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 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.

Conflict Monitoring Across the Life Span

2014 ◽  
Vol 28 (3) ◽  
pp. 124-135 ◽  
Author(s):  
Daniela Czernochowski
Keyword(s):  
Older Adults ◽  
Life Span ◽  
Age Groups ◽  
Conflict Detection ◽  
Response Conflict ◽  
Conflict Monitoring ◽  
Subsequent Performance ◽  
Additional Control ◽  
Performance Response ◽  
Conflict Detection And Resolution

Errors can play a major role for optimizing subsequent performance: Response conflict associated with (near) errors signals the need to recruit additional control resources to minimize future conflict. However, so far it remains open whether children and older adults also adjust their performance as a function of preceding response conflict. To examine the life span development of conflict detection and resolution, response conflict was elicited during a task-switching paradigm. Electrophysiological correlates of conflict detection for correct and incorrect responses and behavioral indices of post-error adjustments were assessed while participants in four age groups were asked to focus on either speed or accuracy. Despite difficulties in resolving response conflict, the ability to detect response conflict as indexed by the Ne/ERN component was expected to mature early and be preserved in older adults. As predicted, reliable Ne/ERN peaks were detected across age groups. However, only for adults Ne/ERN amplitudes associated with errors were larger compared to Nc/CRN amplitudes for correct trials under accuracy instructions, suggesting an ongoing maturation in the ability to differentiate levels of response conflict. Behavioral interference costs were considerable in both children and older adults. Performance for children and older adults deteriorated rather than improved following errors, in line with intact conflict detection, but impaired conflict resolution. Thus, participants in all age groups were able to detect response conflict, but only young adults successfully avoided subsequent conflict by up-regulating control.

scholarly journals Improved Conflict Detection and Resolution for Service UAVs in Shared Airspace

2019 ◽  
Vol 68 (2) ◽  
pp. 1231-1242 ◽  
Author(s):  
Florence Ho ◽  
Ruben Geraldes ◽  
Artur Goncalves ◽  
Marc Cavazza ◽  
Helmut Prendinger
Keyword(s):  
Conflict Detection ◽  
Conflict Detection And Resolution
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