Calibration and Validation of an Age-Based Gravity Model for Transportation Interaction Analysis in High-Density Urban Areas

This study presents an age-based gravity-model framework that applies the conventional gravity model under different age-group population scenarios to examine trip distribution patterns (spatial interaction patterns) in a high-density urban environment. Gaza Governorate was selected as the study area due to its high population density, constrained spatial structure, and intensive daily mobility demands. Data were collected in 2023 through a household survey involving 600 households, direct observation of passenger movements, and travel impedance data consisting of travel distance and travel time between study areas. Age-group populations were classified into three categories (0–14 years, 15–64 years, and 65 years and above) and incorporated as demographic mass variables within separate gravity-model scenarios. Model performance was evaluated using Pearson correlation (R), coefficient of determination (R2), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). The validation results demonstrated acceptable to strong agreement between the survey-derived and observed OD matrices across all age groups. Following calibration, the gravity model successfully reproduced the general spatial concentration of observed trip distribution patterns between origin–destination (OD) zones within the study area. The conventional model and the 15–64 and 0–14 age-group scenarios exhibited moderate explanatory capability. Among the evaluated scenarios, the 15–64 age group achieved the highest coefficient of determination (R2 = 0.518), followed by the 0–14 group (R2 = 0.485), while the 65+ group achieved the lowest value (R2 = 0.339). The results indicate that age composition is associated with variations in the strength and predictability of aggregated transportation interaction patterns, although the overall spatial interaction structure remained broadly consistent across all age groups. The findings suggest that applying the conventional gravity model under age-group population scenarios provides a useful exploratory framework for analysing transportation interactions in data-constrained, high-density urban environments. The proposed framework contributes to the growing literature on age-related mobility by demonstrating how age-group population structures can be incorporated into a conventional OD-based gravity-model framework for comparative trip distribution analysis and may support evidence-based and sustainable trip distribution modelling for transportation planning in data-constrained urban environments. The proposed framework provides an interpretable and data-efficient approach for supporting sustainable urban transportation planning by improving the understanding of age-specific trip distribution patterns in data-constrained high-density urban environments.