Macroscopic modeling of connected autonomous vehicle platoons under mixed traffic conditions

Abstract

Autonomous vehicles (AV) will be present in freeways, and they will have to share current infrastructure with human driven vehicles. This mixed traffic scenario needs to be planed and managed. Some research points that an AV mismanagement could lead to a capacity decrease. This can be solved with connected AV traveling in platoons. Some research exist to that end, but all of them is done using microsimulation tools. These are very powerful and detailed tools but have the shortcoming of strongly rely on an uncertain calibration and give limited insights to the problem. The more robust and simpler to understand macroscopic tools, have almost no platooning models yet. The research presented in this paper fills the gap, by providing a generalized macroscopic model to estimate the average length in vehicle for platoons. This is done by giving a set of rules for AV to form a platoon, including two different platooning schemes representing the best and worst case scenarios. This is of a key importance as greater platoon length is the main factor to drive capacity improvements on highways, which under the appropriate conditions can exceed 10.000 vehicles per hour and lane.