Black Spot Identification and Road Accident Prediction Model on Cebu South Coastal Road (CSCR)

Abstract Millions of people die in road accidents yearly, causing significant damage to the economy and humanity. The main focus study is analyze through Black Spot Identification establish a Prediction Model on Cebu South Coastal Road (CSCR)-N840 Highway. data gathered from government agencies were digitized using SPSS MS Excel. revealed that year 2018 has highest number accident cases with 555 (46.52%) lowest severity ratio 0.41. In contrast, 2019 frequency 159 (13.33%) 0.72. Through APW system, CSCR-N840 Highway’s top black spot locations at 2.6 km, 1.2 2.3 0.9 km,2.2 5.3 4.6 4.7 3.7 5.9 7.6 7.7 8.2 8.5 6.5 10.2km, 11.4 9.4 12.1 12.0 km. Also, researchers presented heat mapping QGIS for visual analysis, where severe traffic usually occur Talisay side CSCR N840 Highway due 13 junctions, 7 intersections, 6 curvatures. Lastly, developed regression model rate decreases gradually an increase volume. Poisson prediction model, as probability increases, may either or slowly decrease.