인명 사고, 차량 화재, 자연재해, 돌발상황 등 긴급상황 발생 시 신속한 대응을 위해 영향권을 정확하게 분석하는 것이 필수적이다. 특히 도로망을 중심으로 한 영향권은 해당 도로의 교통량, 통제 차로 수, 사고 처리 시간에 따라 달라지며, 이를 관리하기 위한 대책 이 필요하다. 따라서 본 연구는 향후 도로 관리 대책 및 의사결정을 지원하기 위해 대기행렬이론을 기반으로 긴급상황 영향권을 분석 하였다. 본 연구에서 영향권은 공간적인 개념으로서 사고 발생지점으로부터 해당 도로 진행 방향 기준 후방으로 도로 소통에 영향을 끼치는 거리로 정의하였다. 사고 발생지점, 사고 발생 링크의 교통량, 차로 수 및 통제 차로 수, 사고 발생 및 사고 종료 시점 등의 변수를 입력 데이터로 설정하였고 긴급상황으로 인해 발생하는 대기행렬길이를 파악하기 위해 대기행렬이론을 적용하였다. 돌발상황 정보를 분석하여 사고 지속시간의 범위를 도출하였으며 이를 기반으로 여러 가지 상황별 영향권을 산출하였다. 유스 케이스별 영향권 산출을 통해 교통량, 이용 가능한 차로 수, 사고 지속시간 각각이 영향권과 어떠한 관계가 있는지 확인할 수 있었다. 본 연구에서 설정한 영향권을 통해 실시간 교통 데이터를 활용하여 유사 상황에서의 영향권을 신속히 파악할 수 있다. 이는 교통사고와 같은 긴급 상황 발생 시 신속하고 정확한 영향권 파악으로 현장 대응 및 의사결정 지원 시스템의 효율성을 높이는 데 중요한 역할을 할 것으로 기대된다.

This study aims to analyze cooperative autonomous driving by integrating two advanced simulation tools, UC-WinRoad and VISSIM. Cooperative autonomous driving refers to the interaction of autonomous vehicles (AVs) with human-driven vehicles, infrastructure, and other road users within a dynamic traffic environment. The integration of UC-WinRoad’s realistic 3D visualization capabilities with VISSIM’s detailed microscopic traffic modeling enables the simulation of complex traffic scenarios, providing a comprehensive analysis of autonomous and connected vehicle behavior. The necessity of this study arises from the growing interest in autonomous driving technologies and the need for reliable tools to evaluate their performance and impact on real-world traffic systems. Simulations offer a safe and cost-effective environment to test AV behavior in various scenarios, including extreme or hazardous conditions that are difficult to replicate in the real world. This study also provides valuable insights into AV-infrastructure interactions, offering data-driven recommendations for policy and infrastructure planning. The outcomes of this research include the development of a methodology for linking UC-WinRoad and VISSIM, simulation results demonstrating potential improvements in traffic flow, safety, and efficiency through cooperative autonomous driving, and the identification of challenges in integrating AVs into existing traffic systems. This research contributes to the advancement of autonomous driving technologies by providing a robust framework for analyzing cooperative driving scenarios, supporting AV and human-driven systems ahead of the fully autonomous traffic systems of the future.

PURPOSES :In this study, we analyzed the road crossing behavior of older pedestrians on a mid-block signalized crosswalk, and compared it to that of younger pedestrians. In addition, we analyzed the correlation between accidents involving older pedestrians while crossing roads and their behavioral characteristics. Finally, we confirmed the reasons for an increase in accidents involving older pedestrians.METHODS :First, 30 areas with the highest incidence of accidents involving older pedestrians while crossing roads were selected as target areas for analysis. Next, we measured the start-up delay (the time elapsed from the moment the signal turns green to the moment the pedestrian starts walking) and head movement (the number of head turns during crossing a road) of 900 (450 older and 450 younger) pedestrians. The next step was to conduct a survey and confirm the differences in judgment between older and younger pedestrians about approaching vehicles. Finally, we analyzed the correlation between the survey results and traffic accidents.RESULTS :The average start-up delay and head movement of the older pedestrians was 1.58 seconds and 3.15 times, respectively. A definite correlation was obtained between head movement and the frequency of pedestrian traffic accidents. The results of our survey indicate that 17.3% of the older pedestrians and 7.8% of the younger pedestrians have a high crash risk.CONCLUSIONS :Behavioral characteristics of older pedestrians were closely correlated with accidents involving older pedestrians while crossing roads in mid-block signalized crosswalks. Our study indicates that in order to reduce the number of accidents involving older pedestrians, it is necessary to develop an improvement plan including measures such as installation of safety facilities taking the behavioral characteristics of older pedestrians into consideration and their safety education.