conference paper

Identifying Types of Telecommuters Based on Daily Travel and Activity Patterns

Abstract

The ongoing health crisis of the COVID-19 pandemic and the imposed social distancing measures have led a significant portion of workers to adopt “working from home” arrangements, which have greater impacts on workers’ daily activity-travel routines. This new-normal arrangement will possibly be sustained in large measure since the pandemic returns at a certain interval with its new variants. This study explores the activity patterns of workers exclusively working from home (telecommuters) after the initial 2020 pandemic year and deemed as “the 2021 post-vaccine” year. The research classified the activity patterns of telecommuters via Latent Class Analysis. The model results suggest that telecommuters’ activity patterns can be split into three distinct classes where each class is associated with several socio-demographics. Class 1 constituted workers from high-income households who tend to have a conventional work schedule but make non-work activities mostly in the evening. Class 2 was composed of workers from low to medium income, non-Asian households whose work is not pre-dominate but with out of home non-work activities spread throughout the day. Last, Class 3 members are workers of middle to older age, living without children, who primarily remain at home during the day with a conventional work schedule. If telecommuting is to continue at levels much greater than prior to the pandemic, then research insights regarding the variations of activity-travel demands of telecommuters could help to make telecommuting a successful travel demand management tool.

conference paper

Heterogeneity in Activity-travel Patterns of Public Transit Users

Abstract

Public transit is considered a sustainable mode of transport that can address automobile dependency and provide environmental, economic, and societal benefits. However, with typical temporal and spatial constraints such as fixed routes and schedules, transfer requirements, waiting times, and access/egress issues, public transit offers lower accessibility and mobility services than private vehicles and thus it is considered a less attractive mode to many prospective users. To improve the performance of transit and in turn to increase its usage, a broader understanding of the daily activity-travel patterns of transit users is fundamental. In this context, this study analyzed transit-based activity-travel patterns by classifying users via Latent Class Analysis (LCA). Using data from the 2017 National Household Travel Survey, the LCA model suggested that transit users could be split into five distinct classes where each class has a representative activity-travel pattern. Class 1 constituted employed white males who made transit-dominant simple work tours. Class 2 was composed of employed white females who made complex work tours. Employed white millennials comprised Class 3 and made multimodal complex tours. Transit Class 4 were non-white younger or older adult groups who made transit-dominant simple non-work tours. Last, Class 5 members made complex non-work tours with recurrent transit use and comprised single older women. This study provided insights regarding the variations of activity-travel patterns and the associated market segments of transit users in the United States. The results can assist transit agencies in identifying transit user groups with particular activity patterns and considering market strategies that can address their travel needs.

published journal article

How do they get by without cars? An analysis of travel characteristics of carless households in California

Abstract

In spite of their substantial number in the U.S., our understanding of the travel behavior of households who do not own motor vehicles (labeled “carless” herein) is sketchy. The goal of this paper is to start filling this gap for California. We perform parametric and non-parametric tests to analyze trip data from the 2012 California Household Travel Survey (CHTS) after classifying carless households as voluntarily carless, involuntarily carless, or unclassifiable based on a CHTS question that inquires why a carless household does not own any motor vehicle. We find substantial differences between our different categories of carless households. Compared to their voluntarily carless peers, involuntarily carless households travel less frequently, their trips are longer and they take more time, partly because their environment is not as well adapted to their needs. They also walk/bike less, depend more on transit, and when they travel by motor vehicle, occupancy is typically higher. Their median travel time is longer, but remarkably, it is similar for voluntarily carless and motorized households. Overall, involuntarily carless households are less mobile, which may contribute to a more isolated lifestyle with a lower degree of well-being. Compared to motorized households, carless households rely a lot less on motor vehicles and much more on transit, walking, and biking. They also take less than half as many trips and their median trip distance is less than half as short. This study is a first step toward better understanding the transportation patterns of carless households.

research report

Policies to Improve Transportation Sustainability, Accessibility, and Housing Affordability in the State of California

Abstract

This report presents an analytical review of empirical research on the interactions between housing availability and production, travel behavior, accessibility, land use policies, and transportation policies. It identifies lessons from this review for California state legislative efforts to improve housing and transportation linkages, and to increase both transportation sustainability and housing affordability. Relevant California state efforts include legislation to influence parking standards; to require up-zoning near transit stations; to influence regional housing and transportation planning goals; and to change environmental review to focus on reducing vehicle miles traveled instead of accommodating road traffic.

dataset

Truck idling and parking data for AB 617 disadvantaged communities study

Abstract

This project investigates air pollution in California communities disproportionately affected by their proximity to transportation corridors, industrial facilities, and logistics centers, focusing on truck-related activities, including idling, parking search, and parking demand, using comprehensive datasets and robust models employing techniques such as Random Forest, Convolutional Neural Network, Bayesian Ridge Regression, and Spatial Error Model. Key findings reveal factors affecting idling times, parking search times, and parking demand, with heavy-duty trucks having the highest idle times and parking search challenges concentrated around transportation arteries and freight yards. The Spatial Error Model highlights relationships between truck activities, socio-economic variables, and air pollution in AB 617 communities. Based on these findings, preliminary policy recommendations include targeted anti-idling campaigns, improved truck parking facilities, cleaner fuels and technologies, enhanced routing efficiency, stricter emission standards, and strengthened land-use planning.

