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    <title>Transport Research International Documentation (TRID)</title>
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    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Behavioral and psychological determinants of pedestrian collisions on arterial roads with evidence from random parameter models</title>
      <link>https://trid.trb.org/View/2604545</link>
      <description><![CDATA[Arterial roads, while comprising a small percentage of total roadway mileage in the U.S., contribute disproportionately to pedestrian fatalities. Focusing on the behavioral and psychological dimensions of crash risk, this study analyzes 1722 pedestrian crashes on principal arterials and 1614 on minor arterials in Louisiana from 2017 to 2021. A Random Parameter Multinomial Logit Model with Heterogeneity in Means and Variance captures the hidden variation in how individual behaviors and situational contexts affect injury outcomes. Results indicate that perceptual challenges (dark conditions without street lighting), driver decision errors (lane departures), and alcohol-impaired judgment are strong predictors of severe or fatal crashes. Marginal effects show elevated risk when pedestrians or drivers navigate low-visibility environments, single-vehicle settings that isolate responsibility, and scenarios involving Black pedestrians who may face systemic exposure and behavioral adaptation under stress. Conversely, proactive behaviors such as attentive movement before impact, lane keeping, and navigating mixed-use areas with higher driver expectancy can reduce the likelihood of severe injury. Psychological and situational determinants differ by arterial class: on principal arterials, perceptual load and alcohol impairment dominate, whereas on minor arterials, risk-taking maneuvers like midblock crossings and expectancy violations shape outcomes. These insights underscore the need for Safe System Approach (SSA) interventions that couple engineering fixes (street lighting, access control, enhanced midblock crossings) with behaviorally informed strategies such as targeted impaired-driving enforcement, perception-based educational campaigns, and context-specific outreach for at-risk demographic groups.]]></description>
      <pubDate>Mon, 20 Apr 2026 11:14:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2604545</guid>
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    <item>
      <title>Fatal Wrong-Way Crashes on Divided Highways, United States, 2014–2023</title>
      <link>https://trid.trb.org/View/2683102</link>
      <description><![CDATA[Wrong-way crashes are relatively rare, but they often result in more severe safety outcomes. This brief reports on the prevalence of fatal wrong-way crashes that occurred on divided highways from 2014 to 2023, along with their associated risk factors, updating and extending previous AAA Foundation for Traffic Safety (AAAFTS) work that examined these crashes. Updated wrong-way crash statistics are provided, previously cited risk factors were examined in reference to the updated data, and potential new risk factors were explored. From 2014 to 2023, 4164 fatal wrong-way crashes occurred on U.S. divided highways and resulted in a total of 5730 fatalities. While annual traffic fatalities nationwide increased over the study period, fatal wrong-way crashes increased even more, indicating that while these crashes are relatively rare, they are a growing issue. Results show that alcohol-impaired drivers, older drivers, drivers without valid licenses, and drivers of older vehicles have higher risk of fatal wrong-way crashes, consistent with previous research. New insights from the current study include findings that risk of fatal crashes is also increased in rural areas, in dawn/dusk and darkness, among drivers who live far away from the crash location, and among drivers of vehicles registered to other people. This wider and more up to date list of risk factors has implications for countermeasures.]]></description>
      <pubDate>Mon, 23 Mar 2026 08:34:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/2683102</guid>
    </item>
    <item>
      <title>How machine learning has been used to detect alcohol-induced driver impairment using in-vehicle sensors: A systematic review</title>
      <link>https://trid.trb.org/View/2670089</link>
