Investigating the effect of Automated Vehicles and Connected and Automated Vehicles on the capacity of freeways using microscopic simulation

Congestion is one of the problems that has bothered many countries in recent decades and has imposed huge costs on many countries. For this reason, many researchers are looking for ways to reduce congestion in transportation networks. On the other hand, it is predicted that the emergence of Automated Vehicles and Connected and Automated Vehicles can be effective in reducing congestion on the roads and increasing the capacity of the roads. For this reason, this study investigates the effect of Automated Vehicles and Connected and Automated Vehicles on the capacity of roads. In this study, a freeway network with the Merge section is used and the simulations are implemented using SUMO microscopic simulator software. In this study, to determine the driving behavior, the car following model for longitudinal movements and the lane changing model for lateral movements have been used. The Krauss car-following model and the LC2013 lane-changing model were used to determine driving behavior in this study. The simulation results show that Automated Vehicles can increase road capacity by up to 52% and Connected and Automated Vehicles can increase road capacity by up to 65%, which indicates the potential of these vehicles to increase capacity and reduce congestion. The results also show that these vehicles can have a significant impact on capacity when the presence of these vehicles on the road is significant.