Please reach out to the project Principal Investigator for more information.

published journal article

Examining the Effects of the Sacramento Dockless E-Bike Share on Bicycling and Driving

Abstract

One way cities are looking to promote bicycling is by providing publicly or privately operated bike-share services, which enable individuals to rent bicycles for one-way trips. Although many studies have examined the use of bike-share services, little is known about how these services influence individual-level travel behavior more generally. In this study, we examine the behavior of users and non-users of a dockless, electric-assisted bike-share service in the Sacramento region of California. This service, operated by Jump until suspended due to the coronavirus pandemic, was one of the largest of its kind in the U.S., and spanned three California cities: Sacramento, West Sacramento, and Davis. We combine data from a repeat cross-sectional before-and-after survey of residents and a longitudinal panel survey of bike-share users with the goal of examining how the service influenced individual-level bicycling and driving. Results from multilevel regression models suggest that the effect of bike-share on average bicycling and driving at the population level is likely small. However, our results indicate that people who have used-bike share are likely to have increased their bicycling because of bike-share.

published journal article

Does Bike-share Enhance Transport Equity? Evidence from the Sacramento, California Region

Abstract

This study examines the rate of bike-share adoption by individuals from different socio-demographic groups and living in different bicycling contexts, as well as how individuals incorporate bike-share service into their travel patterns for different travel purposes and change their use of other modes. Data are from a two-wave survey of bike-share users and a parallel household survey of residents in the Sacramento region. Modeling results for bike-share adoption and use frequency show that low-income individuals are less likely to adopt bike-share but use the service more frequently than other income groups when they do adopt. Low-income users, people of color, and non-auto owners are more likely than other groups to use bike-share frequently for many trip purposes. Individuals living in areas with a stronger biking culture and surrounded by bike infrastructure are less likely to adopt the service and less likely to use it for purposes other than commuting. All users change their use of other modes when they incorporate bike-share into their travel patterns, but low-income individuals, people of color, and non-auto owners would be more severely impacted if the service were to stop.

policy brief

Travel Varies Greatly Between Voluntary Versus Involuntary Carless Households in California

Abstract

In spite of the critical importance of mobility for quality of life and economic well-being, the travel behavior of households without motor vehicles has received insufficient attention even though “carlessness” may bethe most vivid expression of mobility disadvantage in our car-centric society. Approximately 10.6 million (9 %) of U.S. households do not own a motor vehicle (car, pickup, van, SUV, or motorbike), including over one million in California. These “carless” households form two groups: (1) involuntarily carless households who are forced to live without cars, and (2) voluntarily carless households who chose to do so. Since one of the strategic goals of federal transportation policy is “to increase transportation choices and access to transportation services for all” it is essential to understand the travel behavior of households who are unable to own a motor vehicle. Indeed, many involuntarily carless households are experiencing economic hardship, disabilities, racial and age discrimination, or cultural barriers. Understanding the travel pattern of voluntarily carless households is also necessary to formulate policies aimed at decreasing vehicle use. Reducing personal vehicle use would help relieve congestion, decrease road accidents, improve air quality, cut emissions of greenhouse gases, and improve the health of people who switch to more active modes, such as walking and biking.

policy brief

Shifting Transit Use in COVID-19 Pandemic and Its Implications for Transit’s Recovery

Abstract

During the first year of the COVID-19 pandemic, public health and transit agency officials recommended that people drastically curtail their interactions with others to slow the spread of illness. On public transit, where strangers congregate on large vehicles and travel together, the decline in riders was especially dramatic. While walking, biking, and driving, which enable social distancing, substantially recovered in 2021 to pre-pandemic levels, transit use remained – and remains – depressed. But transit use neither fell nor recovered uniformly over the course of the pandemic. While ridership declined in most places, it did so unevenly across neighborhoods and users. Our research suggests that in the early part of the pandemic, transit use declined more dramatically among higher-income people, who were more likely than lower-wage workers to work from home. Because people who owned automobiles could travel about without coming in close contact with strangers, and because vehicle access is positively related to income, those who rode transit early in the pandemic were more likely to be low-income, Black, Hispanic, and immigrants than pre-pandemic transit riders.With many workers still working from home, at least part-time, it is not clear when – or whether – transit trips into and out of major office centers will recover to their former levels. If that is the case, transit demand and service will likely continue to center around lower-income neighborhoods.

policy brief

Student Transportation Options Provided by California Community Colleges Often Limited to Parking Permits and Transit Passes

Publication Date

November 17, 2022

Author(s)

Madeline Brozen, Rasik Hussain, Nicole Matteson