International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Modeling of Inter-Vehicle Accident Prevention and Control System Using Rule-Based Integrated Machine Learning Technique

Nwanze D.E.Department of Computer Science & Maths, Novena University, Ogume, Delta State, NigeriaEze Irene F.Department of Computer Science, Chukwuemeka Odimegwu Ojukwu University, Uli, Anambra State, NigeriaIsizoh A.N.Department of Electronic & Computer Engineering, Nnamdi Azikiwe University, Awka, Nigeria

Vol 7 No 4 (2023): Volume 7, Issue 4, April 2023 | Pages: 174-187

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 03-05-2023

doi Logo doi.org/10.47001/IRJIET/2023.704028

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Abstract

This research focuses on the modeling of inter-vehicle accident prevention and control system using rule-based integrated machine learning technique. From the review of relevant literatures, many works have been developed as solutions for accident detection and control system for vehicles, but despite the success, solution has not been fully obtained which considered tricycle as a major cause of accident, even though it has dominated the means of transport and logistics in many developing countries, especially in Nigeria. To solve this problem, data of tricycles were collected from the Delta State Ministry of Transport, Asaba; and then trained with machine learning algorithm to generate the accident detection model. The rule-based optimization was developed from the information collected from the Federal Road Safety Corp (FRSC) on the standard of inter vehicle distance and then used to develop the control model. The model was implemented with Simulink and evaluated. The result when tested and validated showed that the accident detection accuracy is 98.1%; Mean Square Error (MSE) is 3.0512e-10 and ROC is 0.9807. When compared with other models trained with similar data type, the result showed that the Feed Forward Neural Network (FFNN) developed was better and more accurate with a percentage improvement of 5.1%.

Keywords

Accident, machine learning, tricycle, neural network, vehicle, algorithm


Citation of this Article

Nwanze D.E., Eze Irene F., Isizoh A.N., “Modeling of Inter-Vehicle Accident Prevention and Control System Using Rule-Based Integrated Machine Learning Technique” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 7, Issue 4, pp 174-187, April 2023. Article DOI https://doi.org/10.47001/IRJIET/2023.704028

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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