Initial study of truck accident over dimension and overloading on arterial road using a multinomial logistic regression method

Trucks have an important role in the economy. The increasing number of online buying and selling transactions causes logistics delivery services to be increasingly needed by the community. This causes the volume of truck traffic to also increase. On the other hand, the negative impacts of trucks include infrastructure damage, increased road maintenance costs, air pollution, and increased accident rates. Trucks are one of the biggest contributors to accidents. This is generally influenced by overdimension and overloading trucks. The condition of overloading trucks causes a decrease in truck speed and causes traffic flow to be hampered. Overdimension and overloading trucks will obstruct the view of other vehicle drivers and interfere with visibility while driving, also affecting the vehicle's safe distance. This problem is very interesting and requires handling to reduce the accident rate due to overdimension and overloading trucks. The data for this research were obtained from field surveys and questionnaires, where 194 respondents were found. The accident factor analysis was carried out using the multinomial logistic regression method, by dividing the accident factors into 4 categories, namely the environment, driver, vehicle, and road. This study was conducted to determine the factors that contribute to the occurrence of overdimension and overloading truck accidents and to produce an accident model. The research was carried out on the arterial road in the city of Jombang. From the results of the analysis, it was found that the contributing factors were road surface conditions (X12), traffic volume (X13), accident history (X25), load (X33), dimensions (X34), and speed limit signs (X44). The prediction model formed is Y= -0.374 X12+0.427 X13+0.369 X25+0.447 X33-0.824 X34-0.474 X44. This research is expected to provide alternative solutions in determining transportation policies in order to achieve safe truck regulations.