A Rule Based Reasoning System for Initiating Passive ADAS Warnings Without Driving Distraction Through an Ontological Approach

This source preferred by Huseyin Dogan

Authors: Fan, B., Ma, J., Jiang, N., Dogan, H. and Ali, R.

http://eprints.bournemouth.ac.uk/32068/

Start date: 7 October 2018

Pages: 3511-3517

ADAS (Advanced Driver Assistance Systems) are in-vehicle systems designed to enhance driving safety and comfort. Unlike active ADAS which provide direct intervention to avoid accidents, passive ADAS increase driver's awareness of hazardous situations by giving warnings in advance. It has been noted that these systems can cause distraction when the relevant HMIs (Human-Machine Interfaces) are poorly designed. Current research is limited to address this problem in specific settings which may not be applicable in wider context. This papers aims to provide a universal rule-based solution to allow passive ADAS to initiate warnings without triggering driver distraction through an ontological approach.

This data was imported from Scopus:

Authors: Fan, B., Ma, J., Jiang, N., Dogan, H. and Ali, R.

http://eprints.bournemouth.ac.uk/32068/

Journal: Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018

Pages: 3511-3517

ISBN: 9781538666500

DOI: 10.1109/SMC.2018.00594

© 2018 IEEE. ADAS (Advanced Driver Assistance Systems) are in-vehicle systems designed to enhance driving safety and comfort. Unlike active ADAS which provide direct intervention to avoid accidents, passive ADAS increase driver's awareness of hazardous situations by giving warnings in advance. It has been noted that these systems can cause distraction when the relevant HMIs (Human-Machine Interfaces) are poorly designed. Current research is limited to address this problem in specific settings which may not be applicable in wider context. This papers aims to provide a universal rule-based solution to allow passive ADAS to initiate warnings without triggering driver distraction through an ontological approach.

This data was imported from Web of Science (Lite):

Authors: Fan, B., Ma, J., Jiang, N., Dogan, H., Ali, R. and IEEE

http://eprints.bournemouth.ac.uk/32068/

Journal: 2018 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)

Pages: 3511-3517

ISSN: 1062-922X

DOI: 10.1109/SMC.2018.00594

The data on this page was last updated at 04:54 on April 18, 2019.