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Sponsor: SB1

Alternative Fuel Demand and Adoption Behavior of Heavy-duty Vehicle Fleets in California

Status

Complete

Project Timeline

October 2, 2019 - December 31, 2022

Principal Investigator

Stephen Ritchie

Project Team

Priscilla Chu, Youngeun Bae, Craig Rindt

Sponsor, Program & Award Number

SB1 // STRP Faculty Research: 2020-48
(Also see the UC ITS page)

Areas of Expertise

Freight, Logistics, & Supply Chain Zero-Emission Vehicles & Low-Carbon Fuels

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

On-road medium and heavy-duty vehicles account for approximately 20% of greenhouse gas (GHG) emissions in California’s transportation sector and the air pollutants emitted from these vehicles have detrimental effects on the health conditions of local residents. At the same time, the freight transportation system is responsible for one-third of the jobs in the California economy. Thus, it is imperative to implement mitigation strategies for reducing truck-generated emissions so that these harmful emissions can be decoupled from economic growth. While encouraging HDV fleet operators to purchase alternative fuel vehicles is one of the promising solutions, alternative heavy-duty are still only a very marginal share of the vehicle population. Efforts to increase the share of vehicles using alternative fuels depend on obtaining a better understanding of fleet decision-making behavior as it relates to alternative fuel vehicle choice. This study aims to fill this gap by exploring HDV fleet operator decisions about alternative fuel adoption using both existing literature and new empirical data. To this end, the researchers first develop an initial theoretical framework of AFV fleet adoption behavior in organizations based upon existing theories and literature. The researchers then empirically improve the framework by investigating 20 organizations in California via in-depth qualitative interviews and project reports. The study results contribute theoretically and empirically to a better understanding of the demand-side aspects of AFV adoption by HDV fleet operators, particularly in California and in the other US states that follow California’s environmental policies.

Related Publications

Phd Dissertation | Jan 2021

Alternative Fuel Adoption Behavior of Heavy-duty Vehicle Fleets

Read more
published journal article | Jan 2022

Factors influencing alternative fuel adoption decisions in heavy-duty vehicle fleets
Transportation Research Part D: Transport and Environment

Read more

Synthesizing the State-of-the-Art in Transportation Equity Analysis to Better Understand how Shared Automated Vehicles may Impact Employment Access and Equity

Status

Complete

Project Timeline

April 1, 2022 - March 30, 2023

Principal Investigator

Michael HylandMichael Hyland

Project Team

Tanjeeb Ahmed

Sponsor, Program & Award Number

SB1 // STRP Faculty Research: 2022-37
(Also see the UC ITS page)

Areas of Expertise

Intelligent Transportation Systems, Emerging Technologies, & Big Data Safety, Public Health, & Mobility Justice

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

The negative aspects of existing transportation systems in California tend to disproportionately impact low-income and ethnic-racial minority individuals, households, and communities. Similarly, new technological innovations in transportation, such as automated vehicles, are often seen as primarily benefiting wealthier individuals, households, and communities and in many cases this is true. Hence, there is a need to proactively plan and design future transportation systems to address historical inequities as well as to avoid exacerbating current inequities. This study builds upon a previous research project that explore the implications of shared automated vehicles or “robo-taxis” on employment accessibility. Specifically, this project will consist of a literature review to determine and assess (i) the current state-of-practice in equity analysis in transportation agencies; (ii) the state-of-the-art in equity analysis in the academic literature in the transportation field; (iii) the state-of-the-art in equity analysis in the academic literature outside of the transportation field; and (iv) gaps in the existing literature in terms of evaluating equity. Based on the literature review, the research team will identify and recommend the most appropriate metrics and analytical tools for equity analysis, and then use the recommended metrics and analytical tools to improve the equity analysis of how robo-taxis may impact employment accessibility.

Related Publications

policy brief | May 2023

What are the Equity Implications of Robo-taxis in terms of Job Accessibility Benefits?

