Crash-related Fatalities Research Articles

The local driving safety effect of motorcycle restrictions: Evidence from China

Motorcycles are a highly unstable element that impacts road traffic safety due to insufficient safety protection structures and poor maneuverability. The rapid increase in their use has exacerbated the severity of crash-related fatalities and injuries. While some countries have implemented motorcycle restrictions to address this phenomenon, the causal effect of such policies on reducing the severity of injuries from accidents requires further research. This study employs a difference-in-differences approach to estimate the causal effect of motorcycle restrictions in China on the severity of road crash injuries. The results indicate a significant reduction in the likelihood of fatal or severe injuries occurring in crashes. Specifically, in regions with motorcycle restrictions, the probability of crashes resulting in fatal or severe injuries decreased by 2.9% on average. The results remain robust following placebo and falsification tests and excluding confounding effects. Heterogeneity analysis reveals that motorcycle restrictions primarily affect male drivers and drivers with urban hukou, with no significant differences in effects across drivers of different age groups. Overall, the findings indicate that motorcycle restrictions reduce the number of motorcycles on the road and decrease the probability of motorcycle drivers being at fault in crashes, signifying improved driver behavior and effectively lowering crash severity.

Changing vehicles to reduce older driver fatalities: An effective approach?

Introduction: Age-related frailty leaves older drivers with the greatest fatality risk when involved in a crash compared with younger demographics. This study explored how vehicle features differed between crash-involved older and middle-aged drivers and estimated how those differences contribute to excess older driver fatalities. Methods: We merged Florida's crash data from 2014–2018 with Insurance Institute for Highway Safety and Highway Loss Data Institute databases. We compared the distribution of passenger vehicle age, type, size, and safety features among crash-involved older drivers (ages 70 and older) with crash-involved middle-aged drivers (ages 35–54). From logistic regression models, we estimated declines in older driver fatalities if they drove vehicles like those driven by middle-aged drivers under all and side-impact crash scenarios. Results: Older drivers in crashes were more likely to be in vehicles that were lighter, older, and without standard electronic stability control, standard head-protecting side airbags, and ratings of good in two IIHS crash tests than middle-aged drivers. In adjusted models, the fatality risk for older drivers in all crashes was significantly higher when ESC was not standard (odds ratio [OR], 1.37; 95% confidence interval [CI], 1.12–1.68) or when driving small passenger cars relative to large SUVs (OR, 2.02; 95% CI, 1.25–3.26); in driver-side crashes, the fatality risk doubled when vehicles did not have standard head-protecting side airbags (OR, 2.03; 95% CI, 1.58–2.62). If older drivers drove vehicles similar to middle-aged drivers, we estimated 3.3% and 4.7% fewer deaths in all and side-impact crashes, respectively. Conclusions: These results contribute to evidence suggesting that newer, more crashworthy vehicles with crash mitigation features benefit older drivers because of their heightened risk of crash-related fatality. Practical Applications: At a minimum, older drivers should aim to drive equipped vehicles with widely available features proven to reduce fatalities.

What determines the success of states in reducing alcohol related crash fatalities? A longitudinal analysis of alcohol related crashes in the U.S. from 1985 to 2019

In the United States, nearly 28 people die in alcohol–related motor vehicle crashes every day (1 fatality every 52 min). Over decades, states have enacted multiple laws to reduce such fatalities. From 1982 to 2019, the proportion of drivers in fatal crashes with a blood alcohol concentration (BAC) above 0.01 g/dl declined from 41% to 22%. States vary in terms of their success in reducing alcohol–related crash fatalities. The purpose of this study was to examine factors associated with changes in fatalities related to alcohol–impaired driving at the state level. We created a panel dataset of 50 states from 1985 to 2019 by merging different data sources and used fixed–effect linear regression models to analyze the data. Our two outcome variables were the ratio of drivers in fatal crashes with BAC ≥ 0.01 g/dl to those with BAC = 0.00, and the ratio of those with BAC ≥ 0.08 g/dl to those with BAC < 0.08 g/dl. Our independent variables included four laws (0.08 g/dl BAC per se law, administrative license revocation law, minimum legal drinking age law, and zero tolerance law), number of arrests due to impaired driving, alcohol consumption per capita, unemployment rate, and vehicle miles traveled. We found that the 0.08 g/dl per se law was significantly associated with lower alcohol–related crash fatalities while alcohol consumption per capita was significantly and positively associated with crash–related fatalities. Arrests due to driving under the influence (DUI) and crash fatalities were nonlinearly correlated. In addition, interaction of DUI arrests and two laws (0.08 g/dl BAC per se law, and zero tolerance) were significantly associated with lower crash–related fatalities. Our findings suggest that states which have more restrictive laws and enforce them are more likely to significantly reduce alcohol–related crash fatalities.

