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Automated vehicles are becoming gradually available in restricted environments and are planned to be available for more challenging situations in the near future. Fully automated vehicles (FAVs) will have no drivers and still need to cooperate and interact with other road users outside the vehicle. In this work we propose an interaction framework, which makes it possible for external users to interfere with the FAV guidance in an abstract level via communicating a desired maneuver. The external user can be assumed as a road participant, who shares drivable areas with the FAV, or an operating person such as delivery person, who wants to guide a delivery vehicle remotely. The application area of this framework is the low velocity range, which can be also assumed as semi-stationary environments. The proposed framework explores the percepted static environment and identifies all possible paths with respect to vehicle dynamics, safety and comfort parameters. These paths are processed in order to build a set of meaningful candidates for the further steps. For this goal we have proposed two different methods based on a modified RRT algorithm and a skeletonization of the freespace. In order to extract possible drivable maneuvers out of the current scene, the candidate paths are assigned to predefined maneuver classes and selected with respect to their length and reasonableness. The set of meaningful and drivable maneuvers will be communicated to the user in form of an abstract and simplified catalogue. With this framework we provide both the FAV and the external user with a mutual understanding about the scene and avoid the possible ambiguity in goal understanding. The proposed framework is validated with sensor data from real scenarios.

An Interaction Framework for a Cooperation between Fully Automated Vehicles and External Users in Semi-stationary Urban Scenarios