Risk-Based UAV Corridor Capacity Analysis above a Populated Area

Abstract

To integrate unmanned aerial vehicles (UAVs) into the national airspace in a safe manner, a risk-based approach to the regulation of UAVs is adopted in many countries. Thus, the capacity to permit UAVs in urban airspace also needs to be evaluated in a risk-based sense. In this regard, this paper proposes a methodology to analyze the capacity of UAV corridors on the basis of third-party risk on the ground. By linking the collision rate of the corridor and the failure rates of UAVs with the number of fatalities on the ground, the capacity of the UAV corridor is derived to satisfy the target level of safety. To model the collision rate of UAVs in the corridor, the Reich collision risk model is utilized. Moreover, a ground risk map is generated to compute the third-party risk on the ground using the databases for Seoul, Korea. The results show that the failure rate of UAVs is the dominant factor for determining the capacity of the corridor, even if the number of corridors increases. The proposed methodology could be useful to manage the number of flights for applications where the UAV corridor is fixed and flight continues, such as package delivery.

Data-Driven Insights into Population Exposure Risks: Towards Sustainable and Safe Urban Airspace Utilization by Unmanned Aerial Systems

“…Based on the above study and the FAA technical report, we added bias parameters (in Equation ( 9)) The above results had a similar pattern to the weight-based approach and the aircraft type-based study [15]. When data were collected from an actual accident or experimental simulation [24], the critical area did indicate a good fit based on vehicle weight. The difference in the two-dimensional probability density estimates of crash location between fixed-wing and multi-rotor aircraft further supports this [13].…”

“…Primatesta [13] generated a risk map through a probabilistic approach using different UAV parameters, uncontrolled descent events, environmental characteristics, and uncertainties on parameters. Kim [24] generated a risk map to compute the third-party risk on the ground, which was used to determine the capacity of the corridor. Pang [25] computed an integrated risk cost mapping for different flight height layers and developed a cost-based path optimization model for reducing the risk cost.…”

A Novel Multi-Layer Framework for BVLoS Drone Operation: A Preliminary Study

“…Their proposed algorithm integrates an RRT technique with Detect and Avoid Alerting Logic. Similarly in [14], authors propose a methodology to analyze the capacity of UAV corridors by linking the collision rate of the corridor and the failure rates of UAVs with the number of fatalities on the ground. Finally, the authors in [15] propose an optimization model to navigate an aircraft to reach its destination by minimizing the maximum threat level and the length of the flight path using a geometric procedure.…”

Parametric Study of Structured UTM Separation Recommendations with Physics-Based Monte Carlo Distribution for Collision Risk Model

“…While no consensus on the concept of operation for UTM has been reached at this time, recent works on UAS separation assurance follow two different ConOps: the free flight with detect and avoid (DAA) that requires some level of autonomy [22][23][24][25], and structured flights on established routes with separation standards [26][27][28]. The latter typically utilizes a Reich-inspired model for separation evaluation with a probabilistic distribution function taken from civil aviation.…”