Exploring the risk factors associated with the size and severity of roadway crashes in Riyadh

Unveiling the risks of speeding behavior by investigating the dynamics of driver injury severity through advanced analytics

Single-vehicle crashes, particularly those caused by speeding, result in a disproportionately high number of fatalities and serious injuries compared to other types of crashes involving passenger vehicles. This study aims to identify factors that contribute to driver injury severity in single-vehicle crashes using machine learning models and advanced econometric models, namely mixed logit with heterogeneity in means and variances. National Crash data from the Crash Report Sampling System (CRSS) managed by the National Highway Traffic Safety Administration (NHTSA) between 2016 and 2018 were utilized for this study. XGBoost and Random Forest models were employed to identify the most influential variables using SHAP (Shapley Additive Explanations), while a mixed logit model was utilized to model driver injury severity accounting for unobserved heterogeneity in the data collection process. The results revealed a complex interplay of various factors that contribute to driver injury severity in single-vehicle crashes. These factors included driver characteristics such as demographics (male and female drivers, age below 26 years and between 35 and 45 years), driver actions (reckless driving, driving under the influence), restraint usage (lap-shoulder belt usage and unbelted), roadway and traffic characteristics (non-interstate highways, undivided and divided roadways with positive barriers, curved roadways), environmental conditions (clear and daylight conditions), vehicle characteristics (motorcycles, displacement volumes up to 2500 cc and 5,000-10,000 cc, newer vehicles, Chevy and Ford vehicles), crash characteristics (rollover, run-off-road incidents, collisions with trees), temporal characteristics (midnight to 6 AM, 10 AM to 4 PM, 4th quarter of the analysis period: October to December, and the analysis year of 2017). The findings emphasize the significance of driving behavior and roadway design to speeding behavior. These aspects should be given high priority for driver training as well as the design and maintenance of roadways by relevant agencies.

Effects of road width, radii and speeds on collisions at three-arm priority intersections

Simulation and observational studies have identified the importance of intersection geometries and vehicle speeds in collisions. However, the causal mechanisms of such collisions in low-speed areas and for different collision types remain unclear. This observational study investigates the complex relationships between geometries, speeds, visibilities, and road traffic collisions in the context of low-speed urban areas.Data were collected from 120 three-arm priority intersections in Portsmouth, UK. In 2007, Portsmouth became the first city in the UK to adopt a 20mph speed limit on all residential streets. The city has also adopted the UK's Manual for Streets (MfS) as the design standard for all new priority intersections in low-speed residential areas.Piecewise structural equation models (pSEM) were developed to represent the causal mechanisms that relate to geometries, speeds, speed limits and collisions. Findings indicate the role of combinations of approach lane width, corner radii, speed limit, and type of collision. The interaction of wider approach lanes on the minor arm and larger radii of turns for left-turning vehicles (left-hand driving perspective) was associated with higher numbers of road traffic collisions for right-turning vehicles. It is posited here that this is due to the orientation of the left-turning vehicle blocking the left visibility of the right-turning vehicle. These results give weight to the introduction of the 20mph speed limit zone in Portsmouth and some of the changes brought about by MfS. However, the combined effect of approach width and radii on collisions is novel and could form the basis of further guidance on reducing specific types of collisions at three-arm priority intersections.

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.

Analysis of risk factors affecting traffic accident injury in United Arab Emirates (UAE)

The mortality and severe injuries due to traffic accidents in United Arab Emirates (UAE) are hastening the necessity for a study that can identify the consequential risk factors. This study was conducted by utilizing a 5740 traffic accidents police reports that occurred in Abu Dhabi, UAE between 2008 and 2013. A multinomial logit regression model was applied to determine the significant factors among the 14 potential risk factors that were used in this study. The dependent variable was the level of injury that consisted of four categories: slight injury, medium injury, severe injury, and fatal injury. The results showed that pedestrian, the unutilized seatbelt, roads that had four or more than four lanes, male casualty, 100 km/h speed limit or higher, and casualty older than 60 years were found to be the factors that can increase the probability of being involved in a fatal traffic accident. In contrast, rear-end collisions and intersections had a lower probability of causing fatal injury. Then, the eight significant predictors were included in a neural network to compare the performance of both methods and to identify the normalized importance values for the significant independent variables. The neural network had proven to be more accurate in general than the traditional regression models such as the multinomial logit model.

