scholarly journals A Discrete-Continuous Algorithm for Free Flight Planning

Algorithms ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 4
Author(s):  
Ralf Borndörfer ◽  
Fabian Danecker ◽  
Martin Weiser
Keyword(s):  
Newton Method ◽  
Continuous Optimization ◽  
Optimal Choice ◽  
Flight Path ◽  
Second Step ◽  
Free Flight ◽  
Crossover Point ◽  
Flight Planning ◽  
Discrete Approach ◽  
Enhanced Resolution

We propose a hybrid discrete-continuous algorithm for flight planning in free flight airspaces. In a first step, our discrete-continuous optimization for enhanced resolution (DisCOptER) method computes a globally optimal approximate flight path on a discretization of the problem using the A* method. This route initializes a Newton method that converges rapidly to the smooth optimum in a second step. The correctness, accuracy, and complexity of the method are governed by the choice of the crossover point that determines the coarseness of the discretization. We analyze the optimal choice of the crossover point and demonstrate the asymtotic superority of DisCOptER over a purely discrete approach.

Designated Points-based Free-Flight Approach to Enable Real-Time Flight Path Planning

2021 ◽  
Author(s):  
Jung-Hyun Kim ◽  
Simon I. Briceno ◽  
Cedric Y. Justin ◽  
Dimitri Mavris
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Flight Path ◽  
Free Flight

scholarly journals Using Genetic Algorithms for Navigation Planning in Dynamic Environments

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Ferhat Uçan ◽  
D. Turgay Altılar
Keyword(s):  
Fuel Consumption ◽  
Dynamic Environment ◽  
Dynamic Environments ◽  
Flight Path ◽  
Main Concern ◽  
Planning Problem ◽  
Process Unit ◽  
Flight Planning ◽  
Air Vehicle ◽  
Navigation Planning

Navigation planning can be considered as a combination of searching and executing the most convenient flight path from an initial waypoint to a destination waypoint. Generally the aim is to follow the flight path, which provides minimum fuel consumption for the air vehicle. For dynamic environments, constraints change dynamically during flight. This is a special case of dynamic path planning. As the main concern of this paper is flight planning, the conditions and objectives that are most probable to be used in navigation problem are considered. In this paper, the genetic algorithm solution of the dynamic flight planning problem is explained. The evolutionary dynamic navigation planning algorithm is developed for compensating the existing deficiencies of the other approaches. The existing fully dynamic algorithms process unit changes to topology one modification at a time, but when there are several such operations occurring in the environment simultaneously, the algorithms are quite inefficient. The proposed algorithm may respond to the concurrent constraint updates in a shorter time for dynamic environment. The most secure navigation of the air vehicle is planned and executed so that the fuel consumption is minimum.

In-Flight Planning and Intelligent Pilot Aids for Emergencies and Non-Nominal Flight Conditions Using Automatically Generated Flight Plans

2007 ◽  
Vol 51 (2) ◽  
pp. 55-59 ◽  
Author(s):  
Vittesh V. Kalambi ◽  
Amy R. Pritchett ◽  
Daniel P. J. Bruneau ◽  
Mica R. Endsley ◽  
David B. Kaber
Keyword(s):  
Real Time ◽  
Performance Measures ◽  
Time Of Flight ◽  
Environmental Information ◽  
Flight Path ◽  
Path Generation ◽  
Flight Planning ◽  
Flight Plan ◽  
Direct Route

The following study examined pilots' performance on in-flight planning tasks in non-nominal and emergency conditions using autoflight systems capable of automatically generating a flight plan. The findings revealed that autoflight systems did not significantly impact replanning, while the scenarios did significantly affect the primary performance measures of distance flown and time of flight. Additionally, pilots selected the most direct route when possible and did not distinguish between emergency and non-nominal flight conditions. Pilots also favored use of the automatically generated flight plans. We conclude that: 1) automatic flight path generation benefits in-flight replanning primarily by reducing workload in emergencies; and 2) such a system will require real time access to environmental information, including traffic, weather and terrain, be considered simultaneously.

Agent-Based Approach to Free-Flight Planning, Control, and Simulation

2009 ◽  
Vol 24 (1) ◽  
pp. 14-17 ◽  
Author(s):  
Michal Pechoucek ◽  
David Sislak
Keyword(s):  
Free Flight ◽  
Agent Based ◽  
Flight Planning

Implementation of a “threat and error” model in complex neonatal cardiac surgery patients to identify quality improvement opportunities

2020 ◽  
Vol 30 (6) ◽  
pp. 860-865
Author(s):  
Deanna R. Todd Tzanetos ◽  
Vicki Montgomery ◽  
William Harrington ◽  
Aaron Calhoun
Keyword(s):  
Cardiac Surgery ◽  
Quality Improvement ◽  
Review Process ◽  
Patient Care Team ◽  
Unintended Consequences ◽  
Adverse Outcomes ◽  
Flight Path ◽  
Free Flight ◽  
Multidisciplinary Meetings ◽  
Neonatal Cardiac Surgery

