Public transport demand estimation by calibrating the combined trip distribution-mode choice (TDMC) model from passenger counts: A case study in Bandung, Indonesia

The paper discusses the development of methods and techniques for modelling the public transport demand using low-cost and easily-available traffic (passenger) count information and other simple zonal-planning data. The paper will report on a family of aggregate model combined with a family of mode choice logit model which can be calibrated from traffic (passenger) counts and other low-cost data. The model examined was the Gravity (GR) model combined with the Multi-Nomial-Logit (MNL) model. Non-Linear-Least-Squares (NLLS) and Maximum-Likelihood estimation methods were used to calibrate the parameter of the combined model. The combined TDMC model and the calibration method have been implemented into a micro-computer package capable of dealing with the study area consisting of up to 300 zones, 3000 links and 6000 nodes. The approach has been tested using the 1999 Public Transport Data Survey in Bandung (Indonesia). The model was able to obtain the calibrated parameters which can then be used for forecasting purposes. However, the results were not so encouraging due to the poor public transport data and poor O-D public and private transport matrices. General conclusion regarding the advantageous and the applicability of the approach to other environments are given at the end of the paper.