For over half a century, travel demand models have been used to project travellers’ behaviour under different circumstances such as demographic and economic growth, network improvements and policy changes. The resulting forecasts have been used as the basis for road, transit and other infrastructure investment decisions, so much relies on getting the forecasts ‘right.’ Of course, forecasting is inherently a highly uncertain process: On the one hand, much effort has been spent over the past several years to replace the traditional four-step model with much more rigorous and representative algorithms, such as tour- or activity-based micro-simulation models. On the other hand, even with new algorithmic improvements coming into practice, the application of travel demand models still has not fully addressed the need to improve the credibility and reliability of the outputs. Moreover, the types of issues for which decisions must be made, and the audience that constitutes the decision-makers themselves, are changing. Examples of the former concern changing traveller behaviour to use sustainable transportation modes. As for the latter, financial decision-makers now have a key role, along with engineers and planners, in determining whether or not a project proceeds to implementation: this is true both for projects that are financed entirely with public funds or externally through a public-private partnership. The implications on model development and application are many. They include: • The need to account for pricing (such as tolls) and how people make trade-offs (values of time, values of reliability, etc.) • Changing needs for model validation, to ensure that the model is appropriate to the problem at hand and provides the necessary information at an acceptable level of reliability and credibility to satisfy information requirements. • The types of data that are needed to support these applications. In the end, models must be used to build a credible and reliable ‘case’ – whether it is a business case for internal or external funding approvals, or a case to demonstrate the GHG-reduction impacts of a proposed transit investment for public scrutiny. The paper discusses the changing roles for models and their forecasts in the context of new planning requirements (e.g., sustainability and financing); who needs information and what kind of information they need from the models; the importance of improving model reliability and credibility; and the techniques and data for making these improvements. The paper draws from experience in Canada and the United States, where local and state authorities have had to start positioning themselves to accommodate alternative financing (such as P3) and address new initiatives (such as TDM). The paper will be of interest to Canadian government agencies at all levels that are charged with making investment decisions to meet growing transportation demand and emerging mobility needs.
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