AbstractIntroduction:Neonates undergoing surgery for congenital heart disease are vulnerable to adverse events. Conventional quality improvement processes centring on mortality and significant morbidity leave a gap in the identification of systematic processes that, though not directly linked to an error, may still contribute to adverse outcomes. Implementation of a multidisciplinary “flight path” process for surgical patients may be used to identify modifiable threats and errors and generate action items, which may lead to quality improvement.Methods:A retrospective review of our neonatal “flight path” initiative was performed. Within 72 hours of a cardiac surgery, a meeting of the multidisciplinary patient care team occurs. A “flight path” is generated, graphically illustrating the patient’s hospital course. Threats, errors, or unintended consequences are identified. Action items are generated, and a working group is formed to address the items. A patient’s flight path is updated weekly until discharge. The errors and action items are logged into a database, which is analysed quarterly to identify trends.Results:Thirty one patients underwent flight path review over a 1-year period; 22.5% (N = 7) of patients had an error-free “flight.” Eleven action items were generated – four from identified errors and seven from identified threats. Nine action items were completed.Conclusions:Flight path reviews of congenital cardiac patients can be generated with few resources and aid in the detection of quality improvement opportunities. The regular multidisciplinary meetings that occur as a part of the flight path review process can promote inter-professional teamwork.

Flight path optimization with application to in-flight replanning to changing destinations

2018 ◽  
Vol 90 (8) ◽  
pp. 1192-1202 ◽  
Author(s):  
Luitpold Babel
Keyword(s):  
Flight Path ◽  
Path Optimization ◽  
Minimum Length ◽  
Content Type ◽  
Flight Planning ◽  
Air Vehicle ◽  
Computationally Intensive ◽  
Shortest Path Algorithms ◽  
High Flexibility ◽  
Flight Path Optimization

Purpose The purpose of this paper is to present a new approach for finding a minimum-length trajectory for an autonomous unmanned air vehicle or a long-range missile from a release point with specified release conditions to a destination with specified approach conditions. The trajectory has to avoid obstacles and no-fly zones and must take into account the kinematic constraints of the air vehicle. Design/methodology/approach A discrete routing model is proposed that represents the airspace by a sophisticated network. The problem is then solved by applying standard shortest-path algorithms. Findings In contrast to the most widely used grids, the generated networks allow arbitrary flight directions and turn angles, as well as maneuvers of different strengths, thus fully exploiting the flight capabilities of the aircraft. Moreover, the networks are resolution-independent and provide high flexibility by the option to adapt density. Practical implications As an application, a concept for in-flight replanning of flight paths to changing destinations is proposed. All computationally intensive tasks are performed in a pre-flight planning prior to the launch of the mission. The in-flight planning is based entirely on precalculated data, which are stored in the onboard computer of the air vehicle. In particular, no path finding algorithms with high or unpredictable running time and uncertain outcome have to be applied during flight. Originality/value The paper presents a new network-based algorithm for flight path optimization that overcomes weaknesses of grid-based approaches and allows high-quality solutions. The method can be applied for quick in-flight replanning of flight paths.

scholarly journals Methodology of Transport Scheme Selection for Metro Trains Using a Combined Simulation-Optimization Model

2017 ◽  
Vol 29 (1) ◽  
pp. 23-33
Author(s):  
Svetla Dimitrova Stoilova ◽  
Veselin Valentinov Stoev
Keyword(s):  
Optimization Model ◽  
Simulation Optimization ◽  
Linear Optimization ◽  
Real Data ◽  
Optimal Choice ◽  
Second Step ◽  
Peak Period ◽  
The Real ◽  
Combined Simulation ◽  
Scheme Selection

A major problem connected with planning the organization of trains in metros is the optimization of the scheme of movement, which determines the routing and the number of trains. In this paper, a combined simulation-optimization model including four steps is proposed. In the first step, the train movement has been simulated in order to study the interval between the trains according to the incoming passenger flows at the stations. The simulation model was elaborated using the ARENA software. The results were validated through experimental observations. Using the results obtained from simulations in the second step the correlation between the observed parameters - the incoming passengers and the interval between trains - has been studied. Recent research has established a non-linear relationship between the interval of movement, incoming passengers at the station and passengers on the platform. The third step defines the variant schemes of transportation. The fourth step presents the optimal choice of transportation of trains in metros based on linear optimization model. The model uses the regression obtained in the second step. The practicability of the combined simulation-optimization model is demonstrated through the case study of Sofia’s metro in two peak periods – morning and evening. The model results and the real situation have been compared. It was found that the model results are similar to the real data for the morning peak period but for the evening peak period it is necessary to increase the number of trains.

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