Onboard Evolutionary Risk Recognition System for Automobiles—Toward the Risk Map System
Ogawa, G.
Kise, K.
Torii, T.
Nagao, T.
Subaru Tech. Res. Center, Fuji Heavy Industries Ltd, Mitaka;
This paper appears in: Industrial Electronics, IEEE Transactions on
Publication Date: April 2007
Volume: 54,
Issue: 2
On page(s): 878-886
ISSN: 0278-0046
INSPEC Accession Number: 9400437
Digital Object Identifier: 10.1109/TIE.2007.891654
Current Version Published: 2007-03-12
Abstract
To achieve a system that improves the safety and comfort of the vehicle driving, a recognition system equivalent to the human recognition ability should be developed. However, the vehicle environment is complicated and involves situations so diverse that a uniform recognition processing approach cannot function sufficiently. For a solution to this problem, we have been studying a comprehensive risk recognition system, which we call the risk map system, with learning capability. As part of this paper, a system has been developed that autonomously obtains the image recognition processing. This paper presents a system as an example that automatically learns through genetic programming to obtain the image processing of pedestrians and vehicles taken by an onboard camera system
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