An Improved Cellular Automata Model for Traffic Flow while Using the Internet of Vehicles

We improved the running rules of the traditional NS model by using the cellular automata, combined with the characteristics of Internet of Vehicles. We were also able to establish the single-lane cellular automata model. To increase the accuracy, we proposed a subdivided cellular automata model to study the impact of randomized moderation probability on traffic flow. Then we established a two-lane lane changing model to study the probability of lane changing. The time- space diagrams, flow-density basic diagrams and velocity-density basic diagrams under different densities are generated through the computer simulation. The results show that, compared with traditional environment, Internet of Vehicles improves vehicle speed and traffic flow under the same density conditions. Also, connected vehicles are more likely to change lanes when the road density is high. Thus transparency of vehicle information can alleviate traffic congestion and improve road capacity.