Mathematical Modelling and MPC-Based Optimisation of Urban Traffic Flow in the Yaba and Sabo Areas of Lagos Metropolis
Authors
Department of Mathematics, Yaba College of Technology, Lagos (Nigeria)
Department of Mathematics, Yaba College of Technology, Lagos (Nigeria)
Department of Mathematics, Yaba College of Technology, Lagos (Nigeria)
Department of Mathematics, Yaba College of Technology, Lagos (Nigeria)
Department of Mathematics, Yaba College of Technology, Lagos (Nigeria)
Department of Mathematics, Yaba College of Technology, Lagos (Nigeria)
Article Information
DOI: 10.47772/IJRISS.2025.903SEDU0686
Subject Category: Economics
Volume/Issue: 9/26 | Page No: 9033-9046
Publication Timeline
Submitted: 2025-10-28
Accepted: 2025-11-04
Published: 2025-11-23
Abstract
Traffic jams in Lagos Metropolis are at critical levels, causing annual economic losses estimated in billions of naira and significantly impacting the standard of living. Using Model Predictive Control (MPC), this paper provides a detailed mathematical approach to simulate and enhance metropolitan traffic flow. By adapting the Cell Transmission Model (CTM) to the unique characteristics of Lagos' road networks, we develop a macroscopic traffic flow model. The proposed MPC system integrates real-time traffic data, predictive capabilities, and constraint management to optimise signal timing and traffic routes. The results indicate that the MPC-based method reduces queues by 24%, increases network throughput by 28%, and decreases average travel time by 32%, compared to traditional fixed-time control methods. The model accounts for Yaba and Sabo Areas specific challenges such as mixed traffic composition, informal public transportation networks, and infrastructural constraints.
Keywords
Model Predictive Control, Traffic Flow Optimisation, Cell Transmission
Downloads
References
1. Lagos State Government, Economic Sustainability Report 2024, Ministry of Economic Planning and Budget, Lagos, Nigeria, 2024. [Google Scholar] [Crossref]
2. K. Nagel and M. Schreckenberg, A cellular automaton model for freeway traffic, Journal de Physique I. 1992, vol. 2, no. 12, pp. 2221–2229 [Google Scholar] [Crossref]
3. M. J. Lighthill and G. B. Whitham, On kinematic waves II. A theory of traffic flow on long crowded roads, Proceedings of the Royal Society of London. Series A. 1955, vol. 229, no. 1178, pp. 317– 345, [Google Scholar] [Crossref]
4. C. F. Daganzo, The cell transmission model: A dynamic representation of highway traffic consistent with the hydrodynamic theory, Transportation Research Part B: Methodological. 1994, vol. 28, no. 4, pp. 269–287. [Google Scholar] [Crossref]
5. T. Bellemans, B. De Schutter, and B. De Moor, Model predictive control for ramp metering of motorway traffic: A case study, Control Engineering Practice. 2006, vol. 14, no. 7, pp. 757–767. [Google Scholar] [Crossref]
6. K. Aboudolas, M. Papageorgiou, and E. Kostopoulos, Store-and-forward based methods for the signal control problem in large-scale congested urban road networks, Transportation Research Part C: Emerging Technologies. 2009, vol. 17, no. 2, pp. 163–174. [Google Scholar] [Crossref]
7. T. Tettamanti, I. Varga, B. Kulcsa´r, and J. Bokor, Model predictive control in urban traffic network management, In 16th International IEEE Conference on Intelligent Transportation Systems , The Hague, 2013, pp. 1538–1543. [Google Scholar] [Crossref]
8. L. Li, Y. Wang, and F.-Y. Wang, Robust model predictive control for urban traffic networks, IEEE Transactions on Intelligent Transportation Systems. 2014, vol. 15, no. 6, pp. 2437–2446. [Google Scholar] [Crossref]
9. A. Muralidharan and R. Horowitz, Optimal control of freeway networks based on the link node cell transmission model, Transportation Research Part C: Emerging Technologies. 2015, vol. 51, pp. 1–21. [Google Scholar] [Crossref]
10. V. T. Arasan and R. Z. Koshy, Methodology for modelling highly heterogeneous traffic flow, Journal of Transportation Engineering. 2005, vol. 131, no. 7, pp. 544–551. [Google Scholar] [Crossref]
11. R. Behrens, D. McCormick, and D. Mfinanga, eds., Paratransit in African Cities: Operations, Regulation and Reform. London: Routledge, 2016. [Google Scholar] [Crossref]
12. World Bank, Lagos Urban Transport Project: Implementation Completion and Results Report, Report No. ICR00005234, Washington, DC, 2020. [Google Scholar] [Crossref]
13. UN-Habitat, State of African Cities 2022: Re-imagining Sustainable Urban Transitions, Nairobi: United Nations Human Settlements Programme, 2022. [Google Scholar] [Crossref]
Metrics
Views & Downloads
Similar Articles
- Impact of Foreign Direct Investment in India
- Issues Involved in Digitalisation Special Reference to Indian Tourism Growth
- Relationship Marketing and Customer Loyalty in the Fast-Moving Consumer Goods (FMCG) Industry in Nairobi County
- Financial Literacy or Financial Inclusion? Which is Which, What is What—To Achieve Uganda’s 10-Fold Economic Growth By 2040
- Harnessing Natural Gas for Economic Transformation: Overcoming the Regulatory and Infrastructural Bottlenecks in Nigeria