working paper

Seamless Travel: Measuring Bicycle and Pedestrian Activity in San Diego County and its Relationship to Land Use, Transportation, Safety, and Facility Type

Abstract

This paper provides the data collection and research results for the Seamless Travel project. The Seamless Travel Project is a research project funded by Caltrans and managed by the University of California Traffic Safety Center, with David Ragland, PhD., as the Principal Investigator and Michael Jones as the Project Manager. The project is funded by Caltrans Division of Innovation and Research and is being conducted by the Traffic Safety Center of University of California Berkeley and Alta Planning + Design.

Measuring bicycle and pedestrian activity is a key element to achieving the goals of the California Blueprint for Bicycling and Walking (the Blueprint). Meeting these goals, which include a 50% increase in bicycling and walking and a 50% decrease in bicycle and pedestrian fatality rates by 2010, and increases in funding for both programs, will require a quantifiable and defensible base of knowledge. This research helps meet two of the Blueprint’s major strategic objectives: (1) collecting data on volumes and facilities, and (2) determining the most cost-effective methods of estimating bicycle and pedestrian collision rates.

published journal article

Heterogeneity in Activity-travel Patterns of Public Transit Users: An Application of Latent Class Analysis

Transportation Research Part A: Policy and Practice

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 to consider market strategies that can address their travel needs.

Suggested Citation
Rezwana Rafiq and Michael G. McNally (2021) “Heterogeneity in Activity-travel Patterns of Public Transit Users: An Application of Latent Class Analysis”, Transportation Research Part A: Policy and Practice, 152, pp. 1–18. Available at: 10.1016/j.tra.2021.07.011.

Phd Dissertation

Heterogeneity in Motorists' Preferences for Time Travel and Time Reliability: Empirical Findings from Multiple Survey Data Sets and Its Policy Implications

Abstract

The deregulation experience in airline, banking, and telecommunication suggests that the heterogeneity in consumers’ preferences has important policy significance. However, the varied nature in motorists’ preferences has been hardly recognized in urban passenger transportation sector. In this public sector, the public authority generally offers a uniform class of services to all potential users. This dissertation employs the new advances in econometrics on survey data sets from road pricing experiment in Los Angeles area to study the diversity in motorists’ preferences for travel time and travel time reliability. The empirical findings are used to explore the efficiency and distributional effects of road pricing that accounts for users’ heterogeneity. This dissertation found substantial heterogeneity in motorists’ preferences for both travel time and travel time reliability. Furthermore, based on a simulation model, this dissertation found that road pricing policies catering to varying preferences can substantially increase efficiency while maintaining the same political feasibility as the current experiments. This dissertation also explores how to apply the recent developments in Bayesian econometrics to estimate the multinomial probit models combining different sources of data, which can be used to estimate the diversity in peoples’ preferences with more flexibility in model specification.

Suggested Citation
Jia Yan (2002) Heterogeneity in Motorists' Preferences for Time Travel and Time Reliability: Empirical Findings from Multiple Survey Data Sets and Its Policy Implications. PhD Dissertation. UC Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/u4evf/cdi_cdl_escholarship_oai_escholarship_org_ark_13030_qt7nk0v3kj.

published journal article

A spatially and temporally resolved model of the electricity grid – Economic vs environmental dispatch

Applied Energy

Publication Date

September 1, 2016
Suggested Citation
Ghazal Razeghi, Jack Brouwer and G. Scott Samuelsen (2016) “A spatially and temporally resolved model of the electricity grid – Economic vs environmental dispatch”, Applied Energy, 178, pp. 540–556. Available at: 10.1016/j.apenergy.2016.06.066.

conference paper

An Ensemble Approach to Truck Body Type Classification using Deep Representation Learning on 3D Point Sets

100th Transportation Research Board (TRB) Annual Meeting

Suggested Citation
Yiqiao Li, Koti R Allu, Zhe Sun, Andre Tok, Guoliang Feng and Stephen G. Ritchie (2021) “An Ensemble Approach to Truck Body Type Classification using Deep Representation Learning on 3D Point Sets”. 100th Transportation Research Board (TRB) Annual Meeting, Washington, DC.

