Geographic Information Systems and MATLAB Simulation to Quantify and Analyze Traffic Congestion in Oja Oba Road, Arakale Road, and FUTA North Gate Road of Akure, Ondo State, Nigeria

Abstract

Urban traffic congestion presents persistent challenges to transportation efficiency, economic productivity, and environmental health, particularly in rapidly urbanizing cities. Hence, the objective of this paper is to quantify and analyze traffic congestion in Oja Oba Road, Arakale Road, and FUTA North Gate road of Akure, Ondo State, Nigeria using a combination of Geographic Information Systems (GIS) and MATLAB simulation. In this study, data collected include vehicle speed, travel time, GPS tracking, and odometer markings. The Greenshields traffic model, applied within MATLAB, provided insights into speed-density and flow-density relationships. The result shows that Motorcycles are most prevalent on Arakale Road (8618 ± 3045), with extended travel periods (3153 ± 1153). Tricycles are common on Arakale and Oja-Oba, but their activity on North Gate is minimal. Cars exhibit the highest traffic on North Gate (7169 ± 1794) and Oja-Oba (11753 ± 894) while Buses are heavily concentrated on North Gate road (1696 ± 522). Vans and Trucks have limited traffic overall, with North Gate having the highest volumes, highlighting its importance for goods and freight transport. Travel Durations are longest on North Gate Road for all vehicle types, suggesting higher congestion compared to the other routes. Findings revealed peak congestion during evening hours and distinct congestion patterns across road types, with motorcycles and cars as the primary contributors to traffic volume. This GIS-MATLAB integration offers a robust tool for urban planners, allowing detailed congestion analysis and supporting data-driven strategies to enhance traffic management. The framework can be adapted for other urban centers facing similar congestion issues, facilitating more effective transport infrastructure planning.