      <description><![CDATA[Alcohol-impaired driving is a persistent global public health concern, with limited recent progress in reducing its impact on roads, highlighting the need for innovative approaches. The increasing adoption of machine learning (ML) has led to its application in detecting alcohol-induced driving impairment. This systematic review examines and synthesizes existing research that leverages ML utilizing in-vehicle sensors to detect alcohol-impaired driving, with a focus on the ML models employed and the input variables analyzed.  Studies were included if they applied ML techniques to detect alcohol-induced driving impairment using in-vehicle sensor data. The literature search was conducted in various academic databases and was supplemented by citation-based article retrieval. Primary outcomes of interest were the ML models employed and input variables. A risk of bias assessment was performed to evaluate study reliability and validity.  There were 26 relevant studies identified. The reported classification accuracy was consistently high, with median accuracy of 89%. Although the majority of studies were performed using driving simulators, there was significant heterogeneity with respect to other important study characteristics. The most common input variables used related to vehicle dynamics and control inputs, and the most common ML models implemented were neural networks. This systematic review highlights limitations in the current literature related to significant heterogeneity in study characteristics and methodological issues in many identified studies. While some promising results were observed, further research is required to determine the optimal approach, particularly with respect to finding the most compatible and practical ML models and input variables for reliable detection.]]></description>
      <pubDate>Wed, 25 Feb 2026 08:53:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2670089</guid>
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    <item>
      <title>Factors associated with alcohol-impaired driver crash deaths in the United States, 2018–2022</title>
      <link>https://trid.trb.org/View/2643811</link>
      <description><![CDATA[In the United States, the number of passenger vehicle drivers killed in crashes with blood alcohol concentrations (BACs) at or above 0.08% increased from 4,791 in 2019 to 5,540 in 2020 and remained elevated at 6,042 in 2022. This paper examines changes in alcohol policies, mental health factors, and law enforcement employment during 2018–2022 and their associations with alcohol-impaired driver deaths.  Panel regressions compared high-BAC (≥0.08%) driver deaths across states and months for all ages and ages 16–20. Predictors included state-level alcohol policy indicators (to-go and home-delivery), adult mental health indicators (past-year major depressive episodes and past-year suicide plans), and law enforcement employment levels. COVID-19 closures, vehicle miles traveled, and other variables were included as statistical controls.  From 2018 to 2022, the number of states permitting to-go or home-delivery alcohol purchases from bars or restaurants doubled, law enforcement employment declined, and mental health indicators increased. In a panel regression with all ages of drivers, alcohol home delivery policies, major depressive episodes, and suicide plans were associated with significantly more high-BAC driver deaths, whereas alcohol to-go policies and law enforcement employment were associated with significantly fewer high-BAC driver deaths. Only two predictors (law enforcement employment and suicide plans) were significant predictors of high-BAC driver deaths among ages 16–20.  Although the number of states permitting home-delivery and to-go alcohol increased, the associations with driver deaths were not consistent. Law enforcement employment and suicidality were two independent factors consistently associated with alcohol-impaired driver deaths. As law enforcement employment levels fell and as suicidality increased, alcohol-impaired driver deaths rose. The relationship between mental health factors and alcohol-impaired driving suggests that a broader public health focus that incorporates prevention and treatment services could play a role in helping to reverse the alcohol-impaired driving trend.]]></description>
      <pubDate>Thu, 15 Jan 2026 14:31:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643811</guid>
    </item>
    <item>
      <title>Traffic Safety Facts 2023 Data: Alcohol-Impaired Driving</title>
      <link>https://trid.trb.org/View/2576948</link>
      <description><![CDATA[In 2023 there were 12,429 fatalities in motor vehicle traffic crashes in which at least one driver was alcohol-impaired. This represented 30 percent of all traffic fatalities in the United States for the year. Traffic fatalities in alcohol-impaired-driving crashes decreased by 7.6 percent (13,458 to 12,429 fatalities) from 2022 to 2023. On average, one alcohol-impaired-driving fatality occurred every 42 minutes in 2023.  This fact sheet on alcohol-impaired driving for 2023 covers the following: economic cost for all traffic crashes; drivers; children; crash characteristics; time of day and day of week; data by state; and important safety reminders.]]></description>