Awareness level of safe driving knowledge and practice of specific population drivers: behavioral assessment and educational intervention

PURPOSE

This study aimed to assess car-driving behaviors and attitudes and to measure the changes in the knowledge and behavioral practices associated with road safety measures of 1333 randomly selected young-adult participants (aged 18-24 years) from Jazan University in Gizan city, Saudi Arabia.

METHODS

Data were collected using cross-sectional survey and quasi experimental pre- and post-evaluation educational intervention study including structured questionnaire and take-home educational material.

RESULTS

Results revealed that low compliance with the safety index significantly increased the risk of traffic injuries by 20% [OR = 0.80, 95% CI = (0.59-1.01)]. Whereas the medium category of the safety compliance index is significantly associated with an increasing number of injuries by 6% [OR = 0.94, 95% CI = (0.61-1.52)]. In contrast, both high and medium categories of risk behavior index increased the risk of traffic injuries [OR = 1.08, 95% CI = (0.82-1.43); OR = 0.80, 95% CI = (0.57-1.10), respectively]. Some improvement in risky behavioral practices was seen after the intervention including 'not playing loud music' [86.3%, (P = 0.05)], 'not using mobile phones' [89.4%, (P < 0.05)], and 'not using unprofessional checkups of the car' [71.5%, (P < 0.05)].

CONCLUSION

Ultimately, this unpleasant situation may recommend avoidance of these kinds of intermittent awareness programs; instead, embedding a continuous road safety learning within the life-long educational system as a better and more realistic intervention for reducing the number of road accidents and injuries. Further, establishing various modes of high-capacity city-link public transportation remains among the most recommended strategic and effective options that can curb road traffic injuries in the long run.

Exploring temporal interactions of crash counts in California using distinct log-linear contingency table models

Temporal trait of crashes has huge impact on road crash occurrence and a large proportion of research have considered different time periods to determine the causes and features of crash occurrence or frequency. Compared with other safety studies based on a single time interval, considerably less research has relied on the use of multiple time units, especially for the time intervals of less than one year. The research aims to fill the gap by investigating the temporal distribution of crash counts using multiple time spans including hour, weekday and month. To illustrate the most accurate results possible, both the Chi-square test and Cochran-Mantel-Haenzel tests were employed to explore the independence of various time units based on two-way and three-way contingency tables. Eight contingency table models were developed which can be classified into four groups including Complete Independence, Joint Independence, Conditional Independence and Homogeneous Association. Finally, a set of evaluation criteria were utilized for evaluation of the model performance. The results revealed the significant association existence in all time variables (hour, weekday, month) and the model with both main and all interactive effects of time variables provides best prediction performance. Also, the findings showed that Hour 18, weekdays 1, 6, 7 (Friday and Weekends), and month 8 (August) have the largest number of crash occurrences. It is suggested that both main and interactive effects of time variables should be included for model development, which otherwise might yield misleading information. It is anticipated that research results will benefit the safety professionals with better understanding of the temporal patterns of crashes with different time periods and allow the safety administrators to allocate the safety resources.

