Abstract
Most of the traditional taxi path planning studies assume that the aircraft is in uniform speed, and the model is optimized based on the shortest taxi time. Although it is easy to solve, it does not consider the change of the speed profile when the aircraft turns, and the optimal taxiing time of the aircraft does not necessarily bring the optimal taxiing fuel consumption. In this paper, the aircraft’s taxi distance and the number of turns in the taxi are considered. The aircraft path planning model with the shortest total distance of the airport surface is established. The improved A ∗ algorithm is used to obtain the shortest path P. Based on this, the shortest path P is established. Considering the multitarget velocity profile model of time and fuel consumption, a heuristic search is used to generate an accurate velocity profile for each path to obtain a 4D trajectory of the aircraft and then quantitative analysis of the impact of aircraft pollutant emissions on the airport environment based on 4D trajectory taxi time. The experimental results show that, compared with the traditional optimization method without considering the turning times, the total taxiing distance and turning times of the aircraft are greatly reduced. By balancing the taxiing time and fuel consumption, a set of Pareto-optimal velocity profiles is generated for the aircraft taxiing path; at the same time, it will help the airport save energy and reduce emissions and improve the quality of the airport environment. It has a high practical application value and is expected to be applied in the real-time air traffic control decision of aircraft surface in the future.
Highlights
With the rapid development of the air transport industry, the flight volume of major airports in China is increasing, which makes the airport surface congested, especially causing the aircraft at the airport surface to take too long to taxi, and the runway entrances are queuing up to wait for the number of departing flights, resulting in the work of controllers being overloaded, which seriously threatens the taxiing safety of the aircraft
In 2015, Weiszer et al [4] proposed an aircraft at the airport surface motion database for the high calculation time requirements of existing speed configuration optimization methods and effectively separated path planning and speed profile generation modules through precalculation to avoid the same repeated optimization of taxiway sections
In 2015, Weiszer et al [5] used a Mathematical Problems in Engineering multiobjective optimization method to solve the comprehensive optimization problem combining runway scheduling and ground motion problems. e proposed evolutionary algorithm is based on an improved congestion distance, taking into account delay costs and fuel prices
Summary
With the rapid development of the air transport industry, the flight volume of major airports in China is increasing, which makes the airport surface congested, especially causing the aircraft at the airport surface to take too long to taxi, and the runway entrances are queuing up to wait for the number of departing flights, resulting in the work of controllers being overloaded, which seriously threatens the taxiing safety of the aircraft. In 2014, Ravizza et al [3] and other researchers studied the path planning of aircraft at the airport surface considering time and fuel consumption and introduced a sequence diagram-based algorithm to solve the problem. In 2015, Weiszer et al [4] proposed an aircraft at the airport surface motion database for the high calculation time requirements of existing speed configuration optimization methods and effectively separated path planning (routing and scheduling) and speed profile generation modules through precalculation to avoid the same repeated optimization of taxiway sections. Due to the turning section of the airport surface, the aircraft’s speed profile changed, resulting in additional taxi time Precise algorithms such as multiobjective optimization take full consideration of various scene constraints, such algorithm models are complex and computationally intensive, and it is generally difficult to obtain the optimal solution in an acceptable time. Compared with other complicated algorithms that consider multiple factors, the calculation speed is faster, from an environmental perspective, and considering the taxi time and thrust changes of the 4D trajectory and the comparison and calculation of the pollutant emissions when the ground aircraft adopts a multitarget speed profile, the accurate multitarget taxi 4D trajectory is more conducive to energy saving and emission reduction has a higher practical application value
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