Mathematical Modeling of Traffic Flow in Kampala City Using the Moving Observer Method

The purpose of the study was to investigate the variables affecting traffic flow in Kampala Central Business District (CBD), employing a quantitative approach. The rapid urbanization has led to a huge increase in the number of vehicles, resulting in traffic congestions, delays, and financial losses...

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Main Authors: Okiza,Humphrey, Muhwezi, Lawrence, Omwonylee, Okello Joseph, Awichi, Richard Opaka, Nuwagaba, Savannah
Format: Article
Language:English
Published: East African Journal of Interdisciplinary Studies 2025
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Online Access:http://hdl.handle.net/20.500.12493/2920
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author Okiza,Humphrey
Muhwezi, Lawrence
Omwonylee, Okello Joseph
Awichi, Richard Opaka
Nuwagaba, Savannah
author_facet Okiza,Humphrey
Muhwezi, Lawrence
Omwonylee, Okello Joseph
Awichi, Richard Opaka
Nuwagaba, Savannah
author_sort Okiza,Humphrey
collection KAB-DR
description The purpose of the study was to investigate the variables affecting traffic flow in Kampala Central Business District (CBD), employing a quantitative approach. The rapid urbanization has led to a huge increase in the number of vehicles, resulting in traffic congestions, delays, and financial losses especially in the Kampala CBD area. Data on traffic density, speeds, and driver behaviors were collected for a period of 20 days from five selected road sections leading into and out of the city which included traffic on Entebbe Road, Jinja road, Sir Apollo Kaggwa Road, Yusuf Lule and Wandegeya roads using the moving observer method. Regression analysis was done to identify the relationships between the variables, leading to the development of a predictive model for traffic flow. The study found out that the flow tends to increase as the day progresses and as well flow rate increases with increase in density. As the week progressed, the flow rate decreased as number of people coming to town on weekends is low since there is no work. A mathematical model was generated which could be used to predict the traffic intensity on the road at a given day and time. The model shows that changing from weekdays to weekend, the flow decreases by about 29%, and as density increases by 1%, the flow also increases by 1.5% over time. The study recommends prioritizing public transportation improvement, establishment of out of city parking yards, utilizing the other various means of transport other than road and promoting non-motorized modes of transportation in order to reduce traffic density on the road and subsequently manage congestion.
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spelling oai:idr.kab.ac.ug:20.500.12493-29202025-06-14T00:00:28Z Mathematical Modeling of Traffic Flow in Kampala City Using the Moving Observer Method Okiza,Humphrey Muhwezi, Lawrence Omwonylee, Okello Joseph Awichi, Richard Opaka Nuwagaba, Savannah Traffic Density Traffic Flow Moving Car Observer Method Microscopic Variables Macroscopic Variables. The purpose of the study was to investigate the variables affecting traffic flow in Kampala Central Business District (CBD), employing a quantitative approach. The rapid urbanization has led to a huge increase in the number of vehicles, resulting in traffic congestions, delays, and financial losses especially in the Kampala CBD area. Data on traffic density, speeds, and driver behaviors were collected for a period of 20 days from five selected road sections leading into and out of the city which included traffic on Entebbe Road, Jinja road, Sir Apollo Kaggwa Road, Yusuf Lule and Wandegeya roads using the moving observer method. Regression analysis was done to identify the relationships between the variables, leading to the development of a predictive model for traffic flow. The study found out that the flow tends to increase as the day progresses and as well flow rate increases with increase in density. As the week progressed, the flow rate decreased as number of people coming to town on weekends is low since there is no work. A mathematical model was generated which could be used to predict the traffic intensity on the road at a given day and time. The model shows that changing from weekdays to weekend, the flow decreases by about 29%, and as density increases by 1%, the flow also increases by 1.5% over time. The study recommends prioritizing public transportation improvement, establishment of out of city parking yards, utilizing the other various means of transport other than road and promoting non-motorized modes of transportation in order to reduce traffic density on the road and subsequently manage congestion. Kyambogo University Competitive Research Grant 2025-06-13T09:50:20Z 2025-06-13T09:50:20Z 2024-08-25 Article Okiza, H., Muhwezi, L., Okello, J. O., Awichi, R. O. & Savannah, N. (2024). Mathematical Modeling of Traffic Flow in Kampala City Using the Moving Observer Method East African Journal of Interdisciplinary Studies, 7(1), 241-251. https://doi.org/10.37284/eajis.7.1.2133. 2707-5303 http://hdl.handle.net/20.500.12493/2920 en Attribution-NonCommercial-NoDerivs 3.0 United States http://creativecommons.org/licenses/by-nc-nd/3.0/us/ application/pdf East African Journal of Interdisciplinary Studies
spellingShingle Traffic Density
Traffic Flow
Moving Car Observer Method
Microscopic Variables
Macroscopic Variables.
Okiza,Humphrey
Muhwezi, Lawrence
Omwonylee, Okello Joseph
Awichi, Richard Opaka
Nuwagaba, Savannah
Mathematical Modeling of Traffic Flow in Kampala City Using the Moving Observer Method
title Mathematical Modeling of Traffic Flow in Kampala City Using the Moving Observer Method
title_full Mathematical Modeling of Traffic Flow in Kampala City Using the Moving Observer Method
title_fullStr Mathematical Modeling of Traffic Flow in Kampala City Using the Moving Observer Method
title_full_unstemmed Mathematical Modeling of Traffic Flow in Kampala City Using the Moving Observer Method
title_short Mathematical Modeling of Traffic Flow in Kampala City Using the Moving Observer Method
title_sort mathematical modeling of traffic flow in kampala city using the moving observer method
topic Traffic Density
Traffic Flow
Moving Car Observer Method
Microscopic Variables
Macroscopic Variables.
url http://hdl.handle.net/20.500.12493/2920
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