Read more
Preprint Journal Article | Aug 2023

Equity Implications of Robo-Taxis on Job Accessibility: Avoiding the Ecological Fallacy with Agent-Based Models

Read more

Reducing Congestion by Using Integrated Corridor Management Technology to Divert Vehicles to Park-and-Ride Facilities

Status

Complete

Project Timeline

April 1, 2022 - March 30, 2023

Principal Investigator

Mohammad Al Faruque

Project Team

Tyler Zhang, Mohanad Odema, Rozhin Yasaei

Sponsor, Program & Award Number

SB1 // STRP Faculty Research: 2022-46
(Also see the UC ITS page)

Areas of Expertise

Infrastructure Delivery, Operations, & Resilience Intelligent Transportation Systems, Emerging Technologies, & Big Data

Team Departmental Affiliation

Electrical Engineering and Computer Science

Project Summary

Considerable advancements have been made in traffic management strategies over the past few decades to enhance user mobility on freeways. Still, the continuous growth of metropolitan regions and increasing mobility needs tend to impede such progress. Pre-pandemic, the recent Urban Mobility Report showed that the total cost of traffic delay in the top urban areas in the U.S.has grown by almost 48 percent over the past decade. In many of these regions (such as in California), freeways experience a great deal of traffic congestion, arising from bottlenecks at which high-volume, free-flowing traffic transforms into tightly packed clusters of low-speed vehicles. As such, transportation planners have given special attention to the notion of integrated corridor management (ICM), which encourages the adoption of global traffic management strategies. In practice, this involves consolidating the various traffic components deployed along the corridor (e.g., ramp meter controllers) into a single interconnected system with a global view of traffic condition along the entire corridor, allowing upstream traffic components to be tuned to relieve downstream bottlenecks. In other words, an ICM strategy can coordinate various traffic control units to optimize their operations along the entire freeway, rather than just on pre-specified settings or in localized areas. Connected Vehicles (CV) technology offers significant potential for managing traffic congestion and improving mobility along transportation corridors. This project presents a novel approach using integrated corridor management (ICM) technology to divert CVs to underutilized park-and-ride facilities where drivers can park their vehicle and access public transportation. Using vehicle-to-infrastructure (V2I) communication protocols, the system collects data on downstream traffic and sends messages regarding available park-and-ride options to upstream traffic. A deep reinforcement learning (DRL) program controls the messaging, with the objective of maximizing traffic throughput and minimizing CO2 emissions and travel time. The ICM strategy is simulated on a realistic model of Interstate 5 using Veins simulation software. The results show marginal improvement in throughput, freeway travel time, and CO2 emissions, but increased travel delay for drivers choosing to divert to a park-and-ride facility to take public transportation for a portion of their travel.

Related Publications

research report | Aug 2023

Reducing Congestion by Using Integrated Corridor Management Technology to Divert Vehicles to Park-and-Ride Facilities

Read more
research report | Aug 2023

‪An Integrated Corridor Management for Connected Vehicles and Park and Ride Structures using Deep Reinforcement Learning‬

Read more
policy brief | Sep 2023

Connected Vehicle Technology and AI Could Help Reduce Highway Congestion through Better Utilization of Park and Ride Facilitie

Read more

Reducing Congestion by Using Integrated Corridor Management Technology to Divert Vehicles to Park-and-Ride Facilities

