  This work considers the sensitivity of commute travel times in US metro areas
due to potential changes in commute patterns, for example caused by events such
as pandemics. Permanent shifts away from transit and carpooling can add
vehicles to congested road networks, increasing travel times. Growth in the
number of workers who avoid commuting and work from home instead can offset
travel time increases. To estimate these potential impacts, 6-9 years of
American Community Survey commute data for 118 metropolitan statistical areas
are investigated. For 74 of the metro areas, the average commute travel time is
shown to be explainable using only the number of passenger vehicles used for
commuting. A universal Bureau of Public Roads model characterizes the
sensitivity of each metro area with respect to additional vehicles. The
resulting models are then used to determine the change in average travel time
for each metro area in scenarios when 25\% or 50\% of transit and carpool users
switch to single occupancy vehicles. Under a 25\% mode shift, areas such as San
Francisco and New York that are already congested and have high transit
ridership may experience round trip travel time increases of 12 minutes (New
York) to 20 minutes (San Francisco), costing individual commuters \$1065 and
\$1601 annually in lost time. The travel time increases and corresponding costs
can be avoided with an increase in working from home. The main contribution of
this work is to provide a model to quantify the potential increase in commute
travel times under various behavior changes, that can aid policy making for
more efficient commuting.
