Concerns about the environmental impacts of transportation have turned reducing vehicle-miles traveled (VMT) into a policy priority. One way to decrease VMT is to reduce the length of commuting trips. Unfortunately, the average U.S. commute keeps getting longer. Prior research has investigated the determinants of commuting, but few have analyzed the linkage between housing costs and the length of commuting. This problem is especially salient in California given the state’s perennial housing shortage and the high costs of housing, which have forced many lower- and middle-class households to move inland in search of more affordable housing at the cost of longer commutes. Most of those commuting trips are by car. This project investigates these linkages using Generalized Structural Equation Modeling and analyzing 2012 CHTS data for Los Angeles County – the most populous county in the U.S. The model, which jointly explains commuting distance and time, accounts for residential self-selection and car use endogeneity, while controlling for household characteristics and land use around residences and workplaces. Better understanding the determinants of commuting is critical to inform housing and transportation policy, improve the health of commuters, reduce air pollution, and achieve climate goals.

UPDATED ABSTRACT: Recent California policy discussions suggest that the travel impacts resulting from strategies for housing growth are not well understood, in part because metropolitan growth has always occurred according to local zoning and land use plans. Fundamental alterations of local planning guidelines, in turn, have unknown transportation impacts. This project reviewed and synthesized policy and academic literature on housing-and-transportation linkages. The project team then applied a process developed in related research to categorize tour-based travel patterns and related these to household characteristics. The project team established connections between household tour behavior and residential variables, which were used to classify types of travelers. The focus of this research was on users of public transit and ride hailing services.

With the recent advent of telecommunications and information technologies, telecommuting becomes a rising trend as one of the most important alternative work arrangements. Moreover, due to the current worldwide outbreak of the COVID-19 disease, this choice has turned out to be a more vital one than ever. It is, therefore, crucial to identify the potential groups of workers who are more likely to be the telecommuters and to understand how the telecommuters schedule their daily activities and travel. The goal of this research is to address these issues. In particular, the team will perform the following three tasks: (1) identification of a number of distinct groups of telecommuters with a representative activity-travel pattern and a similar degree of telecommuting adoption (2) finding out similarities and differences in activity-travel behavior between national-level and regional-level (California) telecommuters and between commuters and telecommuters, and (3) investigation of impacts of telecommuting on individual’s time-use and tour behavior as well as the overall transportation system. Two large household travel survey datasets—2012 California Household Travel Survey (CHTS) and 2017 National Household Travel Survey (NHTS) will be used to conduct necessary analysis. This research is expected to provide valuable insights to policy makers on various telecommuter groups and their activity-travel patterns, adoption of telecommuting, and its impacts on travel.