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

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.

scholarly journals How Important Is Conflict Detection to the Conflict Resolution Task?

2016 ◽  
pp. 103-115 ◽  
Author(s):  
Joey Mercer ◽  
Cynthia Gabets ◽  
Ashley Gomez ◽  
Tamsyn Edwards ◽  
Nancy Bienert ◽  
...  
Keyword(s):  
Conflict Resolution ◽  
Conflict Detection

scholarly journals Velocity Obstacle Based Conflict Avoidance in Urban Environment with Variable Speed Limit

Aerospace ◽  
2021 ◽  
Vol 8 (4) ◽  
pp. 93
Author(s):  
Marta Ribeiro ◽  
Joost Ellerbroek ◽  
Jacco Hoekstra
Keyword(s):  
Conflict Resolution ◽  
Conflict Detection ◽  
Fast Time ◽  
Variable Speed ◽  
Variable Speed Limit ◽  
Package Delivery ◽  
Learning Agent ◽  
Variable Speed Limits ◽  
Conflict Detection And Resolution ◽  
Velocity Obstacle

Current investigations into urban aerial mobility, as well as the continuing growth of global air transportation, have renewed interest in conflict detection and resolution (CD&R) methods. The use of drones for applications such as package delivery, would result in traffic densities that are orders of magnitude higher than those currently observed in manned aviation. Such densities do not only make automated conflict detection and resolution a necessity, but will also force a re-evaluation of aspects such as coordination vs. priority, or state vs. intent. This paper looks into enabling a safe introduction of drones into urban airspace by setting travelling rules in the operating airspace which benefit tactical conflict resolution. First, conflicts resulting from changes of direction are added to conflict resolution with intent trajectory propagation. Second, the likelihood of aircraft with opposing headings meeting in conflict is reduced by separating traffic into different layers per heading–altitude rules. Guidelines are set in place to make sure aircraft respect the heading ranges allowed at every crossed layer. Finally, we use a reinforcement learning agent to implement variable speed limits towards creating a more homogeneous traffic situation between cruising and climbing/descending aircraft. The effects of all of these variables were tested through fast-time simulations on an open source airspace simulation platform. Results showed that we were able to improve the operational safety of several scenarios.

scholarly journals A Causal Model for Safety Assessment Purposes in Opening the Low-Altitude Urban Airspace of Chinese Pilot Cities

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Jun Tang ◽  
Wenyuan Yang
Keyword(s):  
Conflict Resolution ◽  
Traffic Management ◽  
Safety Assessment ◽  
Causal Model ◽  
High Reliability ◽  
Time Windows ◽  
Conflict Detection ◽  
Global Perspective ◽  
Graphical Modelling ◽  
Low Altitude

China has been gradually relaxing its ban on the use of low-altitude airspace across the country. To guarantee the high reliability of air traffic management (ATM), conflict detection and conflict resolution (CDR) approaches are indispensable to maintain safe separation between neighbouring small fixed-wing aircraft. In this study, we analyse a temporal and spatial integrated strategy for safety assessment purposes in opening the low-altitude urban airspace of Chinese pilot cities. First, we present a detailed mathematical description of the proposed algorithms based on a spatial grid partitioning system (SGPS). For our system, a conflict detection (CD) algorithm is designed to determine if two trajectories pass through the same grid space within overlapping time windows. A conflict resolution (CR) algorithm integrates a proposed time scheduling-based technique (TST) and vertical change-based technique (VCT), which operate under predetermined basic principles. Then, based on our novel CDR algorithms, a causal model is constructed in graphical modelling and analysis software (GMAS) to generate a state space that can provide a global perspective on scenario dynamics and better understanding of induced conflict occurrences. Finally, simulation results demonstrate that the proposed approach is practical and efficient.

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.

Sign in / Sign up

Export Citation Format

Share Document