Understanding Traffic Accident Patterns on the Jakarta-Cikampek Toll Road: An Integrated Approach Combining Blackspot Analysis and Human Factors
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Relif Karnadi*
Sutanto Soehodho
R. Jachrizal Sumabrata
Traffic accidents on toll roads remain a major safety concern, particularly on high-traffic corridors such as the Jakarta-Cikampek Toll Road in Indonesia. This study aims to identify accident-prone locations (blackspots) and analyze contributing factors, with a focus on human-related aspects such as fatigue and rest adequacy. An integrated approach combining spatial analysis and multiple linear regression was employed to better understand accident patterns and their determinants. The study utilizes historical accident data from the Indonesian National Police Traffic Corps and toll road operators for the period 2021-2023, complemented by interview-based behavioral data. Blackspots were identified using a severity-based weighting method, while regression analysis examined the relationship between rest adequacy and variables such as gender, driving experience, travel characteristics, fatigue indicators, sleep duration, and risk perception. The results indicate that no variables are statistically significant at the 5 percent level. However, gender shows the strongest relationship with rest adequacy (β = -0.313; Sig. = 0.060), while sleep duration (β = 0.156) and risk perception (β = 0.102) exhibit positive tendencies. Fatigue indicators show mixed results, suggesting that fatigue is a complex and multidimensional factor. Spatial analysis also reveals several high-risk segments associated with traffic density and road conditions. These findings highlight the need for integrated safety strategies that address both location-based risks and human factors. The study contributes to evidence-based approaches for improving toll road safety.
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