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Lim, Ji Hyoun
Intelligent Interaction Lab
Research Interests
  • Computational Cognitive Model, Semantic Network Analysis, Human Robot Interaction

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Investigation of driver performance with night vision and pedestrian detection systems, Part 2: Queueing network performance modeling

Cited 9 times inthomson ciCited 9 times inthomson ci
Title
Investigation of driver performance with night vision and pedestrian detection systems, Part 2: Queueing network performance modeling
Author
Lim, Ji HyounOmer TsimhoniYili, Liu
Keywords
DETECTION PROBABILITY; VISUAL-SEARCH; CLUTTER; COGNITION; BEHAVIOR; Cognitive model; human performance modeling; night vision; pedestrian detection; queueing network
Issue Date
2010-12
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, v.11, no.4, pp.706 - 714
Abstract
This paper introduces a queueing network-based computational model to explain driver performance in a pedestrian-detection task assisted with night-vision-enhancement systems. The computational cognitive model simulated the pedestrian-detection task using images displayed by two night-vision systems as input stimuli. The system equipped with a far-infrared (FIR) sensor generated less-cluttered images than the system equipped with a near-infrared (NIR) sensor. Using a reinforcement learning process, the model developed eye-movement strategies for each night-vision system. The differences in eye-movement strategies generated different eye-movement behaviors, in accord with the empirical findings.
URI
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DOI
10.1109/TITS.2010.2049844
ISSN
1524-9050
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DHE_Journal Papers
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