Property Damage Only Crashes Research Articles

Factors affecting crash severity in Roundabouts: A comprehensive analysis in the Jordanian context

Roundabouts are widely embraced for their perceived safety advantages over other types of unsignalized intersections. However, there has been an observed increase in crash rates at roundabouts over time in Jordan. This paper delves into modeling traffic crash severity at roundabouts, considering various factors such as weather, lighting, vehicle characteristics, geometric features, and driver age and gender. To comprehensively analyze roundabout crashes in Jordan, we constructed rule-based classifiers and Random Forest models after balancing the dataset. Rule-based models offer interpretability, albeit with some simplicity trade-off, while Random Forest models provide deeper analysis but require additional explanation. Presenting both outputs to subject matter experts and policymakers facilitates a holistic understanding of factors contributing to roundabout crashes in Jordan. Subsequently, CN2 results revealed that injury severity crashes are influenced by the time of the day, driver age, day of the week, speed, and number of vehicles involved. On the other hand, property damage-only crashes are affected by the number of lanes, time of the day, type of driver fault, lighting conditions, speed, and day of the week. The RF model analysis unveiled crucial factors influencing crash severity in roundabouts, notably the varying impact of driver age, time of day, the number of vehicles involved, seasonality, and vehicle speed. This proposed approach is promising, comprehensive, and not only enhances the understanding of roundabout crashes but also informs the development of effective, localized safety interventions.

Investigating safety and cost-effectiveness of cable median barriers in Louisiana

Objectives Cable median barriers (CMBs) are installed on freeway medians to prevent cross-median crashes and reduce the severity of median-related crashes. Though CMBs are effective in preventing cross-median crashes, they are also known to increase the number of property damage–only (PDO) crashes. The higher frequency of PDO crashes could result in increased CMB maintenance and repair expenses. The aim of this study is to evaluate the safety impact and economic justification of CMBs in Louisiana. Methods Initially, a flowchart was developed using Louisiana crash data to identify targeted crashes, such as median-related and cross-median crashes. This was followed by a 3-year observational before-and-after crash analysis with an emphasis on head-on collisions and crashes involving large trucks. Using a 4-step improved prediction method, crash modification factors were then developed to quantitatively assess the impact of CMBs on crash outcomes, accounting for and adjusting to changes in the annual average daily traffic (AADT) and relevant crash frequencies before and after CMB implementation. Finally, an exhaustive benefit–cost analysis was conducted to determine the cost-effectiveness of CMBs. Results The results revealed that CMBs significantly reduced cross-median crashes of all severities. However, an increase in PDO crashes was observed in both total and median-related crashes. Large truck cross-median crashes and head-on collisions also decreased significantly after CMB implementation. Testing Level 4 (TL-4) CMBs were found to be more effective in preventing vehicles from crossing the median and in reducing crashes of higher severity levels. The benefit–cost ratios, calculated using economic crash unit costs for both total and targeted crashes, were greater than 1. Notably, the estimated benefit–cost ratios were considerably higher, demonstrating that CMBs are cost-effective countermeasures for enhancing traffic safety. Conclusion This study contributes to the understanding of CMB performance from both traffic safety and economic perspectives. The findings may assist transportation agencies in making decisions regarding the management of CMB systems. Based on the comprehensive analysis of CMBs on Louisiana freeways, this project has revealed that CMBs are an effective and economically justified crash countermeasure. Thus, further implementation of CMBs is recommended until better alternatives are available.

Effects of Phi and View Angle Geometric Principles on Safety of Multi-Lane Roundabouts

Conventional intersections that have been replaced by multi-lane roundabouts have experienced a substantial reduction in both injuries and fatal crashes. Property-damage-only (PDO) crashes have also been reduced at some of these roundabouts. However, some multi-lane roundabouts have experienced a significant increase in PDO crashes. The question arises as to why some U.S. multi-lane roundabouts have substantially higher numbers of PDO crashes while other outwardly similar roundabouts do not. In this paper, we examine the hypothesis that the cause of the higher numbers of PDO crashes at some U.S. multi-lane roundabouts is driver confusion, owing to the lack of adherence to horizontal geometric safety design principles related to entry angles. We review research and explore three case studies where adherence to the safety principles related to entry angles—Phi and left view angle—contributed to improved safety.

