Crash Countermeasures Research Articles

Safety evaluation for regulation changes on commercial vehicle operation using multilevel Bayesian methods

Truck-involved crashes cause serious social and economic losses, and the crash severity is higher compared to ordinary vehicles. Driver fatigue is a major crash causation, especially have a larger impact on truck drivers. Therefore, mandating a truck rest-break is one of the road safety management strategies for reducing both truck-involved crash frequency and severity. This paper analyses the change in safety performance according to the revision of the truck rest-break time on highways. Because spatial heterogeneity and homogeneity should be considered to estimate safety effects precisely after executing crash countermeasures, this study estimates the safety effect after the revision of the Trucking Transport Business Act, by developing a model based on the Multilevel Full-Bayes before and after the study. The safety performance function was developed in different section units and distributions, and the crash modification factor was calculated for the most suitable model. As a result of the analysis, the performance of the Multilevel Bayesian Poisson-gamma model was the highest, and it was found that there was a crash reduction effect after the revision of the truck break time. The results of this study can be referred to when preparing measures for road safety regulations.

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.

Insights Into Wire Rope Safety Barrier Crashes Based on Police-Reported Statistics and Narratives

Wire rope safety barrier (WRSB) is known to be highly effective in reducing the severity of off-road or off-path crashes, however fatal and serious injury outcomes still occur in a small percentage of WRSB-involved crashes. Yet, there is little research on why some WRSB crashes result in severe injury while the majority of crashes involve minor injury outcomes. This paper includes detailed analysis of off-path crashes involving WRSB to better understand associated factors that contribute to severe injury outcomes. Three datasets were analysed: four years of NSW police-reported crash data (2014-2017); ten years of Victorian police-reported crash data and police narratives (2008-2017); five years of police narratives from the US (2001-2005). Results supported earlier research that indicated a relatively low percentage of WRSB crashes involved fatal and serious injury outcomes. Yet, adverse vehicle dynamics were also observed, such as vehicle ricochetting and barrier override, suggesting barrier safety performance could be improved. Some crashes also involved impact angles greater than those used in crash tests, supporting earlier, more detailed research that the full range of real-world crash conditions involving WRSB are not covered in barrier test protocols, and these might be the conditions contributing to severe injury outcomes. The findings provide insight into the potential factors associated with the serious injury outcomes of crashes and can guide further improvements in this effective highway crash countermeasure. Future research should include detailed analysis of real-world crashes to identify factors contributing to adverse crash dynamics, injury outcomes and subsequent implications for barrier design.

Examining the who, what, and how of risky driving related crashes in residential areas

This study contributes to efforts towards creating livable communities, by identifying and proposing countermeasures for factors that are associated with residential area crashes. Three risky driving pre-crash actions: driving under the influence of alcohol or drug, aggressive driving, and speeding were considered. The study used residential area crash data from Alabama, USA and developed a latent class multinomial logit model to identify factors associated with the pre-crash actions. The results showed that male drivers had 0.44% and 2.09% higher chances to be at fault in driving under the influence of alcohol or drug and aggressive driving crashes, respectively, while female drivers were found to have a 1.82% higher likelihood to be at fault in speeding-related crashes but less likely to be at fault in aggressive driving or driving under the influence of alcohol or drug-related crashes in residential areas. Speeding and driving under the influence of were found to be the leading contributing factors in rural area residential crashes whereas aggressive driving was more pronounced in urban areas. These findings provide a basis for the implementation of appropriate crash countermeasures to reduce residential area crashes, as part of efforts geared towards promoting community safety and livability across the state.

Investigating the Safety Effectiveness of Wildlife–Vehicle Crash Countermeasures using a Bayesian Approach with a Comparison between Carcass Removal Data and Traditional Crash Data

Wildlife–vehicle crashes (WVCs) pose a significant threat to not only wildlife populations but also highway safety. The most expensive WVC countermeasures include crossing structures with fencing, whereas the least expensive countermeasure is the wildlife warning signs. This study is aimed at estimating the crash modification factors (CMFs) for these two countermeasures using cross-sectional analysis. Two types of WVC data are used in this study: carcass removal data and traditional crash data. A random-intercept Bayesian approach was utilized to incorporate the contributing factors representing traffic volume, roadway geometry, weather conditions, and unobserved heterogeneity resulting from between-site variance. The No-U-Turn Hamiltonian Monte Carlo sampling technique was employed because of its high efficiency in handling complex models. The results suggest that the treatment of implementing wildlife warning signs on hotspots of high WVCs has been ineffective, perhaps because warning signs are passive devices, and the high uncertainty of wildlife interaction still remains. The crossing structures are found to be effective, with an estimated CMF of 0.66 and 0.55 using the carcass data and crash data, respectively. Recommendations could be made to implement more active information dissemination via wildlife-actuated warning signs, where crossing structures may not be feasible. The findings from this study indicate that the carcass removal data are more comprehensive than the crash data, despite the underreporting issue existing in both datasets. Therefore, a unique identifier should be added in both datasets to enable merging the data and obtain more complete results from the analyses.

