Coordination for Connected Automated Vehicles at Merging Roadways in Mixed Traffic Environment

Abstract

In this paper, we present a two-level optimal control framework to address motion coordination of connected automated vehicles (CAVs) in the presence of human-driven vehicles (HDVs) in merging scenarios. Our framework combines an unconstrained trajectory solution of a low-level energy-optimal control problem with an upper-level optimization problem that yields the minimum travel time for CAVs. We predict the future trajectories of the HDVs using Newell's car-following model. To handle potential deviations of HDVs' actual behavior from the one predicted, we provide a risk-triggered re-planning mechanism for the CAVs based on time-to-conflict. The effectiveness of the proposed control framework is demonstrated via simulations with heterogeneous human driving behaviors and via experiments in a scaled environment.Comment: first manuscript, 7 page