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

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 abil...

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Main Authors: Ganasan, Shatiskumar, Norazlianie, Sazali
Format: Conference or Workshop Item
Language:English
English
Published: Springer Singapore 2024
Subjects:
TS Manufactures
Online Access:http://umpir.ump.edu.my/id/eprint/41143/1/Classification%20of%20Distracted%20Male%20Driver%20Based%20on%20Driving%20Performance%20Indicator.pdf
http://umpir.ump.edu.my/id/eprint/41143/2/Classification%20of%20Distracted%20Male%20Driver%20Based%20on%20Driving%20Performance%20Indicator%20%28DPI%29.pdf
http://umpir.ump.edu.my/id/eprint/41143/
https://doi.org/10.1007/978-981-99-8819-8_49
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spelling my.ump.umpir.411432024-05-16T04:26:11Z http://umpir.ump.edu.my/id/eprint/41143/ Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI) Ganasan, Shatiskumar Norazlianie, Sazali TS Manufactures 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). Springer Singapore 2024 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/41143/1/Classification%20of%20Distracted%20Male%20Driver%20Based%20on%20Driving%20Performance%20Indicator.pdf pdf en http://umpir.ump.edu.my/id/eprint/41143/2/Classification%20of%20Distracted%20Male%20Driver%20Based%20on%20Driving%20Performance%20Indicator%20%28DPI%29.pdf 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 https://doi.org/10.1007/978-981-99-8819-8_49
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic TS Manufactures
spellingShingle TS Manufactures
Ganasan, Shatiskumar
Norazlianie, Sazali
Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI)
description 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).
format Conference or Workshop Item
author Ganasan, Shatiskumar
Norazlianie, Sazali
author_facet Ganasan, Shatiskumar
Norazlianie, Sazali
author_sort Ganasan, Shatiskumar
title Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI)
title_short Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI)
title_full Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI)
title_fullStr Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI)
title_full_unstemmed Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI)
title_sort classification of distracted male driver based on driving performance indicator (dpi)
publisher Springer Singapore
publishDate 2024
url http://umpir.ump.edu.my/id/eprint/41143/1/Classification%20of%20Distracted%20Male%20Driver%20Based%20on%20Driving%20Performance%20Indicator.pdf
http://umpir.ump.edu.my/id/eprint/41143/2/Classification%20of%20Distracted%20Male%20Driver%20Based%20on%20Driving%20Performance%20Indicator%20%28DPI%29.pdf
http://umpir.ump.edu.my/id/eprint/41143/
https://doi.org/10.1007/978-981-99-8819-8_49
_version_ 1822924310071738368
score 13.235362

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