Integrated Trip Distribution Modelling using Household Survey Data, Doubly Constrained Gravity Model, and R-Based Calibration: A Case Study of Bi-nuclei Cities

International Journal of Civil Engineering

© 2026 by SSRG - IJCE Journal

Volume 13 Issue 2

Year of Publication : 2026

Authors : Adnya S. Manjarekar, Anand V. Shivapur, Vilas V. Karjinni

10.14445/23488352/IJCE-V13I2P123

How to Cite?

Adnya S. Manjarekar, Anand V. Shivapur, Vilas V. Karjinni, "Integrated Trip Distribution Modelling using Household Survey Data, Doubly Constrained Gravity Model, and R-Based Calibration: A Case Study of Bi-nuclei Cities," SSRG International Journal of Civil Engineering, vol. 13,  no. 2, pp. 337-347, 2026. Crossref, https://doi.org/10.14445/23488352/IJCE-V13I2P123

Abstract:

Recent research has shown that it is vital to comprehend the distribution of trips within urban areas to undertake successful transport planning, especially within the municipal areas that grow at a dominant rate. This paper is a model of the trip distribution of Sangli-Miraj-Kupwad Municipal Corporation based on a household survey and two complementary analytical models. On the one hand, the structured Household Interview Survey provided socio-economic and travel-related data, which, in turn, created an in-depth portrait of household features, travel purposes, and mode preferences in 12 Traffic Analysis Zones. Based on these data, an Origin-Destination matrix was built using the Doubly Constrained Gravity Model with the help of Excel so that both trip productions and attractions were equal to the observed values by balancing αᵢ and βⱼ factors with each other. Second, the deterrence parameters were estimated in RStudio, and inter-zonal flows were sensitive to the cost of traveling, providing another independent statistical assessment of how the model behaves. A combination of these two methods allows obtaining more concise insight into the interactions in spatial travel using strict matrix balancing and the estimation of behavioural parameters. The framework that has been obtained offers an efficient representation of mobility patterns and helps make decisions based on data related to the planning of urban transportation in the study area.

Keywords:

Gravity model, Household Size, Trip distribution, Trip Matrix.

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