Population-Aware Sequential Flight Path Optimization for Low-Noise and Low-Fuel Consumption Departure Trajectory

With the increase in air traffic over the past decades, the reduction of aircraft noise is one of the major challenges facing stakeholders. Flight operating conditions that decrease noise may possibly increase the fuel consumption of aircraft, which is an important factor in airline cost management. In this paper, we propose a methodology to support flight path planning with the aim of optimizing both perceived noise and fuel consumption. We decompose an aircraft flight trajectory into surface and altitude paths to model relevant air transportation constraints. The shortest path for the surface projection is found using Dubins path method and an improved A ∗ algorithm, which considers guide points according to the flight destination, runway angles, spatial separation of aircraft near the airport, population distribution, and steering motion. The altitude path is optimized for low-perceived noise and low-fuel consumption, which is determined by solving the longitudinal governing equations of motion of flight using the distance computed from this surface path. A modified nondominated sorting genetic algorithm II for discrete optimization is developed to obtain Pareto fronts of the optimum altitude paths with reduced computational effort. The methodology is demonstrated by simulating flights departing from Hong Kong International Airport to two compulsory air-traffic-service reporting points. The results are then compared with Quick Access Recorder data and Standard Instrument Departure (SID) tracks. Although certain factors in air transportation that affect departure path planning, such as weather patterns and air traffic mix, are not considered in this method, the resulting surface path exhibits a close similarity with SID tracks. The resulting Pareto fronts of the altitude path exhibit reductions in fuel consumption and perceived noise levels. The tradeoffs between fuel consumption and perceived noise levels are also discussed based on the relevant flight physics for the different routes. This paper presents a flight path optimization methodology for low-fuel consumption and low-accumulated perceived noise levels along a flight path during departure. The methodology is developed for generating a set of four-dimensional departure paths for an aircraft flying from an airport to the compulsory ATS reporting point, considering flight destination, runway angles, spatial separation near an airport, obstacles, populated regions, and steering, to support the decision-making processes of SID planning, flight planners, and pilots. The developed strategy performs surface path planning and altitude path planning sequentially. The former generates the shortest path consisting of initial and subsequent departure paths. Dubins path is applied to determine the initial departure path satisfying constraints of runway angles and spatial separation directions. The population-aware A ∗ with steering constraints algorithm is developed to perform path planning for the subsequent departure path satisfying constraints pertaining to obstacles, populated regions, and steering motions. Altitude paths are generated by solving the longitudinal governing equations of motion of flight. The accumulated perceived noise level and fuel consumption along the paths are computed using the ANP database and performance parameters obtained from evaluating flight dynamics. The nondominated set of fuel consumption and noise level points of the altitude paths is obtained by applying multi-objective optimization using a modified NSGA-II for discrete optimization. A study is conducted on the path planning for an aircraft similar to a Boeing 777-300ER with GE90-115B engines using the developed methodology in two flight scenarios departing from Hong Kong International Airport (HKIA). The population-aware A ∗ with steering constraints method yields a path with close similarity to the Standard Instrument Departure (SID) tracks and certain Quick Access Recorder (QAR) paths by graphical comparison. The multi-objective optimization results show that the trends of fuel and noise level reductions depend on the altitude at the transition point of upper flight level, Mach number, and altitude at the compulsory ATS reporting point. Furthermore, the optimization yields a small cluster of optimal solutions with less than 120 kg variation in fuel consumption and 0 . 8 dB variation in perceived noise.