“Where Have I Heard It?” Assessing the Recall of Traffic Safety Campaigns in the Dominican Republic

Although traffic crashes are the eighth leading cause of death in the world, and are linked to vehicle and infrastructure-related factors, crash-related fatality rates are much higher in low-income countries. Particularly, the Dominican Republic is the country with the highest accident rate in the whole American continent. Therefore, in the past few years, public agencies have been developing different measures aimed at reducing traffic fatalities, including road safety campaigns. The aim of the present study was to assess the recalling of such campaigns among the Dominican population, which may serve as an additional indicator to evaluate their effectiveness in this and other countries of the region presenting similar traffic safety issues. For this cross-sectional study, a nationwide sample composed of 1260 people (50% males and 50% females) with a mean age of 39.3 years was used. The data were collected through personal interviews. Overall, the recall of traffic safety campaigns was found to be very low (9%); male drivers who were employed, possessed a driver’s license and habitually drove were the ones who could commonly remember these campaigns. The results of this study suggest that further evaluation and follow-up could help to maximize the impact of future traffic campaigns and advertisements in the Dominican Republic, as well as in other emerging countries of the region with similar characteristics. Further, key segments of the population such as the female, young, less formally educated and non-driving populations should be also targeted for further actions in this regard.

Using SHRP2 NDS data to examine infrastructure and other factors contributing to older driver crashes during left turns at signalized intersections

Drivers age 65 and over have higher rates of crashes and crash-related fatalities than other adult drivers and are especially over-represented in crashes during left turns at intersections. This research investigated the use of SHRP2 Naturalistic Driving Study (NDS) data to assess infrastructure and other factors contributing to left turn crashes at signalized intersections, and how to improve older driver safety during such turns. NDS data for trips involving signalized intersections and crash or near-crash events were obtained for two driver age groups: drivers age 65 and over (older drivers) and a sample of drivers age 30−49, along with NDS pre-screening and questionnaire data. Video scoring of all trips was performed to collect additional information on intersection and trip conditions. To identify the most influential factors of crash risk during left turns at signalized intersections, machine learning and regression models were used. The results found that in the obtained NDS dataset, there was a relatively small volume of crashes during left turns at signalized intersections. Further, model results found the statistically significant variables of crash risk for older drivers were associated more with health and cognitive factors rather than the infrastructure or design of the intersections. The results suggest that a study using only SHRP2 NDS data will not lead to definitive findings or recommendations for infrastructure changes to increase safety for older drivers at signalized intersections and during left turns. Moreover, the findings of this study indicates the need to consider other data sources and data collection methods to address this critical literature gap in older driver safety.

A detailed finite element model of a mid-sized male for the investigation of traffic pedestrian accidents.

The pedestrian is one of the most vulnerable road users and comprises approximately 23% of the road crash-related fatalities in the world. To protect pedestrians during Car-to-Pedestrian Collisions (CPC), subsystem impact tests are used in regulations. These tests provide insight but cannot characterize the complex vehicle-pedestrian interaction. The main purpose of this study was to develop and validate a detailed pedestrian Finite Element (FE) model corresponding to a 50th percentile male to predict CPC induced injuries. The model geometry was reconstructed using a multi-modality protocol from medical images and exterior scan data corresponding to a mid-sized male volunteer. To investigate injury response, this model included internal organs, muscles and vessels. The lower extremity, shoulder and upper body of the model were validated against Post Mortem Human Surrogate (PMHS) test data in valgus bending, and lateral/anterior-lateral blunt impacts, respectively. The whole-body pedestrian model was validated in CPC simulations using a mid-sized sedan and simplified generic vehicles bucks and previously unpublished PMHS coronal knee angle data. In the component validations, the responses of the FE model were mostly within PMHS test corridors and in whole body validations the kinematic and injury responses predicted by the model showed similar trends to PMHS test data. Overall, the detailed model showed higher biofidelity, especially in the upper body regions, compared to a previously reported simplified pedestrian model, which recommends using it in future pedestrian automotive safety research.

