Modeling Trip Generation Pattern by Adopting Multiple Linear Regression in at Existing Traffic Condition

Abstract The beginning of this study is made with the objective of developing the predicted household trip generation models for Hossana town that involve the socioeconomic characteristics and land use trends. For the purpose of this study, Addis sub town was used in the analysis. In this sub town, 9 nodes of the road segment were also selected for travel flow analysis. Totally 384 forms were distributed in the town for home interview purpose. The data collected was analyzed and classified in order to qualify the social and economic features in each zone using principal component analysis method. Finally, the regression analysis taken under four components reduced by principal component analysis. The relationship between daily household trips and socioeconomic characteristics were developed using Multiple Linear Regression technique under four components reduced by principal component analysis using SPSS software package. P – Values of all variables are less than 0.05 as summarized in the table below. Which show all the variables/components/ are statistically significant within a given confidence interval. R 2  = 0.519 shows that 51.9% of the variation of the dependent variable explained by the explanatory/independent/ variables. The value of goodness of fit indicates that the model is well defined and the trips are a function of the variables chosen for this study.