An Agent-Based Cellular Automata Model for Urban Road Traffic Flow Considering Connected and Automated Vehicles

Considering the development of the vehicle to vehicle (V2V) technology and the popularisation of connected and automated vehicles (CAVs), for an extended period, urban roads will be in a mixed traffic flow scene where CAVs and human-driven vehicles (HDVs) coexist. This paper uses an agent-based cellular automata model to establish a micro-traffic simulation framework for urban roads, called the ABCA-MS model. Considering the characteristics of the intermittent flow of urban roads and signal light control, corresponding car-following and lane-changing rules are established and applied to simulate mixed traffic flow containing CAVs. The simulation results show that the traffic efficiency and the permeability of CAVs show a positive correlation; under the given traffic volume condition, the critical CAVs penetration rate for a traffic state change from congestion to unblocked is 0.4. When the penetration rate of CAVs is in the range of 0–0.4, the improvement of road traffic efficiency is the most significant, and the effect of improvement gradually slows down with the increase of CAVs penetration. Even with a low penetration rate of CAVS, the road capacity can be effectively improved, and the traffic pressure can be alleviated.