The age structure of America is changing. Today, about one in eight Americans are senior residents who are 65 years of age or older, compared to one in 10 in the 1950’s. By 2030, one in five Americans will be 65 or older. The number of senior residents in San Diego County will more than double from 2008 to 2050.

The aging of America may lead to substantial impacts on all areas of society, including the impacts on travel demand and travel patterns. A good understanding of the relationships between aging population and travel patterns will help policymakers identify strategies and actions to plan for alternative future scenarios. This paper is based on a sensitivity analysis of travel patterns, under various population aging scenarios, using the recently completed SANDAG Activity-Based Model (ABM).

First, this paper discusses three aging scenarios. The base scenario is ‘Baby Boom in Place,’ which assumes low levels of migration so that San Diego’s current Baby Boomers ‘age in place.’ The second scenario is ‘Older Population,’ which assumes more retirees move to San Diego as a retirement destination, thus increasing the median age of the population. The third scenario is ‘Younger Population,’ which assumes San Diego’s Baby Boomers begin to leave the region to retire elsewhere, thus deceasing the median age of population.

Second, this paper describes how the three aging scenarios are incorporated in the ABM via the Population Synthesizer. The methodology of generating the control targets of the Population Synthesizer is also discussed.

Third, this paper describes and compares the results from the ABM for the three scenarios. More specifically, statistical analysis is conducted on auto, transit, and non-motorized shares, travel time of day choices (peak vs. non-peak), number of trips by different trip purposes (mandatory vs. non-mandatory), travel destinations (employment center vs. non-employment centers), vehicle miles travelled (VMT), and average trip length and duration.

Finally, this paper discusses the findings of the impact of aging population on regional travel demand and travel patterns, in the context of regional long range transportation planning and how the research may assist policymakers in their decision making process.