Incorporating accident liability into crash risk analysis: A multidimensional risk source approach

In the field of traffic safety, the occurrence of accidents remains a cause of concern for road regulators as well as users. Exploring risk factors inducing the accidents and quantifying the accident risk will not only benefit the prevention and control of traffic accidents but also assist in developing effective risk propagation model for road accidents. This study uses detailed accident record data to mine the risk factors affecting the occurrence of accidents, and quantify the accident risk under the combination of risk factors. First, by reviewing relevant literature and analyzing historical accident, we construct a multi-dimension characterization framework of risk factors with bi-level structure. The Human Factors Analysis and Classification System (HFACS) is applied to supplement and improve the framework. Next, under this framework, we identify the risk factors in traffic accident record, and analyze the statistical characteristics from the level of risk sources and risk characteristics. Then, the concept of accident liability weight is proposed to measure the impact of risk factors on accident occurrence. Through the liability affirmation of risk factors, the accident probability are updated. Last, we establish an accident risk quantify model (ARQM) based on the mean mutual information to compare the likelihood of accidents in different scenarios. In addition, we compare the accident probability and risk under equivalent liability and liability affirmation, as well as give some fundamental ideas regarding how to effectively prevent accidents.

A new approach in analyzing the accident severity of pedestrian crashes using structural equation modeling

Background:

According to official statistics in Iran, there were 17000 fatalities in road traffic crashes in 2018 that 25% of all crash fatalities belong to pedestrians. In most of the researches related to pedestrians’ safety, one aspect of the traffic crash (e.g. the injury or crash severity) is almost considered for the investigation. In order to perform a complete study of the crash, accident size can be utilized which involves different aspects of the crash. Accident size is described in terms of the number of fatalities and injured individuals and the number of dam-aged and involved vehicles in a crash.

Methods:

According to the fact that accident size has multiple indicators and it is not measured directly, traditional methodologies cannot be applied. So, in the present study the effective factors on the accident size of pedestrian crashes are investigated through structural equation modeling. For the purpose of this study, 3718 pedestrian-involved crash data occurred in Isfahan province is used for the modeling. The independent variables are weather conditions, road surface conditions, time, horizontal and vertical alignments, road type and location, driver’s gender and age, vehicle type, pedestrian’s age, gender and clothing color.

Results:

The results indicated that highways, the pedestrians’ invisibility, female and old-aged pedestrians, heavy vehicles, old-aged and female drivers are related to the increase of the accident size in pedestrian crashes. These results denote that the mentioned variables are associated with the higher number of injuries, fatalities, the higher number of involved and damaged vehicles in a crash.

Conclusions:

Present study shows the importance of considering safety improvement measures in highways, educating the people in the society about the traffic safety, the separation of pedestrian and motor vehicle traffic flow and considering the old people in policies and programs for mitigating the accident size.

Nurses’ Readiness for Emergencies and Public Health Challenges—The Case of Saudi Arabia

This study was aimed at assessing the readiness of 200 emergency nurses in the southern part of Saudi Arabia in the management of public health emergencies, major incidents, and disasters by using quantitative research through a self-reporting validated questionnaire containing 10 different dimensions. All registered nurses working in emergency departments who were willing to participate, of all ages and gender groups, were included. Nurses who were not present during the study period because of vacation or maternity leave, nurses at the managerial level, and nursing aides were excluded. The participating nurses reported good knowledge in almost all investigated aspects of the theoretical dimensions of emergency management. However, they revealed perceived weaknesses in practical dimensions of emergency management and difficulties in assessing their own efforts. There was a significant correlation between qualification and the dimensions of emergency preparedness, epidemiology and surveillance, isolation and quarantine and critical resources, which indicates a need for strengthening their practical contribution as well as their theoretical knowledge. Educational initiatives combining theoretical and practical aspects of emergency management may provide an opportunity to examine nurses’ knowledge, skills, and abilities continuously in an environment with no harm to patients.

Identifying the Factors That Increase the Probability of an Injury or Fatal Traffic Crash in an Urban Context in Jordan

The lack of robust studies carried out on urban roads in developing countries makes it difficult to enhance traffic safety, ensuring sustainable roads and cities. This study analyzes the contribution of a number of explanatory variables behind crashes involving injuries on arterial roads in Irbid (Jordan). Five binary logistic regression models were calibrated for a crash dataset from 2014–2018: one for the full database, and the others for the four main crash causes identified by Jordanian Traffic Police reports. The models show that whatever the crash cause, the three most significant factors linked to an injury or fatality lie in urban road sections that are in large-scale neighborhood areas, have fewer than six accesses per kilometer, and have a low traffic volume (under 500 veh/h/ln). Some of these results agree with previous studies in other countries. Jordan’s governmental agencies concerned with urban road safety might use these results to develop appropriate plans and implement priority actions for each crash cause, in addition to undertaking further research for comparative purposes.

