A Study on Selecting the Priority Order of Scenario by ODD for Evaluation of Autonomous Vehicles in Compliance with Road Traffic Laws

In this study, to verify the safety of autonomous vehicles driving safely in compliance with the Road Traffic Laws, a study was conducted on deriving the importance of setting an appropriate scenario for each ODD of autonomous vehicles. To this end, it was intended to classify the types of traffic accidents according to the road structure and to calculate the degree of the impact of traffic law violations on the risk of traffic accidents. The purpose is to present the importance of the scenario according to the ODD of an autonomous vehicle based on the analysis of the risk of traffic accidents caused by violations of the Road Traffic Laws. The main research content consisted of first classifying traffic accident data based on the ODD of autonomous vehicles, secondly analyzing the risk of traffic accidents caused by drivers' traffic violations, and thirdly analyzing the importance of driving ability evaluation scenarios for each ODD of autonomous vehicles. As a result of analyzing the importance of the safety driving ability evaluation scenario by ODD of autonomous vehicles by applying a regression model, it was confirmed that the overpass scenario is the most important in the road type, and it was analyzed that the ODD, which has a great influence on the risk of traffic accidents road surface conditions, is a dry road, and in weather conditions, the scenario in clear weather conditions is the most important. This can be said to be an important item to evaluate when conducting a evaluating the Safe driving ability in a virtual environment, PG, and on a real road. Although this study has limitations in reflecting the actual driving behavior of autonomous vehicles, it is expected that it can be used as basic data for evaluating the driving ability of autonomous vehicles related to the Road Traffic Laws in mixed traffic conditions.