      <pubDate>Mon, 21 Jul 2025 08:51:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2576948</guid>
    </item>
    <item>
      <title>Two programs, too many names? A critical review of ride-sharing and safe-ride programs as alternatives to impaired driving</title>
      <link>https://trid.trb.org/View/2526804</link>
      <description><![CDATA[Alternative transportation programs are widely promoted as a viable strategy for prevention of alcohol-impaired driving (AID) and crashes, with ride-sharing and safe-ride being two major approaches. The scientific literature on these programs frequently uses the terms “ride-sharing” and “safe-ride” interchangeably, though their meaning is not synonymous. This critical review set out to clarify the main characteristics of these programs to advance research, dissemination of the findings, and knowledge transfer in the alternative transportation field for AID and crash prevention. A systematic literature search of six databases using PRISMA-S checklist identified studies of ride-sharing and safe-ride programs to prevent AID or crashes. Inclusion criteria comprised studies published in academic and gray literature between 1980 and 2023. A six-step thematic analysis of included studies identified the defining characteristics of each program. The 32 included studies evaluated for-profit ride-sharing/ride-hailing programs (n = 21) and safe-ride programs (n = 11). No studies on non-profit ride-sharing programs were included. Analyses revealed two main themes. Operational strategies were most important for distinguishing between for-profit ride-sharing and safe-ride programs, with differences in these subthemes: purpose (revenue generation vs. AID reduction), management (private vs. private and other strategies), funding (self-financing vs. external), and promotion (convenient transportation vs. dangers of AID). Service offerings, the second theme, highlighted differences in program costs, availability, accessibility, service capacity, coverage, and types of vehicles used. The scientific literature on ride-sharing was limited to for-profit ride-sharing, suggesting that referring to them as “ride-hailing” in future studies would be more accurate. Both operational strategies and service offerings highlight the advantages and disadvantages of ride-hailing and safe-ride programs in the context of AID. Some programs referred to as ride-sharing programs have the same operational strategies as safe-ride programs, suggesting these be classified as safe-ride programs for conceptual coherence.]]></description>
      <pubDate>Wed, 28 May 2025 16:23:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2526804</guid>
    </item>
    <item>
      <title>Determinants influencing alcohol-related two-vehicle crash severity: A multivariate Bayesian hierarchical random parameters correlated outcomes logit model</title>
      <link>https://trid.trb.org/View/2437656</link>
      <description><![CDATA[Alcohol-related driving remains a significant concern due to its profound association with the likelihood of traffic crashes and the severity of resulting injuries, especially between two vehicles. To investigate the determinants influencing the alcohol-related two-vehicle crash severity, a foundational framework employed was a multinomial logit model. Meanwhile, by incorporating random intercept from individual case and vehicle levels to accommodate unobserved heterogeneity, and covariance matrices to underscore correlated outcomes, a multivariate hierarchical random parameters correlated outcomes logit model was proposed. Additionally, to further explore the potential temporal instability of explanatory variables, a random slope from a per-year indicator was introduced into the model. Crash data from the US Statewide Integrated Traffic Records System (SWITRS) database spanning from January 1, 2016, to December 31, 2021, was used. Three crash injury severity categories were examined, encompassing severe injury, minor injury, and no injury, with characteristics related to the driver, vehicle, road, environment, crash, and time serving as explanatory variables. The model results highlighted significant heterogeneity, with each case and vehicle accounting for 56.9% of the total variance for minor injuries and 50.8% for severe injuries. Furthermore, a significant negative correlation was explicitly exhibited between minor injury and severe injury outcomes at the case level. In terms of potential temporal instability, the authors provided per-year (2016–2019) parameter estimates and identified significant instability for indicators such as non-intersection, broadside and head-on collisions, cloudy weather conditions, and drivers who had been drinking but were not under the influence. Considering the impact of the COVID-19 pandemic, the authors divided the accident time into pre-COVID and during-COVID periods, modeling parameter estimates for both periods. This analysis revealed significant instability in several factors influenced by the pandemic. Additionally, noteworthy disparities in the estimated results of explanatory variables emerged in comparison to those general two-vehicle crashes or alcohol-related crashes, providing valuable insights. For instance, drivers who had been drinking but were not under the influence were less likely to sustain severe injuries, but the probability of minor injuries increased. These findings underscore the significance of thorough investigations into the determinants of injury severity in alcohol-impaired two-vehicle crash severity, along with the temporal instability of such factors. They hold important implications for effective traffic safety management and the formulation of prohibitive countermeasures.]]></description>
      <pubDate>Thu, 17 Oct 2024 09:15:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2437656</guid>
    </item>
    <item>
      <title>Traffic Safety Facts 2022 Data: Alcohol-Impaired Driving</title>
      <link>https://trid.trb.org/View/2384745</link>
      <description><![CDATA[In 2022 there were 13,524 fatalities in motor vehicle traffic crashes in which at least one driver was alcohol-impaired. This represented 32 percent of all traffic fatalities in the United States for the year. Traffic fatalities in alcohol-impaired-driving crashes decreased by 0.7 percent (13,617 to 13,524 fatalities) from 2021 to 2022. One alcohol-impaired-driving fatality occurred every 39 minutes in 2022, on average. Drivers are considered to be alcohol-impaired when their blood alcohol concentrations (BACs) are .08 grams per deciliter (g/dL) or higher. Thus, any fatal traffic crash involving a driver with a BAC of .08 g/dL or higher is considered to be an alcohol-impaired-driving crash, and fatalities occurring in those crashes are considered to be alcohol-impaired-driving fatalities. This fact sheet covers the economic cost for traffic crashes; drivers; children; crash characteristics; time of crashes; data by state; and important safety reminders.]]></description>
      <pubDate>Fri, 31 May 2024 16:49:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2384745</guid>
    </item>
    <item>
      <title>Traffic Safety Facts 2021 Data: Motorcycles</title>
      <link>https://trid.trb.org/View/2192560</link>
      <description><![CDATA[In 2021 there were 5,932 motorcyclists killed, 14 percent of all traffic fatalities. This is the highest number of motorcyclists killed since FARS started data collection in 1975. The number of motorcyclist fatalities in 2021 increased by 8 percent from 2020, from 5,506 to 5,932. An estimated 82,686 motorcyclists were injured in 2021, a 5-percent increase from 78,944 motorcyclists injured in 2020. Per vehicle miles traveled in 2021, the fatality rate for motorcyclists (30.05) was almost 24 times the passenger car occupant fatality rate (1.26). Thirty-six percent of motorcycle riders involved in fatal crashes in 2021 were riding without valid motorcycle licenses. In 2021 motorcycle riders involved in fatal crashes had higher percentages of alcohol impairment than drivers of any other motor vehicle type (28% for motorcycles, 24% for passenger cars, 20% for light trucks, and 3% for large trucks). Forty-three percent of motorcycle riders who died in single-vehicle crashes in 2021 were alcohol-impaired. Motorcycle riders killed in traffic crashes at night were three times more frequently found to be alcohol-impaired than those killed during the day (42% and 16%) in 2021. This fact sheet on motorcycles covers crash characteristics; crash involvement; age; motorcycle engine sizes; speeding; licensing and previous driving records; alcohol; helmet use and effectiveness; data by state; and important safety reminders.]]></description>
      <pubDate>Fri, 09 Jun 2023 10:55:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2192560</guid>
    </item>
    <item>
      <title>TIRF USA Road Safety Monitor 2022: Alcohol-Impaired Driving &amp; COVID-19 in the United States</title>
      <link>https://trid.trb.org/View/2112660</link>
