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Artificial Neural Network Approach to Study the Effect of Driver Characteristics on Road Traffic Accidents

Road traffic accidents are a primary global concern, considering their magnitude and gravity and the subsequent negative impacts on the economy and general well-being of the public. Pakistan is no exception to this worldwide dilemma, with the highest incidence of road traffic accidents in recent yea...

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Main Authors: Ali, A., Ud-Din, S., Saad, S., Ammad, S., Rasheed, K., Ahmad, F.
Format: Conference or Workshop Item
Published: Institute of Electrical and Electronics Engineers Inc. 2021
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124674535&doi=10.1109%2fICDABI53623.2021.9655827&partnerID=40&md5=c35ea1d9cebd1eabfb53997fbd8187b3
http://eprints.utp.edu.my/29167/
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spelling my.utp.eprints.291672022-03-25T01:04:04Z Artificial Neural Network Approach to Study the Effect of Driver Characteristics on Road Traffic Accidents Ali, A. Ud-Din, S. Saad, S. Ammad, S. Rasheed, K. Ahmad, F. Road traffic accidents are a primary global concern, considering their magnitude and gravity and the subsequent negative impacts on the economy and general well-being of the public. Pakistan is no exception to this worldwide dilemma, with the highest incidence of road traffic accidents in recent years. Big cities like Peshawar are rapidly transforming into cities of congestion as they face severe road safety problems. Past Studies reveal that of the many factors affecting road traffic accidents in Pakistan, the factor of the driver is the deadliest, which is why this study aims to understand and model the effect of different driver characteristics on road traffic accidents. The database for this study was constituted via a survey questionnaire. Citing the complex relationship between driver characteristics and road traffic accidents, the Artificial Neural Networks Approach is used in this study. It provided a very supple and assumption-free methodology. The results from this study reveal that the ANN approach can provide an alternative to estimate the risk of a driver's involvement in RTAs by eliminating the need for costly, time-consuming studies such as psycho-technical research. © 2021 IEEE. Institute of Electrical and Electronics Engineers Inc. 2021 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124674535&doi=10.1109%2fICDABI53623.2021.9655827&partnerID=40&md5=c35ea1d9cebd1eabfb53997fbd8187b3 Ali, A. and Ud-Din, S. and Saad, S. and Ammad, S. and Rasheed, K. and Ahmad, F. (2021) Artificial Neural Network Approach to Study the Effect of Driver Characteristics on Road Traffic Accidents. In: UNSPECIFIED. http://eprints.utp.edu.my/29167/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description Road traffic accidents are a primary global concern, considering their magnitude and gravity and the subsequent negative impacts on the economy and general well-being of the public. Pakistan is no exception to this worldwide dilemma, with the highest incidence of road traffic accidents in recent years. Big cities like Peshawar are rapidly transforming into cities of congestion as they face severe road safety problems. Past Studies reveal that of the many factors affecting road traffic accidents in Pakistan, the factor of the driver is the deadliest, which is why this study aims to understand and model the effect of different driver characteristics on road traffic accidents. The database for this study was constituted via a survey questionnaire. Citing the complex relationship between driver characteristics and road traffic accidents, the Artificial Neural Networks Approach is used in this study. It provided a very supple and assumption-free methodology. The results from this study reveal that the ANN approach can provide an alternative to estimate the risk of a driver's involvement in RTAs by eliminating the need for costly, time-consuming studies such as psycho-technical research. © 2021 IEEE.
format Conference or Workshop Item
author Ali, A.
Ud-Din, S.
Saad, S.
Ammad, S.
Rasheed, K.
Ahmad, F.
spellingShingle Ali, A.
Ud-Din, S.
Saad, S.
Ammad, S.
Rasheed, K.
Ahmad, F.
Artificial Neural Network Approach to Study the Effect of Driver Characteristics on Road Traffic Accidents
author_facet Ali, A.
Ud-Din, S.
Saad, S.
Ammad, S.
Rasheed, K.
Ahmad, F.
author_sort Ali, A.
title Artificial Neural Network Approach to Study the Effect of Driver Characteristics on Road Traffic Accidents
title_short Artificial Neural Network Approach to Study the Effect of Driver Characteristics on Road Traffic Accidents
title_full Artificial Neural Network Approach to Study the Effect of Driver Characteristics on Road Traffic Accidents
title_fullStr Artificial Neural Network Approach to Study the Effect of Driver Characteristics on Road Traffic Accidents
title_full_unstemmed Artificial Neural Network Approach to Study the Effect of Driver Characteristics on Road Traffic Accidents
title_sort artificial neural network approach to study the effect of driver characteristics on road traffic accidents
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2021
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124674535&doi=10.1109%2fICDABI53623.2021.9655827&partnerID=40&md5=c35ea1d9cebd1eabfb53997fbd8187b3
http://eprints.utp.edu.my/29167/
_version_ 1738656927465865216
score 13.211869

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