism remains challenging. As such, this study seeks to research into whether it is possible to identify frequent DUI recidivists based on their traffic offense history, so that effective countermeasure could be put in place and in time. This study proposes using the drivers' traffic offense history and length of duration between two DUIs, the duration of re-offending, to identify frequent DUI recidivists. This approach is not only widely adopted in public health, but is also flexible in accommodating many modeling issues such as data censoring, recurrent events, and the inclusion of time-varying covariates to address questions like whether the probability of recidivism increases or decreases with subsequent DUI offenses or other traffic offenses or violations. Our major results show that: (1) For all drivers caught for a DUI, 10 % of them would be caught for another DUI within a year; (2) In contrast, the same one-year recidivism probability for those who accumulated two DUIs and two run-the-red-light could be as high as 17 %; (3) Each subsequent DUI increased the probability of a further DUI offense by 57 %; and (4) Each additional DUI offense was associated with 45 % increase in probability of being involved in a crash involving DUI. Overall, there are clear links between a driver's history of traffic offenses, DUI recidivism, and crash involvement, which could provide valuable information for authorities to profile potential recidivists and apply preventative measures in advance to reduce DUI-related crashes.

Substance use and driver fatality in Norway: An expanded case-control study.

Using alcohol or psychoactive drugs before driving a motor vehicle may increase the risk of crash involvement, injury, and death. This is better documented for alcohol than for drugs. The aim of this study was to expand a previous case-control study on substance use and driver fatality by doubling the number of cases and controls, and hence improve the statistical power and enable the analysis of combined substance use. We collected data on alcohol and drug use from all 1197 drivers of cars and vans who were fatally injured in road traffic crashes in Norway between 2005 and 2020 ('cases') by analyzing blood samples or reviewing other information on substance use. We also collected data on alcohol and drug use among 17,219 drivers in random road traffic ('controls') by analyzing oral fluid samples. Substance use was converted to dichotomous variables (no use/use). We used unconditional logistic regression to estimate adjusted odds ratios (aORs) with 95% confidence intervals (CIs) of driver fatality for mutually exclusive substance groups, adjusted for sex, age, geographic region, urban centrality class, and time interval of the week. Compared to no substance use, the aOR (95% CI) for driver fatality was for alcohol 91 (61-137), stimulants (primarily amphetamines) aOR 22 (9-56), benzodiazepines and z-hypnotics (BZDs) aOR 4.0 (2.7-5.9), tetrahydrocannabinol (THC) aOR 3.4 (1.7-6.7), and opioids aOR 1.4 (0.4-4.9). The aOR for any polysubstance use was 168 (96-297). The combinations of BZDs with stimulants or THC were associated with markedly higher aORs for driver fatality than the use of single substance groups. Alcohol and polysubstance use are the most important predictors of fatal injury, followed by stimulants.

Self-reported drink driving, enforcement, crashes, and crash reporting: A 6-country comparison

