Demand Modelling of Cross-Regional Commuting Trips in Multimodal Networks

The continual expansion of major metropolitan areas caused by the inexorable urban sprawl away from city centres has produced persistent growth in the number of cross-regional trips. This research focuses on acquiring the required understanding of cross-regional travellers' travel behaviour by quantifying the effects of the key factors that influence their travel decisions. A practice-ready framework for modelling cross-regional travel demand in the context of multimodal transportation networks is presented. The framework adopts a comprehensive mode choice model that takes into account the three main decisions faced by intermodal travellers, namely the main mode, access mode, and access station location choices. The three choices and their interactions are carefully considered in the different phases of the model development.;The modelling framework is developed over two phases. In phase I, data from a travel survey are used along with detailed information on transit stations to develop access station choice models for regional and local transit park-and-ride users. In phase II, the access station choice models are utilized within an innovative multimodal trip planner tool that is developed and integrated with the Survey of Cross-Regional Intermodal Passenger Travel (SCRIPT). SCRIPT is an online respondent-customized survey that consists of three sections, collecting revealed preference (RP) data, stated preference (SP) data, and household and personal information. Using SCRIPT's RP/SP data, a set of advanced econometric joint main mode and access mode choice models are developed. The joint RP/SP models reveal meaningful insights into cross-regional commuters' mode choice behaviour. The developed models are validated and calibrated to develop the Interactive Model for Policy Analysis of Cross-Regional Travel (IMPACT) to be used for the prediction of corresponding changes in aggregate modal shares in response to the introduction of new policies. As such, the developed models offer a significant step forward in modelling cross-regional travel decisions by introducing a policy-sensitive travel demand modelling framework.