A comparative analysis of factors influencing the injury severity of daytime and nighttime crashes on a mountainous expressway in China

This study focuses on analyzing the injury severity of crashes occurring at different times of the day and providing insights into crash prevention countermeasures. The data contained 1521 police-reported crashes that occurred on a mountainous expressway between 2012 and 2017, which were divided into two subsamples: the daytime crash sample and the nighttime crash sample. The statistical plausibility of developing separate models for the two subsamples was verified by the likelihood ratio test. Two random thresholds random parameters hierarchical ordered probit models were independently conducted to analyze the relationship between injury severity and risk factors. The results showed that the contributing factors to injury severity were different between the two subsamples. The three factors most likely to cause serious crashes during the daytime were ‘not keep a safe distance’, ‘drunk driving’ and ‘adverse weather’, while during the nighttime, these three factors were ‘fatigued driving’, ‘adverse weather’ and ‘drunk driving’. The same factors can cause more serious consequences during the nighttime than that during the daytime. After fully identifying the contributing factors related to injury severity, and in particular distinguishing the features of daytime and nighttime crashes, some useful suggestions were proposed to mitigate crash injury severity.

A comprehensive analysis of factors that influence interstate highway crash severity in Alabama

This paper identifies factors that influence the severity of interstate crash outcomes and how they vary depending on the location and manner of collision. Four separate injury severity models were developed to explore the differences and similarities in crash factors between single-and multi-vehicle crashes that occurred in rural and urban areas of the state. Random parameters multinomial logit with heterogeneity in means and variances modeling approach was used to account for unobserved heterogeneity in the crash data. The model estimation results show that some driver behavioral factors such as speeding, aggressive driving, failure to use seatbelt, and driving without a valid license were found to significantly contribute to some form of injury outcome. The influence of roadway features such as type of opposing lane separation, collision type, temporal and lighting conditions on crash outcomes were also explored. Some differences and similarities in the associations between these factors and crash injury severity based on the manner and location of crash were unraveled. These findings are expected to guide the implementation of crash countermeasures on interstates. The findings of this study further support the evidence for the analysis of subsets of crash data to unravel underlying complex relationships within factors that influence crash injury severity.

Factors associated with driver injury severity of lane changing crashes involving younger and older drivers

Lane change maneuvers can be a difficult driving task for many drivers, particularly, younger and inexperienced drivers and older drivers. Frequent and improper lane changing has a substantial effect on both traffic operations and safety. This study investigates the factors that contribute to the injury severity of crashes resulting from improper lane change maneuvers involving younger and older drivers in Alabama. Crash data for the study was obtained from the Critical Analysis Reporting Environment (CARE) system developed by the Center for Advanced Public Safety at the University of Alabama. Preliminary data analysis showed that younger drivers were responsible for about 63.1 % of the crashes. Random logit with heterogeneity in means models were developed to identify significant crash factors that were associated with the crash outcomes. The results show that younger male drivers were more likely to be severely injured in lane changing crashes whereas older male drivers were less likely to be severely injured. The results further show that younger drivers were more likely to sustain a major injury on six-lane highways whereas older drivers sustained major injuries from overtaking maneuvers on two-lane highways. It was further found that while younger drivers got into major injury crashes under daylight conditions, older drivers were more likely to be involved in major injury crashes under dark/unlit lighting conditions. Improper lane changing constitutes some form of aggressive driving which needs to be addressed considering that many lives are lost annually from the practice. The findings from this study may be used by road safety advocates and practitioners to identify what and how to target crash countermeasures to the younger and older driver population groups in the state.