Identifying high-risk commercial vehicle drivers using sociodemographic characteristics

Crash data, from the state of Kentucky, for the 2015-2016 period, show that per capita crash rates and increases in crash-related fatalities were higher than the national average. In an effort to explain why the U.S. Southeast experiences higher crash rates than other regions of the country, previous research has argued the regions unique socioeconomic conditions provide a compelling explanation. Taking this observation as a starting point, this study examines the relationship between highway safety and socioeconomic and demographic characteristics, using an extensive crash dataset from Kentucky. Its focus is single- and two-unit crashes that involve commercial motor vehicles (CMVs) and automobiles. Using binary logistic regression and the quasi-induced exposure technique to analyze data on the socioeconomic and demographic attributes of the zip codes in which drivers reside, factors are identified which can serve as indicators of crash occurrence. Variables such as income, education level, poverty level, employment, age, gender, and rurality of the driver’s zip code influence the likelihood of a driver being at fault in a crash. Socioeconomic factors exert a similar influence on CMV and automobile crashes, irrespective of the number of vehicles involved. Research findings can be used to identify groups of drivers most likely to be involved in crashes and develop targeted and efficient safety programs.

Exploring injury severity in head-on crashes using latent class clustering analysis and mixed logit model: A case study of North Carolina

Although only 2 % of crashes are head-on crashes in the United States, they account for over 10 % of all crash-related fatalities. This study aims to investigate the contributing factors that affect the injury severity of head-on crashes and develop appropriate countermeasures. Due to the unobserved heterogeneity inherent in the crash data, a latent class clustering analysis is firstly conducted to segment the head-on crashes into relatively homogeneous clusters. Then, mixed logit models are developed to further explore the unobserved heterogeneity within each cluster. Analyses are performed based on the data collected from the Highway Safety Information System (HSIS) from 2005 to 2013 in North Carolina. The estimated parameters and associated marginal effects are combined to interpret significant variables of the developed models. The proposed method is able to uncover the heterogeneity within the whole dataset and the homogeneous clusters. Results of this research can provide more reliable and insightful information to engineers and policy makers regarding the contributing factors to head-on crashes.

Applying Bayesian data mining to measure the effect of vehicular defects on crash severity

The National Motor Vehicle Crash Causation Survey (NMVCCS), conducted from 2005 to 2007, showed that an estimated 44,000 crashes occurred due to vehicular defects— 2% of the NMVCCS crashes. Vehicle defects have an adverse effect upon overall roadway safety as they can increase the likelihood of traffic crashes, thus increasing the frequency of crash-related injuries and fatalities. Even though Louisiana requires a biennial vehicular safety inspection, recent traffic crash statistics have shown a higher than average percentage of vehicle defect–related crash fatalities in Louisiana (3% of all traffic fatalities). This fact called for an in-depth analysis of the vehicle defect–related crashes in Louisiana. The current study used 7 years (2010–2016) of traffic crash data from Louisiana to investigate the association between crash severity and vehicle-defect types by applying a Bayesian data mining approach. The findings showed that vehicle age is associated with severe injury crashes. Worn tires and defective brakes are the over-represented vehicle-defect categories. The significant association patterns can be used by different stakeholders to enhance roadway safety and reduce vehicular defect associated crashes.

Systematic Literature Review of Insufficient Sleep and Fitness To Drive in Shift Workers

Abstract Date Presented 04/06/19 Shift workers commonly experience insufficient sleep due to working varied shifts. As such, they may experience sleepiness while driving, increasing their risk for crash-related injuries and fatalities. Yet, determinants for fitness to drive in shift workers with insufficient sleep have not been synthesized. This systematic literature review synthesizes and critically appraises peer-reviewed literature on fitness to drive and driving performance in shift workers with insufficient sleep. Primary Author and Speaker: Melissa Knott Contributing Authors: Sherrilene Classen, Sarah Krasniuk, Marisa Tippett, Liliana Alvarez

An Integrative Review on Teen Distracted Driving for Model Program Development.