Unobserved heterogeneity and the effects of driver nationality on crash injury severities in Saudi Arabia

This paper investigates factors that significantly contribute to the injury severity of different drivers of different nationality backgrounds. Using the data from Riyadh, Saudi Arabia, a random parameters multinomial logit model of driver-injury severity was estimated to explore the effects of a wide range of variables on driver injury-severity outcomes. With three possible outcomes (no injury, injury, fatality), only single-vehicle crashes are considered and crashes involving domestic (Saudi) and international (non-Saudi) drivers were modeled separately. Model estimation results show that a wide range factors significantly affect the injury severity outcomes in single-vehicle crashes including driver attributes (such as nationality and age), vehicle characteristics (such as make, model and year of manufacture), driver actions (such as speeding and preoccupation on driving), and other factors (such as location and time of the accident); and that the influence that these variables have on injury-severity probabilities vary considerably between Saudi and non-Saudi drivers. While Saudi Arabia is rather unique because of the large numbers of non-national drivers, the results suggest that different nationalities, with their different cultural, educational and, behavioral backgrounds, may affect risk-taking behavior and resulting crash-injury severities.

The priority setting of factors affecting a crash severity using the Analytic Network Process

Background:

The original step in reducing crash severity is recognition of the involved factors. The aim of this paper is to prioritize the factors affecting crashes severity. The current study was carried out in 2018 in Iran.

Methods:

The present cross-sectional study focuses on factors affecting the crash severity. Due to the compli-cated nature of traffic accidents, Multi-Criteria Decision-Making methods can be considered as an effective approach. In this work, the factors affecting a crash severity were identified and then attained factors were scored by ten traffic safety experts. To prioritize and weigh these factors, the Analytic Network Process method and Super Decisions program were used.

Results:

The results showed four main factors and 60 sub-factors in which the main factors in the order of priority were the safety (the most important sub-factor: speed over the upper limit), the other fac-tors (the most important sub-factor: road user type), the health (the most important sub-factor: drowsiness), and the environment (the most important sub-factor: slipping the road).

Conclusions:

In order to control the crash severity, the presented factors in this study could help traffic safety experts to prioritize and perform controlling actions.

Intersection characteristics that influence collision severity and cost

INTRODUCTION

Traffic engineers require robust tools to assist with their day-to-day decision making, and there is no better example of this than traffic signal warrants. North American traffic signal warrant systems are lacking in how they incorporate motor-vehicle collisions from both a severity and prediction perspective. The objective of this study was to produce reliable collision costs for the development of improved traffic signal warrants that accounted for the variations in severity that practitioners should expect based on the characteristics of the intersection being studied.

METHOD

The primary data used for this analysis were from the National Automotive Sampling System (NASS) Crashworthiness Data System, with adjustments from the NASS General Estimates System and Fatality Accident Reporting System. Generalized ordered logit models were used to identify the most significant intersection characteristics, which were then used to segregate the data to determine expected the collision severity profiles and average costs of both casualty and total collisions at intersections.

RESULTS

The average collision at a signalized intersection was found have a lower severity than the average collision at a stop-controlled intersection. A combination of posted speed limit, urban/rural, and divided/undivided were identified as the most significant intersection characteristics in most cases and were used to delineate the data for developing collision cost estimates.

CONCLUSIONS

Posted speed limit, rural/urban land use, and the presence of divided approaches are intersection characteristics that traffic engineers can readily determine and/or control for that have significant effects on intersection collision severity. Practical applications: The collision costs produced through this process give traffic engineers a reliable estimate that can provide a more substantial foundation for justifying a proposed change in intersection traffic control.

