Temporal Transferability of Vehicle Ownership Models in the Developing World: Case Study of Dhaka, Bangladesh

Abstract

Temporal transferability of model parameters is a critical issue, especially in the context of developing countries where data and resources for transport model development are extremely limited. This study investigates the temporal transferability of vehicle ownership models with special emphasis on exploring the effect of model structure on temporal transferability. The performance of potential updating methods for making the models more transferable are also compared. The household survey data collected from Dhaka, Bangladesh in 2005 and 2010 have been used in this regard. Different forms of random utility and count regression models of car, motorcycle, and bicycle ownership have been developed using income and household size, and number of workers, children, and licensed drivers as explanatory variables. The temporal transferability of each model between the two time periods has been compared rigorously using statistical tests. Results indicate that the multinomial logit model has better temporal transferability than the count regression models. In relation to model updating, the combined transfer estimation method for model updating is found to perform better than the Bayesian updating. The findings can provide useful guidance during application of a pre-existing model in the context of a developing country.