Distracted driving, especially driver inattention, is associated with high levels of crash-related fatalities and injury. Teen novice drivers are one of the groups most likely to drive distracted and to suffer its consequences. Teens have a higher risk of engaging in texting or secondary tasks, e.g., eating while driving. Distracted driving interventions to date aim to improve teen and societal safety, but few have achieved effectiveness. A need exists for effective evidence-based distracted driving interventions. We used an integrative review to identify rigorous evidence, and inform the development of a teen distracted driving educational intervention. This five-step review included: identifying the research problem; collecting literature; evaluating literature; synthesizing data; and presenting results. We searched 6 databases, identifying 185 articles. Following three rounds of inclusion screening (title, abstract, and full-text), captured according to a PRISMA flow chart, 17 studies met inclusion. We categorized these studies, conducted in the U.S., as five intervention types that used approaches including presentations, videos or instructional programs, education or training programs, driving simulator training, in-vehicle monitoring or feedback, and integrated programs. Study designs included randomized controlled trials pre-post, quasi-experimental, and experimental designs with prospective longitudinal cohorts. The studies were heterogeneous in design, intervention and outcome. However, three core themes emerged across studies: i.e., hazard awareness, hazard mitigation and attention maintenance are primary critically necessary skills to prevent distracted driving; engaging a parent or adult as a partner in the intervention process from classroom to car contributed to the effectiveness of the intervention; and leveraging technology in training enhanced the effectiveness of the intervention. Study limitations pertained to a focus on short-term effects; sampling distributions that did not account for gender, age, race, and/or ethnicity; types of interventions; and bias. The limitations affect the generalizability of included study findings and, potentially, the review findings, as they may not apply to populations or contexts outside those synopsized. Strengths included our team's expertise in conducting evidence-based reviews, support of a health science librarian, and use of international review guidelines. As an outcome, we are applying findings of the integrated review to develop a computer-based training addressing teen distracted driving.

Traffic Safety on Acadia National Park Roadways

Travel to Acadia National Park has been rising in the recent past, with over 3.5 million visitors recorded in 2018 (NPS, 2018). With visitation on the rise in Acadia and many of the national parks, there may be increased risks of injuries, and even deaths, from motor vehicle and/or bike crashes. However, statistical relationships between visitation levels and transportation crash-related injuries and fatalities in national parks are not well understood in research on transportation management in parks and protected areas. The roadways in national parks usually support multiple transportation modes and provide recreation opportunities for visitors such as scenic roads. Previous research suggests that traffic accidents are a leading cause of injuries and fatalities in national parks, but it has not been recognized as a prominent safety issue by the general public. This paper selected Acadia National Park as a study case, aiming at analyzing the temporal patterns of motor vehicle and bike crashes from 2007 to 2012, and to identify the factors associated with the monthly counts of motor vehicle and bike crashes. Study results indicated that the average monthly count of multi-vehicle crashes was much higher than that of single-vehicle crashes. Both motor vehicle and bike crashes were concentrated in the summer season. Simple moving average method was used to calculate the hourly counts of traffic crashes. The average single-vehicle crash counts peaked at 14:00, representing 0.002 crash per hour. Multi-vehicle crash counts were highest between 13:00 and 14:00, representing 0.012 crashes per hour. Poisson Log-linear Regression models were conducted to identify the factors impacting motor vehicle crashes and bike crashes. The results suggested that visitor number was an important factor that associated with both motor vehicle crashes and bike crashes. Also, the number of rain days per month had a significant impact on the count of bike lane crashes but had no significant impact on the count of bike path crashes. Therefore, the study recommended park managers to provide biking education specifically for wet conditions. Results of this study identify the quantitative relationship among monthly visitor number, monthly rain days, and monthly count of traffic crashes, which may help build the indicators and standards of public safety on roadways of national parks. Subscribe to JPRA

Using Deep Learning in Severity Analysis of At-Fault Motorcycle Rider Crashes

Motorcyclists are vulnerable highway users. Unlike passenger vehicle occupants, motorcycle riders do not have either protective structural surrounding or the advanced restraints that are mandatory safety features in cars and light trucks. Per vehicle mile traveled, motorcyclist fatalities occurred 27 times more frequently than passenger car occupant fatalities in traffic crashes. In addition, there were 4,976 motorcycle crash-related fatalities in the U.S. in 2014—more than twice the number of motorcycle rider fatalities that occurred in 1997. It shows that, in addition to current efforts, research needs to be conducted with additional resources and in newer directions. This paper investigated five years (2010–2014) of Louisiana at-fault motorcycle rider-involved crashes by using deep learning, which is a competent tool for mapping a high-multidimensional input into a smaller multidimensional output. The current study contributes to the existing injury severity modeling literature by developing a deep learning framework, named as DeepScooter, to predict motorcycle-involved crash severities. The final deep learning model can predict severity types with 100% accuracy with training data, and with 94% accuracy with test data, which is not attainable by using a statistical method or machine learning algorithm. The intensity of severities was found to be more likely associated with rider ejection, two-way roadways with no physical separation, curved aligned roadways, and weekends. It is anticipated that the DeepScooter framework and the findings will provide significant contributions to the area of motorcycle safety.

