Journal of the Japan Society of Applied Electromagnetics and Mechanics
Online ISSN : 2187-9257
Print ISSN : 0919-4452
ISSN-L : 0919-4452
Special Topic: Technology Related to AI Application and Anomaly Detection in Mobility
Real-World Application of Early Detection of Sudden Changes in Driver’s Physical Condition Using Machine Learning and Interpretation Method
Soya AOKIMakoto SEKIGUCHIJunichiro KUWAHARAYasunori YAMAMOTO
Author information
JOURNAL FREE ACCESS

2023 Volume 31 Issue 1 Pages 6-11

Details
Abstract

 In order to decrease fatal traffic accidents, early detection of sudden changes in driver’s physical condition is desired. In this paper, we reported an example of modeling process of "driver’s normal behavior model," which is a part of driver state sensing technology we are developing. By combining machine learning and domain knowledge, we have achieved the model for normal steering operation that had both high prediction accuracy and high interpretability/explainability under real-world conditions.

Content from these authors
© 2023 The Japan Society of Applied Electromagnetics and Mechanics
Previous article Next article
feedback
Top