Status

Complete

Project Timeline

April 1, 2022 - March 30, 2023

Principal Investigator

Mohammad Al Faruque

Sponsor, Program & Award Number

SB1 // STRP Faculty Research: 2022-46

Areas of Expertise

Intelligent Transportation Systems, Emerging Technologies, & Big Data

Team Departmental Affiliation

Electrical Engineering and Computer Science

Project Summary

Considerable advancements have been made in traffic management strategies over the past few decades to enhance user mobility on freeways. Still, the continuous growth of metropolitan regions and increasing mobility needs tend to impede such progress. Pre-pandemic, the recent Urban Mobility Report showed that the total cost of traffic delay in the top urban areas in the U.S.has grown by almost 48 percent over the past decade. In many of these regions (such as in California), freeways experience a great deal of traffic congestion, arising from bottlenecks at which high-volume, free-flowing traffic transforms into tightly packed clusters of low-speed vehicles. As such, transportation planners have given special attention to the notion of integrated corridor management (ICM), which encourages the adoption of global traffic management strategies. In practice, this involves consolidating the various traffic components deployed along the corridor (e.g., ramp meter controllers) into a single interconnected system with a global view of traffic condition along the entire corridor, allowing upstream traffic components to be tuned to relieve downstream bottlenecks. In other words, an ICM strategy can coordinate various traffic control units to optimize their operations along the entire freeway, rather than just on pre-specified settings or in localized areas. Connected Vehicles (CV) technology offers significant potential for managing traffic congestion and improving mobility along transportation corridors. This project presents a novel approach using integrated corridor management (ICM) technology to divert CVs to underutilized park-and-ride facilities where drivers can park their vehicle and access public transportation. Using vehicle-to-infrastructure (V2I) communication protocols, the system collects data on downstream traffic and sends messages regarding available park-and-ride options to upstream traffic. A deep reinforcement learning (DRL) program controls the messaging, with the objective of maximizing traffic throughput and minimizing CO2 emissions and travel time. The ICM strategy is simulated on a realistic model of Interstate 5 using Veins simulation software. The results show marginal improvement in throughput, freeway travel time, and CO2 emissions, but increased travel delay for drivers choosing to divert to a park-and-ride facility to take public transportation for a portion of their travel.

Modeling the interactions of costs, price, choice and performance in shared mobility systems with subscription service possibilities

Status

In Progress

Project Timeline

August 1, 2021 - June 30, 2023

Principal Investigator

r-jayakrishnanR. (Jay) Jayakrishnan

Project Team

Michael Hyland, Sunghi (Sunny) An

Sponsor, Program & Award Number

SB1 // STRP Faculty Research: 2022-42
(Also see the UC ITS page)

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

There are now a number of new and innovative mobility solutions beyond private vehicle ownership and public transit, such as rideshare, carshare, bikeshare, autonomous vehicles, transit, and micro-transit. While the new shared and/or autonomous mobility systems are generally considered ‘greener’ choices, their ultimate impacts are still unknown. Vehicle usage could become more efficient, but the overall number of vehicle miles travelled (VMT) could grow. Public agencies are already concerned by increased VMT from new ride-hailing services and reductions in transit usage which may be due to vehicle-sharing operations not being properly priced. Thus, establishing proper cost models is important for developing effective policies for reducing VMT. This research project will provide a modeling-based decision-making platform to help develop policies to attain California’s goal of equitable and environmentally sustainable transportation. One solution could be MaaS (mobility as a service) systems which employ concepts such as time-shared usage and subscription services. The research project will explore the potential for such systems to increase vehicle-sharing efficiency by examining the interaction between various system costs and optimal pricing choices for consumers.

Will Transit Ridership Ever Recover From COVID-19? A Case Study of Los Angeles

Status

Complete

Project Timeline

August 1, 2021 - June 30, 2023

Principal Investigator

David Brownstone

Sponsor, Program & Award Number

SB1 // STRP Faculty Research: 2022-44
(Also see the UC ITS page)

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

Team Departmental Affiliation

Economics

Project Summary

The COVID pandemic has caused an unprecedented decline in transit ridership, and in turn accelerated the adoption of policies designed to increase transit ridership. Most of those who continued to ride transit during the first year of the pandemic could not afford alternatives such as private cars or transportation network company trips. Therefore, as public travel restrictions and fears have eased any recent increase in transit ridership in response to new policies can be reasonably attributed to new or returning “choice” riders that are crucial to rebuilding transit ridership. This project investigates changes in transit ridership in the Los Angeles Metropolitan Transit Agency (Metro) service area, one of the largest in the United States, with a very diverse population. The project will measure the extent (and geographic locations) of changes in transit ridership as the pandemic ebbs and evaluate the extent to which these may be due to changes in public health restrictions, COVID prevalence, and new policies that Metro adopts to increase ridership. The research team will measure COVID cases and vaccination rates at weekly intervals, and this high frequency of data collection will allow the team to flexibly model the complex dynamics linking COVID to mobility and transit use. The team will also identify disadvantaged communities in the study area and measure any differential impacts on these communities. This project will demonstrate how careful merging of data that is currently being collected by transit agencies, public health agencies, government agencies and private entities, can be used to evaluate policy impacts.

