Modeling and Simulation of Mixed Traffic Flow in Maintenance Operation Zone Considering the Impact of Trucks in an Intelligent Connected Environment

Abstract

With the rapid development of intelligent connected technologies, the introduction of connected and autonomous vehicles (CAVs) into mixed traffic flows of passenger and freight vehicles complicates traffic operations, particularly in sections of expressways where inner lanes are closed for maintenance. Focusing on a scenario of closing the inner lane of a three-lane expressway, this study considers the differences in characteristics and interactive effects between CAVs and human-driven vehicles (HDVs). It integrates road management regulations for maintenance zones and establishes cellular automaton models for car-following and lane-changing behaviors. By varying CAV penetration rates and truck proportions, the study generates fundamental diagrams, space-time diagrams, and lane-changing frequency-density diagrams to quantitatively analyze traffic flow indicators corresponding to different CAV penetration rates and truck proportions. In addition, the study proposes CAV control strategies under the influence of passenger cars and trucks, and compares CAVs with and without control strategies. Finally, it summarizes recommended actions based on the CAV penetration rate threshold. The proposed traffic flow model in a connected mixed environment provides insights for optimizing layout and improving traffic operations in maintenance zones.