Impacts of Connected Automated Vehicles on Large Urban Road Network

As an essential component of the Cooperative Intelligent Transportation System (C-ITS), Connected Automated Vehicles (CAVs) are anticipated to play a significant role in the development of the future mobility service. This paper investigates the impacts of different penetration of CAVs on the urban road network. The investigation is carried out in a vast urban network with Simulation of Urban MObility (SUMO), a microscopic traffic simulator. The estimated factors of the network are network maximum flow, critical density, average speed, congestion duration, and roadway over-saturation degree. The Macroscopic Fundamental Diagram (MFD) has been used to estimate the maximum flow and critical density. In a simulation way, it substantiated that a road network could have less scattered MFDs, even if the traffic flow is distributed heterogeneously. The congestion duration and over-saturation degree are used to check traffic congestion. The simulation results show that applying 100% CAVs can contribute about a 13.55% increase in maximum flow. A similar trend can be found in the critical density for different CAV penetration rates. In a similar congestion situation, the network with 100% CAV driving in can carry more than 130% of the original travel demand. In terms of congestion level, even a low CAV penetration rate may significantly improve the traffic condition.