You have no items in your shopping cart.
ABSTRACT
Traffic congestion is becoming one of the most blatantly worsening problems in urban cities around the world. Traffic in cities continue to grow meteorically in major cities of developing countries as the existing road network is not sufficient for the increasing number of vehicles on roadways and there is inability to build larger and new roadways. As a way to aid the reduction of congestion in cities, an analysis on traffic flow between Ikpokpan junction (Round about) and Adesuwa junction along Sapele road within Benin City metropolis was carried out in order to provide a quantitative understanding of how long congestion persists for future reference. First, the manual count method was used to collect the traffic volume data as needed and the license plate method was also used to obtain the travel time of vehicles during congestion and through the preliminary cleaning, processing, deletion of missing data, combined computation of data according to indicators and other steps to screen and integrate the data we need. Then, the linear regression method is used to construct the traffic congestion model for the existing data, and the actual duration of traffic congestion is obtained. The software programming is solved by SPSS and the congestion prediction is obtained. From the data collected by license plate method for the study area (Adesuwa Junction) and analyzed, average congestion duration and average travel time along the study area was found to be 103.1secs and 200.19secs respectively. Delay in travel time was found to be 180secs. The average traffic volume was found to be 1506vehicles indicating the number of vehicles accommodating the junction during a given time under the prevailing road condition. The SPSS software was calibrated using the linear regression method and the R2 (R squared) value was found to be 0.991 indicating a large positive linear association between the speed, travel time and density data collected. Therefore, the model is suitable for the analysis of the traffic congestion duration along Adesuwa Junction.
