Citation

Emura K, Kato M, Watanabe E. Trans. Soc. Automot. Eng. Jpn. 2022; 53(6): 1102-1107.

Copyright

(Copyright © 2022, Society of Automotive Engineers of Japan)

DOI

10.11351/jsaeronbun.53.1102

PMID

unavailable

Abstract

A human predictive characteristic may affect the traffic accident factors such as prediction failure and carelessness to other movements. In this paper, we propose a new approach to simulate how human vision predicts the driving environment during driving, and to clarify cognitive mechanisms, using deep neural networks that incorporate predictive coding, which is one of the leading theories as the operating principle of the cerebral cortex. Predictive coding assumes that the brain's internal models predict the visual world at all times and that errors between the prediction and the actual sensory input further refine the internal models.

Language: ja

Keywords

cerebral nerve system; deep neural networks; driver attention; driver model; human engineering; human error; machine learning; predictive coding; vision system; visual illusions