Abstract:
Travel time variability or distribution is very important to travel time reliability studies in
transportation systems as developing cities are usually characterized by transportation deficit leading to traffic congestion and other environmental challenges. This study aimed at developing a model for estimating travel times for dynamic highway networks in Akure Metropolis with a view to identifying key factors having significant influence on travel times, determine the extent of their influence; and develop an appropriate model for estimating travel times using Multi-linear regression approach. Travel Time data was collected at three different periods of the day: morning period (7:30 am–8:30 am), free-flow period (12:00 pm–2:00 pm) and evening period (4:00 pm–6:00 pm). The independent variables for the model are Traffic volume, density, average speed of vehicles, and traffic flow. The result analyzed using descriptive statistics in SPSS software environment reveals R2 value of 0.998, 0.993 and 0.957 for Olusegun Obasanjo/Oyemekun/Oba Adesida, Idanre and aggregate model respectively; thereby indicating that the independent variables accounted for substantial variation of travel time in the study area. The result further revealed that traffic volume, flow and speed were significant impacts on travel time at 95% confidence level. The study recommends periodic observation of travel time within the study area to update the developed model.