Objective The objective of this study was to compare drink driving and related road safety issues in 2 urban areas of 6 countries and develop an equation for estimating the rate of crash underreporting to the police in urban areas of countries that lack this information. Methods This study is a secondary analysis of 1 to 2 waves of surveys in pairs of matched medium-sized cities in Belgium, Brazil, China, Mexico, South Africa, and Ohio, United States; the surveys supported evaluation of local alcohol harm reduction efforts. Data were from 2017 to 2019 except 2023 for Mexico. Mailed surveys in Ohio and household interviews elsewhere of quota samples matched to census data yielded 23,240 completed interviews. Relevant questions covered drinking, driving under the influence of alcohol (DUI), DUI enforcement, and, except in South Africa, road crashes. GLM regression provided an equation for estimating police reporting rates of urban injury and no-injury crashes from a country’s purchasing-power parity–adjusted gross domestic product (GDP) per capita. Results The percentage of drivers driving unlicensed was 30% in Mexico and South Africa, 15% in Brazil, 8% in China, and <1% elsewhere. Among adults who both drove and drank, self-reported urban DUI rates ranged from 12% in China to 53% in South Africa, with 4 countries between 18% and 26%. Among those reporting DUI, the percentage stopped by police for doing so was 14% in Belgium, 15% in Brazil, 25% in China, 31% in Mexico, 45% in South Africa, and only 3% in Ohio. The surveys yielded data on 380 urban crashes. Past-year crash involvement was 2% to 3% in Belgium and China and 5% to 6% elsewhere. The 10% injury rate in Ohio crashes was significantly below the 24% to 35% rates elsewhere. Injury crashes were almost universally reported except in Brazil (60% reported). Only 49% to 56% of non-injury crashes were reported, except in Ohio (73%). Perceived alcohol-involved crash rates of 18% to 19% in Belgium and Ohio were significantly lower than the 32% reported in Brazil, 41% in China, and 57% in Mexico. In the regression, GDP per capita and injury involvement were positively associated with police crash reporting. Conclusions Our equation more closely approximates urban police crash reporting rates than prior studies that assumed that they matched U.S. data. DUI enforcement is weak/ineffective in urban Ohio. With suggested adjustments, our survey questions should be usable in other international road safety and DUI studies.

Aggression of electric bike riders in China: comparisons of the Cycling Anger Expression Inventory toward drivers, pedestrians, and other riders

ABSTRACT Electric bikes (e-bikes) account for an unexpected proportion of traffic crash injuries and deaths in China. There is an urgent need to study the factors influencing the aggressive behaviours of e-bike riders and reduce their potential involvement in crashes. In addition, aggression varies when directed at different types of road users, particularly when expressed by vulnerable groups. This study aimed to validate the Cycling Anger Expression Inventory (CAX) for e-bikers and explore whether the expression of aggression in e-bikers differs depending on the recipients, such as drivers, pedestrians, or other riders. The analysis examined the aggression specificity of e-bikers by employing tests of measurement invariance (MI). These findings indicate that adaptive/constructive expression has emerged as a mainstream strategy for managing e-biker anger. E-bikers exhibited the highest levels of aggression toward drivers. These results provide a strong basis for the prevention and intervention of aggression and accidents among Chinese e-bikers.

An investigation of relationships between aberrant driving behavior and crash risk among long-haul truck drivers traveling across India: A Structural Equation Modeling approach

IntroductionRoad Traffic Crashes (RTC) are showing an increasing trend around the world. Empirical evidence suggests that the majority of the crashes are attributed to unsafe or dangerous driving behaviors among drivers. However, little is known about the crash risk among professional drivers such as Long-Haul Truck Drivers (LHTDs) considering aberrant driving behaviors in developing countries like India. Objectives: This study aims to investigate the direct effects of characteristics of LHTDs including socio-demographic, work and vehicle, health-related lifestyle on crash risk. This study also attempts to investigate the indirect impacts of socio-demographic characteristics on crash involvement among LHTDs mediated through aberrant driving behaviors. MethodsUsing cross sectional study design, face-to-face interviews were conducted among LHTDs in Salem city, Tamil Nadu, India. A Driver Behavior Questionnaire (DBQ) consisting of 23 items was utilized to measure aberrant driving behaviors among LHTDs and information related to background variables was also collected. A total of 756 valid samples were used for analysis purpose. Exploratory factor analysis confirmed a four-factor solution including errors, lapses, ordinary, and aggressive violations and the identified structure was validated using confirmatory factor analysis. The deployment of Structural Equation Model (SEM) enabled identification of interrelationships among identified latent and observed variables. Results: The developed SEM model showed that all the identified four latent constructs were positively associated with crash involvement among LHTDs. The results further revealed that age and marital status were found to exhibit an indirect impact on crash involvement in addition to direct effects. ConclusionThe findings from this study could serve road safety authorities and Indian trucking industries to target risky driving behaviors in order to develop engineering and interventional countermeasures.

