Navigating urban gridlock: A study of traffic congestion and sustainable mobility solutions in the urban center

Abstract

BACKGROUND AND OBJECTIVES: Traffic congestion, a prevalent global issue, has entrenched itself as a persistent problem, posing substantial challenges for residents and commuters, especially in developing nations. This study addresses this concern by delving into the intensity, patterns, and traffic characteristics within selected road corridors in the Abeokuta metropolis, Nigeria.METHODS: Data on road types and land use were systematically gathered through structured observations using a pre-designed checklist. Traffic counts were conducted to capture characteristics during the morning and evening peak periods. Traffic volume and capacity were measured in "vehicles per hour" (vph) and Passenger Car Units per hour (PCU/hr). To analyze the data, a chi-square test was used to examine differences in traffic volume between the peak hours, while Analysis of Variance was applied to assess variations in traffic composition across the studied road corridors.FINDINGS: The study's findings spotlight Sapo-Ijaye-Iyana Mortuary, recording the highest daily peak traffic volume at 2315 vph, with cars dominating at 4444 vph. Buses emerged as the most impactful vehicle class, influencing 4872 PCU/hr. The Chi-square test indicates no significant differences in vph between morning and evening peaks (x=0.822604; p=0.84405). Correspondingly, Analysis of Variance results (f=3.3106; p=1.0000) suggest that traffic composition did not significantly differ across the surveyed roads.CONCLUSION: Based on the findings of the study, it is recommended to enhance road capacities by upgrading infrastructure to accommodate both current and future transportation needs. Additionally, the development of alternative traffic routes, such as rail lines, is suggested to ease the movement of heavy-duty trucks and reduce road congestion. The adoption of intelligent transportation systems is also encouraged to improve traffic management and optimize transportation efficiency.