Driver Distraction Recognition-driven Collision Avoidance Algorithm for Active Vehicle Safety

Bera, Asish

Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/8491

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DC Field	Value	Language
dc.contributor.author	Bera, Asish	-
dc.date.accessioned	2023-01-16T06:31:25Z	-
dc.date.available	2023-01-16T06:31:25Z	-
dc.date.issued	2021	-
dc.identifier.uri	https://ieeexplore.ieee.org/abstract/document/9564648	-
dc.identifier.uri	http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8491	-
dc.description.abstract	This paper integrates human driver factors with a model-based Collision Avoidance System (CAS) to enhance the safety of semi-autonomous vehicles. Driver Activity Recognition (DAR) through Driver Distraction States (DDS) has been used as the key component to trigger the CAS so that collisions can be averted. DDS has been generated using realistic normal driving scenarios and suitably integrated with a Full State Feedback (FSF) controller-based CAS. The integrated algorithm has been tested using a Hardware in Loop (HiL) setup, which is interfaced with the vehicle dynamics software IPG TruckMaker ® . The performance of the algorithm has been evaluated for various on-road scenarios and found to be effective in avoiding rear-end collisions.	en_US
dc.language.iso	en	en_US
dc.publisher	IEEE	en_US
dc.subject	Computer Science	en_US
dc.subject	Collision Avoidance	en_US
dc.subject	Convolutional neural network (CNN)	en_US
dc.subject	Driver Distraction	en_US
dc.subject	Driver Activity Recognition	en_US
dc.subject	Hardware in Loop	en_US
dc.title	Driver Distraction Recognition-driven Collision Avoidance Algorithm for Active Vehicle Safety	en_US
dc.type	Article	en_US
Appears in Collections:	Department of Computer Science and Information Systems

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