published journal article

Beginning the transformation

Mechanical Engineering

Publication Date

May 1, 2006

Author(s)

Mark Williams, Scott Samuelsen
Suggested Citation
Mark Williams and Scott Samuelsen (2006) “Beginning the transformation”, Mechanical Engineering, 128(05), pp. 40–43. Available at: 10.1115/1.2006-may-4.

published journal article

Mobility and environment improvement of signalized networks through Vehicle-to-Infrastructure (V2I) communications

Transportation Research Part C: Emerging Technologies

Publication Date

July 1, 2016

Author(s)

Gerard Aguilar Ubiergo, Wenlong Jin
Suggested Citation
Gerard Aguilar Ubiergo and Wen-Long Jin (2016) “Mobility and environment improvement of signalized networks through Vehicle-to-Infrastructure (V2I) communications”, Transportation Research Part C: Emerging Technologies, 68, pp. 70–82. Available at: 10.1016/j.trc.2016.03.010.

policy brief

Transportation Network Companies Might Be Pulling Riders from Public Transit, but This Could Change

Publication Date

May 1, 2023

Author(s)

Susan Shaheen, Elliot Martin, Adam Stocker

Abstract

Transportation Network Companies (TNCs, also known as ridehailing and ridesourcing) have expanded across California over the past decade and changed the way people travel. Using a smartphone, travelers can quickly summon a vehicle from almost anywhere and know what the estimated wait time, travel time, and cost will be before stepping into the vehicle. While TNCs are clearly addressing an unmet need for travelers, their growing popularity has raised a number of policy questions, including if TNCs are shifting people away from public transit and other travel modes (e.g., carshare, walking, biking).

Suggested Citation
Susan Shaheen, Elliot Martin and Adam Stocker (2023) Transportation Network Companies Might Be Pulling Riders from Public Transit, but This Could Change. Policy Brief. UC ITS. Available at: https://doi.org/10.7922/g2rf5sbh.

published journal article

Compound Risk of Air Pollution and Heat Days and the Influence of Wildfire by SES across California, 2018–2020: Implications for Environmental Justice in the Context of Climate Change

Climate

Publication Date

October 1, 2022

Author(s)

Shahir Masri, Yufang Jin, Jun Wu

Abstract

Major wildfires and heatwaves have begun to increase in frequency throughout much of the United States, particularly in western states such as California, causing increased risk to public health. Air pollution is exacerbated by both wildfires and warmer temperatures, thus adding to such risk. With climate change and the continued increase in global average temperatures, the frequency of major wildfires, heat days, and unhealthy air pollution episodes is projected to increase, resulting in the potential for compounding risks. Risks will likely vary by region and may disproportionately impact low-income communities and communities of color. In this study, we processed daily particulate matter (PM) data from over 18,000 low-cost PurpleAir sensors, along with gridMET daily maximum temperature data and government-compiled wildfire perimeter data from 2018–2020 in order to examine the occurrence of compound risk (CR) days (characterized by high temperature and high PM2.5) at the census tract level in California, and to understand how such days have been impacted by the occurrence of wildfires. Using American Community Survey data, we also examined the extent to which CR days were correlated with household income, race/ethnicity, education, and other socioeconomic factors at the census tract level. Results showed census tracts with a higher frequency of CR days to have statistically higher rates of poverty and unemployment, along with high proportions of child residents and households without computers. The frequency of CR days and elevated daily PM2.5 concentrations appeared to be strongly related to the occurrence of nearby wildfires, with over 20% of days with sensor-measured average PM2.5 > 35 μg/m3 showing a wildfire within a 100 km radius and over two-thirds of estimated CR days falling on such days with a nearby wildfire. Findings from this study are important to policymakers and government agencies who preside over the allocation of state resources as well as organizations seeking to empower residents and establish climate resilient communities.

Suggested Citation
Shahir Masri, Yufang Jin and Jun Wu (2022) “Compound Risk of Air Pollution and Heat Days and the Influence of Wildfire by SES across California, 2018–2020: Implications for Environmental Justice in the Context of Climate Change”, Climate, 10(10), p. 145. Available at: 10.3390/cli10100145.