An Optimal Strategy for a Conflict Resolution Problem

Purpose A number of automated tools will be required for the purpose of enabling efficient services in air traffic control. The purpose of this paper is to devise an optimal flight trajectory search method that optimizes airspace system efficiency for 3D space in the presence of uncertainties. Design/methodology/approach This paper put forward an optimization model for generating applicable solutions of multi-aircraft conflict resolution problem, and the solution is based on the principle of optimality. Findings The conflict resolution problem between multiple aircraft can be described by spatial discretization, and the approach taken digitizes the 3D space into a grid of nodes. Practical implications The simulation examples are given to illustrate the validity of trajectory search model and stress on the impact of different system parameters. Originality/value Realistic constraints that are convenient to operate are incorporated in the system model, and the results show that it can provide reliable decision-making for conflict avoidance.

Download Full-text

Conflict Resolution Based on Cooperative Coevolutionary with Dynamic Grouping Strategy for Multi-Aircraft

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.333-335.1251 ◽

2013 ◽

Vol 333-335 ◽

pp. 1251-1255

Author(s):

En Yu Liu ◽

Xiang Min Guan ◽

Xue Jun Zhang ◽

Jie Zeng

Keyword(s):

Conflict Resolution ◽

Empirical Studies ◽

Optimal Solution ◽

Planning Problem ◽

Grouping Strategy ◽

Multi Agent ◽

Resolution Problem ◽

Path Planner ◽

Path Planning Problem ◽

Research Show

Conflict resolution problem (CRP) plays a crucial role in the guarantee of safety. This paper formulates CRP as a multi-agent path planning problem which aims to find optimal paths for aircrafts. An algorithm named CCDG is proposed to tackle it based on cooperative coevolutionary (CC) with a dynamic grouping strategy for aircraft. CCDG makes aircraft divided into several equal sub-groups according to the dynamic grouping strategy. Each sub-group can adopt an evolutionary algorithm (EA) to optimize the aircrafts paths fully distributed and in parallel. Optimal solution is obtained through cooperation and coordination with all sub-populations. Empirical studies using extremely scenario adopted by previous research show that CCDG outperformed the existing approach (the fast GA), and the popular path planner that each aircraft uses an EA. Moreover, CCDG succeed to improve the airspace safety and reduce cost for CR.

Download Full-text

Sequence Assignment Model for the Flight Conflict Resolution Problem

Transportation Science ◽

10.1287/trsc.2013.0480 ◽

2014 ◽

Vol 48 (3) ◽

pp. 334-350 ◽

Cited By ~ 5

Author(s):

Zhe Liang ◽

Wanpracha Art Chaovalitwongse ◽

Elsayed A. Elsayed

Keyword(s):

Conflict Resolution ◽

Assignment Model ◽

Resolution Problem ◽

Sequence Assignment

Download Full-text

Real-time Conflict Resolution Algorithm for Multi-UAV Based on Model Predict Control

Algorithms ◽

10.3390/a12020047 ◽

2019 ◽

Vol 12 (2) ◽

pp. 47

Author(s):

Hao-xiang Chen ◽

Ying Nan ◽

Yi Yang

Keyword(s):

Conflict Resolution ◽

Model Predictive Control ◽

Real Time ◽

Predictive Control ◽

Decentralized Coordination ◽

Resolution Rule ◽

Resolution Problem ◽

Resolution Algorithm ◽

Sample Time ◽

Multi Uav

A real-time conflict resolution algorithm based on model predictive control (MPC) is introduced to address the flight conflict resolution problem in multi-UAV scenarios. Using a low-level controller, the UAV dynamic equations are abstracted into simpler unicycle kinematic equations. The neighboring UAVs exchange their predicted trajectories at each sample time to predict the conflicts. Then, under the predesignated resolution rule and strategy, decentralized coordination and cooperation are performed to resolve the predicted conflicts. The controller structure of the distributed nonlinear model predictive control (DNMPC) is designed to predict potential conflicts and calculate control variables for each UAV. Numerical simulations of multi-UAV coordination are performed to verify the performance of the proposed algorithm. Results demonstrate that the proposed algorithm can resolve the conflicts sufficiently in real time, while causing no further conflicts.

Download Full-text