The effectiveness and efficacy of driving interventions with ADHD: a Dutch perspective

The diagnosis of attention deficit hyperactivity disorder (ADHD) has been identified as a factor associated with an increased risk of involvement in car crashes. As a result, individuals in the Netherlands who are diagnosed with ADHD are mandated to undergo a psychiatric evaluation before obtaining their driving licence, optionally complemented with a driving test. Recent research has, however, demonstrated that 96% of individuals pass this procedure and can drive unrestrictedly, suggesting that current regulations have a limited impact and that a different regulatory approach may be warranted. This paper addresses three such potential interventions, exploring the scientific basis of implementing mandatory behavioural training programmes, the mandatory installation of driver monitoring systems, and temporary driving restrictions. To initiate this exploration, an analysis is made of the body of literature pointing towards a subpar driving performance in those with ADHD, accompanied by a discussion of the underlying symptoms and behaviours contributing to these findings. Furthermore, between- and within-individual factors affecting ADHD driving performance are reviewed. This examination illuminates a consistent pattern of substandard driving performances among those with ADHD, whereby the period shortly post-licensure stands out as a focal point for regulatory approaches. Following these results, the three potential driving interventions are reviewed to discern their impact on road safety when implemented specifically for drivers with ADHD. Corresponding studies suggest that all these interventions hold promise in improving driving performances, but the analysis is limited by the scarcity of long-term, ADHD-specific research. The paper concludes by discussing the feasibility of these ADHD-specific driving interventions, weighing their potential benefits, e.g., reduced crash rates, along with their associated costs, such as potential stigma and hindrance in societal integration and participation. Additionally, avenues for future research in these domains are outlined.

Sociodemographic and psychological factors affecting motor vehicle crashes (MVCs): a classification analysis based on the contextual-mediated model of traffic-accident involvement

The study aimed to determine the sociodemographic and psychological profiles of drivers with a history of motor vehicle crashes (MVCs), following the contextual-mediated model of crash involvement, and trying to define similarities and differences with drivers without MVCs. Although road trauma prevention has become a central public health issue, the study of psychological determinants of MVCs does not have consistent results due to methodological and theoretical weaknesses. Three-hundred and forty-five active drivers (20% females) completed an extensive office-based fitness-to-drive evaluation including measures of cognition, personality, self-reported driving-related behaviors, attitudes, as well as computerized measures of driving performance. The Classification and Regression Tree method (CART) was used to identify discriminant predictors. The classification identified several relevant predictors; the personality trait of Discostraint (as a distal context variable; cut-point: 50 T points) and motor speed (as a proximal context variable; cut-point: 64 percentile ranks). The global classification model increased approximately 3 times the probability of identifying people with a history of MVC involvement, starting from an estimated prevalence of being involved in an MVC in a period of five years in the population of active drivers. Consistent with the ‘contextual-mediated model of traffic accident involvement’, the results of the present study suggest that road trauma analysis should focus on both distal and proximal driver-related factors by paying attention to their association in determining MVCs. These results represent a valuable source of knowledge for researchers and practitioners for preventing road trauma.

Fatal crashes involving vehicles with driver warning systems: Identifying risk factors using a correlated random parameters ordered logit modeling approach

Recent advancements in vehicular technology are expected to enhance traffic safety by either warning the drivers or by automating the tasks related to driving to reduce the human driver's involvement. The driver warning systems (DWSs) are designed to warn drivers in unsafe situations such as forward collision, lane departure, or when changing lanes with vehicles in blind spot areas. Although these features are designed to enhance safety, recent crash data shows vehicles with these features are still getting involved in crashes, making it necessary to identify the contributing factors. Further, it also requires research to quantify the benefits of vehicles with one or multiple DWS in terms of safety during multivehicle crashes. This study presents a methodological framework to compare factors affecting fatal crashes involving vehicles with no, one and two DWSs. A three-step method is proposed to incorporate unobserved heterogeneity while modeling. Fixed parameter and correlated random parameter order logit models are employed. The results shows that correlated random parameters ordered logit model outperforms traditional fixed parameter ordered logit model. Vehicles equipped with DWSs are safer than vehicles without DWSs during wet or snowy road conditions, when the vehicle skids laterally or longitudinally, and at intersections. Vehicles with one or both DWSs can reduce drink-and-drive and speeding-related crash involvement than vehicles without DWSs. Female and elderly drivers are at a higher risk while driving a vehicle with one or both DWSs compared to driving a vehicle without DWSs, demanding vehicular modifications.