Safety effects of roundabout conversions in Carmel, Indiana, the Roundabout City

Introduction: Roundabouts are a proven safety countermeasure for intersection safety. This study examined the safety effects of roundabout conversions in Carmel, Indiana, also known as the “Roundabout City.” Doing so is of particular interest because Carmel has a high density of roundabouts and its drivers understand their effectiveness and are familiar with navigating them. This study also adds to the current state of knowledge about innovative double-teardrop roundabouts (i.e., linked roundabouts with teardrop-shaped central islands). Method: Negative binomial models accounting for correlation within site pairs were applied to evaluate the safety effects of converting conventional intersections to roundabouts on total crashes, injury crashes, and property-damage-only (PDO) crashes between study sites and control sites for different roundabout types (single-lane, multi-lane, and double-teardrop). We compared crash data from a 2-year period before the installation of the roundabouts with the 2-year period after the conversions. Results: Injury crashes were 47% lower than what would have been expected without the roundabout conversions. The effects were strongest at the double-teardrop roundabouts, where injury crashes were significantly reduced by 84% and total crashes by 63%. Single-lane roundabouts experienced significant decreases of 51% in total crashes and 50% in PDO crashes (and a nonsignificant decrease of 50% in injury crashes). Multi-lane roundabouts were associated with increases in total and PDO crashes but a 15% decrease in injury crashes, though all were nonsignificant. Conclusions: Overall, the City of Carmel’s roundabout program is associated with reductions in injury crashes, which indicates improvements to safety. Single-lane and double-teardrop roundabouts are associated with improvements in the occurrence and severity of crashes. Practical Applications: Double-teardrop roundabouts should be considered for installation at interchange terminals to improve highway safety.

Disaggregated traffic conditions and road crashes in urban signalized intersections

Introduction: Road safety studies in signalized intersections have been performed extensively using annually aggregated traffic variables and crash frequencies. However, this type of aggregation reduces the strength of the results if variables that oscillate over the course of the day are considered (speed, traffic flow, signal cycle length) because average indicators are not able to describe the traffic conditions preceding the crash occurrence. This study aims to explore the relationship between traffic conditions aggregated in 15-min intervals and road crashes in urban signalized intersections. Method: First, an investigation of the reported crash times in the database was conducted to obtain the association between crashes and their precursor conditions. Then, 4.1 M traffic condition intervals were consolidated and grouped using a hierarchical clustering technique. Finally, charts of the frequency of crashes per cluster were explored. Results: The main findings suggest that high vehicular demand conditions are related to an increase in property damage only (PDO) crashes, and an increase in the number of lanes is linked to more PDO and injury crashes. Injury crashes occurred in a wide range of traffic conditions, indicating that a portion of these crashes were due to speeding, while the other fraction was associated with the vulnerability of road users. Traffic conditions with: (a) low vehicular demand and a long cycle length and (b) high vehicular demand and a short cycle length were critical in terms of PDO and injury crashes. Practical Applications: The use of disaggregated data allowed for a stronger evaluation of the relationship between road crashes and variables that oscillate over the course of the day. This approach also permits the development of real-time risk management strategies to mitigate the frequency of critical traffic conditions and reduce the likelihood of crashes.

Modeling highly imbalanced crash severity data by ensemble methods and global sensitivity analysis

Crash severity has been extensively studied and numerous methods have been developed for investigating the relationship between crash outcome and explanatory variables. Crash severity data are often characterized by highly imbalanced severity distributions, with most crashes in the Property-Damage-Only (PDO) category and the severe crash category making up only a fraction of the total observations. Many methods perform better on outcome categories with the most observations than other categories. This often leads to a high modeling accuracy for PDO crashes but poor accuracies for other severity categories. This research introduces two ensemble methods to model imbalanced crash severity data: AdaBoost and Gradient Boosting. It also adopts a more reasonable performance metric, F1 score, for model selection. It is found that AdaBoost and Gradient Boosting outperform other benchmark methods and generate more balanced prediction accuracies. Additionally, a global sensitivity analysis is adopted to determine the individual and joint impacts of explanatory factors on crash severity outcome. Vertical curve, seat belt use, accident type, road characteristics, and truck percentage are found to be the most influential factors. Finally, a simulation-based approach is used to further study how the impact of a particular factor may vary with respect to different value ranges.

