Article Contents
Article Contents

# Traffic flow modeling and optimization control in the approach airspace

• *Corresponding author: Xiaoqiong Huang

The first author is supported by "Civil Aviation University of China Open Fund of CAAC Key Laboratory of Civil Aviation Wide Surveillance Safety Operation Management & Control Technology (NO:202103)", "Full-time postdoctoral R&D fund (NO:2021SCU12048)"and"Sichuan Science and Technology Program (NO:2022YFG0180)"

• Air traffic control behaviors in civil aviation approach airspace include arrival time control, aircraft sequencing and aircraft diversion. In the airspace with heavy air traffic flow, air traffic controllers need to make the best decision for multiple flights in a given space and time range. The topic of this paper is the optimization in civil aviation approach airspace. In this paper, the flight operation involves multiple different resource, and the flight path selection is reset based on the given flight constraints to optimize the objective function. This paper presents an optimal decision model for controlling the flight flow in the approach airspace. The performance of the model is evaluated in different simulation scenarios.

Mathematics Subject Classification: Primary: 90B06; Secondary: 90B20.

 Citation:

• Figure 1.  Simplified configuration of the approach airspace

Figure 2.  The altitude profiles and speed profiles of departures

Table 1.  Assessment of various configurations for case 1

 Approach Prediction horizon/min I-1 I-2 I-3 S-1 S-2 S-1 S-2 S-1 S-2 M1 / 1.35 1.33 1.41 1.38 1.37 1.35 M2 2 1.23 1.21 1.30 1.29 1.35 1.33 4 1.19 1.18 1.28 1.26 1.32 1.29 6 1.18 1.16 1.27 1.24 1.31 1.28 8 1.15 1.13 1.26 1.23 1.28 1.25 10 1.14 1.12 1.24 1.20 1.26 1.23 M3 2 1.08 1.07 1.18 1.17 1.24 1.20 4 1.06 1.05 1.16 1.14 1.22 1.19 6 1.05 1.04 1.10 1.09 1.20 1.18 8 1.03 1.02 1.08 1.07 1.17 1.15 10 1.02 1.00 1.05 1.00 1.15 1.00

Table 2.  Assessment of various configurations for case 2

 Approach Prediction horizon/min Total deviations Total aircraft number S-1 S-2 S-1 S-2 M1 / 1.36 1.34 1.47 1.46 M2 2 1.34 1.30 1.44 1.43 4 1.31 1.29 1.43 1.42 6 1.28 1.27 1.41 1.40 8 1.25 1.24 1.40 1.39 10 1.24 1.22 1.36 1.33 M3 2 1.21 1.20 1.33 1.31 4 1.19 1.17 1.30 1.28 6 1.16 1.15 1.27 1.25 8 1.14 1.13 1.24 1.22 10 1.12 1.00 1.21 1.00

Table 3.  Assessment of various configurations for case 3

 Approach Prediction horizon/min (I-1, I-2) (I-1, I-3) (I-2, I-3) M1 / (1.33, 1.34) (1.29, 1.33) (1.29, 1.31) M2 2 (1.27, 1.29) (1.26, 1.31) (1.26, 1.27) 4 (1.22, 1.25) (1.23, 1.28) (1.23, 1.24) 6 (1.20, 1.24) (1.21, 1.25) (1.21, 1.21) 8 (1.19, 1.21) (1.19, 1.23) (1.18, 1.20) 10 (1.17, 1.18) (1.18, 1.20) (1.16, 1.18) M3 2 (1.14, 1.16) (1.16, 1.17) (1.15, 1.17) 4 (1.09, 1.13) (1.13, 1.14) (1.12, 1.11) 6 (1.08, 1.11) (1.10, 1.11) (1.09, 1.10) 8 (1.05, 1.07) (1.07, 1.09) (1.06, 1.08) 10 (1.02, 1.03) (1.04, 1.06) (1.05, 1.04)
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