Statistical Model Comparison of Causes and Risk Perception Based on Road Characteristics in Bicycle and Motorcycle Accidents

Abstract

This paper presents the concept of a research to compare the causes and risk recognition of bicycle and motorcycle accidents based on road characteristics. The number of seriously injured people in traffic accidents in Osaka Prefecture is 1.5 times higher than that of the second highest prefecture in Japan, with bicycle and motorcycle accidents accounting for more than 70% of the total. To address this issue, this study focuses on the causes of accidents as seen from road characteristics, and furthermore on their relationship with risk recognition. As a research method, we first use a statistical model to calculate the accident occurrence rate for each road characteristic based on a digital road map. Next, we calculate the risk recognition rate for each road characteristic using questionnaire data. After that, we visualize the difference between the accident occurrence rate and risk recognition rate based on these and propose appropriate countermeasures.