## 1 Introduction
Although they occur less frequently, RTCs had a high severity index in the study area, with 73% of severe RTCs involving people between the ages of 15 and 44. The study also discovered that people between the ages of 15 and 44 were more frequently involved in RTCs with a large number of fatalities and injured victims. According to [PERSON] et al. 's (2022) [8] research, there is a 26% chance of a collision occurring merely as a result of speeding, a rise of 63% from an earlier estimate. Furthermore, the likelihood of a collision rises from 26% to 33% when speeding and brake failure are factored in, more than tripling the initial odds of a collision. [PERSON] et al. (2022) [9] used the random forest approach to evaluate the same research region and discovered that the two most significant factors impacting the severity of injuries in RTCs are the reason for the crash and the kind of collision. They also demonstrated that the research region had substantial spatial dependence, with clustered spatial patterns found within a distance threshold of 500 m, in addition to the findings on the factors determining the severity of injuries in RTCs. The analysis used by the authors, which employed Getis Ord Gi*, the crash severity index, and spatial autocorrelation analysis based on Moran's I, was successful in locating and ranking crash hotspots as well as evaluating the severity of the crashes. The Saudi Arabian government has implemented various measures to enhance road safety across the country in recent years, including in the region of Al-Ahsa. These measures include increasing the presence of traffic police personnel, improving the road infrastructure, and intensifying awareness programs aimed at promoting safe driving practices. Additionally, the government has established the Saudi Traffic Safety Society, which plays a significant role in fostering road safety through educational campaigns and awareness initiatives. As a result of these concerted efforts, the number of road crashes in Al-Ahsa and Saudi Arabia as a whole has witnessed a decline in recent years [7]. However, it remains crucial for drivers to exercise caution, comply with traffic regulations, and prioritize the safety of themselves and other road users in order to prevent collisions and ensure a safe driving environment. The study aims to improve our understanding of severe crashes and offer a more useful analytical framework for analyzing crash data by combining these efforts in the following two main points:  
1. Providing insight into the types and causes of severe crashes in the Al-Ahsa region:  
This study makes a significant addition by offering insightful information about the factors that contribute to serious crashes in the Saudi Arabian province of Al-Ahsa. The study intends to find patterns and trends related to severe crashes using data analysis, taking into account underlying causes such as the type of vehicle, crash types, road conditions, and driver behavior. 2. Employing the newly proposed proportion-based analytic hierarchy process (PBAHP) for crash data analysis:  
The development and use of the proportion-based analytic hierarchy process (PBAHP) approach for crash data analysis is another significant contribution of this study. The study suggests a novel strategy that overcomes the methodological limitation associated with the conventional analytic hierarchy process (AHP) method, such as inconsistent pairwise comparisons and reliance on subjective judgments, by allowing the weighting and ranking of items based on their relative occurrence. The newly developed PBAHP was applied to analyze the factors involved in traffic crashes and then to develop a utility function for predicting the severity of crashes. The implementation of this technique has not been found in the literature; instead, several variants of AHP were used for the data collected through surveys and interviews.