AHP 기법을 활용한 도로 인프라 측면에서의 자율주행차량 주행 난이도 비교분석
Comparative Analysis of Driving Difficulty of Automated Vehicles in Therms of Road Infrastructure Using AHP Method
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초록
본 연구는 주행 고난이도 상황에서 인프라 정보 연계를 통해 도로 상황 인지 수준이 고도화되면 자율주행 수준을 높일 것으로 판단하여, 자율주행차량이 주행하기 어려운 고난이도 상황을 도로 인프라 운영 측면에서 도출하고자 하였다. 난이도 평가 지표를 도로 인프라 조건 및주행상황 등 3단계로 구분하여 전문가 대상 설문조사 후 계층화 분석을 하였다. 분석결과, 단속류 도로가 연속류 도로보다 주행 난이도가 월등히 높고, 단속류 도로 하위의 비신호 교차로와 회전교차로의 주행 난이도가 높게 평가되었다. 또한 난이도가 높은 6가지 주행 상황도 비신호교차로 및 회전교차로에서 발생되는 상황인 것으로 평가되었다. 자율주행차량의 주행 난이도는 다른 차량과의 상충 가능성이 높고 도로에서 차량 스스로가 인지해야 할 요소들이 많으며 현재 주행하는 주행흐름에 급격한 변화를 겪게 될수록 높아지는 것으로 분석되었다.
Abstract
The purpose of this study is to find the driving difficulty of automated vehicles in terms of road infrastructure operation. It was judged out of this study that the level of automated driving would be enhanced if the road situation recognition ability was advanced through the presentation of infrastructure information during the difficult driving situations. The difficulty evaluation index was divided into three stages, and a survey of experts and an AHP were conducted. The result of the AHP showed that the driving difficulty of the interrupted flow was much higher than that of the uninterrupted flow. The AHP results also showed that and the driving difficulty of unsignalized intersections and roundabouts under an interrupted flow was evaluated as the highest. The top six driving situations with high difficulty were also evaluated to occur under unsignalized intersections and roundabouts.
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