A Causal Model for Safety Assessment Purposes in Opening the Low-Altitude Urban Airspace of Chinese Pilot Cities

Abstract

China has been gradually relaxing its ban on the use of low-altitude airspace across the country. To guarantee the high reliability of air traffic management (ATM), conflict detection and conflict resolution (CDR) approaches are indispensable to maintain safe separation between neighbouring small fixed-wing aircraft. In this study, we analyse a temporal and spatial integrated strategy for safety assessment purposes in opening the low-altitude urban airspace of Chinese pilot cities. First, we present a detailed mathematical description of the proposed algorithms based on a spatial grid partitioning system (SGPS). For our system, a conflict detection (CD) algorithm is designed to determine if two trajectories pass through the same grid space within overlapping time windows. A conflict resolution (CR) algorithm integrates a proposed time scheduling-based technique (TST) and vertical change-based technique (VCT), which operate under predetermined basic principles. Then, based on our novel CDR algorithms, a causal model is constructed in graphical modelling and analysis software (GMAS) to generate a state space that can provide a global perspective on scenario dynamics and better understanding of induced conflict occurrences. Finally, simulation results demonstrate that the proposed approach is practical and efficient.