Title :
A new approach to detecting distracted car drivers using eye-movement data
Author :
Mizoguchi, Fumio ; Nishiyama, Hiroki ; Iwasaki, Hisao
Author_Institution :
Fac. of Sci. & Tech., Tokyo Univ. of Sci., Noda, Japan
Abstract :
In our study, we generate new rules for determining whether or not a driver is distracted, using collected data about the driver´s eye movement and driving data by learning as a new approach to detecting distracted car drivers. We use a learning tool, namely a support vector machine (SVM), to generate the rules. In addition, we focused on a qualitative model of a driver´s cognitive mental load in a prior study and investigated the relationship between this model and the driver´s distraction. In the investigation, we verify driver´s eye movements and driving data that are inconsistent with the model.
Keywords :
behavioural sciences computing; cognition; data handling; learning (artificial intelligence); support vector machines; traffic engineering computing; SVM; distracted car drivers detection; driver cognitive mental load; driver eye movement; eye-movement data; learning approach; rule generation; support vector machine; Decision support systems;
Conference_Titel :
Cognitive Informatics & Cognitive Computing (ICCI*CC), 2014 IEEE 13th International Conference on
Conference_Location :
London
Print_ISBN :
978-1-4799-6080-4
DOI :
10.1109/ICCI-CC.2014.6921470