Measuring the impact of COVID-19 policies on local commute traffic: Evidence from mobile data in Northern California

Abstract

The COVID-19 pandemic upended the world economy and significantly altered how people work by imposing limits on in-person interactions. The policy response in places like California illustrate a range of scenarios that are applicable more broadly, from stringent restrictions on travel to flexible directives. This study focuses on the impact of various policy instruments the State of California implemented on morning peak hour and home-based work traffic volume in the San Francisco Bay Area and California’s Central Valley. Previous studies have not been able to measure COVID-19′s impact on commute traffic at a sufficiently local level, nor have they tested the impact of policy instruments on local commute traffic. We fill this gap by using mobile-derived morning peak hour traffic volume data from StreetLight Insights along with census-based neighborhood socioeconomic characteristics to model neighborhood-level variation in morning traffic volume and distance traveled. Remote work, a policy the private sector initiated, had a more significant and lasting effect than state policy. Morning traffic volume did not recover in response to policies aiming to provide businesses and people greater flexibility and predictability, and while vaccination was associated with a recovery of morning peak hour and home-based traffic, that recovery was short of pre-COVID levels. The effect of remote work undergirds inequities in commute burden. Economic sectors deemed essential and lower-income workers saw the lowest decreases in commute traffic and fastest recovery. Policymakers and planners ought to consider the occupation mix as a key ingredient in understanding the impact of telework ability and takeup on future transportation infrastructure improvements across various regions.