A numerical model for impacts of left-turn non-motorized vehicles on through lane capacity metrics
There is a conflict between through motor vehicles and the left-turn non-motorized vehicles, and the capacity of straight-line motor vehicles decreases. This study analyzes the impacts of left-turn non-motorized vehicles on the capacity of through motor vehicle lanes. A correction coefficient model for calculating the reduced capacity of through motor vehicle lanes has been developed based on analysis of the conflicting points at an intersection and the negative exponential function of traffic flow distribution. With consideration of intersection geometric design, channelization, and traffic characteristics, the correction coefficient model was further enhanced by regression to capture the impacts of left-turn non-motorized vehicles from the same and the opposite directions. A simulation with VISSIM is used to validate the developed model. It shows that the calculated capacity from the correction coefficient model is close to the simulation results. The experiment indicates that the derived model is highly accurate in calculating the capacity of through motor vehicle lanes and has potential application for situations of mixed traffic in China. The study shows that the capacity of a through traffic lane at the permitted phase decreases with the increase of left-turning non-motorized vehicles, and the impact of left-turning non-motorized vehicles from the same direction is more significant. The results show that the traffic capacity of straight-line motor vehicle decreases with the increase of the left-turn non-motorized vehicles flow rate and the influence of the left-turn non-motor vehicle is more obvious. It is suggested that in practice, the correction coeffi-cient of non-motor vehicle on the left turn should be 0.88, and the correction coefficient on the left turn should be 0.95, respectively. The study recommends coefficient values for both non-motorized vehicles from the same and opposite directions for use in real applications.