PURPOSES : Even when autonomous vehicles are commercialized, a situation in which autonomous vehicles and regular drivers are mixed will persist for a considerable period of time until the percentage of autonomous vehicles on the road reaches 100%. To prepare for various situations that may occur in mixed traffic, this study aimed to understand the changes in traffic flow according to the percentage of autonomous vehicles in unsignalized intersections. METHODS : We collected road information and constructed a network using the VISSIM traffic simulation program. We then configured various scenarios according to the percentage of autonomous vehicles and traffic volume to understand the changes in the traffic flow in the mixed traffic by scenario. RESULTS : The results of the analysis showed that in all scenarios, the traffic flow on major roads changed negatively with the mix of autonomous vehicles; however, the increase or decrease was small. By contrast, the traffic flow on minor roads changed positively with a mix of autonomous vehicles. CONCLUSIONS : This study is significant because it proactively examines and designs traffic flow changes in congested traffic that may occur when autonomous vehicles are introduced.

PURPOSES : The aim of this study was to compare the performance of the QUEENSOD method and the gravity model in estimating Origin-Destination (O/D) tables for a large-sized microscopic traffic simulation network. METHODS : In this study, an expressway network was simulated using the microscopic traffic simulation model, VISSIM. The gravity model and QUEENSOD method were used to estimate the O/D pairs between internal and between external zones. RESULTS: After obtaining estimations of the O/D table by using both the gravity model and the QUEENSOD method, the value of the root mean square error (RMSE) for O/D pairs between internal zones were compared. For the gravity model and the QUEENSOD method, the RMSE obtained were 386.0 and 241.2, respectively. The O/D tables estimated using both methods were then entered into the VISSIM networks and calibrated with measured travel time. The resulting estimated travel times were then compared. For the gravity model and the QUEENSOD method, the estimated travel times showed 1.16% and 0.45% deviation from the surveyed travel time, respectively. CONCLUSIONS : In building a large-sized microscopic traffic simulation network, an O/D matrix is essential in order to produce reliable analysis results. When link counts from diverse ITS facilities are available, the QUEENSOD method outperforms the gravity model.

PURPOSES : This study evaluated the feasibility of implementing protected-permissive left-turn (PPLT) signals at three-leg signalized intersections. METHODS: A three-leg signalized intersection with permissive left-turn was first selected. A VISSIM simulation model was constructed using data collected from the test site. The VISSIM network was calibrated by adjusting related parameter values in order to minimize the difference between the simulated and surveyed critical gap. The calibrated network was validated by the number of waiting left-turning vehicles per cycle. Finally, the mobility and safety measures were extracted from simulation runs in which permissive, protected left turns as well as PPLTs were realized based on diverse traffic volume scenarios. RESULTS : The mobility-related measures of effectiveness (MOEs) of the case with PPLT outperformed the other two left-turn treatment scenarios. In particular, the average waiting time per cycle for the left-turn vehicles in the case with PPLT was reduced by 30 s. The safetyrelated MOEs of the case with PPLT were somewhat higher than those in the case with protected left-turns and much higher than those in the case with permissive left-turns. CONCLUSIONS : Based on the mobility- and safety-related MOEs generated from the VISSIM simulation runs, the use of PPLT seems to be feasible at three-leg signalized intersections where the left-turn is permissive and a pedestrian signal exists at the conflicting approach. However, in order to use the PPLT in earnest, it is necessary to revise the road traffic act, traffic signs, and related manuals.