PREDICTION OF THE NUMBER OF ROAD TRAFFIC ACCIDENTS OCCURRENCE ON THE LOKOJA-ABUJA-KADUNA EXPRESSWAY USING GREY-ARTIFICIAL NEURAL NETWORK MODEL
DOI:
https://doi.org/10.33003/fjs-2026-1002-4406Keywords:
Road Traffic Accidents, Vehicular Crashes, Grey System Model, Artificial Neural Network Model, Lokoja-Abuja-Kaduna ExpresswayAbstract
Globally, Road Traffic Accidents (RTAs) rank among the leading causes of death, a situation exacerbated in developing countries where road networks are the primary transport means. Consequently, developing reliable models to predict RTAs has become an urgent international priority for reducing loss of life and property. The conventional grey GM(1,1) prediction model, despite its proven usefulness across various domains, is prone to overestimation and underestimation, limiting its dependability. This paper uses an integrated Grey-Artificial Neural Network Model (GANNM) to enhance predictive accuracy for RTAs on Nigeria's Lokoja-Abuja-Kaduna expressway from 85.97% to 96.02%. Additionally, the results demonstrate that the GANNM resolves the estimation inaccuracies of the grey GM(1,1) approach, yielding critical data to support Nigerian policymakers in crafting effective road management strategies to enhance safety on this highway.
References
Bayode, O., Aiyelokun, O., Osanyinlokun, O.,and Adanikin, A.“Enhancing Road Crash Prediction: A Comparative Study of Machine Learning Algorithms and Safety Performance Functions on the Lagos-Ibadan Expressway”, Nigerian Journal of Technology, 2025; 44(2), pp. 215–221 . https://doi.org/10.4314/njt.v44i2.5
Chen, X.; Zhang., H and Wong, C. U. I. (2024). Optimization study of tourism total revenue prediction model based on the Grey Markov chain: A case study of Macau. AIMS Mathematics, 9(6), 16187– 16202.
Chunxia, L.; Tong, S.; Shou, C.; Shouyang, W.; Kin Keung, L and Lu, G. (2016). An improved grey neural network model for predicting transportation disruptions. Expert Systems with Applications, 45, 331–340.
DʼAmico, G.; De Blasis, R and Vigna, V. (2025). Energy production forecasting: An application of the Grey Markov chain model to data from Italy. Renewable and Sustainable Energy, 1, 0003.
Deng, J. L. (1990). Grey system theory tutorial. Huazhong University of Science and Technology mPress.
Deng, M.; Zhang, K and Mehta, S. (2002). Prediction of protein function using protein-protein
interaction data. Proceedings of the IEEE Computer Society Bioinformatics Conference, 1, 197–206.
Enwerem, G. C and Ali, G. A. (2016). Economic effects of bad roads on vehicle maintenance in
Nigeria. International Journal of Scientific and Research Publications, 6(6), 761–766.
John, C.; Darwin, J.; Noime, B and Vensurmar, C. (2017). Analysis of vehicle crash injury-severity in a super high way: A Markovian approach. Industrial Engineering Department Publishing, Adamson University.
Kalyan, M. (2015). The application of grey system theory in predicting the number of deaths of
women by committing suicide—A case study. Journal of Applied Quantitative Methods, 10(1), 48– 55.
Lawal, A.; Saidu, D. Y.; Didigwu, N. E.; Abdulla, A.; Isaac, A and Mohammed, Y. (2022). Forecasting Nigeria annual yam production using Grey System Model. International Journal of Mathematical Sciences and Optimization: Theory and Applications, 8(1), 107–114.
Li H, Chen L (2025) Traffic accident risk prediction based on deep learning and spatiotemporal features of vehicle trajectories. PLoS One 20(5): e0320656. https://doi.org/10.1371/journal.pone.0320656
Li Q, Xie J.(2024). Bridge Alignment Prediction Based on Combination of Grey Model and BP Neural Network[J]. Applied Sciences, 14(17): 7955.
Liu, S; Yang, Y and Forest, J. (2016). Grey data analysis: Methods, models and applications.
Springer.
Nyothiri, A.; Weidong, Z.; Sahraoui, D and Yibo, A. (2018). Accident prediction system based on Hidden Markov Model for Vehicular Ad-Hoc Network in urban environments. Information, 9(12), 311.
Saeed, O. B.; Abubakar, U. Y.; Lawal, A and Usman, A. (2021). Prediction of vehicular accidents along Lokoja-Abuja-Kaduna express way Nigeria using Grey-System Model GM(1,1). Journal of Science, Technology, Mathematics and Education (JOSTMED), 17(3), 87–94.
Thanikachalam, R. ., Babu, M. ., Rahuman, D. A. S. ., Swain, S. ., Chandrasekaran, S. ., & Veeran, R. . (2025). Machine Learning Models for Road Accident Prediction for Smart Cities: A Comprehensive Analysis. International Journal of Basic and Applied Sciences, 14(2), 391-400. https://doi.org/10.14419/gw398342
Wei L.(2024). Design of Sustainable Construction Cost Estimation System Based on Grey Theory—BP Model[J]. Journal of Information & Knowledge Management, 23(02): 2450011.
Xiaoyan, Hu. (2025). Application of Grey BP Neural Network in Predicting the Number of Employees in the Cultural and Sports Industry of Yunnan Province. GAIIS '25: Proceedings of the 2025 2nd International Conference on Generative Artificial Intelligence and Information Security,
P 302 - 306
Xiao, X. P and Song, Z. M. (2004). Foundations of grey technology and applications. Science Press.
Xiaoxia, C.; Long, Y and Jun, L. (2018). Vehicular driving risk prediction based on Markov chain model. Discrete Dynamics in Nature and Society, 2018, Article 4954621.
Xu, Y.; Lin, T and Du, P. (2024). A hybrid coal prediction model based on grey Markov optimized by GWO—A case study of Hebei province in China. Expert Systems with Applications, 115895. https://doi.org/10.3390/info9120311
Zhou, Z; Zhou X and Qi H. (2024). Near miss prediction in commercial aviation through a combined model of grey neural network[J]. Expert Systems with Applications, 255: 124690.
Downloads
Published
Issue
Section
Categories
License
Copyright (c) 2026 Lawal Adamu
This work is licensed under a Creative Commons Attribution 4.0 International License.
