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Taskeed Jabid
East West University

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PSO-ANN in preventing traffic collisions: a comparative study Md. Ashikuzzaman; Wasim Akram; Md. Mydul Islam Anik; Mahamudul Hasan; Md. Sawkat Ali; Taskeed Jabid
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i3.pp1796-1803

Abstract

Traffic accident is a global threat which causes health and economic casualties all around the world. Due to the expansion of transportation systems, congestion can lead to spike road accident. Every year thousands of people have died due to traffic accidents. Various technologies have been adopted by modern cities to minimize traffic accidents. Therefore, to ensure people’s safety, the concept of the smart city has been introduced. In a smart city, factors like road, light, and weather conditions are important to consider to predict traffic mishap. Several machine learning models have been implemented in the existing literature to determine and predict traffic collision. But the accuracy is not enough and there exist a lot of challenges in determining the accident. In this paper, an approach of particle swarm optimization with artificial neural network (PSO-ANN) has been proposed to determine traffic collision using the dataset of the transport department of United Kingdom. The performance of PSO-ANN outperforms the existing machine learning model. PSO-ANN model can be adopted in the transportation system to counter traffic accident issues. Random Forest, Naıve Bayes, Nearest Centroid, K-Nearest Neighbor classification have been used to compare with the proposed PSO-ANN model.
An intelligent road accident reduction system using device-to-device communication Taskeed Jabid; Nazmul Hasan Rizvy; Fateza Tuj Zohora Mow; Tanjina Zaman Shosy; Md. Sawkat Ali; Maheen Islam; Samia Binta Hassan; Mahamudul Hasan
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1729-1739

Abstract

Every year thousands of people are dying due to road accidents and most of the accidents are occurring in urban areas and highways. As the number of vehicles is increasing day by day, the probability of the occurrence of the accident is also increasing. A system has been introduced in this paper that can reduce road accidents by sending an alert to drivers via smartphones. For this purpose, an android-based application has been developed. To reduce the accident, every driver of the car must have the application. Firstly, the location of the vehicle will be collected from the driver’s smartphone, then the data will be sent to the server through the application. An algorithm has been also developed using Haversine Formula which calculates the distance among the vehicles. A total of five cases have been implemented according to the dataset and compared for the performance evaluation. An extensive experimental study and comparison have been performed with the other methods where a complete performance is focused that can be claimed to reduce road accidents via the device-to-device communication process.
Co-Authors Fateza Tuj Zohora Mow Mahamudul Hasan Maheen Islam Md. Ashikuzzaman Md. Mydul Islam Anik Md. Sawkat Ali Nazmul Hasan Rizvy Samia Binta Hassan Tanjina Zaman Shosy Wasim Akram