Crash Casualties Research Articles

Pedestrian and Car Occupant Crash Casualties Over a 9-Year Span of Vision Zero in New York City

Vision Zero has been increasingly embraced by jurisdictions across the United States. Existing research primarily focuses on the theoretical principles and effectiveness of specific engineering measures. However, there is limited understanding of the holistic effects of Vision Zero treatments, in the context of street type and urban environment. We developed a street typology framework to categorize street segments using four design and operational features: street width, traffic direction (one- versus two-way), number of travel lanes, and presence of on-street parking. We applied a sample-based partitioning around medoids algorithm to classify 90,327 street segments in New York City. This process results in six distinctive types of street segment. To integrate neighborhood-level factors (e.g., land use variables and sociodemographics), we aggregated street segments of a given street type for each neighborhood. Negative binomial regression models were developed for pedestrian and car occupant crash injuries and fatalities separately for three periods: 2014 to 2016, 2017 to 2019, and 2020 to 2022. Our findings showed that street-segment groups with narrower, two-way sections and greater tree canopy coverage were significantly associated with a lower risk of casualties for both pedestrians and motorized users. Street-segment groups located in neighborhoods with a larger percentage of African American and Hispanic American residents experienced a significantly greater risk of casualties. Vision Zero treatments had mixed effects on safety outcomes. Streets treated with leading pedestrian intervals showed a lower risk of casualties. Neighborhood- and arterial slow zones were associated with a lower risk of car occupant casualties.

Unveiling Crash Casualties: A Neural Network Model for Crash Type Classification Using Traffic Datasets

Abstract: Traffic accidents, a significant public health burden with substantial economic costs, necessitate proactive measures for sustainable transportation. This study investigates the efficacy of neural networks in predicting crash types using traffic data. We propose a deep learning model that leverages the power of recurrent neural networks (RNNs) for sequential traffic pattern analysis and convolutional neural networks (CNNs) for extracting spatial features from traffic data. The model, trained on a labeled traffic dataset, learns to identify patterns and relationships between traffic characteristics (e.g., speed, volume, weather) and different crash types (e.g., rear-end collision, single-vehicle). The evaluation focuses on the model's accuracy in predicting crash types using metrics like precision, recall, and F1-score. This research contributes to the development of intelligent traffic management systems (ITMS) that can proactively identify and mitigate potential accidents, ultimately enhancing road safety and promoting a more sustainable transportation future.The implementation results indicate that the proposed method yields an accuracy of 82.93% approximately.

Demographic and injury trends for car crash casualties hospitalized in Level I Trauma centers over two decades: data from the National Trauma Registry

BackgroundDuring the past two decades, there have been many changes in automotive and medical technologies, road infrastructure, trauma systems, and demographic changes which may have influenced injury outcomes. The aim of this study was to examine injury trends among traffic casualties, specifically private car occupants, hospitalized in Level I Trauma Centers (TC).MethodsA retrospective cohort study was performed based on data from the Israel National Trauma Registry. The data included occupants of private cars hospitalized in all six Level I TC due to a traffic collision related injury between January 1, 1998 and December 31, 2019. Demographic, injury and hospitalization characteristics and in-hospital mortality were analyzed. Chi-squared (X2) test, multivariable logistic regression models and Spearman’s rank correlation were used to analyze injury data and trends.ResultsDuring the study period, 21,173 private car occupants (14,078 drivers, 4,527 front passengers, and 2,568 rear passengers) were hospitalized due to a traffic crash. The percentage of females hospitalized due to a car crash increased from 37.7% in 1998 to 53.7% in 2019. Over a twofold increase in hospitalizations among older adult drivers (ages 65+) was observed, from 6.5% in 1998 to 15.7% in 2018 and 12.6% in 2019. While no increase was observed for severe traumatic brain injury, a statistically significant increase in severe abdominal and thoracic injuries was observed among the non-Jewish population along with a constant decrease in in-hospital mortality.ConclusionsThis study provides interesting findings regarding injury and demographic trends among car occupants during the past two decades. Mortality among private car occupant casualties decreased during the study period, however an increase in serious abdominal and thoracic injuries was identified. The results should be used to design and implement policies and interventions for reducing injury and disability among car occupants.