What, Who, and When? The Perceptions That Young Drivers and Parents Have of Driving Simulators for Use in Driver Education

Driver education providers may utilise technologies such as driving simulators to augment their existing courses. Understanding the perceptions that young drivers and parents have of simulators may help to make simulator-based driver education more accepted and more likely to be effective. Young drivers and parents completed an online questionnaire that included a “simulator invention” visualisation task. Items based on the Goals for Driver Education framework investigated perceptions of the most appropriate skill type, while others examined the most suitable target group for simulator training, and timing in relation to completing a formal driver education course for simulator training to occur. Both groups perceived that simulators were most appropriate for training a combination of physical, traffic, psychological, and social driving skills with learner drivers during attendance at a novice driver education program. Young drivers and parents had similar perceptions regarding the amount that each skill type should be trained using a simulator. Understanding the perceptions of young drivers and parents, and especially those who are somewhat naïve to the use of driving simulators, may aid in the introduction and administration of simulator training and may increase the effectiveness of driver education as a crash countermeasure.

Modeling of road traffic crash countermeasures in Ogun State

Road traffic crash is a global concern and Nigeria is not left behind. In 2016, 387 Road Traffic Crashes were recorded in Ogun State out of which 279 persons were killed and 1366 were injured The aim of the study is to develop a model for describing road traffic crash countermeasures in Ogun State. Questionnaire on existing safety measures which involved 8 questions were administered to 240 respondents drawn from six of the twenty LGAs of Ogun State. A multivariate regression model was developed for describing road traffic crash countermeasures. The model revealed that all the countermeasures contributed positively to the overall level of road traffic crash control. Maintenance of road network with positive regression parameter of 1.0610 contributed most to the overall reduction in road traffic crash in the study area. It is therefore concluded that more attention should be channeled towards road maintenance and rehabilitation in Ogun State. Keywords: Countermeasures, crashes, road network, road maintenance

Exploratory spatial analysis of traffic crashes, road mortality and morbidity in Nigeria

AbstractThis study examined the spatial distribution of road traffic crashes, mortality and morbidity in Nigeria for the period 2007–2017. The influence of exposure, road network and socio‐demographic characteristics on fatalities and injuries was analysed. Data were obtained from Federal Road Safety Corps and Annual Abstract of Statistics. Spatial statistical techniques were employed to determine the pattern of crashes, mortality and morbidity. Ordinary least squares and geographically weighted regression models were used to identify significant variables. Crashes and mortality declined by 47.9 per cent and 46.3 per cent respectively, while morbidity increased by 78.6 per cent. Crashes, mortality and morbidity were significantly clustered and high in Niger, Kaduna, FCT, Kogi and Nassarawa States. FCT recorded the highest crashes and injured persons, while Kaduna recorded the highest fatalities. Variables that significantly influenced spatial variation of mortality and morbidity were length of asphaltic concrete, surfaced dressed and earth roads, unemployment and population density. This study shows that type of road is a major factor that contributes to road crash mortality and morbidity. Crash countermeasures such as implementation of safety standards during road construction, speed reduction strategies and enforcement of seat belt use and child restraint should be implemented.

Identifying characteristics that impact motor carrier safety using Bayesian networks

Problem StatementIn the U.S., a safety rating is assigned to each motor carrier based on data obtained from the Motor Carrier Management Information System (MCMIS) and an on-site investigation. While researchers have identified variables associated with the safety ratings, the specific direction of the relationships are not necessarily clear. ObjectiveThe objective of this study is to identify those relationships involved in the safety ratings of interstate motor carriers, the largest users of the U.S. transportation network. MethodBayesian networks are used to learn these relationships from data obtained from MCMIS for a 6-year period (2007–2012). ResultsOur study shows that safety rating assignment is a complex process with only a subset of the variables having statistically significant relationship with safety rating. They include driver out-of-service violations, weight violations, traffic violations, fleet size, total employed drivers, and passenger & general carrier indicators. ApplicationThe findings have both immediate implications and long term benefits. The immediate implications relate to better identification of unsafe motor carriers, and the long term benefits pertain to policies and crash countermeasures that can enhance carrier safety.

Crash causes, countermeasures, and safety policy implications

There are interrelationships between crash causes, countermeasures, and policy implications, but they are not necessarily direct and obvious. Part of the problem is the definition of a cause. The seminal 1979 Indiana University “Study of Accident Causes” has cemented some false assumptions that must be overcome to yield an effective crash countermeasures policy. The taxonomy of crash causes and the prevalence of different causes are determined by the investigators, who are biased in different ways. The prevalent notion that approximately 90 percent of the crashes are due to human errors or failures is due to a threshold bias, and the implied notion that 90 percent of the countermeasures should be directed at changing these behaviors is based on an erroneous assumption that the cure must be directly linked to the stated cause. A more balanced approach to the definition of a cause and to the search for crash countermeasures is needed, and the safe system approach appears to be a most promising one.

