ABSTRACT
The lack of information on bus travel time in Makurdi metropolis to enable trip makers plan for journeys is seen as a challenge in recent times. This study developed a multiple linear regression model for predicting bus travel time along bus routes within the metropolis and this was achieved throughmeasurement of the physical characteristics of the roadway, identification of those factors that constitute impediment to intra-city bus travel time, measurement of intra-city bus travel time on the routes and development of prediction models for intra-city bus travel time using statistical package for social science and the development of curve fittings for the built models with data collected from field survey. The physical characteristic of the routes under study was determined and the lane width values obtained on the field where 3.6m, 3.7m, and 3.5m for Wadata, Modern Market, and Air force base routes respectively and these values conform with the Federal Ministry of works Highway Design Manuel 2013 which states that 3.35-4.0m lane width be used for safety, efficiency and ease of operation and the manual also states that the minimum median width be 1.2m and usable shoulder width of 3m are desirable on all highways but narrow widths are acceptable on low volume highway.The factors that affect intra-city bus travel times were also determined with speed of travel, dwell times, 3-leg intersection and Cross intersections, volume of traffic which all ranged from 427-775 vehicles/hour which falls under the traffic category of heavy traffic as stated in the Federal Ministry of works Highway Design Manual, 2013 that traffic more than 1000vehicles/day belongs to Heavy traffic, and number of roundabout and the route lengths been predominant.The traffic data was collected from the metropolis using moving vehicle technique method of estimating travel timeduring survey, there was delay and congestion during the peak periods as compared to the off-peak period.From the regression analysis conducted,the built modelscaptured route length which shows that the model is a good one for both peak and off-peak periods. A high value of coefficient of correlation for Peak and Off-Peak periods, R = 0.978 and R= 0.997 was obtained which indicates that there is a high and good correlation of about 97.8% and 99.7% between the dependent and independent variables and the models are very good reflection of the current traffic situation in the state capital. The coefficient of determination R2 which is a measure of goodness-of-fit, was found to be 0.956 and 0.994 respectively which indicates that 95.6% and 99.4% of the dependent variable (Travel time) at a confidence level of 95% and significant level of 0.05 is explained by both regression models. The findings also revealed that R2 value for the Off-peak period is relatively high which defines high accuracy of the model and the Peak period is associated with more complications but represent a more realistic travel situation. The major findings, in the light of the peculiar set of present day conditions established that route length, T-junction and travel speed are important parameters used in the prediction of travel time because they contributed significantly to the built modelat 95% confidence level and 0.05 interval levels. The proposed model is conceptually and operationally simple and should be used for cities in Nigeria having such challenges as noticed in Makurdi metropolis. On-street parking should be regulated so as to reduce traffic congestion on the highways within the metropolis