A tractable interaction model for trajectory planning in automated driving

This paper presents an efficient model for combining automotive trajectory planning with predicted environment interactions, named progressively interacting trajectories (PITRA). It allows to plan trajectories for fully-automated vehicles by actively considering how other traffic participants will react to the trajectory, while retaining many of the advantages of variational trajectory optimization methods, in particular expressiveness and ease of computation. This enables maneuvers such as proactively claiming a gap during a lane change in dense traffic, which is impossible to model in classical variational models. The PITRA approach does not rely on a specific prediction model, but can be used in combination with a wide range of existing models. Its model assumptions and limitations are derived theoretically and demonstrated in several realistic scenarios.