Identification of Traffic Accident-Prone Locations (Black Spots) Based on Road Geometry in Purbalingga Regency

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Abstract

The number of traffic accidents in Indonesia is very high, reaching 1,150,025 accidents with 27,329 fatalities in 2024. Efforts to reduce the number of accidents include identifying and addressing accident-prone areas. The method used to determine black-spot is based on the Equivalent Accident Number (EAN) and Upper Control Limit (UCL). The weakness of the EAN-UCL method is that black-spot can only be determined after data on accidents and casualties, both life and property, is available. Therefore, research is needed to find new methods and approaches to determine black-spot locations without having to wait for accidents and casualties. The aim of this research is to formulate a model for determining black-spot locations based on road geometric facilities. Each road geometric parameter is compared with the standard road geometric design according to its function and is weighted. The total weighted value is analyzed statistically to determine whether the road section is categorized as a black-spot location or not. Six geometric road parameters include vehicle speed, lane width, shoulder width, sidewalk width, median width, and the difference in elevation between shoulder and edge of the road pavement (drop-off). Black-spot locations in Purbalingga Regency include Bayeman Tlahab Lor Karangreja road, Majasari Bukateja road, Bojongsari road, Mayjend Sungkono Kalimanah Wetan road, Gembong Bojongsari road, Kejobong road, Selanegara Kaligondang road, Kebutuh Bukateja road, Bojong Bukateja road, and Bojanegara Padamara. There are differences in the ranking of black-spot locations between the EAN-UCL method and the weighting method based on road geometric facilities.

Keywords

Black spot traffic safety road geometric equivalent accident number upper control limit.

References

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How to Cite

[1]
“Identification of Traffic Accident-Prone Locations (Black Spots) Based on Road Geometry in Purbalingga Regency”, JTERA, vol. 11, no. 1, pp. 1–10, Jun. 2026, doi: 10.31544/jtera.v11.i1.2026.1-10.