Use Case Category: Advanced Driving User Story: Complex manoeuvres in cross-border settings Location: Spain-Portugal (ES-PT) cross-border corridor According to 3GPP TS 22.186 R16, Advanced Driving “enables semi-automated or fully-automated driving. Longer inter-vehicle distance is assumed. Each vehicle and/or Road Side Unit (RSU) shares data obtained from its local sensors with vehicles in proximity, thus allowing vehicles to coordinate their trajectories or manoeuvres. In addition, each vehicle shares its driving intention with vehicles in proximity. The benefits of this use case group are safer traveling, collision avoidance, and improved traffic efficiency”. Scenario 2: Automated Overtaking: When an automated vehicle needs to overtake a vehicle that precedes it, additional information provided by communication technologies will drastically improve and complement the information provided by its sensor constellation. There are many situations where the dimensions of other vehicles can cover the field of view of the autonomous vehicle sensors (for example, a truck can reduce the vision of a camera, a laser or a radar sensor). Moreover, according to the route followed by the vehicle, it can happen that a highway exit or a toll is near to the point where the overtaking takes place, and a queue of vehicles can complicate the scenario reducing free space and therefore producing a less appropriate manoeuvre. Other complex scenario can appear when there are vehicles behind the automated vehicles that occludes the vision of rear sensors. Considering that we are driving on a two-lane road with a right-hand traffic regulation, this occlusion can produce that the automated vehicle is not able to perceive a vehicle driving fast in the left lane. The purpose of this use case is to extend the 360º perception layer of the automated vehicle by integrating communication capabilities in the different vehicles of the scenario and additional road sensors (e.g. traffic radars) in the infrastructure. In this way, vehicles will be able to share their positions, speeds, sizes, etc., as well as the road-side infrastructure, helping automated vehicle to understand current situation and thus take the best decision of how to proceed with the automated overtaking.