Impact of the revised Unified Federal Traffic Law on crash casualties in Abu Dhabi Emirate: Interrupted time series analysis

In recent years, different developing countries have shown growing interest in enacting road safety policies. However, research on their effectiveness in reducing crashes, injuries, and deaths is limited. This study evaluated the impact of traffic safety measures introduced in the revised Unified Federal Traffic Law in the Emirates of Abu Dhabi (AD) and the United Arab Emirates (UAE) on crash and casualty reductions. In particular, it examines the 2009 enactment of the black-point system. To the best of our knowledge, this is the first study to consider this topic in a desert or UAE context. Box–Tiao intervention analysis was used to examine monthly AD police data from January 2007 to December 2013. The analysis utilized a dynamic programming approach to test for structural changes in the AD casualty data and empirically confirm the presence and exact location of breakpoints (intervention time). The interrupted time-series analysis results indicated a significant drop in casualty rates post-intervention. Since the intervention, the AD has witnessed a slow downward trend in the crash casualty rate. These findings confirm the effectiveness of the implemented safety measures. They provide quality information to authorities regarding implementing and adopting life-saving interventions and road safety management.

A multilevel decision-making approach for road infrastructure management

ABSTRACT The design of effective road safety countermeasures requires a network diagnosis supported by data. Moreover, infrastructures need to be ready for the introduction of vehicle-to-infrastructure communications to support technologies, as truck platooning. Ascendi, a motorway concessionaire, developed an action plan to decrease crash frequency and casualties that rests in data recorded by automatic vehicle counting devices. To have a good network representation, new equipment will provide more data, thus enhancing the selection of countermeasures. We developed a multilevel decision-support approach to define equipment location. The process stages correspond to three levels of analysis: (1) clustering for road segment classification (network level); (2) quantification of the devices to install ensuring similar coverage (concession level); (3) device allocation according to geographical and cost criteria (segment level). An iterative and participatory process involving Ascendi resulted in a proposal for adding 43 devices to the existing 72, increasing the network coverage to 39%.

Using GPS Probe Speed Data to Estimate the Attribution of Speeding on Casualty Crashes: A Case Study in Queensland

While the relationship between vehicle speed and crash risk and severity are well understood, precise quantifications of the attribution of speeding to casualty crashes remains more elusive, due in part to the lack of reliable network-wide speed survey data. A relatively new source of network-wide speed data is Global Positioning System (GPS) probe data. This paper explores the feasibility of using this data, along with existing crash risk estimates, to determine the proportion of casualty crashes attributable to travelling at various speeds above the posted limit on Queensland roads. Findings were generally consistent with other data sources, highlighting the danger associated with high-level speeding (more than 20 km/h over the speed limit), estimating that up to 32.5% of all casualty crashes were attributable to this behaviour. Analyses also showed the risks associated with low-level speeding (1-10km/h over the limit), with up to 19.2% of all casualty crashes estimated to be attributable to such behaviour. The implications of these findings on road safety are discussed. Notwithstanding the limitations of GPS speed probe data, the findings suggest that it represents a promising source of network-wide speed data for estimating the attribution of speeding in casualty crashes. Efforts should be made to improve the reliability of this data by increasing the representativeness of vehicles contributing to the data.

Towards Linking Climate and Weather Phenomena to Road Safety Outcome Part 3 of 3: Short-term influences of weather patterns

This paper is the last of a three-part series. Part 1 identified the breadth of weather factors collectively contributing to crash risk and consolidated relevant research. Part 2 illustrated the cyclic nature of climate, weather, and crashes and how they vary over time. In part 3, the differences in weather conditions on days with high and low casualty crash numbers, days with high fatal crash numbers, and long sequences of days with and without fatal crashes were analysed using readily available Bureau of Meteorology (BOM) metrics: maximum and minimum daily temperature, daily rainfall, 6-hour synoptic charts, daily solar radiation, and water vapour pressure (for 9am and 3pm). The results showed marked differences between high and low casualty crash days. Spatial distributions of daily crashes show alignment with the movement of weather patterns across Victoria as observed in synoptic charts, particularly in relation to low pressure systems and troughs, likely duration of damp pavement conditions and periods of extreme heat and cold (well above or well below average for that time of year in that location). Understanding how specific climate and weather events can influence crash risk may help develop additional strategies to improve road safety and reach the target of zero deaths.