Impact of Cognitive Distractions on Drivers’ Anticipation Behavior in Vehicle-bicycle Conflict Situations

Overall, the rate of vehicle-bicycle collisions is continually increasing. In the United States alone, bicyclist fatalities contributed to 2.3 percent of all crash related fatalities in 2015. In most of these cases, crashes occur due to distracted drivers who are unable to correctly anticipate the bicyclists at the hazardous locations on the roadways such as, intersections and curves. The objective of the current study is to contribute to the divisive literature surrounding cell phone use while driving by specifically measuring, the effects of a secondary mock cell phone task on hazard anticipation performance across common vehicle-bicycle conflict situations. Two groups of 20 drivers each, navigated seven unique scenarios on a driving simulator while being monitored by an eye tracker. One group of participants performed a hands free mock cellphone task while driving, while the second group drove without any additional tasks outside of the primary task of driving. Analysis of the proportion of anticipatory glances using a logistic regression model revealed a significant main effect of the mock cellphone task at reducing the proportion of such glances made by the drivers towards potential bicyclist threats on the roadway.

Gendered Analysis of Fatal Crashes among Young Drivers in Alabama, USA

As part of broader research efforts to understand the factors contributing to crashes involving younger drivers, it is important to characterize the crash contributing factors of the at-fault younger drivers. This study applied latent class analysis (LCA) to identify subgroups with statistically distinct patterns in the contributing factors of fatal crashes involving young male and female drivers in Alabama. Model estimation results reveal that crashes on rural roads are a serious issue in Alabama. It was also observed that a high proportion of the young driver fatal crashes occurred on weekends and closer to the driver’s place of residence. Interestingly, the proportion of crashes involving speeding increased with age for males and decreased with age for females. In general, younger female drivers (15–18 years) were more likely to be involved in speed and aggressive driving related fatal crashes than their male counterparts. Also, fatal crashes involving driving under influence (DUI) increase with age for both male and female drivers, with a significant increase for drivers between 19 and 21 years of age. These study findings suggest that specific attention should be focused towards younger drivers in rural communities and communities with lower socioeconomic opportunities. Targeted education and outreach campaigns, combined with appropriate enforcement efforts could meaningfully change the attitudes and behaviors related to road safety.

Exploring traffic safety culture and drunk driving: An examination of the community and DUI related fatal crashes in the U.S. (1993–2015)

This project explores the relationship between structural level factors associated with community traffic safety culture toward alcohol and alcohol related fatal crashes in the United States from 1993 to 2015. Multilevel growth curve models were estimated to explore these relationships within longitudinal data. As hypothesized, increases in factors associated with anti-alcohol community norms, values, attitudes, and beliefs were related to decreases in alcohol related crashes at the county level. Conversely, measures associated with pro-alcohol factors were related to increased alcohol related crashes. These findings are consistent with traffic safety culture, social norms theory, and the Positive Community Framework (PCF).

Work-related nonfatal injuries in Alaska’s aviation industry, 2000–2013

Aviation is a critical component of life in Alaska, connecting communities off the road system across the state. Crash-related fatalities in the state are well understood and many intervention efforts have been aimed at reducing aircraft crashes and resulting fatalities; however, nonfatal injuries among workers who perform aviation-related duties have not been studied in Alaska. This study aimed to characterize hospitalized nonfatal injuries among these workers using data from the Alaska Trauma Registry. During 2000–2013, 28 crash-related and 89 non-crash injuries were identified, spanning various occupational groups. Falls were a major cause of injuries, accounting for over half of non-crash injuries. Based on the study findings, aviation stakeholders should review existing policies and procedures regarding aircraft restraint systems, fall protection, and other injury prevention strategies. To supplement these findings, further study describing injuries that did not result in hospitalization is recommended.

A Finite Element Model of a Midsize Male for Simulating Pedestrian Accidents.

