INTEGRATED ALGORITHM FOR COMPILINGAND ASSESSMENT OF DIRECT ROUTES RESTRICTIONS IN FREE ROUTE AIRSPACE OF UKRAINE

The article describes the principles of acceptability assignment for direct routes restrictions in free route airspace of Ukraine for publication in Route Availability Document and further use by the Integrated Initial Flight Plan Processing System of Eurocontrol. The algorithms of correct generation of direct routes restrictions for the selected issues in a horizontal and vertical plane were proposed. As a main decision criteriafor these algorithms were chosen the shortest distance to the state boundary (in a horizontal plane) and space attitude (location) of aircraft (in avertical plane).

Surveys of Large Waterfowl and Their Habitats Using an Unmanned Aerial Vehicle: A Case Study on the Siberian Crane

Waterfowl surveys, especially for endangered waterfowl living in wetlands, are essential to protect endangered waterfowl and to create a management scenario of their habitats. Unmanned aerial vehicles (UAVs) are powerful new tools for waterfowl surveys. In this paper, we propose one method for a habitat survey and another for a waterfowl species distribution survey. The habitat survey method obtained the waterfowl’s habitat and spatial distribution with a UAV automatic flight plan in the aggregation area. The waterfowl species distribution survey was used to detect and identify waterfowl species with high-spatial-resolution images from a free UAV flight plan in the aggregation area or areas where individuals were suspected to be present. The UAV-based data showed not only the area where waterfowl were found, but also additional ground surveys. The results showed that the species and locations of the waterfowl were recorded more accurately and efficiently using the distribution method based on the images from the UAV. The waterfowl habitat type and the number of waterfowl were obtained in detail using the habitat survey method. UAV-derived counts of waterfowl were greater (+37%) than ground counts. The results indicated the feasibility and advantages of using a low-cost UAV survey of large waterfowl in wetland regions with complex vegetation. This study provides one case study of large waterfowl numbers and habitat surveys. The UAV-based methods also provide a feasible and scientific way to obtain basic data for the protection and management of waterfowl.

New flight plan optimisation method utilising a set of alternative final point arrival time targets (RTA constraints)

This study investigates a new aircraft flight trajectory optimisation method, derived from the Non-dominated Sorting Genetic Algorithm II method used for multi-objective optimisations. The new method determines, in parallel, a set of optimal flight plan solutions for a flight. Each solution is optimal (requires minimum fuel) for a Required Time of Arrival constraint from a set of candidate time constraints selected for the final waypoint of the flight section under optimisation. The set of candidate time constraints is chosen so that their bounds are contiguous, i.e. they completely cover a selected time domain. The proposed flight trajectory optimisation method may be applied in future operational paradigms, such as Trajectory-Based Operations/free flight, where aircraft do not need to follow predetermined routes. The intended application of the proposed method is to support Decision Makers in the planning phase when there is a time constraint or a preferred crossing time at the final point of the flight section under optimisation. The Decision Makers can select, from the set of optimal flight plans, the one that best fits their criteria (minimum fuel burn or observes a selected time constraint). If the Air Traffic Management system rejects the flight plan, then they can choose the next best solution from the set without having to perform another optimisation. The method applies for optimisations performed on lateral and/or vertical flight plan components. Seven proposed method variants were evaluated, and ten test runs were performed for each variant. For five variants, the worst results yielded a fuel burn less than 90kg (0.14%) over the ‘global’ optimum. The worst variant yielded a maximum of 321kg (0.56%) over the ‘global’ optimum.