Development of the road safety strategic plan in Greece, 2021-2030

Despite the most significant improvement in road safety performance among the EU countries during the period 2010-2020 and achieving the target of halving road fatalities, Greece still remains behind the EU average in terms of road fatalities per population. This paper presents the Greek Road Safety Strategic Plan for the decade 2021-2030. With this Plan, Greece adopts the Safe System Approach and the Vision Zero by 2050. The Strategic Plan is in alignment with the EU Road Safety Strategy aiming to halve road fatalities and serious injuries by 2030. Eight targets for road crash casualties’ reduction and eight targets for the improvement of road safety performance are proposed for 2030, with intermediate targets for 2025. A list of 200 Road Safety Measures within 44 Actions within the five UN Pillars is also set. Finally, an integrated system for monitoring road safety is proposed.

A data fusion approach of police-hospital linked data to examine injury severity of motor vehicle crashes

Injury severity studies typically rely on police-reported crash data to examine risk factors associated with traffic injuries. The police crash database includes essential information on roadways, crashes and driver-vehicle characteristics but may not contain accurate and sufficient information on traffic injuries. Despite sizable efforts on injury severity modelling, very few studies have employed hospital records to classify injury severities accurately. As such, the inferences drawn from the police-recorded injury severity classifications may be questionable. This study investigates factors affecting road traffic injuries of motor vehicle crashes in two approaches (1) police-reported injury severity data and (2) a data fusion approach linking police and hospital records. Data from 2015 to 2019 were collected from the Abu Dhabi Traffic Police Department and linked with hospital records by the Department of Health, Abu Dhabi. A total of 6,333 casualty crashes were categorised into non-severe, severe, and fatal crashes following police-reported data and non-hospitalised, hospitalised and fatal crashes based on the police-hospital linked data. The state-of-the-art random thresholds random parameters hierarchical ordered Probit models were then employed to examine the differences in factors affecting crash-injury severities between police-reported and police-hospital linked data. While there are similarities between these two approaches, there are numerous notable differences in injury severity factors. For instance, head-on collisions are associated with high crash-injury severities in the model with police-hospital linked data, but they tend to show low injury severities in the model with police-reported data. In addition, the police-reported approach identifies that crashes occurred in remote areas and angle collisions are associated with low injury severities, which is not intuitive. These findings highlight that modelling the misclassified injury severity in police crash data may lead to wrong estimations and misleading inferences. Instead, the data fusion approach of police-hospital linked data provides critical and accurate insights into road traffic injuries and is a valuable approach for understanding traffic injuries.

A New Transit Safety Narrative

Public transportation is, overall, a relatively safe (low crash risk) and secure (low crime risk) transport mode. Transit travel has about one-tenth the traffic casualty (injury or death) rate as automobile travel, and residents of transit-oriented communities have about one-fifth the per capita crash casualty rate as in automobile-oriented communities. Transit also tends to have lower overall crime rates than automobile travel, and transit improvements can help reduce overall crime risk by improving surveillance and economic opportunities for at-risk populations. Despite its relative safety and security, many people consider transit travel dangerous and are reluctant to use it or support service expansions in their communities. Various factors contribute to this excessive fear, including the nature of transit travel, heavy media coverage of transit-related crashes and crimes, and conventional traffic safety messages that emphasize danger rather than safety. Transit agencies can help create a new transit safety narrative by better communicating transit’s overall safety and security impacts and providing better guidance concerning how users and communities can enhance transit safety and security.

Factors affecting fatal PTW at-fault crash outcome metrics at intersections and non-intersections in South Korea

Fatal crashes involving Powered Two-Wheelers (PTWs) are a major health concern in South Korea due to the increase in their usage in the logistics industry. Owing to the way, they are operated on the roadways, most riders end up in fatal crashes. Interestingly, little research exists regarding the impact of risk factors on fatal crashes involving at-fault PTW riders. This study employs a copula-based regression technique to simultaneously model the relationship between crash-risk factors and crash outcome metrics of fatal PTW rider-at-fault crashes, namely the number of crash casualties (casualty size) and the number of vehicles involved in a crash (crash size) at intersections and non-intersection segments. The proposed method was superior compared to the SEM-based bivariate regression approach, and the estimation results showed that there exists a positive relationship between both outcome variables. From the analysis, it was identified that while "other violations" comprising speeding and wrongful overtaking had varying effects on crash size outcomes at the intersection and non-intersection segments, variables such as daytime, winter, head-on collisions, and pedestrian involvement had positive impact on the crash consequence metrics irrespective of the crash location. Insights drawn from the study are used in recommending appropriate countermeasures for improving PTW safety.