Does a cautious driving style reduce the crash risk of older drivers? An analysis using a novel driving style recognition method

Older drivers who are aware of their declining functions tend to adopt a cautious driving style to compensate for their declining driving abilities. However, whether cautious older drivers are associated with a reduced crash risk has not been well studied. In this study, we examined the association between older drivers’ cautious driving style and crash risk using a novel driving style recognition method. We proposed a driving style recognition method that does not require predefined thresholds and applied it to the driving data of 71 drivers comprising 59 drivers aged 65 years or older (mean age 72.4; 67.8 % male) and 12 drivers aged 51–64 years (mean age 58.3; 66.7 % male). Drivers were classified into cautious and relatively aggressive groups based on the classification results of their speed, acceleration, and braking styles. The results showed that cautious drivers were characterized by older age, poorer Trail Making Test Part B performance, less frequent night driving, and lower driving exposure, indicating that older drivers may adopt multiple compensatory strategies. Although the crash involvement rate of cautious older drivers was approximately half that of relatively aggressive drivers, the difference was not statistically significant. Furthermore, this difference was expected to decrease when driving exposure was considered. Older drivers who adopted a cautious driving style but were involved in traffic crashes had poorer visual acuity and contrast sensitivity. The results of this study indicate that a cautious driving style alone may not be sufficient to compensate for older drivers’ declining functions, particularly the loss of two visual functions observed in the present study.

Exploring the association between the Arabic version of the Traffic Locus of Control, driving behavior, and road traffic crashes: A multidimensional approach.

The Traffic Locus of Control scale (T-LOC) serves as a measure of drivers' personality attributes, providing insights into their perceptions of potential causes of road traffic crashes (RTCs). This study meticulously evaluated the psychometric properties of the Arabic version of T-LOC (T-LOC-A) among Lebanese drivers. Additionally, the study aimed to explore associations between the T-LOC scale and various driving variables, including driver behavior, accident involvement, and traffic offenses. A cross-sectional study was conducted among Lebanese drivers using a face-to-face approach. The validation of the Arabic version of T-LOC (T-LOC-A) occurred through a two-stage process: translating and culturally adapting T-LOC in the first stage, and testing its psychometric properties in the second stage. Data were collected using a comprehensive self-reported questionnaire in Arabic, covering demographic and travel-related variables, risk involvement, and measures such as the Driver Behavior Questionnaire (DBQ) and T-LOC. Exploratory factor analysis and confirmatory factor analysis were performed to scrutinize the factorial structure of T-LOC. Pearson correlation and chi-square tests were used for continuous and categorical variables, respectively. Two logistic regression analyses were executed to probe associations between T-LOC and involvement in road traffic crashes (RTCs) and T-LOC subscales with the occurrence of traffic offenses. The study included 568 drivers, predominantly male (69%) and aged between 30 and 49 years (42.1%). The findings revealed that T-LOC-A exhibited robust psychometric properties, with excellent reliabilities (α = 0.85) and adherence to the original four-factor structure, encompassing self (α = 0.88), other drivers (α = 0.91), vehicle/environment (α = 0.86), and fate (α = 0.66). The multidimensional structure was statistically supported by favorable fit indices. Gender differences revealed men attributing responsibility to other drivers, while women leaned towards fate and luck beliefs. Regarding driver behavior, the "other drivers" and self-dimensions of T-LOC-A correlated positively with aggressive violations. The fate dimension showed positive associations with aggressive violations and lapses. The "other drivers" subscale correlated positively with errors, and the vehicle/environment subscale with lapses. External T-LOC factors were positively associated with accident involvement, while the "LOC self" factor emerged as a protective element. In terms of traffic offenses, "LOC fate" displayed a positive association, while the "LOC self" factor showed a protective effect. In conclusion, the Arabic T-LOC is a reliable and valuable instrument, suggesting potential improvements in driving safety by addressing drivers' locus of control perceptions.