Built environment effects on bike crash frequency and risk in Beijing

IntroductionBuilding a safe biking environment is crucial to encouraging bicycle use. In developed areas with higher density and more mixed land use, the built environment factors that pose a crash risk may vary. This study investigates the connection between biking risk factors and the compact built environment, using data for Beijing. MethodIn the context of China, this paper seeks to answer two research questions. First, what types of built environment factors are correlated with bike-automobile crash frequency and risk? Second, how do risk factors vary across different types of bikes? Poisson lognormal random effects models are employed to examine how land use and roadway design factors are associated with the bike-automobile crashes. ResultsThe main findings are: (1) bike-automobile crashes are more likely to occur in densely developed areas, which is characterized by higher population density, more mixed land use, denser roads and junctions, and more parking lots; (2) areas with greater ground transit are correlated with more bike-automobile crashes and higher risks of involving in collisions; (3) the percentages of wider streets show negative associations with bike crash frequency; (4) built environment factors cannot help explain factors contributing to motorcycle-automobile crashes. Practical ApplicationsIn China's dense urban context, important policy implications for bicycle safety improvement drawn from this study include: prioritizing safety programs in urban centers, applying safety improvements to areas with more ground transit, placing bike-automobile crash countermeasures at road junctions, and improving bicycle safety on narrower streets.

Evaluation of left-turn lane offset using the naturalistic driving study data

IntroductionThe Strategic Highway Research Program 2 (SHRP 2) Naturalistic Driving Study (NDS) data were used to evaluate gap acceptance behavior of drivers at left-turn lanes with negative, zero, or positive offsets ranging from −29ft to +6ft. The objectives of the study were to develop guidance for the design of offset left-turn lanes used as a safety countermeasure, and to provide insight regarding the use of the NDS data to future users. MethodThe study included 3350 gaps in opposing traffic evaluated by 145 NDS volunteer drivers and 275 non-NDS drivers at 14 two-way stop-controlled intersections and 44 signalized opposing left-turn pairs. Logistic regression was used to model the critical gap length for drivers as a function of offset, under conditions when their view was either blocked or not by an opposing left-turning driver. ResultsThe analysis found that the critical gap was longer at left-turn lanes with negative offsets than at those with zero or positive offsets, and was also longer when sight distance was blocked by an opposing left-turning vehicle. Sight distance was much more likely to be restricted by an opposing left-turning vehicle at negative-offset and drivers at those intersections were less likely to accept a gap when an opposing left-turn driver was present. ConclusionsLonger gap lengths could potentially result in decreased operational efficiency of an intersection. In addition, drivers making left-turns at negative-offset left-turn lanes are, on average, more likely to leave the shortest amount of time between their turn and the arrival of the next opposing through-vehicle, which may present a potential safety concern. Practical applicationsThe findings provide guidance for highway designers considering using offset left-turn lanes as a crash countermeasure. This research also highlights the benefits and limitations of using the SHRP 2 NDS data to answer similar research questions.

Association knowledge for fatal run-off-road crashes by Multiple Correspondence Analysis

In 2013, 346 out of 616 fatal crashes in Louisiana were single vehicle crashes with Run-Off-Road (ROR) crashes being the most common type of single vehicle crash. In order to create effective countermeasures for reducing the number of fatal single vehicle ROR crashes, it is important to identify any associated key factors that can quantitatively assess the performance of roads, vehicles and humans. This research uses Multiple Correspondence Analysis (MCA), a multidimensional descriptive data analysis method that associates a combination of factors based on their relative distance in a two dimensional plane, to analyze eight years (2004–2011) of fatal ROR crashes in Louisiana. This method measures important contributing factors and their degree of association. The results revealed that drivers of lightweight trucks, drivers on undivided state highways, male drivers in passenger-vehicles at dawn, older female (65–74) drivers in non-passenger vehicles, older drivers facing hardship to yield in partial access control zones, and drivers with poor reaction time due to impaired driving were closely associated with fatal ROR crashes.Results of the MCA method can help researchers select the most effective crash countermeasures. Further work on the degree of association between the identified crash contributing factors can help safety management systems develop the most efficient crash reduction strategies.

