A Joint Model System of Mode Choice, Destination Choice, and Departure Time Choice for Nonwork Trips

(PI: Chandra Bhat)

Mode choice, departure time choice, and destination choice are important components of a travelers' trip-making decisions. At an aggregate level, these choices determine the number and spatial-temporal pattern of vehicle trips on urban roadways. Consequently, understanding the factors that affect travelers' mode, departure time, and destination choice is a necessary pre-requisite to examining the potential effectiveness of policy measures aimed at alleviating traffic congestion and reducing mobile-source emissions.

In the travel demand literature, departure time choice has received relatively little attention compared to the other choice dimensions characterizing trips. In this project, we are explicitly modeling the time-of-day dimension of choice jointly with the travel mode and destination choice dimensions. Such a joint model will enable the evaluation of transportation control measures (TCMs) which are specific to certain time periods of the day and to certain spatial corridors. For example, congestion pricing is likely to be implemented in select corridors in an urban area. Such a TCM will not only have an impact on travel mode, but may also affect departure time and destination choices of individuals. Thus, an individual may shift her/his shopping trip from the PM peak period to the PM off-peak period, or may change her/his location for shopping, in response to a congestion pricing scheme. The propensity for these shifts may be a function of the congestion pricing as well as individual socio-demographics and network characteristics. Understanding the temporal and spatial displacements of travel is not only important to evaluate the effects of policy actions on traffic congestion, but also to assess the impact on the spatial-temporal pattern of mobile-source emissions.

The focus is on nonwork trips in the proposed project. The field of travel demand modeling has, in general, paid substantially more attention to the work trip relative to nonwork trips. Nonwork travel, however, accounts for about three-fourths of the total trips in urban areas and projections suggest that this proportion is only likely to increase as suburbanization and lifestyle changes impact individuals' travel

Keywords: Destination choice and travel mode choice modeling, non-work trip modeling, urban travel demand forecasting.