      <description><![CDATA[The Traffic Injury Research Foundation, USA, Inc. (TIRF USA) surveyed 1,503 drivers in October 2022 regarding alcohol-impaired driving for its 8th annual public opinion survey, the 2022 USA Road Safety Monitor (RSM). The 2022 RSM also addressed COVID-19, decreased traffic volumes, and risky driving behavior. Findings include: 19.6% of survey respondents reported driving when they thought they exceeded the legal limit for alcohol, as compared to 22.5% in 2021; of these respondents 30.7% thought they were okay to drive and 12.6% thought they could still drive carefully. During the COVID-19 pandemic, 16.5% of survey respondents reported that they frequently drove within two hours of using alcohol, as compared to 18.2% prior to the pandemic; 24.1% reported sometimes (25.3% prior to pandemic), and 59.4% reported rarely (56.5% prior to pandemic). The report also discusses characteristics of respondents who reported driving over the legal limit and the use of designated drivers or safe rides.]]></description>
      <pubDate>Tue, 28 Feb 2023 09:18:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2112660</guid>
    </item>
    <item>
      <title>Prevalence of alcohol among drivers, riders and pedestrians injured in road traffic crashes in Cameroon: a cross-sectional study</title>
      <link>https://trid.trb.org/View/2016359</link>
      <description><![CDATA[The use of alcohol among road users injured in road traffic crashes and admitted to three major hospitals in Cameroon was studied. Alcohol use was measured using breathalyzers, and data on age, gender, education level, religion, type of road user, time of the crash, crash characteristics, and injury severity were recorded using a questionnaire. Of the 350 participants, 30.9% had blood alcohol concentrations (BACs) above 0.08% (legal limit for drivers); the proportion was highest among motorcycle riders (36.5%), followed by pedestrians (24.8%) and motor vehicle drivers (18.9%). The proportion with BAC above 0.08% was highest on weekend nights and among those who were most seriously injured. Those who reported being Muslims had a lower prevalence of alcohol. Multivariable logistic regression analysis confirmed those associations. Many road traffic injuries could have been avoided if the patient had not consumed alcohol. Actions should therefore be taken to reduce the proportion of alcohol-impaired road users. Supplemental data for this article is available online at https://doi.org/10.1080/17457300.2022.2030365 .]]></description>
      <pubDate>Tue, 11 Oct 2022 11:59:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2016359</guid>
    </item>
    <item>
      <title>Alcohol-impaired driving among adults—USA, 2014–2018</title>
      <link>https://trid.trb.org/View/1957016</link>
      <description><![CDATA[Alcohol-impaired driving (AID) crashes accounted for 10,511 deaths in the USA in 2018, or 29% of all motor vehicle-related crash deaths. This study describes self-reported AID in the USA during 2014, 2016 and 2018 and determines AID-related demographic and behavioral characteristics. Data were from the nationally representative Behavioral Risk Factor Surveillance System. Adults were asked ‘During the past 30 days, how many times have you driven when you have had perhaps too much to drink?’ AID prevalence, episode counts and rates per 1000 population were estimated using annualized individual AID episodes and weighted survey population estimates. Results were stratified by characteristics including gender, binge drinking, seatbelt use and healthcare engagement. Nationally, 1.7% of adults engaged in AID during the preceding 30 days in 2014, 2.1% in 2016 and 1.7% in 2018. Estimated annual number of AID episodes varied across year (2014: 111 million, 2016: 186 million, 2018: 147 million) and represented 3.7 million, 4.9 million and 4.0 million adults, respectively. Corresponding yearly episode rates (95% CIs) were 452 (412–492) in 2014, 741 (676–806) in 2016 and 574 (491–657) in 2018 per 1000 population. Among those reporting AID in 2018, 80% were men, 86% reported binge drinking, 47% did not always use seatbelts and 60% saw physicians for routine check-ups within the past year. Although AID episodes declined from 2016 to 2018, AID was still prevalent and more common among men and those who binge drink. Most reporting AID received routine healthcare. Proven AID-reducing strategies exist. Data are available in a public, open access repository.]]></description>
      <pubDate>Mon, 13 Jun 2022 13:14:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/1957016</guid>
    </item>
    <item>
      <title>Examining U.S. drivers’ characteristics in relation to how frequently they engage in speeding on freeways</title>
      <link>https://trid.trb.org/View/1909103</link>