Truck drivers’ behaviour on road traffic crash involvement: A structural equation modeling approach

Truck drivers’ behaviour on road traffic crash involvement: A structural equation modeling approach

MODELLING THE FACTORS AFFECTING CRASH OCCURRENCE AND FREQUENCY RESULTED FROM MOBILE PHONE USE WHILE DRIVING: EVIDENCE FROM AL-NAJAF, IRAQ

The recent reports of road traffic accident statistics in Iraq have disclosed a rise in the number of crash injuries resulted from the use of mobile phone while driving. This paper aims to explore the factors contributing to the occurrence and prevalence of such crashes and near crashes in Al-Najaf governorate, Iraq. A representative sample of 417 drivers were interviewed as part of a questionnaire driving survey. Several frequency and modelling analyses were conducted using the IBM SPSS software. The frequency analysis revealed a high use of mobile phones for calling and texting activities while driving. Almost 20% and 55% of the interviewed drivers reported their involvement in a crash or in a near crash because of such use, respectively. Regarding the developed logistic models, the crash involvement sequential regression analysis revealed that factors such gender, education, handheld phoning, calling-answering frequency, and inadequate driving can affect the likelihood of crash occurrence. In contrast, the ordinal logistic near miss models revealed that age, gender, high phone use rate, and improper driving due to such use are influential factors in rising the likelihood of being in multiple near crashes. The analysis results confirm the influence of using phones in distracting the attention of drivers and hence threating their lives; as a result, these findings would be enlightening for agencies and policy makers interested in highway safety.

Does recognizability of connected and automated vehicles (CAVs) platoons affect drivers’ behavior and safety?

Platoons of connected and automated Vehicles (CAVs) comprising both passenger cars and trucks are expected to appear on highways in the coming years. Though prior studies explored driver behaviors in the presence of CAV platoons, it remains unknown whether it is necessary for a traditional vehicle’s driver to recognize CAV platoons in a mixed traffic environment for safe maneuvering. This study aims to test the hypothesis that drivers behave differently when interacting with recognizable CAV platoons compared to interacting with non-recognizable CAV platoons. A driving simulator experiment was conducted featuring four merging and diverging scenarios. Participants were informed beforehand that blue-colored vehicles driving with short gaps would be CAV platoons. However, they also encountered CAV platoons consisting of several vehicles with different colors (not blue). The blue-colored platoon was considered as recognizable CAV platoons and the latter as non-recognizable CAV platoons. Performance indicators including speed, maximum acceleration and deceleration, standard deviation (SD) of speed and acceleration, and time-to-collision (TTC) were considered to examine drivers’ behavior. The generalized estimating equation (GEE) approach was applied to evaluate the effect of recognizability and demographic characteristics on driver performance. The GEE results revealed significant improvement in drivers’ behavior in the presence of recognizable CAV platoons. The merging SD of speed and acceleration were around 32% and 29% lower, respectively in the presence of recognizable CAV platoons. The merging TTC was around 20% higher in the presence of recognizable CAV platoons. Although no significant main effect of recognizability was found for diverging maneuvers, a noteworthy result was that male drivers had around 37% higher diverging TTC than female drivers in the presence of recognizable CAV platoons. The findings also suggested significant effects of gender, age, driving experience, and education on driver performance while merging, as well as effect of gender and prior crash involvement on driver performance while diverging. These findings provide valuable insights to transportation planning authorities in determining the potential need for making CAV platoons recognizable and developing associated guidelines for safer traffic movements in mixed traffic environments.