A crash severity analysis at highway-rail grade crossings: The random survival forest method

This paper proposes a machine learning approach, the random survival forest (RSF) for competing risks, to investigate highway-rail grade crossing (HRGC) crash severity during a 29-year analysis period. The benefits of the RSF approach are that it (1) is a special type of survival analysis able to accommodate the competing nature of multiple-event outcomes to the same event of interest (here the competing multiple events are crash severities), (2) is able to conduct an event-specific selection of risk factors, (3) has the capability to determine long-term cumulative effects of contributors with the cumulative incidence function (CIF), (4) provides high prediction performance, and (5) is effective in high-dimensional settings. The RSF approach is able to consider complexities in HRGC safety analysis, e.g., non-linear relationships between HRGCs crash severities and the contributing factors and heterogeneity in data. Variable importance (VIMP) technique is adopted in this research for selecting the most predictive contributors for each crash-severity level. Moreover, marginal effect analysis results real several HRGC countermeasures’ effectiveness. Several insightful findings are discovered. For examples, adding stop signs to HRGCs that already have a combination of gate, standard flashing lights, and audible devices will reduce the likelihood of property damage only (PDO) crashes for up to seven years; but after the seventh year, the crossings are more likely to have PDO crashes. Adding audible devices to crossing with gates and standard flashing lights will reduce crash likelihood, PDO, injury, and fatal crashes by 49 %, 52 %, 46 %, and 50 %, respectively.

Safety effects of automated section speed control on the Italian motorway network

Introduction: Automated Section Speed Control (ASSC) has been identified as an effective countermeasure to reduce speeds and improve speed limit compliance. Method: An Empirical Bayes (EB) before-and-after study was performed in this research in order to evaluate the impact of the ASSC system on the expected crash frequency. The study was carried out on a sample of 125 ASSC sites of the Italian motorway network covering 1252 km, where a total of 21,721 crashes were recorded during a 10-year analysis period from 2004 to 2013. Results: Overall, the EB analysis estimated a significant 22% reduction in the expected crash frequency due to the implementation of the ASSC system. The analysis indicated that the effect is slightly larger on property damage only (PDO) crashes (−23%) than on fatal injury (FI) crashes (−18%) and that the highest reductions in crash frequency are expected for multi-vehicle FI crashes (−25%) and multi-vehicle PDO crashes (−31%). Furthermore, the results indicated that the ASSC system is more effective in reducing crash rates when traffic volume increases and it is therefore strongly recommended as a countermeasure to improve safety on high-traffic-volume motorway sections.

Severity of motorcycle crashes in Dar es Salaam, Tanzania

Objective: Motorcycles are a common mode of transportation in low- and middle-income countries. Tanzania, in particular, has experienced an increased use of motorcycles in the last decade. In Dar es Salaam, motorcycles provide door-to-door travel and often operate where more conventional services are uneconomical or physically impossible to maneuver. Although motorcycles play a crucial role in improving mobility in the city, they have several safety issues. This study focuses on identifying factors influencing the severity of motorcycle crashes.Method: A multinomial logit analysis was conducted to identify factors influencing the severity of motorcycle crashes in Dar es Salaam, Tanzania. The severity categories were fatal, severe injury, minor injury, and property damage only (PDO). The analysis was based on a total of 784 motorcycle crashes that occurred from 2013 to 2016.Results: The following factors were found to increase the probability of a fatality: Speeding, driving under the influence, head-on impact, presence of horizontal curves, reckless riding, off-peak hours, violations, and riding without a helmet. The results indicate that crashes occurring on weekdays, during peak hours, at intersections, involving a rear-end impact, in daylight, on street roads, and under clear weather conditions decrease the probability of a fatality. However, minor injury and PDO crashes were found to be associated with crashes occurring during peak hours, at intersections, and on street roads, as well as failure to yield right-of-way.Conclusions: Several countermeasures are recommended based on the study findings. The recommended countermeasures focus on the holistic safety improvement strategies constituting the three Es of highway safety, namely, engineering, education, and enforcement.

