Statistical Modeling of Time Headway on Urban Roads: A Case Study in Baghdad

Abstract

Time headway is an important feature of traffic engineering, determined by measuring the time elapsed between successive vehicles crossing a point on the road. This paper proposes a time headway modeling of urban roads for each lane of the selected sites based on headway distribution. The study was conducted in the capital of Baghdad, Iraq. The Mohamed Al-Qassim and Qanat Al-Jaish highways were chosen to collect field headway data. Data were obtained using image processing and Python for video analysis. Each road consisted of six lanes divided into three lanes in each direction. The three lanes were studied in the forward movement of both highways. Seven flow rates were considered for the headway data to evaluate the flow state for each lane. The EasyFit 5.5 software was used to select an appropriate headway distribution for each flow rate, using a method depending on the Kolmogorov Smirnov test for each lane. The results demonstrated that the proper model per lane was different. The selected distributions were used to develop a model through nonparametric regression using Theil's slope estimator method.