Influence of horizontally curved roadway section characteristics on motorcycle-to-barrier crash frequency

The purpose of this study was to investigate motorcycle-to-barrier crash frequency on horizontally curved roadway sections in Washington State using police-reported crash data linked with roadway data and augmented with barrier presence information. Data included 4915 horizontal curved roadway sections with 252 of these sections experiencing 329 motorcycle-to-barrier crashes between 2002 and 2011. Negative binomial regression was used to predict motorcycle-to-barrier crash frequency using horizontal curvature and other roadway characteristics. Based on the model results, the strongest predictor of crash frequency was found to be curve radius. This supports a motorcycle-to-barrier crash countermeasure placement criterion based, at the very least, on horizontal curve radius. With respect to the existing horizontal curve criterion of 820 feet or less, curves meeting this criterion were found to increase motorcycle-to-barrier crash frequency rate by a factor of 10 compared to curves not meeting this criterion. Other statistically significant predictors were curve length, traffic volume and the location of adjacent curves. Assuming curves of identical radius, the model results suggest that longer curves, those with higher traffic volume, and those that have no adjacent curved sections within 300 feet of either curve end would likely be better candidates for a motorcycle-to-barrier crash countermeasure.

A Novel Approach to Assessing Road-Curve Crash Severity

Curves are a common feature of road infrastructure; however, crashes on road curves are associated with increased risk of injury and fatality to vehicle occupants. Countermeasures require the identification of contributing factors. However, current approaches to identifying contributors use traditional statistical methods and have not used self-reported narrative claim to identify factors related to the driver, vehicle, and environment in a systemic way. Text mining of 3,434 road-curve crash claim records filed between 1 January 2003 and 31 December 2005 at a major insurer in Queensland, Australia, was undertaken to identify risk levels and contributing factors. Rough set analysis was used on insurance claim narratives to identify significant contributing factors to crashes and their associated severity. New contributing factors unique to curve crashes were identified (e.g., tree, phone, oversteer) in addition to those previously identified via traditional statistical analysis of police and licensing authority records. Text mining is a novel methodology to improve knowledge related to risk and contributing factors to road-curve crash severity. Future road-curve crash countermeasures should more fully consider the interrelationships between environment, the road, the driver and the vehicle, and education campaigns in particular could highlight the increased risk of crash on road curves.

Empirical Bayes Approach for Estimating Urban Deer-Vehicle Crashes Using Police and Maintenance Records

Deer-vehicle crashes are a growing problem in Iowa where deer-vehicle crashes represent 13% of all crashes reported. In 2009, these crashes resulted in nine fatalities and 451 injuries in the state. Deer-vehicle crashes are a problem even in urban areas of Iowa. It is known that deer-vehicle crashes are typically underreported. To address this underreporting, deer carcass salvage reports may be used to augment deer-vehicle crash reports. The objective of this paper is to exploit two sources of deer-vehicle crash data using a statistically reliable assessment methodology, empirical Bayes, to assess the potential for safety improvement of 150 urban highway sections in Iowa. Reconciliation of records to reduce double counting is discussed and a negative binomial regression model of deer-vehicle crash frequency as a function of roadway and environmental factors is estimated. The 25 most promising segments for deer-vehicle crash countermeasures are identified, mostly located on high-speed roadways, roadway segments with gravel right shoulders, and segments adjacent to grasslands. The methodology facilitates the identification of locations for countermeasure implementation as well as monitoring deer-vehicle crash trends.

Four-Lane to Five-Lane Urban Roadway Conversions for Safety

Undivided roadways have consistently exhibited low safety performance, particularly in urban or suburban areas where roadside development is relatively intense. Changing a four-lane undivided road to a divided roadway by either building a boulevard cross-section or installing a physical barrier is a desirable option to improve safety performance of an undivided roadway, but it requires significant resources. This article introduces a crash countermeasure successfully implemented on two different segments of undivided roadways in Louisiana. This crash countermeasure is to change an undivided four-lane roadway to a five-lane roadway with a center lane for left turns by restriping pavement markings without increasing pavement width. Although the five-lane roadway is no longer an acceptable roadway type in Louisiana, the impressive crash reductions on both roadway segments demonstrate it is a feasible solution under constrained conditions. Based on the statistical analysis with 6 years of crash data (3 years before and 3 years after excluding the implementation year), the crash modification factors for both roadways are estimated to be less than 0.5 with a standard deviation less than 0.07. Although it is not surprising to see the biggest crash reduction comes from the rear-end collisions, the other types of collision are also reduced.