A Hybrid model for locating new emergency facilities to improve the coverage of the road crashes

We propose an emergency facility-locating model aimed at increasing the coverage of emergency demand throughout the city. The proposed model takes into account the status and location of the emergency facilities in the network and identifies locations suitable for the construction of new facilities. Here, Data Envelopment Analysis (DEA) and Maximum Coverage Location Problem (MCLP) have been combined in a single model. To do so, design problem and evaluation problem are considered concurrently to maximize the efficiency of services provided by emergency facilities across the city in response to the demand. Moreover, the total emergency demand in each district was considered in relation to the population density, the fatal, injurious, and property damage only (PDO) crashes. The coverage area of each emergency facility was assumed to be proportional to the average ambulance speed in the surrounding road network during rush hours. The available budget was included in the model to let the model function under various fiscal conditions. Model input variables consisted of average number of mortalities, injuries and PDO crashes as well as the population density of each urban district. The output variables of the model included the coverage share of proposed emergency centers and hospitals equipped with ambulances. The model was tested on the network of Tehran (Iran). It is recommended to add the location of some emergency centers and hospitals to the network. Moreover, the results showed that ten urban districts had efficiency problem in provision of emergency services.

Safety Impacts of Signing and Pavement Markings on Property-Damage-Only Crashes at Multi-Lane Roundabouts

Conventional intersections that have been replaced by multi-lane roundabouts have experienced a substantial reduction in both injury and fatal crashes. Property-damage-only (PDO) crashes have also been reduced at some of these roundabouts. However, some have experienced a significant increase in PDO crashes. This has caused some jurisdictions to question the suitability of multi-lane roundabouts despite their benefit of reduced injury and fatal crashes. The question arises as to why some U.S. multi-lane roundabouts have high numbers of PDO crashes whereas other outwardly similar roundabouts do not. This paper examines the hypothesis that the cause of the higher numbers of PDO crashes at some U.S. multi-lane roundabouts is driver confusion and information overload, arising from a combination of poor geometric layout, signing, and pavement markings. Successful roundabout design requires that the geometric layout, the signing, and the pavement markings act together to give a simple, clear message to the drivers, thereby avoiding driver confusion and reducing PDO crashes. This paper reviews research and explores the best practice for roundabout signing and pavement marking using established traffic engineering principles and discusses aspects of the 2009 Manual on Uniform Traffic Control Devices that may contradict these principles. The paper highlights two case studies of poorly performing U.S. multi-lane roundabouts, where the revised signing and pavement markings achieved 37–80% reduction in PDO accidents.

Safety analysis of urban arterials at the meso level

Urban arterials form the main structure of street networks. They typically have multiple lanes, high traffic volume, and high crash frequency. Classical crash prediction models investigate the relationship between arterial characteristics and traffic safety by treating road segments and intersections as isolated units. This micro-level analysis does not work when examining urban arterial crashes because signal spacing is typically short for urban arterials, and there are interactions between intersections and road segments that classical models do not accommodate. Signal spacing also has safety effects on both intersections and road segments that classical models cannot fully account for because they allocate crashes separately to intersections and road segments. In addition, classical models do not consider the impact on arterial safety of the immediately surrounding street network pattern. This study proposes a new modeling methodology that will offer an integrated treatment of intersections and road segments by combining signalized intersections and their adjacent road segments into a single unit based on road geometric design characteristics and operational conditions. These are called meso-level units because they offer an analytical approach between micro and macro. The safety effects of signal spacing and street network pattern were estimated for this study based on 118 meso-level units obtained from 21 urban arterials in Shanghai, and were examined using CAR (conditional auto regressive) models that corrected for spatial correlation among the units within individual arterials. Results showed shorter arterial signal spacing was associated with higher total and PDO (property damage only) crashes, while arterials with a greater number of parallel roads were associated with lower total, PDO, and injury crashes. The findings from this study can be used in the traffic safety planning, design, and management of urban arterials.

