Statistical Analysis of Accident Patterns and The Causes at A State Road in Perlis

Abstract

According to data from the World Health Organization, approximately 1.3 million road users are at high risk of road traffic accidents every year. This study aims to assess accident patterns and causes on a state road between Kangar and Alor Setar. The evaluation of accident pattern employed include the chi-squared test (CST) and the level of service (LOS) survey. Analysis using Pearson CST reveals that age and vehicle type are significant factors in accidents. Specifically, individuals below 30 years old have a higher likelihood of being involved in accidents (ρ= 0.037), while motorcycles are more prone to accidents (ρ= 0.000). However, gender does not appear to impact accident involvement significantly (ρ= 0.911). The LOS E category indicates unstable traffic flows during Monday and Friday evenings. To evaluate accident causes from the perspective of road users, a questionnaire was used, and its validity and reliability were ensured through a pilot study. Four hypotheses were developed, examining human factors, vehicle factors, environmental factors, and road condition factors as independent variables. The results reveal that a majority of road users (33.3%) travel 1 to 3 times per week, with 23.1% of them being involved in accidents on this road. The validity test using the structural model identifies road factors (t= 6.166, ρ= 0.000), vehicle factors (t= 4.3399, ρ= 0.000), and human factors (t= 2.893, ρ= 0.005) as the most significant contributors to accidents. Hence, it is crucial for authorities to prioritize countermeasures focusing on these factors to reduce accidents on this road.