Surveillance-based Risk Assessment Model between Urban Air Mobility and Obstacles

Abstract

Urban Air Mobility is expected to resolve some problems in urban transportation such as traffic congestion and air pollution. Various studies for a large-scale commercialization of UAM are being actively conducted. To that end, the UAM Traffic Management system aims at securing a safety and an efficiency of UAM operations. In this study, a risk assessment model is proposed to evaluate the risk of collision between a vehicle and surrounding obstacles. The proposed model is conceived from the past studies for determining a proper separation distance between parallel runways for their independent operations. The model calculates the risk that the surveillance system fails to meet a target level of safety for a given buffer zone size between a designed route and surrounding obstacles. The model is applied to one of the routes proposed in K-UAM roadmap to evaluate its performances.

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“…Various ATM programs within German Aerospace Center (DLR) initiatives are discussed by the authors in [9]. The authors in [10] propose an assessment model for vehicleobstacle collision hazards. In detail, the authors of the paper [11] discuss cutting-edge Deep Learning techniques for ATM.…”