Impacts of Connected Automated Vehicles on Freeway Traffic Patterns at Different Penetration Levels

In this paper we investigate the effects of connected automated vehicles on traffic patterns. We first experimentally study traffic patterns using two connected human-driven vehicles, which are equipped with vehicle-to-vehicle (V2V) communication, and a connected automated vehicle, which is able to respond to V2V information and control its longitudinal motion. Our experimental results indicate the long-range feedback may benefit traffic flow and that car-following models with delay are able to replicate the experimental results. The data fitted models are used in simulations for a 100-car network to study traffic dynamics with partial penetration of connected automated vehicles.