Developing a Home-based Trip Generation Model for a Suburb Area of a City: Case of Furi Sub-city, Sheger City

Rapid urbanization in Furi Sub-city has increased travel demand, placing considerable pressure on the existing transportation system. Developing locally calibrated trip generation models is therefore essential for reliable travel demand forecasting and effective transportation planning. This study develops and compares household-level home-based trip generation models using Multiple Linear Regression (MLR) and Multiple Classification Analysis (MCA). Household travel survey data were collected from 383 randomly selected households to examine the influence of socioeconomic and demographic characteristics on home-based trip production. MLR was employed to estimate continuous trip generation models, whereas MCA was used to derive category-based trip rates, and model performance was evaluated using goodness-of-fit statistics and prediction accuracy measures. The results indicate that household size, number of students, vehicle ownership, and the numbers of employed and unemployed household members are the principal determinants of home-based trip generation in Furi Sub-city. Although both MLR and MCA adequately captured household travel behavior, MLR generally demonstrated higher explanatory power and lower prediction errors for most trip purposes; whereas MCA showed better performance for total home-based trip generation based on validation error measures. Overall, the findings suggest that MLR provides a more reliable approach for household trip generation modeling in the study area, while MCA offers an interpretable alternative for estimating category-based trip rates. The locally calibrated models developed in this study provide valuable inputs for travel demand forecasting, transportation planning, and evidence-based policy development in Furi Sub-city and other rapidly urbanizing areas with similar socioeconomic characteristics.