This study aims to analyze the mitigation effects of phantom traffic jams on highways in a mixed traffic environment in which autonomous vehicles (AVs) and human-driven vehicles coexist. It focuses on identifying the key factors that contribute to phantom congestion and evaluating the extent to which the introduction of AVs can stabilize traffic flow and alleviate nonrecurring congestion. To achieve this goal, a theoretical analysis was conducted to examine the major causes of phantom traffic jams, including variations in the vehicle speed, road gradients, driver behaviors (for example, acceleration and deceleration), and visual adaptations in tunnel sections. Based on these factors, simulation scenarios were constructed using VISSIM to replicate real-world conditions in highway tunnel segments. The scenarios varied according to the AV penetration rate (0%, 20%, 40%, and 60%) and incorporated key traffic indicators such as the vehicle composition, speed, and headway. Traffic flow stability was evaluated using metrics including the average travel speed, headway consistency, and frequency of acceleration and deceleration events across sections. The simulation results showed that as the proportion of AVs increased, the average travel speed improved, and both the headway stability and flow continuity were enhanced. In particular, tunnel segments with higher AV ratios experienced fewer deceleration events and reduced behavioral variability, contributing to a more stable traffic flow. These findings suggested that AVs could play a critical role in mitigating phantom traffic jams by maintaining steady speeds and safe following distances, thereby reducing the instability caused by human driving behaviors. This study offers a foundational reference for future traffic congestion mitigation strategies and AV policy development, particularly in anticipation of increasingly mixed traffic environments.
PURPOSES : Because a driving simulator typically focuses on analyzing a driver’s driving behavior, it is difficult to analyze the effect on the overall traffic flow. In contrast, traffic simulation can analyze traffic flow, that is, the interaction between vehicles; however, it has limitations in describing a driver’s driving behavior. Therefore, a method for integrating the simulator and traffic simulation was proposed. Information that could be controlled through driving experiments was used, and only the lane-change distance was considered so that a more natural driving behavior could be described in the traffic flow. METHODS : The simulated connection method proposed in this study was implemented under the assumption of specific traffic conditions. The driver’s lane-changing behavior (lane-changing distance, deceleration, and steering wheel) due to the occurrence of road debris was collected through a driving study. The lane-change distance was input as a parameter for the traffic simulation. Driving behavior and safety were compared between the basic traffic simulation setting, in which the driver's driving behavior information was not reflected, and the situation in which the driving simulator and traffic simulation were integrated. RESULTS : The number of conflicts between the traffic simulation default settings (Case 1) and the situation in which the driving simulator and traffic simulation were integrated (Case 2) was determined and compared for each analysis. The analysis revealed that the number of conflicts varied based on the level of service and road alignment of the analysis section. In addition, a statistical analysis was performed to verify the differences between the scenarios. There was a significant difference in the number of conflicts based on the level of service and road alignment. When analyzing a traffic simulation, it is necessary to replicate the driving behavior of the actual driver. CONCLUSIONS : We proposed an integration plan between the driving simulator and traffic simulation. This information can be used as fundamental data for the advancement of simulation integration methods.
감천항은 부산항의 늘어나는 화물 수요에 대처하고 북항의 기능을 보완하기 위해 개발되었다. 일반부두뿐만 아니라 1997년에는 컨테이너 부두가 개장되어 현재 최대 50,000DWT급 컨테이너 선박이 입 출항 하고 있다. 그러나 감천항은 어선, 잡종선 등 소형선박들의 입 출항의 비중이 50%에 가깝고, 동부두 방면에 건설 중인 공영 수산도매시장이 2008년에 개장할 예정이다. 따라서 감천항의 항만관제 운영계획을 설정하기에 앞서 입 출항하는 선박의 장래 연간교통량을 파악하는 것이 필요하다. 또한 감천항은 방파제 입구가 협소하며, 방파제 전방에서 선박이 통항할 때 교차상태가 상존한으로 해상충돌사고의 위험이 높아 이에 대한 교차상태위험 분석이 요구되고 있다. 따라서 본 연구에서는 감천항의 장래 교통량을 추정하고, 시뮬레이션을 통해 통항위험에 대한 정량적인 분석을 수행하였다.