Related Publications

policy brief | Jan 2024

COVID-19 Vaccination Rates Influenced Bus Ridership Recovery

Read more

Telecommuting and the Open Future

Status

Complete

Project Timeline

August 1, 2021 - June 30, 2023

Principal Investigator

Jae Hong Kim

Project Team

Alex Okashita, Harold Arzate

Sponsor, Program & Award Number

SB1 // STRP Faculty Research: 2022-41
(Also see the UC ITS page)

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment

Team Departmental Affiliation

Urban Planning and Public Policy

Project Summary

The COVID-19 pandemic has generated renewed interest in how telecommuting can alter the workings of cities and regions, but there is little guidance on how to align planning practice with the new reality. Shelter-at-home policies forced businesses to rapidly develop a telework infrastructure to continue their operations to the extent possible. In the wake of the pandemic, the prevalence of telecommuting has become the new normal, although this varies across industries. New questions arise from this rapid technological adoption. How will telecommuting growth affect cities? Should planners be worried about telecommuting growth? How should planners deal with this proliferation? This report synthesizes the research on telecommuting and its consequences to help planners better understand what effects may occur from the proliferation of telecommuting and what lessons can be drawn from research findings. Emphasis is on the broad relevance of telecommuting to many domains of planning, including housing, land use, community development, and inclusive place-making, while attention is paid to changes in travel demand, vehicle miles traveled (VMT), and greenhouse gas emissions. The research suggests that telecommuting can occur in a variety of ways, and its impacts are largely dependent not only on the type/schedule of telecommuting but on the built environment, transit accessibility, and other amenities/opportunities the location provides. The varying impacts reported in the research can be seen as an encouragement for planners to actively create a better future rather than merely responding to the rise of telecommuting. Given the breadth of telecommuting’s impacts, systematic coordination across various planning domains will be increasingly important. This report also calls for collaboration across cities to guide the ongoing transformation induced by telecommuting not in a way that leads to more residential segregation but in a way that provides more sustainable and inclusive communities.

Related Publications

research report | Jan 2024

Telecommuting and the Open Future

Read more
policy brief | Jan 2024

What Does the Prevalence of Telecommuting Mean for Urban Planning?

Read more

Telework Trends in California: Before, During, and Possibly After the Pandemic

Status

Complete

Project Timeline

April 1, 2022 - June 30, 2023

Principal Investigator

Jean-Daniel Saphores

Project Team

Md Rabiul Islam, Monica Ramirez-Ibarra

Sponsor, Program & Award Number

SB1 // STRP Faculty Research: 2022-43
(Also see the UC ITS page)

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

Forced by the COVID-19 pandemic and enabled by technology improvements, telework has received a big boost over the past 15 months. In addition to reducing vehicle miles traveled (VMT), decreasing energy use, and lowering emissions of both air pollutants and of greenhouse gases, telecommuting has numerous potential co-benefits, including saving time (from commuting) and money (on gas and parking), increasing schedule flexibility, potentially improving work-life balance, and reducing stress (Gajendran and Harrison, 2007). To understand the extent to which telecommuting could increase because of the pandemic, this project will analyze a unique dataset on commuting and telework collected during a May-June 2021 random survey of Californians conducted by IPSOS. In addition, the research will quantify changes in VMT and in the resulting emissions of air pollutants and greenhouse gases. Quantifying recent changes in telecommuting is important to update sustainable community strategies and for understanding the likely contribution of telecommuting in meeting California’s GHG reduction targets.

Related Publications

published journal article | Feb 2025

WILL COVID-19 jump-start telecommuting? Evidence from California
Transportation

Read more
policy brief | Aug 2024

Did COVID-19 Fundamentally Reshape Telecommuting in California?

