Activity-Based Models

Activity-based models are the new generation of travel demand models. Activity-based modeling treats travel as being derived from the demand for personal activities. Travel decisions, therefore, become part of a broader activity scheduling process based on modeling the demand for activities rather than merely trips. These models have significant advantages over traditional trip-based models, usually based on a four-step paradigm, in explaining travel behavior and response to policies.

The growing complexity in travel patterns and the need to estimate changes in travel behavior in response to new policies and advanced technology call for a better understanding of such issues as the effects of new information and communication technologies on travel behavior, the effects of land use and growth management on travel behavior, and travelers' response to auto-restraining policies. Understanding such effects, which is essential for an improvement in the design of new policies, is the main motivation behind the development and advancement of activity-based models.

The basic notions of activity-based demand analysis and modeling can be found in the contribution of researchers T. Hägerstrand and F. S. Chapin, who postulate that the activity demand is motivated by basic human desires, such as the desire for survival, social encounters, and ego gratification. Hägerstrand's time geography theory focuses on personal and social constraints when explaining our need for activity participation, while Chapin focuses more on opportunities and choices rather than the constraints.

In activity-based modeling the basic travel unit is a tour defined as the sequence of trip segments that start at home and end at home. Some simplified versions of activity-based models, referred to as tour-based modeling, deal directly with tours without deriving them from the daily activity pattern as done in activity-based models. The explicit modeling of activities and the consequent tours and trips enable a more credible analysis of the responses to policies and of the subsequent effects of policies on traffic and air quality.

The rich spectrum of issues that activity-based models can account for include travel behavior changes in response to activity timing modifications, for example, flexible working hours and opening hours of stores; the impact of various land use policies on shifting activity patterns, such as mixed-use development, that increase walkable access to various activities; and the ability to consider the trade-off between out-of-home and in-home activities. This later feature is very important in analyzing the effect of technology advancement and Internet services on substituting out-of-home activities requiring travel with in-home-activities.

[Page 12]One of the main factors for the improved behavioral realism of activity-based models is their ability to consider the secondary effects of policies. Secondary effects are those adjustments to an activity pattern that are made in response to a primary impact. For example, a transit subsidy may result in a commuter changing the mode of travel for the trip between home and work from drive alone to transit; this is the primary effect of the policy. However, because the person no longer drives to work, it is not possible to stop on the way home to buy groceries. Therefore, when the person now returns home by transit, it is now necessary to take the car and drive to a nearby store. This is the secondary effect.

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