Developing passenger mode choice models for Brisbane to reflect observed travel behaviour from the South East Queensland Travel Survey

The South East Queensland Infrastructure Plan and Program 2007-2026 was developed to identify the needs of the expected growth, with an estimated cost of $20.5 billion. The plan has listed sixty-five major transport projects for the study area, including busways to serve the northern and eastern suburbs, a rail line to the new major urban development at Springfield and the Gateway Motorway upgrade. In order to examine these infrastructure initiatives in terms of expected demand for each mode and impact on travel patterns, a multi-modal strategic transport model is essential. This paper presents the methodology used in developing a fully-functional mode choice module capability to be incorporated into the Brisbane Strategic Transport Model (BSTM); capable of estimating mode shares in a multi-modal travel environment. The new mode choice module consists of unique logit models developed for eight trip purpose categories namely home-based work (white collar) (HBW-W), home-based work (blue collar) (HBW-B), home-based education (primary & secondary) (HBE-PS), home-based education (tertiary) (HBE-T), home-based shopping (HBS), home-based other (HBO), work-based work (WBW) and other non-home-based trips (ONHB). The model specification developed for the mode choice module consists of two private vehicle modes of car as driver and car as passenger; three public transport modes of walk to public transport, park and ride and kiss and ride; and two non-motorised modes of walking and cycling all-the-way. The models were estimated using the revealed preference data collected in the 2003/04 South East Queensland Travel Surveys (SEQTS). A number of nested logit structures were tested along with simple multinomial logit model specifications, in order to determine the most appropriate model representing the targeted population, for each trip purpose. This paper presents the final model estimation results for each trip purpose; and discusses the statistical significance and stability of the estimated coefficients and the mode-specific constants, along with illuminating the main findings. The percentage modal split, determined from the values of the estimated parameters, is also presented and examined for each trip purpose. Finally, the paper presents a few examples of the sensitivity analysis conducted on various level-of-service attributes, in order to surmise the relative elasticity of the parameter for all the modes for a certain type of trips. The model estimation results for home-based work trips, modelled separately for white and blue collar workers, indicated a significant difference in the estimated coefficients' values pointing towards the distinctly dissimilar travel behaviour of the two set of respondents for travelling to work. Similarly, the unique models calibrated for HBE-PS and HBE-T showed a substantial disparity in the estimated mode shares. No primary or secondary school trip-maker was found to use park and ride as a valid travelling option, while more than 5% tertiary education trips were estimated to be carried out using the mode. The demographic characteristics of the household were found to have a significant influence on the mode choice for most of the trip purposes. An interesting finding from the model estimation runs was that these variables, when employed in the utility functions of car modes, mostly showed an enormous influence in driving the mode shares in favour of car. It indicates that the car-ownership and household variables play a considerable role in the mode choice decision-making process for each trip purpose. After conducting various sensitivity analyses, it was observed that most of the level-of-service variables were adequately inelastic to all the modes for all trip purposes, except for HBW-W, HBE-PS and HBE-T trips. Hence, apart from these three trip types, it is concluded that the variation in the values of most of the mode choice influencing parameters, such as in-vehicle travel time or out-of-pocket trip fare of public transport, are not likely to considerably divert the mode shares in favour of non-car modes.