Pre-Flight Conflict Detection and Resolution for UAV Integration in Shared Airspace: Sendai 2030 Model Case

Abstract

The increasing demand for services performed by Unmanned Aerial Vehicles (UAVs) requires the simulation of Unmanned Aircraft System Traffic Management (UTM) systems. In particular, Pre-Flight Conflict Detection and Resolution (CDR) methods need to scale to future demand levels and generate conflict-free paths for a potentially large number of UAVs before actual takeoff. However, few studies have examined realistic scenarios and the requirements for the UTM system. In this paper, we focus on the Sendai 2030 model case, a realistic projection of UAV usage for deliveries in one area in Japan. This model case considers up to 21,000 requests for Unmanned Aircraft Systems (UAS) operations over a 13 hour service time, and thus poses a challenge for the Pre-Flight CDR methods. Therefore, we propose an airspace reservation method based on 4DT (3D plus time Trajectories) and map the Pre-Flight CDR problem to a Multi-Agent Path Finding (MAPF) problem. We study first-come first-served (FCFS) and ''batch'' processing of UAS operation requests, and compare the throughput of those methods. We analyze the air traffic topology of deliveries by UAVs, and discuss several metrics to better understand the complexity of air traffic in the Sendai model case. INDEX TERMS Unmanned aircraft system traffic management (UTM), pre-flight conflict detection and resolution (CDR), multi-agent path finding (MAPF), air traffic complexity metrics.

Unmanned Aerial Traffic Management System Architecture for U-Space In-Flight Services

“…Finally, regarding the implementation of particular in-flight services, there are different approaches for conflict resolution and emergency management. Many works [28][29][30] have focused on flight planning and scheduling at a strategic level, i.e., in the pre-flight phase; though in-flight automated decision-making has not been properly covered in UTM systems. In general, given the massive search space to find optimal resolutions for conflicts in Very Low-Level (VLL) airspace scenarios, approximate solutions based on heuristic solvers [28] or lane maneuvers [30] predominate over optimal deconfliction approaches.…”

The Rise of Drones in Internet of Things: A Survey on the Evolution, Prospects and Challenges of Unmanned Aerial Vehicles

“…According to [127], one of the first proposals for a UTM construct -"Internet of Drones" [128] -emphasised the importance of such interdisciplinary approaches by combining best practices in air traffic control networks, cellular networks as well as the internet to devising one of the first UTM constructs in scientific literature. Since then we have witnessed a clear interest in such holistic research as seen in [5], [102], [127], [129]- [136] on UTM systems, in addition to domain-specific research on airspace design in [101], [111], [113]- [120], collision avoidance and risk mitigation in [103]- [106], [137]- [146] and communication and cybersecurity in [96]- [100], [147]- [159] as summarised below in Table 2.…”

A Conflict Risk Analysis of MAV\UAV Flight in Shared Airspace

“…Radmanesh et al generated collision-free 3D trajectories for multiple UAVs operating in shared airspace based on a partial differential equation (PDE) and modeling the porosity values as a function of the risk of conflict [8]. Ho et al used preflight conflict detection, and resolution (CDR) methods generate to conflict-free paths for a potentially large number of UAVs before actual takeoff [9]. Based on the established protect zone, the closest point of approach (CPA) strategy is employed by Shi et al to detect potential conflicts [10].…”