PURPOSES : This study aimed to identify factors affecting the duration of traffic incidents in tunnel sections, as accidents in tunnels tend to cause more congestion than those on main roads. Survival analysis and a Cox proportional hazards model were used to analyze the determinants of incident clearance times. METHODS : Tunnel traffic accidents were categorized into tunnel access sections versus inner tunnel sections according to the point of occurrence. The factors affecting duration were compared between main road and tunnel locations. The Cox model was applied to quantify the effects of various factors on incident duration time by location. RESULTS : Key factors influencing mainline incident duration included collision type, driver behavior and gender, number of vehicles involved, number of accidents, and post-collision vehicle status. In tunnels, the primary factors identified were collision type, driver behavior, single vs multi-vehicle involvement, and vehicles stopping in the tunnel after collisions. Incidents lasted longest when vehicles stopped at tunnel entrances and exits. In addition, we hypothesize that incident duration in tunnels is longer than in main roads due to the reduced space for vehicle handling. CONCLUSIONS : These results can inform the development of future incident management strategies and congestion mitigation for tunnels and underpasses. The Cox model provided new insights into the determinants of incident duration times in constrained tunnel environments compared to open main roads.

PURPOSES : The purpose of this study is to propose a method of quantitative bus deceleration and acceleration time based on automatic vehicle location data generated by a bus operating system. METHODS : The digital tachometer graph (DTG) data of commercial vehicles and the bus departure and arrival time data collected through the Korean bus information system (BIS) were matched and utilized to accurately reflect the deceleration and acceleration position of the bus. It was determined whether the bus arrived (or departed) at bus stations based on the BIS data, and the acceleration and deceleration times were calculated by classifying the bus status section (deceleration-stop-acceleration-driving) based on the DTG speed data. RESULTS : The deceleration and acceleration times calculated using the proposed method were analyzed using the z-test for the bus type and peak and non-peak times. Notably, there was a difference in the acceleration time for each vehicle type. The results were compared with the reference values of TCQSM and the calculated values, and the results were similar. CONCLUSIONS : This study is meaningful in that it conducted basic research on calculating the acceleration and deceleration times by fusing currently available data. In addition, new types of buses that have not been presented in the existing reference values have the advantage of being able to be calculated without a separate investigation if only data are produced according to the current bus management system.