Understanding risky driving behaviors among young novice drivers in Nigeria: A latent class analysis coupled with association rule mining approach

Traffic crashes are significant public health concern in Nigeria, particularly among young drivers. The study aims to explore the underlying pattern of risky driving behaviors and the associations with demographic factors among young drivers in Nigeria. A combined approach of Latent Class Analysis (LCA) and Association Rule Mining is applied to the dataset comprising responses from 684 young drivers who complete the “Behavior of Young Novice Drivers Scale” (BYND) questionnaires. The LCA identifies four distinct classes of drivers based on the risky behavior profiles: Reckless-Speedsters, Cautious Drivers, Distracted Multitaskers, and Emotion-impacted Drivers. Association rule mining further connects these driver classes to demographic and driving history variables, uncovering intriguing insights. Reckless-Speedsters predominantly consist of young males who engage in riskier driving behaviors, including exceeding speed limits and disregarding traffic rules. Conversely, Cautious Drivers, also predominantly young males, exhibit a safer driving profile marked by rule adherence and a notably lower crash rate. Distracted Multitaskers, sharing a demographic profile with Cautious Drivers, diverge significantly due to their higher crash involvement, hinting at a propensity for distracted driving practices. Lastly, Emotion-Impacted Drivers, primarily comprising young employed males, display behaviors influenced by emotions, shorter driving distances, and prior unsupervised driving experience. Most of the behaviors are attributed to inadequate traffic control, absence of traffic signs in most of the roads, preferential treatment, and lack of strict law enforcement in the country. The findings hold substantial implications for road safety interventions in Nigeria, urging targeted approaches to address the unique challenges presented by each driver class. With acknowledging the study limitations and advocating for future research in objective measures and emotion-behavior interactions, the comprehensive approach provides a robust foundation for enhancing road safety in the Nigerian context.

The role of driver head pose dynamics and instantaneous driving in safety critical events: Application of computer vision in naturalistic driving

This paper investigates the role of driver behavior especially head pose dynamics in safety–critical events (SCEs). Using a large dataset collected in a naturalistic driving study, this paper analyzes the head pose dynamics and driving behavior in moments leading up to crashes or near-crashes. The study uses advanced computer vision and mixed logit modeling techniques to identify patterns and relationships between drivers’ head pose dynamics and crash involvement. The results suggest that driver-head pose dynamics, especially poses that indicate distraction and movement volatility, are important factors that can contribute to undesirable safety outcomes. Marginal effects show that angular deviation for head pose dynamics indicated by yaw, pitch and roll increase the likelihood of crash intensity by 4.56%, 4.92% and 8.26% respectively. Furthermore, traffic flow and lane changing also contribute to increase in likelihood of crash intensity. These findings provide new insights into pre-crash factors, especially human factors and safety–critical events. The study highlights the importance of considering human factors in designing driver assistance systems and developing safer vehicles. This research contributes by examining naturalistic driving data at the microscopic level with early detection of behaviors that lead to SCEs and provides a basis for future research on automation.

Behind the wheel: Probing into personality, skills, and driving behavior’s role in bus rapid transit crashes

Objective Personality traits and driving skills are significantly associated with driving behaviors and crashes. In the case of professional bus drivers, the relationships amongst these variables have not been sufficiently examined in terms of road crashes. Therefore, this study seeks to examine the relationship between personality traits, driving skills, driving behaviors, and crash involvement among Bus Rapid Transit (BRT) drivers. Methods The study employed a comprehensive data collection strategy involving self-reported questionnaires, including the driver behavior questionnaire, driver skill inventory, and Big Five inventory, alongside Global Positioning System (GPS)-extracted speeding data from a sample of 166 drivers. To explore the relationship between variables, the study utilized the Partial Least Squares Structural Equation Model (PLS-SEM) as the analytical method. Result The findings reveal that self-reported violations and actual speeding performed by drivers were positively associated with crash involvement, whereas positive driving behavior negatively influences violation, errors, speeding and crash involvement. The study also found that the safety skills were negatively associated with violations, errors, and speeding, while higher perceptual-motor skills were associated with higher instances of speeding violations, resulting to a higher possibility of getting involved in a crash. Finally, the study reveals that certain personality traits (extraversion and neuroticism) were positively associated with violations, errors, and speeding, leading to a higher risk of getting involved in crashes, whereas certain personality traits (conscientiousness and agreeableness) were associated with safe driving. Conclusion The study findings offer valuable insights into the predictors of crashes among professional BRT drivers, which can be used to enhance driving practices, ensuring the safety of the public. Moreover, these findings provide transportation agencies with better management and decision-making capabilities to implement effective interventions to improve road safety.