Read more

Development of New Privacy-preserving Method for Traffic Data Collection and Analysis

Status

Complete

Project Timeline

August 1, 2021 - September 30, 2023

Principal Investigator

Wenlong Jin

Project Team

Jooneui Hong

Sponsor, Program & Award Number

SB1 // STRP Faculty Research: 2022-45
(Also see the UC ITS page)

Areas of Expertise

Other

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

Traditional methods for data collection, such as the National Household Travel Survey, focus on trips by a small sample of either travelers, locations, or times. With the prevalence of GPS devices and smartphones, big transportation data from more travelers and locations over longer timespans are more readily available and can substantially help to improve the management, planning, and design of transportation systems. However, travelers, private companies, and public agencies are reluctant to share such data due to privacy concerns. This project will develop a new privacy-preserving method for collecting and analyzing traffic data. This method is based on a new framework for transportation system analysis, in which a network is considered a single entity, and trips are tracked in a relative space with respect to the remaining distance to individual travelers’ destinations. Such data are sufficient for characterizing traffic dynamics but without revealing Personally Identifiable Location Information. This method works for either a city road network or freeway corridors, as well as for multimodal trips. The project will systematically calibrate and validate the new method and will discuss the policy implications for data collection and analysis for California’s traffic systems.

Related Publications

research report | Feb 2026

Development of New Privacy-preserving Method for Traffic Data Collection and Analysis: The Bathtub Model Approach

Read more
policy brief | Jan 2025

Using a “Bathtub Model” to Analyze Travel Can Protect Privacy While Providing Valuable Insights

Read more
Preprint Journal Article | Sep 2023

Priority Queue Formulation of Agent-Based Bathtub Model for Network Trip Flows in the Relative Space

Read more

Quantifying the Electric Grid Cost Savings of Increasing E-Bike Mode Share

Status

Complete

Project Timeline

October 1, 2022 - June 14, 2024

Principal Investigator

Michael HylandMichael Hyland

Project Team

Kate Forrest, Brian Tarroja, Ritun Saha, Michael Mackinnon

Sponsor, Program & Award Number

SB1 // STRP Faculty Research: 2023-40
(Also see the UC ITS page)

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation Zero-Emission Vehicles & Low-Carbon Fuels

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

Electrifying vehicles to meet transportation demands is critical to support the transition away from fossil fuels. The replacement of fossil-fuel-powered vehicles with battery electric vehicles (BEVs) is expected to play a major role. The mass deployment of BEVs without reducing vehicle-miles-traveled, however, will increase the peak load on the electric grid, requiring more costly upgrades to electrical system supply and distribution capacity. While improved smart grid management can mitigate these expenses, the real-world acceptance of smart charging programs by BEV drivers remains uncertain. Since most vehicle trips are less than 5 miles, an alternative to mitigate increases in peak electric loads would be to substitute more energy-efficient transportation modes, such as electric bikes (e-bikes), for future BEV trips. While prior studies have analyzed various benefits of increasing e-bike market share – including shorter travel times in congested cities, mental and physical health benefits, and lower emissions – no studies have quantified the cost-saving benefits for the electric grid infrastructure of increasing e-bike mode share. This project will develop a model to quantify the extent to which substituting e-bikes for BEVs reduces grid peak loads imposed by vehicle electrification, and to analyze the equipment needs and monetary costs associated with required upgrades. To accomplish this, the researchers are focusing on an analysis for the San Diego region. First, they will analyze vehicle trips in the San Diego region using the San Diego Association of Governments’ agent- and activity-based travel model system. Using this data, they will identify when, where, and for how long BEVs are parked and available for charging to ensure that these vehicles can meet all their intended trips. Second, the team will develop an in-house electric vehicle charging model to translate trip data into hourly electric grid load profiles for different vehicle types and infrastructure scenarios over an entire year. Lastly, the researchers will determine how substituting e-bikes for BEVs across different trip types and distances affects the annual peak electric grid load and estimate the cost savings from upgrading the electric distribution infrastructure in two representative neighborhoods—one single-family-oriented and one multi-family-oriented.

Related Publications

published journal article | Feb 2025

Estimating the electricity system benefits of scaling up E-bike usage in California
Journal of Cleaner Production

Read more
policy brief | Jul 2024

Shifting Future Electric Vehicle Trips to e-Bikes Could Help Reduce Electricity Demand at Critical Times in California

Read more

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