Multi-runway airport hot spot recognition method based on Monte Carlo simulation

Abstract

Abstract: The runway and taxiway systems of large airports are becoming more and more complex. For the newly built airport, it is difficult to find the hot spots due to the lack of historical operational data. Aiming at the identification of taxiing hot spots in multi-runway airports, a fast identification method based on Monte Carlo simulation is proposed. Firstly, the ground network model of airport flight area is modeled using Dijskra algorithm to determine the set of Q shortest paths between any current node in the airport ground network and the runway entrance or parking area. Then, the traffic flow and aerodrome control rules are modeled, identifying the hot spots of multirunway airport via Monte Carlo simulation. Taking the double runway “West Takeoff and East Landing”,operation of Changsha Huanghua Airport as an example, the simulation result and published taxiing hotspots in AIP CAAC are compared, verifying the validity of the proposed approach.

Key words: multi-runway airport, hot-spot identification, Monte Carlo simulation, shortest path, Dijskra algorithm

CLC Number:

V352

MENG Linghang, TIAN Chuan. Multi-runway airport hot spot recognition method based on Monte Carlo simulation[J]. Journal of Civil Aviation University of China, 2020, 38(3): 8-11.

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