Network Flow Dynamics Modeling and Analysis of Arrival Traffic in Terminal Airspace

• Main Authors: Lei Yang, Suwan Yin, Minghua Hu
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Terminal airspace; arrival traffic; network flow modeling; flow dynamics
• Online Access: https://ieeexplore.ieee.org/document/8732445/

This paper reveals and explores the flow dynamics of arrival traffic in a terminal airspace network on both mesoscopic and macroscopic levels in a systematic way from empirical data to dynamics modeling. The existence of link-based typical fundamental diagram (FD) that expresses the fundamental relations of newly defined flow-density-speed and network-based arrival macroscopic fundamental diagram (MFD-A) that represents aggregate demand-supply dynamics is demonstrated using empirical data collected in Guangzhou Terminal Airspace. After establishing heterogeneous FDs for flows along a different route segments using piecewise approximation, a density-speed-based modified cell transmission model (MCTM) is developed to simulate the spatio-temporal evolution of flow and congestion in arrival network for the enhancement of the adaption to non-uniform cell length and unique speed profile in terminal airspace. To further improve the simulation accuracy without compromising computational time, hybrid simulation is designed by deploying a queuing inspector (QI) to MCTM. The proposed network flow model is shown to be an efficient and accurate method capable of capturing the flow evolution at mesoscopic and macroscopic levels and supporting air traffic flow prediction and control. In the end, characteristics of arrival flow dynamics, including hysteresis, critical steady state (CSS), critical unsteady state (CUS), and its acceptable duration are discussed in depth as crucial theoretical parameters for air traffic flow management. This study provides a novel perspective method to model and understand the evolution of air traffic flow, and underpins advanced technical potentials for future air traffic management.