Analyzing start-up time headway distribution characteristics at signalized intersections

Abstract

Time headway distributions play an important role in analyzing driver behavior prediction, road service evaluation, traffic state estimation, et al. Thus, less attention was paid on the start-up time headway distributions at urban signalized intersections. To bridge the gap, we proposed a novel framework with three-parameter burr model and log-logistic distribution model to analyze vehicle start-up time headway distribution characteristics at signalized intersections. First, we collected a large amount of start-up time headway samples at the signalized intersection located at Guangzhou city in China. Second, all the vehicle start-up sample data have been processed and analyzed with three-parameter Burr model and log-logistic distribution curves. Third, we explored vehicle start-up time headway distribution characteristics by considering and regard less of queuing positions. Last but not least, we have applied our model to analyze saturated time headway distributions, and estimate minimum green time for vehicle queues passing through intersections. The findings of our research can help transport authorities set more reasonable green time at intersections, and improve urban transportation commuting efficiency.