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.
[1]
Jun Chen,et al.
A real-time Active Routing approach via a database for airport surface movement
,
2015
.
[2]
Edmund K. Burke,et al.
A more realistic approach for airport ground movement optimisation with stand holding
,
2013,
Journal of Scheduling.
[3]
Jun Chen,et al.
Preference-Based Evolutionary Algorithm for Airport Runway Scheduling and Ground Movement Optimisation
,
2015,
2015 IEEE 18th International Conference on Intelligent Transportation Systems.
[4]
Nan Li,et al.
A Study on the Strategy for Departure Aircraft Pushback Control from the Perspective of Reducing Carbon Emissions
,
2018
.
[5]
Edmund K. Burke,et al.
An online speed profile generation approach for efficient airport ground movement
,
2018,
Transportation Research Part C: Emerging Technologies.
[6]
Edmund K. Burke,et al.
Toward a More Realistic, Cost-Effective, and Greener Ground Movement Through Active Routing: A Multiobjective Shortest Path Approach
,
2016,
IEEE Transactions on Intelligent Transportation Systems.