Traffic Injury Prevention

Traffic Injury Prevention

Published by Taylor & Francis

Online ISSN: 1538-957X

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Print ISSN: 1538-9588

Journal websiteAuthor guidelines

Top-read articles

31 reads in the past 30 days

Figure 1: Fall kinematics of the ATD in configuration 1 (perpendicular curb): (a) overview of the 170
Figure 2: Fall kinematics of the ATD in configuration 2 (curb placed at an angle of 55°) : (a) overview of 192
Head impact kinematics and peak head, neck, and chest injury metrics for the six crash tests. 201 Bold values indicate the Injury Assessment Reference Values (IARVs), and values in red exceed the 202
Assessing bicycle helmet protection for head and neck in E-scooter falls

February 2025

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178 Reads

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26 reads in the past 30 days

Factors affecting injury severity in motorcycle crashes: Different age groups analysis using Catboost and SHAP techniques

January 2024

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528 Reads

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22 Citations

Objective: Motorcycle crashes often result in severe injuries on roads that affect people’s lives physically, financially, and psychologically. These injuries could be notably harmful to drivers of all age groups. The main objective of this study is to investigate the risk factors contributing to the severity of crash injuries in different age groups. Methods: This Objective is achieved by developing accurate machine learning (ML) based prediction models. This research examines the relationship between potential risk factors of motorcycle-associated crashes using (ML) and Shapley Additive explanations (SHAP) technique. The SHAP technique further helped interpreting ML methods for traffic injury severity prediction. It indicates the significant non-linear interactions between dependent and independent variables. The data for this study was collected from the Provincial Emergency Response Service RESCUE 1122 for the Rawalpindi region (Pakistan) over three years (from 2017 to 2020). The Synthetic Minority Oversampling Technique (SMOTE) is employed to balance injury severity classes in the pre-processing phase. Results: The results demonstrate that age, gender, posted speed limit, the number of lanes, and month of the year are positively associated with severe and fatal injuries. This research also assesses how the modeling framework varies between the ML and classical statistical methods. The predictive performance of proposed ML models was assessed using several evaluation metrics, and it is found that Catboost outperformed the XGBoost, Random Forest (RF) and Multinomial Logit (MNL) model. Conclusion: The findings of this study will assist road users, road safety authorities, stakeholders, policymakers, and decision-makers in obtaining substantial and essential guidance for reducing the severity of crash injuries in Pakistan and other countries with prevailing conditions.

Aims and scope


Publishes research on traffic safety, crash causation and injury prevention/treatment, including driver and road, economic and substance related aspects.

  • Traffic Injury Prevention publishes research on medicine, engineering, public health, and traffic safety in order to foster the science of traffic injury prevention.
  • The archival journal focuses on research, interventions, and evaluations within the areas of traffic safety, crash causation, injury prevention, and treatment.
  • General topics within the journal's scope are: Driver behavior, Road infrastructure, Emerging crash avoidance technologies, Crash and injury epidemiology, Alcohol and drugs, Impact injury biomechanics, Vehicle crashworthiness, Occupant restraints, Pedestrian safety, Evaluation of interventions, Economic consequences, Emergency and clinical care (specific to traffic injury prevention).
  • The journal includes full length papers, review articles, case studies, brief technical notes, and commentaries.
  • Traffic Injury Prevention operates a single anonymized peer review policy.
  • Authors can choose to publish gold open access in this journal and …

For a full list of the subject areas this journal covers, please visit the journal website.

Recent articles


Impact of naturalistic cannabis use on lateral control and speed: A driving simulator study
  • Article

June 2025

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8 Reads




Figure 1 provides a detailed outline of the steps involved in the research methodology.
Figure 2. The results of the location-allocation analysis indicate the candidate points for visits and their respective levels of importance.
arak-Salafchegan seven-day patrol schedules.
comparison between the relative frequency of visits to each point and their level of importance.
Spatial-temporal planning of road traffic speed management mobile resources: Enhancing road traffic safety by optimizing resource utilization
  • Article
  • Full-text available

June 2025

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12 Reads










Seatbelt use trends by pregnancy status and state in the United States, 2011–2024

