Analysis of vehicle headway distribution on multi-lane freeway considering car–truck interaction

Abstract

The primary objective of this study is to identify the characteristics of vehicle headway on multi-lane freeway under lane management in China considering car–truck interaction. More specifically, the study focused on answering the following two questions: (1) whether the car–truck interaction has impact on headway, that is, headway varies by different leading and following vehicle types and (2) what is the best-fitted distribution model for particular headway type under lane management. The team collected traffic data, including traffic flow rates, percentage of trucks, speeds, headways, and so on from four segments of Shanghai-Nanjing freeway, Jiangsu Province in China. Then, some statistical methods were used to analyze the vehicle headway. It was found that car–car, car/truck, and truck–truck headways are significantly different from each other. Also, the traffic flow rate, percentage of trucks, and lane position were found to have an influence on the vehicle headway through the tests. Using the maximum-likelihood estimation, Kolmogorov–Smirnov test, and chi-square test techniques, the distribution models and parameter functions for each headway type were built and validated. The results showed that lognormal model is suitable for car–car and truck–truck headway types, and inverse Gaussian model fits the car/truck headway type well.