Real‐time identification of traffic conditions prone to injury and non‐injury crashes on freeways using genetic programming

SummaryThis study applied the genetic programming (GP) model to identify traffic conditions prone to injury and property‐damage‐only (PDO) crashes in different traffic states on freeways. It was found that the traffic conditions prone to injury and PDO crashes can be classified into a high‐speed and a low‐speed traffic state. The random forest (RF) analyses were conducted to identify the contributing factors to injury and PDO crashes in these two traffic states. Four separate GP models were then developed to link the risks of injury and PDO crashes in two traffic states to the variables selected by the RF. An overall GP model was also developed for the combined dataset. It was found that the separate GP models that considered different traffic states and crash severity provided better predictive performance than the overall model, and the traffic flow variables that affected injury and PDO crashes were quite different across different traffic states. The proposed GP models were also compared with the traditional logistic regression models. The results suggested that the GP models outperformed the logistic regression models in terms of the prediction accuracy. More specifically, the GP models increased the prediction accuracy of injury crashes by 10.7% and 8.0% in the low‐speed and high‐speed traffic states. For PDO crashes, the GP models increased the prediction accuracy by 7.4% and 6.0% in the low‐speed and high‐speed traffic states. Copyright © 2016 John Wiley & Sons, Ltd.

Site-Specific Safety Analysis of Diverging Diamond Interchange Ramp Terminals

A site-specific analysis of the safety of diverging diamond interchange (DDI) ramp terminals was conducted for the first time. Crash modification factors (CMFs) were developed for DDI ramp terminals for different crash severity levels. The ramp terminal CMFs complement the project-level DDI CMFs developed in previous research. The study used data from 20 ramp terminals in Missouri. The safety evaluation was conducted with two before-and-after observational methods: comparison group (CG) and empirical Bayes (EB). Because of inaccurate crash locations, a systematic crash location correction process was developed. An extensive review of 8,400 individual crash reports was conducted for the calibration and safety evaluation. Both before-and-after safety evaluation methods produced consistent results. The DDI design replacing a conventional diamond decreased the numbers of ramp terminal–related crashes for all severity levels. The most significant crash reduction by method was observed for fatal and injury (FI) crashes: 73.3% (CG) and 63.4% (EB). Property damage only (PDO) crashes were reduced by 21.0% (CG) and 51.2% (EB). The total crash frequency also decreased by 42.7% (CG) and 54.0% (EB). The EB CMF values for the DDI ramp terminal were 0.366 for FI crashes, 0.488 for PDO crashes, and 0.460 for total crashes. This study serves as a case study for conducting a site-specific analysis of ramp terminals or other interchange facilities. The methodology that was used is transferable and can be used to quantify the safety effects of other innovative intersection and interchange designs.

Safety assessment of the conversion of toll plazas to all-electronic toll collection system

Traditional mainline toll plaza (TMTP) is considered the most high-risk location on the toll roads. Conversion from TMTP or hybrid mainline toll plaza (HMTP) to an all-electronic toll collection (AETC) system has demonstrated measured improvement in traffic operations and environmental issues. However, there is a lack of research that quantifies the safety impacts of these new tolling systems. This study evaluated the safety effectiveness of the conversion from TMTP or HMTP to AETC system. An extensive data collection was conducted that included hundred mainline toll plazas located on more than 750miles of toll roads in Florida. Various observational before-after studies including the empirical Bayes method were applied.The results indicated that the conversion from the TMTP to an AETC system resulted in an average crash reduction of 76, 75, and 68% for total, fatal-and-injury and property damage only (PDO) crashes, respectively; for rear end and lane change related (LCR) crashes the average reductions were 80 and 74%, respectively. The conversion from HMTP to AETC system enhanced traffic safety by reducing crashes by 24, 28 and 20% of total, fatal-and-injury, and PDO crashes respectively; also, for rear end and LCR crashes, the average reductions were 15 and 22%, respectively.Overall, this paper provided an up-to-date safety impact of using different toll collection systems. The results proved that the AETC system significantly improved traffic safety for all crash categories; and changed toll plazas from the highest risk on Expressways to be similar to regular segments.