June 2025

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23 Reads

Objectives Seatbelts decrease injuries and fatalities in motor vehicle collisions. Most seatbelt use studies are performed at a national or international scale, yet many lack data granularity to evaluate trends in population subgroups that might have differing belt use behaviors, such as pregnant females. Using data from the Center of Disease Control and Prevention Behavioral Risk Factor Surveillance System (BRFSS), this study aims to evaluate geographic differences in habitual seatbelt use and trends over time across respondent factors, focusing on pregnant females. Methods Weighted responses of “always wearing seatbelt” in the 2011–2024 BRFSS were aggregated by state, year, age group, sex, and pregnancy status and analyzed using a Bayesian zero-one-inflated beta regression. State seatbelt enforcement was coded as primary or secondary and added into the model. Results There were 1,149,325 total responses: 585,543 nonpregnant females (33.3% aged 18–29); 23,356 pregnant female (49.4% aged 18–29); and 540,426 males (39.5% aged 18–29). On average, primary enforcement states exhibit increased habitual seatbelt use adjusted for other factors (aOR = 1.63 (95% CrI 1.36–1.97)). In a secondary enforcement state, pregnant females had higher odds vs. nonpregnant females of habitual seatbelt use (aOR = 1.20 (95% CrI 1.02–1.44) for ages 18–29; aOR = 1.20 (0.99–1.42) for ages 30–44). Pregnancy effects were smaller in primary enforcement states. The probability of habitual seatbelt use among pregnant females increased since 2020 (primary enforcement: 0.86–0.88; secondary: 0.80–0.83), but decreased for nonpregnant females during the same period (primary enforcement: 0.85–0.82; secondary: 0.78–0.75). Regional variations in seatbelt use patterns and trends were identified. Conclusions Seat belt primary enforcement laws could increase habitual usage, regardless of age group and pregnancy status. Pregnant females continued to have higher habitual seatbelt use, with stronger effects among younger survey respondents. Additionally, we have identified a cluster of states in the Southeast with declining seatbelt use among both pregnant females and males. Better understanding of local enforcement policies and occupant attitudes toward seat belts can help develop interventions aimed at improving seat belt compliance and in-turn occupant safety.


factor scores for TaeG, cBQ, and rTrS.
relationships between secondary task engagement while cycling with self-reported errors, violations, risk perceptions, and regulations, as well as affinity for technology.
Multilinear regression analysis of self-reported secondary task engagement.
Is our growing affinity for technology a challenge for preventing distracted cycling? An Australian study

June 2025

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11 Reads

Objectives The core aim of this study was to assess secondary task engagement among Australian cyclists, considering demographic, behavioral, and psychosocial factors as potential contributors. Methods This study used the information provided by a sample of 1,240 Australian cyclists (24% females; 74% males; 2% non-binary) aged M = 53.6 (SD 12.9) years. They responded to an online survey on cycling-related affairs, including demographic, psychosocial (Risk Perception and Regulation Scale, RPRS), behavioral (Cycling Behavior Questionnaire, CBQ), and technology-related (Affinity for Technology Questionnaire, TAEG) factors. Results After analyzing the TAEG properties and outcomes in this Australian sample, it was found that engagement in secondary tasks while riding varies significantly according to demographic and cycling behavioral profiles. For instance, older cyclists were less likely to report engaging in secondary tasks while riding. In terms of cycling behavior, respondents who reported higher rates of violations were more likely to report high engagement with technology while riding. Moreover, the results from a multilinear regression model predicting secondary task engagement indicated associations between self-reported cycling behavior and engagement in secondary tasks, as well as a strong relationship between traffic violations and the latter. Additionally, knowledge of traffic rules and self-reported positive behaviors showed a significant negative relationship with secondary task engagement, suggesting that these respondents were less inclined to use mobile devices while riding. Conclusion Overall, the findings of this study support the hypothesis that secondary task engagement can be statistically explained by demographic factors (such as age and gender), attitudinal factors, and cycling behavior. These findings highlight several challenges and implications for cycling safety practices, particularly considering the increasing normalization of technology-related secondary tasks in transport activities such as cycling.






Figure 1. Data process methodology for aDS and benchmark comparison.
Figure 4. comparison of observed Waymo and average benchmark Airbag Deployment crashes in all locations over 56.7 million miles. comparisons labeled with an asterisk (*) had a statistically significant difference in crashed vehicle rates (See Table 6).
Data sources relied upon in the current study.
Waymo rider-only millions of miles by calendar year and location.
comparison of aDS and human benchmark (with dynamic benchmark adjustment) crashed vehicle rates in all locations combined by crash type in
Comparison of Waymo Rider-Only crash rates by crash type to human benchmarks at 56.7 million miles

Objective SAE Level 4 Automated Driving Systems (ADSs) are deployed on public roads, including Waymo’s Rider-Only (RO) ride-hailing service (without a driver behind the steering wheel). The objective of this study was to perform a retrospective safety assessment of Waymo’s RO crash rate compared to human benchmarks, including disaggregated by crash type. Methods Eleven crash type groups were identified from commonly relied upon crash typologies that are derived from human crash databases. Human benchmarks were developed from state vehicle miles traveled (VMT) and police-reported crash data. Benchmarks were aligned to the same vehicle types, road types, and locations as where the Waymo Driver operated. Waymo crashes were extracted from the NHTSA Standing General Order (SGO). RO mileage was provided by the company via a public website. Any-injury-reported, Airbag Deployment, and Suspected Serious Injury + crash outcomes were examined because they represented previously established, safety-relevant benchmarks where statistical testing could be performed at the current mileage. Results Data were examined over 56.7 million RO miles through the end of January 2025; resulting in a statistically significant lower crashed vehicle rate for all crashes compared to the benchmarks in Any-Injury-Reported and Airbag Deployment, and Suspected Serious Injury + crashes. Of the crash types, V2V Intersection crash events represented the largest total crash reduction, with a 96% reduction in Any-injury-reported (87–99% confidence interval) and a 91% reduction in Airbag Deployment (76–98% confidence interval) events. Cyclist, Motorcycle, Pedestrian, Secondary Crash, and Single Vehicle crashes were also statistically reduced for the Any-Injury-Reported outcome. There was no statistically significant disbenefit found in any of the 11 crash type groups. Conclusions This study represents the first retrospective safety assessment of an RO ADS that made statistical conclusions about more serious crash outcomes (Airbag Deployment and Suspected Serious Injury+) and analyzed crash rates on a crash type basis. The crash type breakdown applied in the current analysis provides unique insight into the direction and magnitude of safety impact being achieved by a currently deployed ADS system. This work should be considered by stakeholders, regulators, and other ADS companies aiming to objectively evaluate the safety impact of ADS technology.





