Scenario-Tree Model Predictive Control for Vehicle Interactions in Highway Setting

In this letter, we present a modeling and control design framework for modeling and influencing the drivers' decisions in highway scenarios using one or more vehicles as actuators. Our approach relies on a driver's decision-making model that is used to design a scenario-tree model predictive controller, which calculates acceleration and lane change commands for a set of controlled vehicles. We illustrate our modeling and control framework in a two-lane highway example, with two vehicles, one autonomous and one human-driven. Results from numerical simulations demonstrate how our approach can efficiently influence the lane changes of one vehicle using the other as a control actuator.