      <description><![CDATA[Speeding and speed-related crashes have consistently represented over 25% of all traffic fatalities over the past two decades. The severity of these speed-related incidents not only impact the drivers but all road users. Thus, characterizing drivers who speed, understanding their motivations, and identifying the types of risky driving behaviors associated with speeding play a critical role in developing, implementing, and sustaining effective countermeasures. Using a survey administered to a U.S. nationally representative sample (N = 2,930 licensed drivers aged 16 or older), this study develops a partial proportional odds model to examine differences in characteristics between types of speeders – frequent, occasional, and non-speeders – and explores characteristics and risk driving behaviors that are most associated with speeding behavior. Additionally, motivations for speeding are examined for drivers who frequently speed compared with those who occasionally speed. Results show speeders tended to engage in other unsafe driving behaviors, such as distracted, aggressive, unbelted, and alcohol-impaired driving. Among demographic and socio-economic variables examined in this study, drivers’ age was the greatest associated determinant. The association with engagement in red-light running, however, outweighed that with drivers’ age. Interestingly, as drivers’ educational attainment increased, so did their engagement in speeding. Further, the interaction between educational attainment and engagement in aggressive driving was also predictive of speeding behavior. For motivations for speeding, frequent speeders were more likely to report enjoying driving fast and disagreeing with speed limits compared with occasional speeders. The findings of this study are useful towards identifying the various characteristics and behaviors of drivers who engage in speeding, which can provide future insights into where effective countermeasures and prevention efforts should be focused.]]></description>
      <pubDate>Tue, 29 Mar 2022 09:58:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/1909103</guid>
    </item>
    <item>
      <title>TIRF USA Road Safety Monitor 2021: Alcohol-impaired driving &amp; COVID-19 in the United States</title>
      <link>https://trid.trb.org/View/1900915</link>
      <description><![CDATA[This fact sheet summarizes the national results of the 2021 USA Road Safety Monitor (USA RSM) on alcohol-impaired driving. This is the seventh annual public opinion survey conducted by the Traffic Injury Research Foundation USA, Inc. (TIRF USA) with sponsorship from Anheuser-Busch Foundation. The survey takes the pulse of the nation regarding the alcohol-impaired driving issue by means of an online survey of a random, representative sample of United States drivers aged 21 years or older. A total of 1,498 drivers completed the poll in September 2021 (results can be considered accurate within plus or minus 2.5%, 19 times out of 20). The fact sheet summarizes key findings regarding the prevalence of alcohol-impaired driving, reasons for engaging in this behavior and characteristics of these drivers. Survey results are compared to data from previous years. In response to the COVID-19 pandemic, this RSM also describes the effects of the pandemic on risky driving behaviors. Research showed decreased traffic volumes led to increases in speeding and impaired driving (Hughes et al. 2020; Thomas et al. 2020; Vanlaar et al. 2021) and this survey provides additional insight.]]></description>
      <pubDate>Wed, 26 Jan 2022 14:26:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/1900915</guid>
    </item>
    <item>
      <title>Traffic Safety Facts 2019 Data: Alcohol-Impaired Driving</title>
      <link>https://trid.trb.org/View/1870323</link>
      <description><![CDATA[All 50 States, the District of Columbia, and Puerto Rico have set a threshold making it illegal to drive with a BAC of .08 g/dL or higher. In addition, people under 21 are legally prohibited from drinking alcohol (except in Puerto Rico where the legal drinking age is 18). Operating a commercial vehicle at a BAC of .04 g/dL or above is a violation of Federal regulations and may result in criminal charges. In 2019 there were 10,142 people killed in alcohol-impaired-driving crashes, an average of 1 alcohol-impaired-driving fatality every 52 minutes. These alcohol-impaired-driving fatalities accounted for 28 percent of all motor vehicle traffic fatalities in the United States in 2019. This fact sheet presents information on drivers; children; crash characteristics; time of day and day of week; data by state; economic cost for all traffic crashes; and important safety reminders.]]></description>
      <pubDate>Tue, 24 Aug 2021 10:36:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/1870323</guid>
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