Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI)

Ganasan, Shatiskumar and Norazlianie, Sazali (2024) Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI). In: Intelligent Manufacturing and Mechatronics, Lecture Notes in Networks and Systems. 4th International conference on Innovative Manufacturing, Mechatronics and Materials Forum, iM3F2023 , 07 – 08 August 2023 , Pekan, Malaysia. pp. 587-595., 850. ISSN 2367-3389 ISBN 978-981-99-8819-8

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Abstract

Distracted driving causes most road accidents and injuries. Cell phones, food, radios, and passenger conversations are all distractions. Distractions may slow a driver's response time and increase the risk of accidents. Studies reveal that even minor distractions may impair a driver's ability to drive safely. This study examines how distracted driving affects male drivers. Using US and Malaysian databases will do this. This research included drivers with at least two years of experience to guarantee a representative sample. Each dataset chose 35 and 58 drivers. Driver distraction level, a new class characteristic, has four levels: no, mild, moderate, and severe. Weka software was used for “data mining” to get insights from a vast dataset. Weka is a strong data mining and machine learning program including algorithms for data preparation, classification, regression, clustering, and visualization. We applied these algorithms on their datasets using its GUI or command-line parameters. Speed, braking, acceleration, steering, lane offset, lane position, and time were used to assess driving performance. Male drivers were more likely to be distracted driving based on their driving skills which is identified by the driving performance indicator (DPI).

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Weka; Distracted driving; Data mining; Machine learning; Classification; Driving performance indicator (DPI)
Subjects:	T Technology > TS Manufactures
Faculty/Division:	Faculty of Manufacturing and Mechatronic Engineering Technology
Depositing User:	Miss Amelia Binti Hasan
Date Deposited:	08 May 2024 08:35
Last Modified:	16 May 2024 04:26
URI:	http://umpir.ump.edu.my/id/eprint/41143
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