Neuromorphic Hardware Accelerated Lane Detection System

Shinwook KIM  Tae-Gyu CHANG  

IEICE TRANSACTIONS on Information and Systems   Vol.E100-D   No.12   pp.2871-2875
Publication Date: 2017/12/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2017PAL0004
Type of Manuscript: Special Section LETTER (Special Section on Parallel and Distributed Computing and Networking)
Category: Architecture
lane detection,  neuromorphic hardware,  neural network,  autonomous vehicle,  

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This letter describes the development and implementation of the lane detection system accelerated by the neuromorphic hardware. Because the neuromorphic hardware has inherently parallel nature and has constant output latency regardless the size of the knowledge, the proposed lane detection system can recognize various types of lanes quickly and efficiently. Experimental results using the road images obtained in the actual driving environments showed that white and yellow lanes could be detected with an accuracy of more than 94 percent.