Methodological Issues in Developing Mode Choice Models for Dhaka, Bangladesh

Abstract

This paper presents issues and challenges associated with development of a comprehensive mode choice model for Dhaka, the capital of Bangladesh and the 11th largest city in the world. As in most other developing countries, reliable level-of-service data are not available for the wide variety of motorized and nonmotorized modes used by travelers in Bangladesh. In addition, the 12 million inhabitants of Dhaka have wide differences in affordability of and accessibility to various modes. These differences result in substantial heterogeneity in inhabitants' choice sets. These choice sets are also unobserved in the data and not easily inferable from the limited information of the network. This paper identifies key limitations of the available data and proposes methods to overcome those limitations. A probabilistic choice set of modes from a small-scale stated preference survey has been used to account for the absence of actual choice set data. The systematic and stochastic errors in the network-derived time data are explicitly accounted for in the model structure. The improvements from the proposed approaches are demonstrated by prediction tests using holdout samples. The proposed approaches have immense potential to improve travel mode choice models for other cities of Bangladesh, as well as cities in other developing countries, which very often face similar data issues.

A comprehensive model to capture the preference for mass rapid transit in Dhaka

“…Value of time (VOT) has been calculated from the estimated model parameters as an alternative to demonstrate the improvement of the current model from the previously developed mode choice models for Dhaka city. However, a prediction test of the RP portion of the model has been presented in Enam and Choudhury (2011).…”

“…It may be noted that a indicates the fixed component of the measurement error (if any), b indicates the systematic scale difference between the true and the measured values (if any) and e represents the random part of the error. The methodology is further elaborated in Enam and Choudhury (2011). The basic difference between the approaches proposed in this work and that followed by Walker et al (2008) is that the travel time has been treated here as an observed variable with some measurement errors, while in the latter case travel time has been treated as a latent variable.…”

Modelling the Behavioural Response to Congestion Pricing in Dhaka, Bangladesh

“…The estimated cost and time coefficients indicate an average value of time (VOT) of 101.19 BDT/h. It may be noted the VOT derived from an RP study conducted around the same period reported VOT to be 106.80 BDT/h [13]. The similarities in the values serve as an indirect validation of the current study.…”

“…Among the previous models, Ahsan [2], DITS [10], Habib [16], STP [29], Hasan [17], DHUTS [9] and Enam and Choudhury [13,14] are noteworthy. However, these models are either based on revealed preference (RP) data and/or focus on SP data with improved public transport options, and none of them have explored the potential response to congestion pricing or any other car restriction policy.…”

Application of Discrete Choice Models for Exploring Traveller’s Behaviour at Egyptian Transport Network

“…The sensitivity analyses executed on the level-of-service characteristics explained their proportional flexibility suspected for each travel mode and for a specific trip aim. Enam and Choudhury [10] specified the essential restrictions on the obtainable information accompanied with the derivation of an inclusive modal split model for the capital of Bangladesh, Dhaka which is the 11th largest city in the world in resident's number. They suggested procedures to conquer those restrictions.…”