Towards linking climate and weather phenomena to road safety outcomes Part 1 of 3: The collective involvement of weather manifestations

Climate and its many weather manifestations can help explain annual variations in fatalities and casualty crashes. Part 1 of a 3-part series identifies the breadth of weather factors which collectively contribute to crash risk reviewing and consolidating relevant research. The series identifies the need for interventions in advance of and during certain weather events, providing pathways for further research. The key climate drivers for Victoria produce complex interactions forming short-term (hours, days, weeks) and long-term (months, years, decades) weather patterns that influence crash occurrence and their spatial and temporal distribution across the state. Although analysis of Victorian crash records found weather was involved in at least 10% of fatal and casualty crashes, this is considered under-estimated as many weather-related events are not recorded nor considered in crash analysis. Spatial distributions of annual and daily crashes show alignment with movement of weather patterns across Victoria observed in Bureau of Meteorology synoptic charts, particularly in relation to low pressure systems and troughs, duration of damp pavement conditions, suddenly changing/unseasonal events, and periods of extreme heat and cold. Understanding how climate influences variations in crash occurrence can be used to develop appropriate strategies to improve road safety and help reach the target of zero deaths.

Towards linking climate and weather phenomena to road safety outcomes part 2 of 3: Longer-term influences of climate drivers

This paper is Part 2 of a three-part series illustrating how climate phenomena and weather metrics vary within a year and between years that can effect road safety. Part 1 identified the breadth of weather factors collectively contributing to crash risk and consolidated relevant research. The key climate drivers for Victoria produce complex interactions forming short-term and long-term weather patterns influencing crash occurrence and their spatial and temporal distribution across the state. The study found that the Southern Annular Mode (SAM) with its roughly 14-day cycle has the most significant influence on Victorian casualty crashes (also cyclic). A Chi-Square Goodness-of-Fit Test showed a statistically significant association (at the 0.05 significance level) between casualty crash numbers and each of the climate drivers. For fatal crashes, however, there was no statistically significant association, likely due to low numbers and randomness. Whilst this paper focuses on Victoria, other jurisdictions can use the approach presented using their local context of climate, latitude, and geography to identify patterns and influences on crashes. Understanding climate influences on crash occurrence within and between years assists strategy development for improving road safety and reaching the target of zero deaths.

Characteristics of suicide-related crashes and their potential interventions: A literature review

Objective To develop countermeasures to decrease road trauma, it is essential to increase our understanding of fatal and injury crashes with suicidal intent. As suicide-related crashes can be difficult to identify it seems likely suicide-related road fatalities and injuries are under-reported. Under-reported crashes may lead to two policy issues: these types of casualty crashes may not receive adequate funding for countermeasure development and implementation due to not having a sufficient evidence-basis to justify allocation of resources, and may be miscategorized as having other factors contributing to the crashes, thus resources may be incorrectly allocated to countermeasures to address these other factors. This paper seeks to develop and document characteristics and potential countermeasures to identify and prevent such crashes. Methods Two literature reviews of peer-reviewed journal manuscripts were performed to identify suicide-crash characteristics and potential countermeasures and strategies. Of 61 peer-reviewed journal manuscripts identified from the literature searches, 17 manuscripts fit the criteria and were reviewed. Information regarding the characteristics of suicide-related crashes, as well as potential strategies and countermeasures were gleaned from these manuscripts. Results A list of characteristics was developed, underpinning development of a methodology to identify these types of crashes. Strategies and countermeasures recommended by international (road-) agencies to identify and prevent suicide-related crashes were documented and discussed. Conclusion As suicide-related crashes almost always take place in public space, the grief and pain resulting from such crashes not only relates to the victim, the people who knew the victim, but in many cases also involve the general public. It is therefore paramount to start the discussion about suicide-related crashes to increase awareness, increase willingness to establish a reliable data and knowledge base, and encourage help seeking in individuals at increased risk of attempting suicide using this method.