Patterns of injury detected by pan-computed tomography after road traffic accidents: retrospective review from a trauma center in Saudi Arabia

BACKGROUND

Pan-scan (whole-body) computed tomography (CT) has a paramount role in the diagnosis of injuries in road traffic accidents (RTA).

OBJECTIVE

Identify patterns of injuries on pan-CT scans.

DESIGN

Retrospective medical record review.

SETTING

Tertiary care center.

PATIENTS AND METHODS

The records of all RTA patients who presented to the radiology department at King Fahad Military Medical Complex (KFMMC) in Dhahran for the 3-year period from July 2014 to July 2017 and underwent pan-CT were retrospectively reviewed. Drivers and front-seat passengers with complete clinical information on seating, safety and mechanism of injury were selected. Children under 5 years of age, pregnant women and back-seat passengers were excluded. Patterns of injuries were categorized as 'no abnormality detected' (NAD), isolated or combined head, face and neck (H), isolated or combined chest, abdomen and pelvis (C) or both regions of the body (B).

MAIN OUTCOME MEASURES

Injury patterns on pan-CT scans.

SAMPLE SIZE

305 RESULTS: Most patients were males (n=287, 94.1%). The median age was 26 years for males (IQR, 22-33 years) and 30 years for females (IQR, 28-39). More than two-thirds were drivers (all males); the remainder were front-seat passengers. Young males were most often involved. The most common type of accident was a roll-over. Of those who sustained injuries, 273 (89.5%) were not wearing a seat belt (unrestrained). The patterns of injuries were NAD (87, 28%), H (27, 9%), C (93, 30.5%), B (98, 32%).

CONCLUSION

When abnormalities were detected, most high-speed vehicular injuries affected the torso. Unrestrained young male drivers are most often involved in RTAs in Saudi Arabia.

LIMITATIONS

Retrospective study with a small sample size. Types and severity of injuries on pan-CT were not documented.

CONFLICT OF INTEREST

None.

Incidence and Pattern of Mandible Fractures in the Madinah Region: A Retrospective Study

Objectives

The objective of the study is to study the incidence and pattern of mandible fractures in the holy city of Madinah in the Kingdom of Saudi Arabia over a retrospective period of 3 years from 2013 (1434H) to 2016 (1436H) and to compare the results with those from other regions of Saudi Arabia and elsewhere.

Materials and Methods

Relevant data of patients admitted to the King Fahad Hospital, Madinah with a fracture of the mandible during the study were collected from their medical records and radiographs. The age, gender, etiology, role of the patient, site, and number of fractures in the patients were evaluated. The data were analyzed by standard statistical methods.

Results

A total of 197 patients with fracture of the mandible were admitted in the period of the study by the Oral Maxillofacial Surgery Department, King Fahad Hospital, Madinah. There were 165 male and 32 female patients. The ages ranged from 3 to 86 years with a mean of 24 years. A total of 260 fractures of Mandible were documented. The largest number (113) of patients was found in the age group between 16 and 30 years. Trauma caused by motor vehicle road traffic accidents (RTAs) was the main etiology of the fractures followed by falls and assault. The majority of the patients were in the role of vehicle drivers. The condylar anatomical site of mandible was most frequently affected and constituted the largest number (103) of fractures followed by the angle (51), parasymphysis (45), and then by the body (23) of the mandible. Dentoalveolar fractures were present in 22 cases. Very less number of coronoid fractures (7), followed by those of the ramus (5), and least number at the symphysis (4) of the mandible were found.

Conclusion

RTA was the most common etiology for trauma and fracture of the mandible. The males outnumbered the female patients, the largest number of patients with trauma and mandible fracture was found in the age group between 16 and 30 years and frequency of condylar fractures was higher.

