conference paper
Phd Dissertation |
Jan 2008
research report
The COVID-19 pandemic has had a significant impact on public transit ridership in the United States, especially for rail transit. Land use, development density, and the pedestrian environment are strongly associated with station-level transit ridership. This study examines how these characteristics affect transit ridership pre- and post-COVID and how they differ across station types based on longitudinal data for 242 rail stations belonging to Bay Area Rapid Transit, San Diego Metropolitan Transit System, Sacramento Regional Transit, and LA Metro between 2019 and 2021. We found overall a 72% decrease in station-level ridership, but changes were not uniform. Station areas with a higher number of low-income workers and more retail or entertainment jobs tend to have lower ridership declines, while areas with a large number of high-income workers, high-wage jobs, and higher job accessibility by transit had more ridership losses. When comparing station area ridership and activity changes based on mobile phone user data, ridership declined more drastically than activity across all four rail systems, which implies that rail transit riders switched to other modes of transportation when accessing the station areas. Given these findings, it is likely that rail transit services oriented toward commute travel, especially core station areas with jobs for higher income workers, will continue to have an uneven recovery, posing critical implications for transit resilience planning and equity in the post-pandemic era. Considering sources of funding other than passenger fares to sustain rail transit, strategizing to reinvent and reinforce downtowns as destinations, and shifting rail transit services to appeal to non-commute travel can be promising strategies to support rail transit.
published journal article |
Dec 2025
policy brief |
Sep 2024
working paper
In this essay we offer a view of what economics can say about and learn from urban structure. In doing so, we reach into neighboring disciplines; but we do not aspire to a complete survey even of urban economics, much less of the related fields of urban geography or urban planning. Our focus on internal structure should provide Mayor Daley a more complete basis for comparing Chicago’s density to that of New York, or its degree of centralization to that of Los Angeles. (Throughout this essay we use the word “city,” or the name of a particular city, to mean an entire urban region; other terms with similar meanings are “metropolitan area” and “urban area.”)
working paper |
Aug 1993
working paper |
Sep 1994
working paper |
Oct 1995
working paper |
Oct 1995
research report
This project further adapt and enhance the previous research of relevance to event-based Advanced Traveler Information Systems (ATIS) and implement the algorithms for traffic management in Anaheim. This study is also answering some basic questions in ATIS implementation associated with routing strategies, driver’s compliance and network performance. This research develops algorithms for static and dynamic optimal Changeable Message Signs (CMS). The optimized CMS schemes are based on performance evaluations using a traffic simulation-based evaluation model, DYNASMART (Dynamic Network Assignment Simulation Model for Advanced Road Telematics). Performance of ATIS depends on drivers’ compliance behavior, and the compliance issue is addressed in this research. This study develops a framework of driver’s compliance model, and incorporates it into the evaluation framework. The model includes inherent value of guidance system, and the value is analyzed via day-to-day update approach. A limited field test is implemented for the event traffic management. The implementation involves the Caltrans-UCI ATMS research testbed framework at the UCI Institute of Transportation Studies, as well as the physical hardware available for communication to the city of Anaheim. The analytical and heuristic algorithms proposed for use here include those for static and dynamic traffic simulation-assignment. The essential part of algorithmic research is to adapt the network optimization algorithms to generate traffic rerouting plans, which involve aggregation of network paths and their translation to a format usable for changeable message signs existing in Anaheim, as well as other event-based information supply hardware.
working paper |
Jun 1999
research report
published journal article
published journal article
This paper presents the first investigation of the effects of optimal energy taxation in an urban spatial setting, where emissions are produced both by residences and commuting. When levying an optimal direct tax on energy or carbon use is not feasible, the analysis shows that exactly the same adjustments in resource allocation can be generated by the combination of a land tax, a housing tax, and a commuting tax. We then analyze the effects of these taxes on urban spatial structure, showing that they reduce the extent of commuting and the level of housing consumption while increasing building heights, generating a more-compact city with a lower level of emissions per capita.
published journal article
published journal article
Based on the analysis of case studies carried out in seven US cities, attempts to evaluate the potential for expanding the role of private provision of urban commuter bus services. Describes the type and extent of present schemes, the viability of non-subsidized schemes, the issues involved in subsidizing, and finally, assesses the problems and potential of private provision.-R.Land
published journal article
This study examines changes in activity-travel patterns of employed people during a recession by using a tour-based representation of the activity-based approach. The term tour is defined as a sequence of trips and activities that begins and ends at home and contains at least one non-home activity. Tours are classified based on the presence of work and/or non-work activities. We are interested in investigating how a recession can affect an individual’s tour choices. We developed a rigorous methodological framework by using multi-group structural equation modeling (SEM) to analyze changes in tour choice. In particular, we developed a causal structure conceptualsizing the interrelationships among socio-demographic and economic characteristics, activity-travel participation, and the choice of various work and non-work tours. Using data from the American Time Use Survey (ATUS), the study found that activity-travel relationships and their role in tour choice differed in the recession year (2009) compared to pre- and post-recession years (2009 and 2012, respectively). By analyzing temporal changes in causal structure, we identified four sub-trend groups defined by: (1) norms that did not change in pre-, during, and post-recession years, (2) norms that changed during the recession but returned to the old norm, (3) norms that changed during the recession and were maintained as new norm, and finally (4) 2006 norms that did not change during the 2009 recession but changed after the recession. Via analysis of multiple group SEM, we identified instances of each of these cases and provided potential rationales in the context of how a recession can influence norms and thus can affect activity-travel behavior.