Investigating pedestrian-vehicle crashes on interstate highways: Applying random parameter binary logit model with heterogeneity in means

In the U.S., the interstate highway system is categorized as a controlled-access or limited-access route, and it is unlawful for pedestrians to enter or cross this type of highway. However, pedestrian-vehicle crashes on the interstate highway system pose a distinctive safety concern. Most of these crashes involve ‘unintended pedestrians’, drivers who come out of their disabled vehicles, or due to the involvement in previous crashes on the interstate. Because these are not ‘typical pedestrians’, a separate investigation is required to better understand the pedestrian crash problem on interstate highways and identify the high-risk scenarios. This study explored 531 KABC (K = Fatal, A = Severe, B = Moderate, C = Complaint) pedestrian injury crashes on Louisiana interstate highways during the 2014–2018 period. Pedestrian injury severity was categorized into two levels: FS (fatal/severe) and IN (moderate/complaint). The random parameter binary logit with heterogeneity in means (RPBL-HM) model was utilized to address the unobserved heterogeneity (i.e., variations in the effect of crash contributing factors across the sample population) in the crash data. Some of the factors were found to increase the likelihood of pedestrian’s FS injury in crashes on interstate highways, including pedestrian impairment, pedestrian action, weekend, driver aged 35–44 years, and spring season. The interaction of ‘pedestrian impairment’ and ‘weekend’ was found significant, suggesting that alcohol-involved pedestrians were more likely to be involved in FS crashes during weekends on the interstate. The obtained results can help the ‘unintended pedestrians’ about the crash scenarios on the interstate and reduce these unexpected incidents.

Corridor-Level Auto Occupancy in Mobility Monitoring Efforts: A Crash-Based Approach

Vehicle occupancy (the number of persons per vehicle) is fundamental to evaluations of transportation system performance focused on the movement of people rather than solely vehicles. Historically, obtaining detailed estimates of occupancy has required manual (expensive) field data collection. This paper reports on a crash-based approach for estimating occupancy. Because some characteristics, such as the presence of multiple passengers aged 16 to 21, may affect the likelihood of crash involvement, the study examined ways to control possible crash bias using two methods. The first—heuristic bias correction, which entails synthesizing missing samples—is useful for smaller jurisdictions where there is no ground truth value readily available but an area-wide occupancy measure is needed. The second—statistical bias correction, which uses manual observations for calibration followed by the creation of a model—is suitable for obtaining occupancy at the corridor level. The approach is demonstrated with 12 years of fall and spring crash data for the Hampton Roads region of southeastern Virginia, U.S., representing 1.7 million people and 50,000 crashes. Testing showed estimated occupancies were within roughly 0.05 of true occupancy when corridor-specific calibration was performed. Further, the larger number of samples used for an area-wide occupancy means that heuristic bias correction is not always necessary: for cities with more than 200 samples, the difference between uncorrected and corrected occupancies was 0.02. For states that report the number of occupants for crashes with and without injury, this approach holds promise for estimating vehicle occupancy for both corridors and regions.