Understanding patterns of moped and seated motor scooter (50 cc or less) involved fatal crashes using cluster correspondence analysis

ABSTRACT Moped and seated motor scooter (50 ccs or less) riders have a relatively high risk of becoming crash casualties. Comparison between 2015 and 2019 fatal crash data indicates that fatal moped crashes have increased by 76%, whereas fatal motorcycle crashes have decreased by 2%. This study collected moped and seated motor scooter-related fatal crash data for five years (2015–2019) from the Fatality Analysis Reporting System (FARS) to perform the analysis. Using an innovative categorical data analysis method known as cluster correspondence analysis (CCA), this study identified some critical clusters with a group of co-occurring variable categories. The contextual understanding of fatal crash patterns could guide authorities in developing data-driven interventions and countermeasures aiming to minimize moped collisions and related fatalities. The findings of this study can provide a better understanding of the patterns of contributing factors in moped and seated motor scooter fatal crashes.

Factors affecting motorcycle crash casualty severity at signalized and non-signalized intersections in Ghana: Insights from a data mining and binary logit regression approach

Despite the countless benefits derived from motorcycle usage, it has become a significant public health concern, particularly in developing countries, due to the plateauing number of fatal/serious injuries associated with them. Although it has been well documented that the frequency and fatality rates of intersection-related motorcycle crashes are high, little research efforts have been made to explore the contributory factors influencing motorcycle-involved crashes at these locations. Interestingly, no study has investigated the latent patterns and chains of factors that simultaneously contribute to the injury severity sustained by motorcycle crash casualties at intersections under different traffic control conditions in developing countries. Since motorcycles are mostly used as taxis in developing countries, it is imperative to consider the injury severity sustained by all crash casualties in the motorcycle safety analysis. This study bridges the research gap by employing a plausible data mining tool to explore hidden rules associated with motorcycle crash casualty injury severity outcomes at both signalized and non-signalized intersections in Ghana's most densely populated region, Accra, using three-year crash data spanning 2016–2018. Besides, a binary logit regression model was also employed to explore the impact of crash factors on casualty severity outcomes using the same dataset. The results from both analysis techniques were consistent; however, the data mining technique provided chains of factors which provided additional insights into the groups of factors that collectively influence the casualty injury severity outcomes. From the rule discovery results, while full license status, daytime/daylight, and shoulder presence increased the risk of fatal injuries at signalized intersections, factors such as inattentiveness, good road surface, nighttime, shoulder absence, and young rider were highly likely to increase casualty fatalities at non-signalized intersections. By controlling all or some of these risk factors, the level of injury severity on the roadways could be reduced. Based on the findings, we provide enforcement, education, and engineering-based recommendations to help improve motorcycle safety.

Bad light, bad road, or bad luck? The associations of road lighting and road surface quality on road crash severities in Indonesia

The United Nation’s Sustainable Development Goals (SDGs) have mandated that all countries reduce road crash fatalities by half by 2020. In the context of developing countries such as Indonesia, we hypothesized that the government could minimize road crash severities by providing road lighting and improving road surfaces. Employing road crash data from the Central Traffic Control of the Indonesian National Police and the negative binomial regression method, we revealed that road lighting and surface improvements are associated with lower road crash casualties of 4.2% and 3.4%, respectively. Road lighting and road surface improvements also correspond to lower road fatalities. Given the estimates and cost structure, we found that for the same cost, the potential cost-effectiveness is at least three times higher for road light improvements than for road surface improvements.

