Modeling trailer-traffic flow on a Kenyan highway

Abstract

Traffic flow modelling is studied in order to ease congestion on roads. However, congestion is also caused by irregular occurrences, such as traffic accidents, poor roads, vehicle disablement, spilled loads and hazardous materials. This study explored the area of poor roads which was considered to be as a result poor planning for road network repairs. Traffic flow was categorized to be either in low, intermediate, or high volume. Modelling for every flow required a different distribution namely the Exponential, Pearson type III and Normal distributions for low, intermediate and high traffic flow volume respectively. However, we modelled the trailers traffic flow using a model that covered all the 3 states, in this case, the Pearson type III distribution. Further, we investigated the shape of the probability distribution function assumed by the trailers. After data collection, extraction and analysis, Pearson type III distribution model was calibrated to fit. Lastly, Kolmogorov-Smirnov and Chi-square tests of goodness of fit was run on the observed data. Although, the data was also fitted into Normal, Erlang, Exponential, Beta and Gamma Distributions, Pearson type III distribution provided the best fit.