Impact of alcohol driving-while-impaired license suspension duration on future alcohol-related license events and motor vehicle crash involvement in North Carolina, 2007 to 2016

Background/PurposeLicense suspensions are a strategy to address alcohol-impaired driving behavior and recidivism following an alcohol driving while impaired (alcohol-DWI) conviction. Little is known about the specific impacts of conviction-related suspensions on safety outcomes and given recent fluctuations in alcohol-impaired driving behavior, crashes, and suspension trends, updated and focused assessments of this intervention are necessary. This study aimed to 1) examine the association between type of recent alcohol-DWI suspension and having a secondary alcohol-related license outcome and/or future crash event in North Carolina (NC) between 2007 and 2016; and 2) assess potential modification of these associations by race/ethnicity. MethodsWe used linked NC licensing data, NC crash data, and county-level contextual data from a variety of data sources. We compared individuals ages 21 to 64 who sustained initial (1-year) versus repeat (4-year) suspensions for alcohol-related license and crash involvement outcomes. We estimated unadjusted and adjusted hazard ratios (aHRs) using Cox proportional hazards models and produced Kaplan-Meier (KM) survival curves using a three-year follow-up period. After observing statistically significant modification by race/ethnicity, we calculated stratified aHRs for each outcome (Black and White subgroups only, as other subgroups had low numbers of outcomes). Results122,002 individuals sustained at least one alcohol-DWI conviction suspension (117,244 initial, 4,758 repeat). Adjusted KM survival curves indicated that within three years of the index suspension, the predicted risks of having a license outcome and crash outcome were about 8 % and 15 %, respectively, among individuals with an initial suspension and 5 % and 10 %, respectively, among individuals with a repeat suspension. After adjusting for potential confounding, we found that compared to those with an initial suspension, those with repeat suspensions had a lower incidence of future license (aHR: 0.49; 95 % CI: 0.42, 0.57) and crash outcomes (aHR: 0.67; 95 % CI: 0.60, 0.75). Among Black individuals, license outcome incidence was 162 % lower among repeat versus initial index suspension groups (aHR: 0.38; 95 % CI: 0.26, 0.55), while for White individuals, the incidence was 87 % lower (aHR: 0.54; 95 % CI: 0.45, 0.64). Similarly, crash incidence for repeat versus initial suspensions among Black individuals was 56 % lower (aHR: 0.64; 95 % CI: 0.50, 0.83), while only 39 % lower among White individuals (aHR: 0.72; 95 % CI: 0.63, 0.81). ConclusionsDecreased incidence of both license and crash outcomes were observed among repeat versus initial index suspensions. The magnitude of these differences varied by race/ethnicity, with larger decreases in incidence among Black compared to White individuals. Future research should examine the underlying mechanisms leading to alcohol-impaired driving behavior, convictions, recidivism, and crashes from a holistic social-ecological perspective so that interventions are designed to both improve road safety and maximize other critical public health outcomes, such as access to essential needs and services (e.g., healthcare and employment).

An exploratory study of parent acceptance of sanctions for driving offenses committed by their children

Objective Graduated driver licensing (GDL) systems are effective at reducing young driver crashes but rely on active parental involvement. However, some parents may accept sanctions (e.g., demerit points, monetary fines) for traffic offenses committed by their children, leading to experiences of punishment avoidance by young drivers. This aim of this exploratory study was to investigate several demographic and psychosocial influences that could possibly be associated with parent acceptance of sanctions. Method An online survey was completed by parents of young drivers (N = 149, M = 48.88 years, SD = 4.76 years; female = 86%) from 3 Australian states. The survey included measures of sociodemographic characteristics and driving history (e.g., crash involvement), socioeconomic status, parenting style, knowledge of their child’s driving behavior, perceptions of their ability to manage their child’s driving, attitudes toward GDL, and previous or potential acceptance of demerit points or payment of fines for road offenses committed by their child. Results Twenty-nine percent of parents had accepted or would accept a sanction on behalf of their child. Number of children overall, number of children licensed, and household income were associated with parent acceptance of a sanction. Parenting style, attitude toward GDL restrictions, parent confidence in their knowledge of GDL restrictions and ability to manage their child’s driving, and belief that their child would follow rules were not associated with (non)acceptance of a sanction. Conclusions These exploratory findings suggest that family size and income may be important influences on parent acceptance of sanctions on behalf of their offending children. The findings related to the psychosocial variables are discussed considering other research and the limitations of the study.