Study on Motorcycle Crash Cost in Bandung City

Crash cost is an important component for conducting economic analysis in selecting countermeasures for crash locations. It is used to convert the benefit of crash or fatality reduction into monetary terms. Many research on crash cost have been carried out in Indonesia. Most of the research utilized gross output/human capital approach. However, this approach has been widely criticized for not being able to describe the quality of life of crash casualties and the costs of pain, grief and suffering (i.e. human cost). The concept of Value of Statistical Life (VoSL) has been introduced by InDeV (2016) to calculate the human cost, which is assessed by using willingness to pay approach. To obtain a more reliable estimation of crash cost for Indonesia, it is necessary to conduct a study on crash cost involving motorcycles which incorporates the estimation of human cost. The VoSL is obtained by interviewing motorcycle users for willingness to pay with safety equipment. Based on the analysis, it is obtained that the value of statistical life (VoSL) for fatality in a road crash was estimated to be Rp.2.3 billion. The unit cost of fatal injury is Rp.3.08 billion, serious injury is Rp.333 million and slight injury is Rp.24.9 million. The unit cost of fatal crash on arterial roads is Rp.3.23 billion, serious crash is Rp.451 million and the slight crash is Rp.114 million. The unit cost of fatal crash on collector roads is Rp.3.16 billion, serious crashes is Rp.381 million and minor crash is Rp.69.4 million. The unit cost of fatal crash on local roads is Rp.3.09 billion, serious crash is Rp.338 million, and minor crash is Rp.29.8 million. Keywords: Motorcycle crash cost, gross output approach, human capital approach, willingness to pay approach

Evaluation of a warning system to reduce the risk of casualty crashes at rural junctions in South Australia

Objective This study evaluated the effectiveness and potential safety benefits of a Rural Junction Active Warning System (RJAWS), which uses variable speed limit signs (VSLSs) to temporarily impose a reduced speed limit along the major road when another vehicle is approaching on the minor road or turning into the minor road from the far-side major leg. Methods The RJAWS was trialed at 4 3-leg rural junctions between 2-lane roads in South Australia. A quasi-experimental before–after analysis was conducted. The free-flow speed of vehicles along the junction major approaches was used as an indicator of the risk of a casualty crash with adjacent traffic. Events with activated and nonactivated VSLSs after the RJAWS installation were analyzed separately. Travel speed, speed limit compliance, and the relative risk of a casualty crash were compared. The potential risk of casualty crashes relative to traveling at the default speed limit was calculated based on a known relationship between travel speed and relative casualty risk for rural roads in South Australia. Results When the reduced speed limit signs are activated, the average travel speed along the major road is reduced between 11.3 and 22.1 km/h, with a consequent reduction of the expected average casualty risk between 42% and 65% compared to before the RJAWS installation. . Though compliance with the reduced posted speed limit was low, the RJAWS still proved effective in reducing travel speed because the majority of drivers traveled through the monitored junctions at speeds below the default speed limit when the sign was activated. Conclusions This evaluation indicated that the trialed RJAWS can potentially reduce the risk of fatal and serious injuries at junctions under conditions that may present the opportunity for an adjacent-direction collision with another vehicle. Extending the RJAWS installation to additional junctions is strongly suggested. Further monitoring is needed to determine whether safety benefits are sustained over the long term.

Effect of pavement condition and geometrics at signalised intersections on casualty crashes

IntroductionThis study investigated the effects of pavement surface condition and other control factors on casualty crashes at signalized intersections. It involved conducting a before and after study for road surface condition and situational factors. It also included assessing the effects of geometric characteristics on safety performance of signalized intersections post resurfacing to control for the effect of pavement surface condition. Pavement surface condition included roughness, rutting, and skid resistance. The control factors included traffic volume, light and surface moisture condition, and speed limit. The geometric characteristics included approach width, number of lanes, intersection depth, presence of median, presence of shared lane, and presence of bus stop. MethodTo account for the repeated observations of the effect of light and surface moisture conditions in four occasions (day-dry, day-wet, night-dry and night-wet) Generalized Estimating Equation (GEE) with Negative Binomial (NB) and log link function was applied. For each signalized intersection in the sample, condition data are collected for the year before and after the year of surface treatment. Crash data, however, are collected for a minimum of three and maximum of five years before and after treatment years. ResultsThe results show that before treatment, light condition, road surface moisture condition, and skid resistance interaction with traffic volume are the significant contributors to crash occurrence. For after treatment; light condition, road surface moisture condition, their interaction product, and roughness interaction with light condition, surface moisture condition, and traffic volume are the significant contributors. The geometric variables that were found to have significant effects on crash frequency post resurfacing were approach width interactions with presence of shared lane, bus stop, or median. ConclusionsThe findings confirm that resurfacing is significant in reducing crash frequency and severity levels.Practical Applications: The study findings would help for better understanding of how geometric characteristics can be improved to reduce crash occurrence.