# Severity Prediction of Highway Crashes in Saudi Arabia Using Machine Learning Techniques
## 3 Materials and Methods
### Study Area and Collection of Accident Data  
Out of 13 provinces in Saudi Arabia, Qassim Province (shown in Figure 2B) was selected as the study area [54]. In geographical terms, Qassim Province lies between 40\({}^{\circ}\)000 E and 45\({}^{\circ}\)000 E longitude and 23\({}^{\circ}\)300 N and 28\({}^{\circ}\)000 N latitude, with 10 sub-provinces and 155 localities, divided into 13 governorates, namely Buraidah, Unaizah, AlAsyah, Uyun Al-Jiwa, Al-Badaya'a, Al Bakiriyah, Daria, Al Mithnab, Al Nabhamya, Ar Rass, Riyadh Al-Khabra, Al Shammasiya, and Oklat AlSkoor [55]. There are 1.3 million people living in Qassim, and the province covers 58,046 square kilometers [55]. Approximately 49% of Qassim's population resides in Buraydah, the province's capital city. Located in the  
Figure 1: Severity prediction framework.  
middle of the KSA with extensive agricultural activities, it links the north with the south and the west with the east, hence heavy carriers travel on its roads for different agricultural, commercial, religious, and cultural purposes. With 205,000 tons of dates produced annually (both for local consumption and export), the region has been able to enhance its economic value, being one of the largest producers of luxury dates in the Middle East. In addition, various types of fruits and vegetables are extensively produced.  
It is worth mentioning that the number of traffic accidents has witnessed a decreasing trend in recent years for many reasons, mainly due to the implementation of mitigation strategies [56]. In 2010, more than 4232 injuries and 1054 deaths were recorded in Qassim [5], reducing periodically until 2016 [57]. Figure 2 illustrates the distribution of RTAs for the given assessment period and clearly shows a continuous reduction in the number of accidents. [PERSON] et al. [57] found that speeding, irregular overtaking, irregular turning, failing to prioritize other vehicles, irregular stops, lack of road readiness, driver carelessness, cell phone usage while driving, and disobeying traffic laws were the most important causes of RTAs. Apart from not wearing a seat belt, these are the ten most common causes of RTAs in Qassim Province.  
This analysis is based on traffic crash data collected from the Ministry of Transport and Logistic Services. The data contains information about accidents that have occurred on the main highways under the jurisdiction of Ministry of Transport. During the period of  
Figure 2: Description of study area: **(A)** Qassim Province highlighted on a map of Saudi Arabia; **(B)** study area boundaries; **(C)** yearly distribution of data collected.  
data collection, between January 2017 and December 2019, 3506 accidents were reported. The data also consists of detailed information on various explanatory variables, as shown in in Table 1.  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Variables** & **Description** & **Variable Categories** & **Frequencies** \\ \hline Dependent Variable & & & \\ \hline Accident\_categories & Severity of crash & Property damage only (PDO)/Injury/Death & 49.2\%, 43.3\%, 7.5\% \\ \hline Independent Variables & & & \\ \hline Temporal Attributes & & & \\ \hline Day & Day of the week & Sunday/Monday/Tuesday/Wednesday/Thursday/Friday/Saturday & 15\%, 15\%, 15\%, 16\%, 15\%, 11\%, 13\% & 15\%, 15\%, 15\%, 16\%, 15\%, 11\%,  Friday/Saturday & 13\% \\ \hline Day\_Type & Weekday or weekend & Weekday/Weekend & 76\%, 24\% \\ \hline Rush\_Hour & Time of the day (TOD) & Peak hours/Non-peak hours & 59\%, 41\% \\ \hline Season & Season of the year & Summer/Autumn/Winter/Spring & 62\%, 11\%, 15\%, 12\% \\ \hline Month & Month of the year & January/February/March/April/May/June/July/August/September/October/November/December & 4.7\%, 4.7\%, 6.5\%, 6\%, 5\%, 5\%, 30\%, 15\%, 5\%, 5\%, 5\%, / 30\%, 5\%, 5\%, 5\%, 5\%, / 30\%, 5\%, 5\%