Developing Calibration Factors for Crash Prediction Models with Consideration of Crash Recording Threshold Change

The focus of this paper is on presenting a revised method to develop calibration factors (CFs) with consideration of the change in the crash recording threshold (CRT), which is a minimum value to report crashes. The higher the CRT, the fewer the number of recorded property damage only (PDO) crashes. In this paper, a threshold adjustment factor was defined and used to estimate the new CFs. Because the threshold change affects only the total number of crashes and the PDO crashes, the percentage of fatal and injury (F/I) crashes before the threshold change needs to be adjusted to properly estimate the total number of F/I crashes. The revised method was verified with case studies using Illinois data. Five years of crash data were gathered and used to develop CFs for five roadway types, including two-lane undivided (2U), two-lane with a two-way left-turn lane (3T), four-lane undivided (4U), four-lane divided (4D), and four-lane with a two-way left-turn lane (5T). Because of an increase in the CRT in 2009, a method is needed to supplement the standard approach to adjust CFs with consideration of the effect of the new CRT. The CFs for 2U and 3T before–after considering the threshold adjustment factor were 1.44/1.32 and 1.24/1.12, respectively, while the CFs before–after the threshold change for 4U, 4D, and 5T were 0.99/0.85, 0.68/0.55, and 0.77/0.69, respectively. The results proved that the revised method can help state and local agencies predict the number of crashes without redeveloping new CFs resulting from the change in CRT.

Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots

Hot spot identification (HSID) aims to identify potential sites—roadway segments, intersections, crosswalks, interchanges, ramps, etc.—with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset.

Assessing the Effect of Weather States on Crash Severity and Type by Use of Full Bayesian Multivariate Safety Models

Rather than investigate the isolated effects of individual weather elements on crash occurrence, this study investigated the aggregated effect of weather states, defined as a combination of various weather elements (e.g., temperature, snow, rain, and wind speed), on crash occurrence. The main argument was that a combination of weather elements might better represent a particular weather condition and subsequent safety outcome. Therefore, to explore the effect of various weather states on crash severity and type, this study defined 12 weather states, based on temperature, snow, rain, and wind speed, and developed multivariate safety models by using 11 years of daily weather and crash data for Edmonton, Alberta, Canada. The proposed models were estimated in a full Bayesian context via a Markov chain Monte Carlo simulation, while a posterior predictive approach assessed the models’ goodness of fit. Results suggested that property-damage-only (PDO) crashes increased by 4.5% to 45% because of adverse weather states and showed that PDO crashes were more affected by adverse weather states than were severe (injury and fatal) crashes. For crash type, adverse weather states were associated with an increase of 9% to 73.7% for all crash types, with the highest increase for run-off-the-road crashes. Duration of daylight was found to be significant and negatively related to all crash types and PDO crashes. Sudden weather changes of major snow or rain were statistically significant and positively related to all crash types. Days of the week and seasons of the year were used as dummy variables and were statistically significant in relation to crash occurrence.

Validity of surrogate measures of alcohol involvement when applied to nonfatal crashes

Since the 1970s, nighttime fatal crashes have been used as a surrogate measure for alcohol-related fatalities for crashes for which more direct measures were absent. The validity of this approach was confirmed in 1985 but has not been re-evaluated since. Although this measure has also been applied to identify alcohol involvement in nonfatal crashes, its validity when applied to nonfatal cases has never been determined. The objective of this study was to evaluate the appropriateness of using nighttime crashes as surrogate measures for alcohol impairment when applied to fatal and nonfatal injury and property damage only (PDO) crashes. To do so, we used data from a crash–control design study collected at the roadside in two U.S. states between 1997 and 1999, as well as from the 1997–1999 and 2004–2006 Fatality Analysis Reporting System. The outcome of this study confirms the validity of using nighttime crashes as a surrogate measure for alcohol-related fatalities and supports the use of after-midnight crashes for measuring alcohol involvement in nonfatal and PDO crashes when the number of late-night crashes permits.