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Towards Sustainable Road Safety in Saudi Arabia: Investigating Causes of Road Accidents Associated with Driving Behavior Using a Bayesian Belief Network
By Muhammad Muhitur Rahman Muhammad Muhitur Rahman Scilit Preprints.org Google Scholar * , Md Kamrul Islam Md Kamrul Islam Scilit Preprints.org Google Scholar * , Ammar Al-Shayeb Ammar Al-Shayeb Scilit Preprints.org Google Scholar and Md Arifuzzaman Md Arifuzzaman .org Google Scholar
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Received: 11 April 2022 / Revised: 19 May 2022 / Accepted: 20 May 2022 / Published: 22 May 2022
Understanding the causes and effects of traffic accidents is critical to developing road and action plans in a country. The causal hypothesis illuminates how accidents occur and can be applied to accident analysis to more accurately anticipate, prevent, and manage traffic safety programs. Driving behavior is a critical factor to consider in determining the causes of traffic accidents. Improper driving behavior is a set of actions taken on the road that can result in abnormal conditions that can result in traffic accidents. In this study, using Al-Ahsa city in Saudi Arabia East Province as a case study, a Bayesian belief network (BBN) model was established by incorporating an expectation-maximization algorithm. The model examines the relationships between indicator variables with a special focus on driving behavior to measure the uncertainty associated with accident outcomes. The BBN was devised to analyze intentional and unintentional driving behaviors that cause various types of accidents and mishaps. The results showed when considering speed alone, there is a 26% chance that collision will occur; this is an increase of 63% over the first estimate. When brake failure was considered in addition to speed, the probability of a collision jumps from 26% to 33%, more than doubling the probability of a collision compared to the initial value. These findings showed that the BBN model was able to efficiently investigate the complex connections between driver behavior and the accident causes inherent in traffic accidents.
Sustainable road safety; driver behavior; multi-criteria decision making; Bayesian belief network; causality; sustainable road condition; road safety modeling; Al-Ahsa
A transportation system cannot be sustainable unless it is safe for people, and human life is the most precious resource. Road safety not only includes the steps taken to reduce the risk of road-related injuries and deaths, but also includes the feeling of being safe while on the road and the confidence that the user will not be seriously injured or killed while it’s on. Safety is now recognized in global environmental policy as critical to achieving sustainable development and must be a prerequisite for mobility, especially in countries where the number of road deaths remains high. The goal of a sustainable and safe traffic system is to eliminate road deaths, serious injuries and permanent injuries by systematically reducing the underlying risks of the entire traffic system. Human aspects are the main focus: the traffic system can be realistically changed to ensure optimal safety by examining the behavior, skills and limitations of drivers.
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Traffic, accidents and pollution are three problems that are becoming more and more prominent in urban areas as both the population and the car fleet continue to increase. The most damaging of the three elements described above is an accident in or near a city center. According to the World Health Organization (WHO), more than 1.3 million people died in road accidents in 2010, while 20 to 50 million people were injured [1]. Between 1975 and 1998, the number of people killed or injured in road traffic accidents increased by about 44% in Malaysia and by more than 200% in Colombia and Botswana. The World Health Organization has also predicted that road traffic accidents will be the sixth leading cause of mortality and the second leading cause of disability in developing countries by the year 2020 if current trends continue [2]. According to a review of 404 accident reports from 14 different types of accidents, the road environment played a role in approximately 14.5% of all accidents [3]. According to the findings of the WHO study [1], 30 deaths per 100,000 people were observed in Saudi Arabia in 2007, and 6358 deaths occurred as a result of traffic accidents. In addition, according to the WHO report [4], in the Kingdom of Saudi Arabia, traffic accidents are the largest cause of injuries, deaths and disability, and the cost of treating those injured or killed in road traffic accidents were projected to be SAR 652.5 million [2, 3]. Officials in Saudi Arabia have revealed that road accidents occur every minute in the country, and the kingdom is considered one of the top countries in the world when it comes to road accidents, with around 21 deaths per day, ranking it the second deadliest country in the Middle East [5, 6].
There are many factors that cause traffic accidents. Some of these causes are related to road geometry, and some are related to driver behavior. Driving behavior is one of the important issues when analyzing the causes of traffic accidents. A report on the city of Mekelle in northern Ethiopia showed that human risk behavior is behind 96% of accidents [7]. A study in an eastern Mediterranean region showed that 86% of drivers engaged in at least one risky driving behavior while driving [8]. Crash-causing risky driving habits include speeding, ignoring red light signals, sudden lane changes, blocking intersections, not using seat belts, and vehicles turning suddenly [9]. If the effects and extent of inappropriate driving attitudes and behavior on the severity and type of accidents can be identified, it will be useful in developing suitable road safety policies that would prevent road accidents. Saudi Arabia, similar to many other countries around the world, has created tactics and scenarios to reduce and resolve traffic accidents when they occur. However, despite the depreciation and awareness measures implemented by the Traffic Department and other relevant departments, which have taken it upon themselves to confront this danger, Saudi Arabia continues to experience a significant problem regarding traffic accidents; therefore it is essential to analyze the effects of driving behavior on traffic accidents in the Saudi Arabian context.
It is essential to understand the causes and effects of traffic accidents in order to adopt appropriate safety strategies and action plans. Some of these causes are reflections of the inappropriate attitude or behavior of drivers, such as speeding, suddenly changing lanes, and tailgating [10]. Various studies have attempted to analyze and categorize types of driving behaviour. Some researchers divided driving behavior into two broad categories: “cautious” and “aggressive” driving [11]. A driver who does not accelerate may start the breaks of their car unexpectedly, and maintaining the correct speed is considered to be careful and cautious driver [12]. The Pennsylvania Department of Transportation defined aggressive driving as “the operation of a motor vehicle in a manner that endangers or is likely to endanger persons or property” [10]. Eboli et al. [13] analyzed average speed as well as the 50th and 85th percentile speeds of a road segment of a two-lane Italian rural road and classified driving behavior into three categories: (1) safe, (2) unsafe, and (3) safe but potentially dangerous. In another study conducted by Taubman-Ben-Ari et al. [14], it was suggested that driving behaviors are classified into four groups: (1) careless and reckless driving: this driving behavior is characterized by high speed, illegal maneuvers, and racing to seek thrills while driving; (2) anxious driving: related to ineffective relaxation activities with feelings of tension and alertness while driving; (3) hostile and angry driving: includes drivers with antagonistic attitudes and annoyance, such as anger, and these emotions are expressed through actions such as flashing their headlights at others; and (4) prudent and patient behavior: expressed through a good attitude, planning for unforeseen situations in
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