Operational Data Analytics of Over Dimensional and Overloaded Truck in Indonesia

Abstract

Over Dimension and Overload (ODOL) vehicles are one of the factors that cause road conditions to be easily damaged and potholes and can cause the risk of traffic accidents. ODOL vehicles are considered very detrimental to road infrastructure and increase the risk of accidents, inefficiency due to damaged road conditions, and air pollution because of excess exhaust gases. Road damage due to ODOL also triggered an increase in the budget for the maintenance of national roads, toll roads, and provincial roads, with an average of Rp 43.45 T per year. Based on data from the National Police Corps from the Integrated Road Safety Management System (IRSMS) regarding accidents in 2018, ODOL trucks are one of the biggest contributors to traffic accidents. This study aims to determine the causes of vehicle overload and over dimension. The method used is to use the triangulation method. Triangulation of techniques means that researchers use different data collection techniques to obtain data from the same source. The results showed a relationship between vehicle modification and ODOL violations which were proven using Chi-square analysis. The chi-square value is 55,259 with a p-value of 0.000 at a significance level of 1%. This shows a significant relationship between vehicle modification and Over Dimension and Overload (ODOL) vehicle violations.