I. Introduction
A world-wide increase of urbanizations together with the necessity to connect these growing cities to their surroundings initiates an interest in utilizing Unmanned Aerial Vehicles (UAV) as a possible carrier of cargo and Urban Air Mobility (UAM) vehicle for passenger transport in urban areas. Projected scenarios involve several thousands of air vehicles sharing the urban airspace [1][2]. Further, it is estimated that a large number of unmanned aerial systems will also participate in the airspace with applications like parcel delivery or medical supplies. SESAR’s study on the increasing number of drones predicts a European fleet of over 8 million by 2050. Among these more than 500,000 drones will be of commercial applications [3]. It is foreseen that such an increase in traffic will require an unmanned traffic management (UTM) [4], for example, the European U-space [5]. In most more complex UTM-systems a conflict detection (CD) or a conflict detection and resolution (CDR) system at tactical or safety-net level is needed to, for example, include unforeseen participants like rescue helicopters, or to allow for dynamically changing demands. This tactical conflict detection may either be accomplished by external monitoring services or by on-board sensors. In any case a definition of a safe area around each vehicle is required in order to enable both, strategic planning and tactical de-conflicting. CDR methods have been investigated in many contexts resulting in a rich pool of terminology. For example, the idea of "remain well-clear" (RWC) in manned and unmanned aviation [6] is closely linked to the question. Here, a "well-clear violation" (WCV) would describe conditions in which a conflict is described to be dangerous by the terms of the given application. In a broader sense, computation of well-clear volumes and corresponding violations can be seen as a special case of CD.