Investigation of drivers' behavior towards speeds using crash data and self-reported questionnaire

Speeding is a key contributing factor in roadway crashes in the United Arab Emirates (UAE) and elsewhere. Understanding how drivers behave towards speed management devices (i.e., speed cameras, radars, speed limits and speed warning signs) as well as factors affecting drivers' involvement in speed-related crashes might help in improving traffic safety. This study aims to identify and quantify the factors that affect drivers' compliance with speed enforcement and management devices as well as drivers' involvement in at-fault speed-related crashes in the Emirate of Abu Dhabi (AD), UAE. Two different datasets were collected from the same drivers' population in AD to provide different valuable information regarding the speeding problem. The first dataset was obtained from crashes' reports while, the second dataset was obtained from a self-reported questionnaire survey that was carried out among a total of 442 drivers in AD. Three logistic regression models were developed to identify the significant variables that affect (1) the occurrence of speed related crash (using crashes reports data), (2) drivers' compliance with speed limits (using questionnaire data), and (3) involvement in at-fault speed related crashes (using questionnaire data). The findings revealed that drivers' factors (gender, age, and nationality), vehicle factor (vehicle type), roads and environment factors (weather, road type and speed limit) were the significant factors that affect the occurrence of speed-related crashes in AD. The questionnaire findings revealed that running late, low values of posted speed limits and no sufficient police enforcement were the three main reasons that make motorists drive over the speed limits. In addition, the results indicated that drivers' characteristics (i.e., gender, education and income), drivers' responses to speed enforcement and management devices, and drivers' awareness about the importance of such devices in improving traffic safety were the main factors that affecting both drivers' compliance with speed enforcement devices and drivers' involvement in at-fault speed-related crashes. A comparison between the analysis results of traffic crashes and questionnaire datasets as well as a comparison between the findings of this study and existing literature are also provided.

Road safety and road traffic accidents in Saudi Arabia. A systematic review of existing evidence

OBJECTIVES

To identify the changing trends and crucial preventive approaches to road traffic accidents (RTAs) adopted in the Kingdom of Saudi Arabia (KSA) over the last 2.5 decades, and to analyze aspects previously overlooked.

METHODS

This systematic review was based on evidence of RTAs in KSA. All articles published during the last 25 years on road traffic accident in KSA were analyzed. This study was carried out from December 2013 to May 2014 in the Department of Family and Community Medicine, Taibah University, Al-Madinah Al-Munawwarah, KSA.

RESULTS

Road traffic accidents accounted for 83.4% of all trauma admissions in 1984-1989, and no such overall trend was studied thereafter. The most frequently injured body regions as reported in the latest studies were head and neck, followed by upper and lower extremities, which was found to be opposite to that of the studies reported earlier. Hospital data showed an 8% non-significant increase in road accident mortalities in contrast to police records of a 27% significant reduction during the years 2005-2010. Excessive speeding was the most common cause reported in all recent and past studies.

CONCLUSION

Disparity was common in the type of reporting of RTAs, outcome measures, and possible causes over a period of 2.5 decade. All research exclusively looked into the drivers' faults. A sentinel surveillance of road crashes should be kept in place in the secondary and tertiary care hospitals for all regions of KSA.

Road Traffic Injury as a Major Public Health Issue in the Kingdom of Saudi Arabia: A Review

Injury was the largest single cause of disability-adjusted life years and death in the Kingdom of Saudi Arabia in 2013. The vast majority of injury-related fatalities are deaths caused by road traffic. Measures to control this serious public health issue, which has significant consequences for both Saudi families and the Saudi economy as a whole, have been underway for years but with little success. Most attempts at intervening revolve around attempts for enforcing stricter traffic laws and by installing automated traffic monitoring systems that will catch law breakers on camera and issue tickets and fines. While there has been much research on various factors that play a role in the high rate of road traffic injury in The Kingdom (e.g., driver behavior, animal collisions, disobeying traffic and pedestrian signals, environmental elements), virtually no attention has been given to examining why Saudi drivers behave the way that they do. This review provides a thorough account of the present situation in Saudi Arabia and discusses how health behavior theory can be used to gain a better understanding of driver behavior.