According to Moss and Qing (2012), super commuters are on the rise in the US.  In their recent analysis, a super commuter works in the central county of a metropolitan area, but lives beyond the boundaries of that metropolitan area, commuting long distances by air, rail, car, bus, or some combination.  This is a definition based on distance.  According to the US Census Bureau (2005), extreme commuters are also growing, defined as workers who travel 90 minutes or more to work, one-way. A definition based on time.  This paper seeks to improve upon these methods for defining a “long” commute.  Using the 2006-10 American Community Survey(ACS) we examine the spatial patterns, demographic, and transportation characteristics of commuters who travel either 50 or more miles or 60 minutes or more to get to work, utilizing the mean travel times and average block-to-block distances traveled for individual home-to-work flows.

The analysis will evaluate the national, county-level and metropolitan area patterns of “extreme” or “super” commuting, examining time and distance, first, independently, and then jointly. We will analyze the commutes determining the county-to-county flow pairs with the highest average distance and time; noting counties with the highest distance traveled, and extremes in inflow and outflow.   We plan to map the long commutes by counties and metropolitan areas and examine these measures in relationship to travel mode choice, in the presence of demographic characteristics such as income, age, marital status, presence of children, gender, and occupation.

Additionally, Alameda County, CA and Washington, DC will be study areas to compare changes in travel time and distance over the decade.  Alameda County, CA, which contains San Jose, experienced fast growth in recent decades due to computer and internet companies that migrated there and flourished. With this growth in business came an imbalance in jobs and housing, creating longer commutes (see Cervero 1996).  In contrast, Washington, DC has experienced steady growth, but Washingtonian commuters still report some of the longest commute times in the US. Using the 2000 Census Transportation Planning Package and the 2006-10 ACS we have the same data for both sites from two periods.  This will enable us to address the question of how commute times, distances traveled, or commute mode choice may change over time.  Those results will better inform how to define extreme commutes.