| description abstract | Mode choice models used for travel demand forecasting generally include “major” transportation modes of driving, ridesharing, walking, and riding public transit. In the Toronto Area, these make up 96% of all trips. This paper describes the challenge of realistically modeling “minor” modes, while maintaining behavioral realism in the rest of the model. This is critical to public policy since increasing the mode share of bicycling, commuter rail, and school bus has the potential to reduce emissions, save on expensive auto infrastructure, encourage healthier lifestyles, reduce congestion, and support liveable communities. The tour-based model presented in this paper simulates household interactions as part of the mode choice process. Model parameters are estimated using a choice-based sample of tours in the Toronto Area and a genetic algorithm. The model shows very good results for commuter rail and school bus modes, but limited success for the drive access subway, taxi, and bicycle modes. Representation of niche markets through restricted choice sets allows for a parsimonious utility function that includes level of service, land-use, activity, and socioeconomic variables. | |