Pedestrians represent one of the most vulnerable road users and comprise nearly 22% the road crash-related fatalities in the world. Therefore, protection of pedestrians in car-to-pedestrian collisions (CPC) has recently generated increased attention with regulations involving three subsystem tests. The development of a finite element (FE) pedestrian model could provide a complementary component that characterizes the whole-body response of vehicle-pedestrian interactions and assesses the pedestrian injuries. The main goal of this study was to develop and to validate a simplified full body FE model corresponding to a 50th male pedestrian in standing posture (M50-PS). The FE model mesh and defined material properties are based on a 50th percentile male occupant model. The lower limb-pelvis and lumbar spine regions of the human model were validated against the postmortem human surrogate (PMHS) test data recorded in four-point lateral knee bending tests, pelvic\abdomen\shoulder\thoracic impact tests, and lumbar spine bending tests. Then, a pedestrian-to-vehicle impact simulation was performed using the whole pedestrian model, and the results were compared to corresponding PMHS tests. Overall, the simulation results showed that lower leg response is mostly within the boundaries of PMHS corridors. In addition, the model shows the capability to predict the most common lower extremity injuries observed in pedestrian accidents. Generally, the validated pedestrian model may be used by safety researchers in the design of front ends of new vehicles in order to increase pedestrian protection.

Social policy and crash fatalities: a multivariate time series analysis

ABSTRACTThis paper is concerned with changes over time in road safety. Most research, rooted in the deterrence hypothesis, focuses on the impact of reductions in the blood alcohol concentration (BAC) limits on crash-related fatalities. Our study, drawing on opportunity theories of social action, extends this research by examining the relative effects of safety innovations, exposure risk, and changes in BAC limits, on deaths resulting from motor vehicle accidents. The multivariate time series analyses indicate that the implementation of seatbelt legislation and the number of vehicle miles traveled directly affect, while the reduction of BAC limits indirectly affects, the number of crash-related fatalities. The implication of these findings for determining the optimal research design for assessing the impact of legislative initiatives on crash-related injuries and deaths are discussed.

An evaluation of the effect of Ohio's graduated driver licensing law on motor vehicle crashes and crash outcomes involving drivers 16 to 20 years of age

ABSTRACTObjective: Nationally, motor vehicle crashes are the leading cause of death among youth ages 16 to 20 years. Graduated driver licensing (GDL) laws have been implemented to reduce motor vehicle crashes among teen drivers. Studies have shown decreases in teen crash rates and crash-related fatality rates following enactment of GDL laws. However, GDL laws typically apply to teens only until their 18th birthday; therefore, the effect, if any, that GDL laws have on youth drivers ages 18 to 20 years and whether these programs should be extended to include these older youth warrant further study. The objective of this study was to evaluate the effects of Ohio's 2007 revised GDL law on motor vehicle crashes and crash-related injuries for crashes involving teen drivers ages 16 to 20 years, with a focus on the effects on crashes involving drivers ages 18 to 20 years.Methods: Cross-sectional analysis of motor vehicle crashes involving drivers ages 16 to 20 years in Ohio in the pre-GDL (2004–2006) and post-GDL (2008–2010) periods was performed. Descriptive statistics and population-based crash rates for drivers and occupants ages 16 to 20 years were calculated, as well as rate ratios and 95% confidence intervals (CIs) comparing crashes in the pre-GDL and post-GDL periods.Results: Compared with the pre-GDL period, the post-GDL period was associated with lower crash rates for drivers age 16 years (relative risk [RR] = 0.94; 95% CI, 0.90–0.98), age 17 years (RR = 0.90; 95% CI, 0.88–0.93), age 18 years (RR = 0.95; 95% CI, 0.92–0.97), and ages 16–17 years combined (RR = 0.92; 95% CI, 0.90–0.95). Crash rate was higher for the post-GDL period for drivers age 19 years (RR = 1.04; 95% CI, 1.01–1.07), age 20 years (RR = 1.09; 95% CI, 1.05–1.13), and ages 18–20 years combined (RR = 1.02; 95% CI, 1.00–1.03).Conclusions: Unlike previous studies, this investigation used linked data to evaluate the outcomes of all occupants in crashes involving drivers ages 16–20 years. The post-GDL period was associated with lower crash, injury crash, and fatal crash involvement among drivers and occupants ages 16–17 years but higher overall crash involvement for drivers and occupants ages 19 years, 20 years, and 18–20 years combined. These findings support extending GDL restrictions to novice drivers ages 18 through 20 years to reduce crashes in that group.