Factors Influencing Traffic Accidents on the Cipularang Toll Road: An Analysis Using Multiple Linear Regression
Main
Dedi Kurniawan*
Sutanto Soehodho
R. Jachrizal Sumabrata
Traffic accidents remain a critical issue in road safety, particularly on toll roads with high traffic intensity such as the Cipularang Toll Road. This study aims to analyze the factors influencing traffic accidents by applying a multiple linear regression approach, with a focus on human-related factors represented by driver physical condition. Data spanning 2023–2025 from the Cipularang Toll Road corridor were collected through structured interview surveys and supported by secondary data from official accident records. The variables examined include driver characteristics, vehicle conditions, traffic and environmental factors, and behavioral aspects. The results show that estimated speed and driving license type have a statistically significant effect on the dependent variable at the 5% significance level. Estimated speed is identified as the most influential factor, indicating that higher speeds are associated with a decline in driver physical condition, which may increase accident risk. The selection of physical condition as the dependent variable is supported by police reports indicating that a substantial number of accidents are caused by driver fatigue, drowsiness, and reduced alertness, especially on long-distance toll roads. Other variables, although not statistically significant, demonstrate relationships consistent with theoretical expectations. These findings highlight the importance of addressing both speed management and driver fatigue in reducing accident risk. The study contributes to evidence-based road safety strategies by providing a comprehensive analysis of accident-related factors, helping policymakers and toll road operators design more effective safety interventions, especially on high-risk segments like the Cipularang Toll Road.
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