Prescription pattern of driving-impairing psychotropic medications in Tabriz in 2022

May 2025

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3 Reads

Objectives: Some psychotropic medications could impair drivers' cognitive skills, concentration and reaction by affecting the central nervous system (CNS), thereby increasing the risk of traffic accidents. However, there is limited evidence regarding the prescription pattern of these medications in Iran. The present study aims to investigate the prescription pattern of psychotropic medications impairing driving in Tabriz, Iran. Methods: In this descriptive-analytical cross-sectional study, psychotropic medications prescribed by physicians in Tabriz from March, 2021, to March, 2022, were reviewed. The data were obtained from Iranian Social Security Organization (SSO), which included 1,167,460 eligible prescriptions. Psychotropic medications were classified into six main categories based on reliable scientific sources, and their level of effect on driving was determined using driving-impairing medication classification system. The data were analyzed using Stata 17.0 and Chi-square test. The significance level was considered to be less than 0.05. Results: The results showed out of 1,167,460 prescribed psychotropic medications, 65.32% were for women, and the rest were for men. The most frequently prescribed medications were antidepressants (38.07%), followed by anxiolytics (18.60%) and antipsychotics (15.48%), respectively. More than half of the medications (57.10%) was categorized to have moderate effect, 23.73% was categorized to have mild effect and 18.87% was categorized to have severe effect on driving. Gabapentin, sertraline, nortriptyline, fluoxetine and trifluoperazine were the most frequently prescribed medications, respectively. A significant correlation was observed between the impairment category of prescribed medications and patients' gender and age (P <0.001). Additionally, general practitioners prescribed the highest number of medications with severe adverse effects, while neurosurgeons, general surgeons, neurologists and psychiatrists prescribed the highest number of medications with moderate adverse effects on driving. Conclusions: More than half of the prescribed psychotropic medications in Tabriz was categorized to have moderate effects on driving, and about one-fifth was categorized to have severe effects. Antidepressants, anxiolytics and antipsychotics are considered to have the most relevant impairing effects on driving according to the categorization system, with gabapentin, sertraline, nortriptyline, fluoxetine and trifluoperazine being the most frequently prescribed medications. The findings highlighted the importance of raising awareness among physicians and patients about the effects of psychotropic medications on driving.



Comparison of male and female SUV-driver injury rates in similar crashes

May 2025

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4 Reads

Objective: The current study sought to determine the extent of differences in serious injury risk by sex using crash data maintained by individual U.S. states. As with many earlier studies, crash and vehicle differences were controlled. The vehicles of interest were restricted to SUVs, the most popular vehicle type in the U.S. Methods: Records of SUV-driver crash involvements during 2017 to 2023 were obtained from motor-vehicle crash files maintained by 13 states. Logistic regressions were used to model the odds of a serious or fatal injury for each of the states (A or K on the KABCO scale). Common predictors were light condition (dark vs. daylight), road surface condition (dry vs. slippery), vehicle age (7-12 years old vs. younger), vehicle weight ratio (case vehicle to partner vehicle), driver age (< 25 years vs. 25-64 years vs. 65+ years), and driver sex (female vs. male). An overall female-to-male injury odds ratio was computed from the weighted average of the logarithms of individual state odds ratios. Results: The data were restricted to safety-belt-restrained SUV drivers in head-on crashes with another passenger vehicle. Serious and fatal injuries were coded for 3.8% of the female drivers and 3.4% of the male drivers. Crashes in darkness and crashes of older drivers were significantly more likely to result in serious/fatal injuries, while crashes of younger drivers were significantly less likely to result in serious/fatal injuries. Female drivers were 17% more likely than males to incur serious/fatal injuries (95% confidence limits 8% to 27%). When the opposing vehicle was another SUV, female drivers were only 11% more likely than males to incur serious/fatal injuries (95% confidence limits -4% to 28%). However, female drivers were 20% more likely than males to incur at least minor injuries (95% confidence limits 13% to 28%). Conclusions: Observed differences in serious injury rates for female and male drivers declined after accounting for other driver, vehicle, and crash characteristics. In similar crash circumstances, female drivers are more likely than males to be injured, but this difference is clear only for minor injuries.


Editors