ASSESSMENT OF TRAFFIC FLOW ON AKWA IBOM STATE HIGHWAYS USING SPEED DENSITY REGRESSION COEFFICIENT

ABSTRACT In an attempt to estimate the operating speeds and volume of traffic on highway lanes as a function of predicted demands, speed-density models were estimated using data from highway sites. Speed, flow, and volume are the most important elements of traffic flow. In this study, the speed-density regression models are compared using five highways in relation to their correlation coefficient, based on the daily traffic flow data obtained from the roads. The traffic flow data were collected by hourly traffic counts on each road. The coefficient of correlation () proved to have the best fit, with higher confidence and less variation for a two-lane highway than for a one-lane highway. The space-mean speed () and density () relationships for the two-lane highways are: s = 346.62 – 0.0025d,\quad s = 106.34 – 0.0026d,\quad s = 216.41 – 0.0025d Whereas the space-mean speed () and density () relationships for the one-lane highways are: s = 353.36 – 0.0022d,\quad s = 307.65 – 0.0012d The correlation coefficient revealed that the two-lane highways — Uyo – Abak Highway (UAH), Uyo – Ikot Ekpene Highway (UIH), and Etinan – Uyo Highway (EUH) — have a better fit of correlation coefficient than the one-lane highways — Ikot Ekpene – Umuahia Highway (IUH) and Ikot Ekpene – Aba Highway (IAH). The calibrated speed-density model showed that the one-lane highways have higher values of traffic data for space-mean speed, with less variation than the two-lane highways. It can also be observed that the characteristics of the two-lane and one-lane highways are different, and the relationships of their three traffic flow factors (flow, speed, and density) are also different. This research provides practical applications for speed estimation, construction, maintenance, and optimization of highways using the speed-density models, which will enhance traffic monitoring, traffic control management, traffic forecasting, and model calibration.