Research on UAV conflict resolution based on dynamic conflict detection model

2021 ◽  
Author(s):  
Qiang Zhou ◽  
Guobao Cheng
Keyword(s):  
Conflict Resolution ◽  
Conflict Detection ◽  
Detection Model

scholarly journals An ant colony algorithm model for UAV sense and avoid based on ADS-B

2021 ◽  
Vol 39 (4) ◽  
pp. 761-769
Author(s):  
Mengting Yuan ◽  
Hongwei Shi
Keyword(s):  
Conflict Resolution ◽  
Ant Colony Algorithm ◽  
Conflict Detection ◽  
Safety Performance ◽  
Ant Colony ◽  
Heuristic Function ◽  
Sense And Avoid ◽  
Detection Model ◽  
Resolution Model ◽  
Resolution Strategy

In the context of airspace fusion, in order to improve the safety performance of UAV and prevent the occurrence of air collision accidents, an ant colony algorithm model for UAV sense and avoid based on ADS-B monitoring technology is proposed. The model mainly consists of two parts: the deterministic conflict detection model makes the full use of ADS-B information to calculate the geometric distance from the horizontal and vertical planes to identify the conflict target, and the conflict resolution model is based on the ant colony algorithm which introduces the comprehensive heuristic function and sorting mechanism to plan the route again for achieving the collision avoidance. The simulation results show that the conflict detection model can effectively identify the possible threat targets, and the conflict resolution model is not only suitable for the typical two aircraft conflict scenarios, but also can provide a better resolution strategy for the complex multiple aircraft conflict scenarios.

A stochastic conflict detection model revisited

2000 ◽  
Author(s):  
Karine Blin ◽  
Marianne Akian ◽  
Frederic Bonnans ◽  
Eric Hoffman ◽  
Claude Martini ◽  
...  
Keyword(s):  
Conflict Detection ◽  
Detection Model

A PARALLEL ARCHITECTURE FOR AI NONLINEAR PLANNING

1990 ◽  
Vol 04 (02) ◽  
pp. 215-232 ◽  
Author(s):  
SUKHAN LEE ◽  
KYUSIK CHUNG
Keyword(s):  
Conflict Resolution ◽  
Distributed Processing ◽  
Parallel Architecture ◽  
State Level ◽  
Conflict Detection ◽  
Parallel And Distributed Processing ◽  
Resource Level ◽  
Planning Algorithm ◽  
Conflict Detection And Resolution ◽  
Nonlinear Planning

This paper presents a resource-level conflict detection and conflict resolution scheme which is combined with a state-level backward planning algorithm and provides efficient conflict detection and global conflict resolution for nonlinear planning. The scheme keeps track of the usage of individual resources during planning, and constructs a Resource-Usage Flow (RUF) structure (based on which conflict detection and resolution is accomplished). The RUF structure allows the system to perform minimal and nonredundant operations for conflict detection and resolution. Furthermore, resource-level conflict detection and resolution facilitates problem decomposition in terms of resources, thereby providing easy implementation in a parallel and distributed processing environment. Performance analysis indicates that the proposed architecture has a speed-up factor of the average depth of a plan network, D(Na), compared to the distributed NOAH, where Na (the total number of action nodes at the completion of planning) and D(Na) are considerably larger than the number of resources involved in planning as well as the number of initial goal states.

Is consciousness necessary for conflict detection and conflict resolution?

2013 ◽  
Vol 247 ◽  
pp. 110-116 ◽  
Author(s):  
Ling Xiang ◽  
Baoxi Wang ◽  
Qinglin Zhang
Keyword(s):  
Conflict Resolution ◽  
Conflict Detection

scholarly journals A policy conflict detection mechanism for multi-controller software-defined networks

2019 ◽  
Vol 15 (5) ◽  
pp. 155014771984471 ◽  
Author(s):  
You Lu ◽  
Qiming Fu ◽  
Xuefeng Xi ◽  
Zhenping Chen ◽  
Encen Zou ◽  
...  
Keyword(s):  
Network Architecture ◽  
Detection Algorithm ◽  
Conflict Detection ◽  
Detection Methods ◽  
Software Defined Network ◽  
Software Defined Networks ◽  
Network Environment ◽  
Detection Mechanism ◽  
Policy Conflict ◽  
Detection Model

As the network environment expands and becomes more complex, the deficiencies of decision-making capabilities in the single-controller software-defined network architecture are increasingly exposed. Currently, software-defined networks have gradually adopted a multi-controller-based architecture. However, in this architecture, multiple controllers may cause conflicts in the flow policies, which may cause failures such as security and route conflicts. Most of the existing detection methods are only aimed at specific types of conflicts. Aiming at the above insufficiency, this article proposes a policy conflict detection mechanism for multi-controller software-defined network. First, it quantifies and classifies the software-defined policy conflict itself to provide the basis for detection mechanism; then, it proposes a conflict detection model and its deployment scheme for multi-controller software-defined networks; finally, based on the software-defined flow policy’s structure, a multi-branch tree-based policy conflict detection algorithm is proposed to accurately detect the universal types of conflicts. The experimental results under the campus network environment prove that our method can effectively detect the conflict of flow policies existing in the multi-controller software-defined network and has advantages over the existing methods in the integrity, accuracy, and efficiency of the detection.

scholarly journals A Credit Conflict Detection Model Based on Decision Distance and Probability Matrix

2022 ◽  
Vol 2022 ◽  
pp. 1-7
Author(s):  
Xiaodong Zhang ◽  
Congdong Lv ◽  
Zhoubao Sun
Keyword(s):  
Influencing Factors ◽  
Elderly Care ◽  
Distance Matrix ◽  
Conflict Detection ◽  
Support Vector ◽  
Similarity Matrix ◽  
Detection Model ◽  
Model Based ◽  
Internet Finance ◽  
The Impact

Considering the credit index calculation differences, semantic differences, false data, and other problems between platforms such as Internet finance, e-commerce, and health and elderly care, which lead to the credit deviation from the trusted range of credit subjects and the lack of related information of credit subjects, in this paper, we proposed a crossplatform service credit conflict detection model based on the decision distance to support the migration and application of crossplatform credit information transmission and integration. Firstly, we give a scoring table of influencing factors. Score is the probability of the impact of this factor on credit. Through this probability, the distance matrix between influencing factors is generated. Secondly, the similarity matrix is calculated from the distance matrix. Thirdly, the support vector is calculated through the similarity matrix. Fourth, the credit vector is calculated by the support vector. Finally, the credibility is calculated by the credit vector and probability.

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