Remote Geotechnical Evaluation of Rights of Way of Hydrocarbon Transmission Lines

Due to the health emergency currently affecting the planet, it has been impossible for engineering specialists to carry out direct inspections of the land. During this time, it has been necessary to develop techniques and procedures that allow engineers to obtain information from the land remotely. Here, they are supported by the technology that allows them to record images remotely via drones and communicate so they can perform inspections by auxiliary field personnel, directed at a distance by specialists. To do this, a preliminary flight plan is defined, based on the experience and knowledge of the terrain by the specialist and the visual of the drone is transmitted via the Internet from a PC in the field. Later, which images to record and the sites that require more detail or a direct inspection by the field assistant are defined. Finally, the field assistant transmits the images of the inspection. In this way, the specialist’s training and experience, the operational ease of the drone, and the skill of the field staff are taken advantage of. This article details the procedure for remote inspection, and ways in which it can even be extended to corridor recognition tasks to define the layout of rights of way.

DEVELOPMENT AND ANALYSIS OF 2D FLIGHT PLANNING SEARCH ENGINE CONSIDERING FUSION OF SWIM DATA

Flight planning is one of the essential factors of the airline operation. The selection of routes will determine the economic value of the flight. However, some conditions may prevent the flight to use the most optimum route due to airspace restriction or weather condition. The research aims to develop a search engine program that uses dynamic flight parameters that considers fusion of System Wide Information Management (SWIM) data including weather data and NOTAM to produce the most optimum route in 2D flight planning. The Dijkstra’s pathfinding is implemented in Python programming language to produce the flight plan. The navigation data used is enroute airway in Indonesian FIR regions. The scenario used is a flight from Jakarta to Makassar with duration of 2 hours flight with considering the effect of restricted airspace and weather blockage during in-flight. The study also uses the optimum route produced by the algorithm to be compared with the possible alternate routes to define how optimum the route is. Adding a restricted airspace parameter will result in a new optimum flight plan that able avoids the airspace and the most minimum distance. The effect of external wind parameter could influence the optimum route which may vary depends on the speed of the wind.

New flight trajectory optimisation method using genetic algorithms

This paper presents a new flight trajectory optimisation method, based on genetic algorithms, where the selected optimisation criterion is the minimisation of the total cost. The candidate flight trajectories evaluated in the optimisation process are defined as flight plans with two components: a lateral flight plan (the set of geographic points that define the flight trajectory track segments) and a vertical flight plan (the set of data that define the altitude and speed profiles, as well as the points where the altitude and/or speed changes occur). The lateral components of the candidate flight plans are constructed by selecting a set of adjacent nodes from a routing grid. The routing grid nodes are generated based on the orthodromic route between the flight trajectory’s initial and final points, a selected maximum lateral deviation from the orthodromic route and a selected grid node step size along and across the orthodromic route. Two strategies are investigated to handle invalid flight plans (relative to the aircraft’s flight envelope) and to compute their flight performance parameters. A first strategy is to assign a large penalty total cost to invalid flight profiles. The second strategy is to adjust the invalid flight plan parameters (altitude and/or speed) to the nearest limit of the flight envelope, with priority being given to maintaining the planned altitude. The tests performed in this study show that the second strategy is computationally expensive (requiring more than twice the execution time relative to the first strategy) and yields less optimal solutions. The performance of the optimal profiles identified by the proposed optimisation method, using the two strategies regarding invalid flight profile performance evaluation, were compared with the performance data of a reference flight profile, using identical input data: initial aircraft weight, initial and final aircraft geographic positions, altitudes and speed, cost index, and atmospheric data. The initial and final aircraft geographic positions, and the reference flight profile data, were retrieved from the FlightAware web site. This data corresponds to a real flight performed with the aircraft model used in this study. Tests were performed for six Cost Index values. Given the randomness of the genetic algorithms, the convergence to a global optimal solution is not guaranteed (the solution may be non-optimal or a local optima). For a better evaluation of the performance of the proposed method, ten test runs were performed for each Cost Index value. The total cost reduction for the optimal flight plans obtained using the proposed method, relative to the reference flight plan, was between 0.822% and 3.042% for the cases when the invalid flight profiles were corrected, and between 1.598% and 3.97% for the cases where the invalid profiles were assigned a penalty total cost.