Abstract:For the last three decades, policy makers and transportation planners have devised a series of policy instruments to tackle traffic congestion, starting with supply and demand controls. Transportation Systems Management (TSM) and Transportation Demand Management (TDM) programs are well-known classes of such policy strategies. Although many of these strategies have been implemented, they have failed to reduce traffic congestion. One of the reasons for this failure is that there is often a discrepancy, sometimes large, between the responses to congestion that are assumed by policy makers and those that are actually adopted by individuals. This mismatch in behavioral responses makes policies less effective, and needlessly consumes large amounts of time and money in their trial-and-error implementation.

As one of a series of studies on individuals' adoption and consideration of travel-related strategies in response to congestion, this study explores the relationships between the adoption and consideration of bundles of travel-related strategies by identifying characteristics associated with patterns of adoption and consideration among bundles, and by developing discrete choice (binary logit) models for individuals' consideration of each bundle. In particular, we focus on whether the adoption of lower-cost, short-term strategies significantly and/or dynamically (using time since adoption variables) affects the consideration of higher-cost, longer-term ones. We also investigate whether individuals with a high liking for travel, indicative of a positive utility of travel, are resistant to higher-cost, longer-term travel-reduction strategies.