Modeling the Effect of the Platoon Size of CAVs on Mixed Traffic Flow: A Cellular Automaton Method

Abstract

This study proposes a cellular automaton model incorporating the platoon size of connected automated vehicles (CAVs) to examine their impact on mixed traffic flow. First, vehicles are classified into three modes, human-driven vehicles (HDVs), adaptive cruise control (ACC), and cooperative adaptive cruise control (CACC), by considering the characteristics of the car-following behavior. Second, the CACC is further subdivided into interplatoon and intraplatoon car-following modes due to the limitations of the platoon size of CAVs. Then, cellular automaton rules are developed for each of these four modes. Finally, numerical simulation experiments are conducted to analyze the influence of the penetration rate and platoon size of CAVs on mixed traffic flow. The results demonstrate that (1) the simulation results closely align with the theoretically derived outcomes, with an error rate of only 0.46% at a penetration rate of 100%; (2) when the penetration rate of CAVs reaches 100%, increasing the platoon size further enhances the traffic capacity; and (3) the optimal platoon size is determined to be seven CAVs under moderate traffic density.