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

• 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/

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.