Research On 4-Dimensional Trajectory Based Airport Ground Movement Guidance And Control Technologies

The airport plays an important role in the air transportation system,and also serves as the key link connecting the en route and ground traffic.With the continuous increase of air traffic demand,traditional airport surface operations show major drawbacks such as large uncertainty and low resource utilization,which lead to more and more congestions on the airport surface.Driven by the Advanced Surface Movement Guidance and Control System and the Airport Collaborative Decision Making technologies,more precise 4-dimensional taxiing trajectories based surface operations are becoming the new development direction.Based on an in-depth analysis of the existing research,this paper makes a systematic study on the problems involved in the four-dimensional taxiing trajectory planning and execution stages.It proposes a set of conflict-free full 4-dimensional taxiing trajectory generation method,develops a simulation system to evaluate the 4-dimensional trajectory following errors and verify its feasibility for guidance,and extends the trajectory surveillance and disruption recovery methods.First,a conflict-free time-based taxiing route search method is proposed.Time-based taxiing route imposes control point arrival time constraints upon the conventional taxiing route,which provides the basis for full 4-dimensional trajectory generation.To avoid the uncertainty of the node-segment taxiway model,the proposed method keeps the taxiway central line structures within intersections based on virtual zone division,and further abstract the zone division model to enhance route search efficiency.To generate conflict-free,efficient and fluent route,the proposed method uses time windows upon taxiway zones to avoid conflicts,minimizes the taxi time to improve ground movement efficiency,and introduces the maximum traversal time constraint to reduce waiting time during taxiing.A search algorithm based on the principle of A* is proposed,which introduces the arrival time window and dominance rule to find the best route satisfying all the requirements.The proposed algorithm also provides a general solution for the shortest path problem with time windows and the maximum traversal time constraint.Second,to generate full conflict-free 4-dimensional taxiing trajectory,an online speed profile generation method based on the time-based taxiing route is proposed.According to the characteristic of the time-based taxiing route with control point arrival time requirement,the proposed method takes the road section within each zone as the elementary unit to formulate a nonlinear optimization model for online speed profile generation.This avoids the limitation of the existing offline speed profile generation approach in handling the control point arrival time requirement.A real-time solution algorithm is developed for the nonlinear optimization model following the framework of matheuristics.The solution algorithm uses linear programming,metaheuristic and enumeration algorithm,respectively,to determine the exact control point arrival time,speed and detailed acceleration/deceleration phase between control points.Nonlinear optimization algorithms are utilized to further improve the solution quality,which eliminates the overshoots on the initial feasible speed profile.Experimental results on datasets with different airport layouts and traffic densities demonstrate the capability of the proposed method to generate efficient and fuel-saving speed profiles online.Third,a simulation study for 4-dimensional taxiing trajectory based guidance is proposed.A following-the-greens guidance simulation system is constructed using control theoretic models.A proportional-integral-derivative controller is designed to dynamically calculate the position of the navigation lamp that should be lighted.An experimental test is conducted using departing and arriving data upon a typical airport layout.The conflict-free time-based taxiing route search and online speed profile generation methods are integrated to provide conflict-free 4-dimensional taxiing trajectories required by the simulation system.To reflect pilot driving behavior diversity,different pilot reaction times are produced using the Monte Carlo method.Based on the experimental results,the guidance error with different navigation lamp control approaches,and the taxiing conflicts and fuel consumption under different error levels are analyzed,which preliminarily verify the feasibility of conflict-free 4-dimensional taxiing trajectories in the guidance stage,and provide effective feedback for the generation of more robust 4-dimensional taxiing trajectories.Fourth,a surface surveillance video based ground movement trajectory monitoring method is proposed.To calibrate the camera,the proposed method utilises geometric features in the surveillance video to calculate two vanishing points on the airport surface,which are further utilized to determine the vanishing point in the vertical direction and the focal length of the camera.Considering the static background characteristic of the surveillance video,the proposed method determines the position of moving targets in the image through background subtraction and motion region merging.Considering the low-angle characteristic of the surveillance video,the proposed method uses feature point detection,tracking and trajectory clustering to differentiate moving targets,projects the feature point trajectories into the three dimensional space based on the calibration results,and estimates the speeds of the moving targets according to the heights of the feature points.Real world airport surface surveillance videos are utilized to verify the feasibility of the proposed trajectory monitoring method.Fifth,a mixed integer programming based airport ground movement disruption recovery method is proposed.In case the planned taxiing routes of aircraft become infeasible due to disruptive events,the proposed method would adjust the planned routes in a global optimal approach,and bring the ground movements back into order.This avoids the adverse impact on the follow-up operations as is inherent to the existing route adjusting methods based on local priority exchange.Taking advantage of the complex constraint and objective function modeling capability of mixed integer programming,the proposed method constructs the routing and conflict avoidance constraints under the impact of disruptive events to realize conflict-free route adjustment.At the same time,it minimizes the taxiing time and the destination arrival time and route changes,to reduce the impact on the ground movement efficiency and other surface operations.To meet the calculation time requirement in the dynamic environment,a group based iterative conflict avoidance solution approach is proposed.Simulation results with typical disruptive events demonstrate the effectiveness of the proposed method.