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Sponsor: SB1

What Drives Success in Public Shared Micromobility Programs?

Status

Complete

Project Timeline

September 1, 2020 - August 30, 2021

Principal Investigator

Michael HylandMichael Hyland

Project Team

Jean-Daniel Saphores, Arash Ghaffar

Sponsor, Program & Award Number

SB1 // STRP Faculty Research: 2021-38
(Also see the UC ITS page)

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

Cities across the US and the world have implemented shared micromobility services, including e-scooters and (e-)bikes. These services offer moderate-speed, space-efficient, and carbon-light mobility, which promotes environmental sustainability and healthy travel. The benefits of shared micromobility coupled with the availability of data have fueled a growing literature on shared micromobility ridership. To assess the ingredients for and obstacles to successful shared micromobility programs, this project performed a meta-analysis of 29 studies that estimate statistical models of zone- or station-based shared micromobility trip counts, including 22 that examine station-based bikeshare systems. The meta-analysis reveals positive elasticities between shared micromobility usage and population density, employment density, median household income, bus stops, metro stations, bike infrastructure, and nearby station capacity. In contrast, station elevation has a negative elasticity. These magnitudes can inform shared micromobility providers and transportation planners seeking to plan/design shared micromobility systems to promote environmentally sustainable travel. The meta-analysis also reveals that the existing literature fails to (i) capture spatial dependencies, and (ii) discuss the practical implications of model parameters.

Related Publications

published journal article | Aug 2023

Meta-analysis of shared micromobility ridership determinants
Transportation Research Part D: Transport and Environment

Read more
policy brief | Aug 2023

What Drives Shared Micromobility Ridership?

Read more

Factors Affecting Development Decisions and Construction Delay of Housing in Transit-Accessible and Jobs-Rich Areas in California

Status

Complete

Project Timeline

September 1, 2020 - August 30, 2021

Principal Investigator

Nicholas Marantz

Project Team

Doug Houston, Jae Hong Kim, Youjin Kim, Narae Lee

Sponsor, Program & Award Number

SB1 // STRP Faculty Research: 2021-37
(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

Recent state legislation has attempted to address California's housing affordability crisis by encouraging new development in transit-accessible and/or jobs-rich areas. But policymakers lack adequate information in two key areas: the effects of transportation laws and plans on the decisions of developers regarding whether and where to build housing; and the determinants of delays in approvals for proposed projects in jobs-rich and transit-accessible areas. Drawing on a unique dataset detailing all residential projects of five units or more that were approved from 2014 through 2017 in seven Southern California jurisdictions, this project will analyze the extent to which transportation policies, rules, plans, and investments influence the location of new housing and delay the construction of new housing. Using descriptive statistics and multivariate modeling, the research team will examine developers' decisions concerning whether and where to build housing, identifying how project-level attributes and contextual variables, including those related to transportation, affect decisions about whether and where to build infill projects in jobs-rich and transit-rich locations. This work will also include a systematic comparison of permitting timelines for otherwise comparable projects with different degrees of transit availability or job accessibility, along with multivariate modeling to assess the determinants of delay.

Related Publications

policy brief | Jul 2022

What Can Be Done to Speed Up Building Approval for Multifamily Housing in Transit-Accessible Locations?

Read more
research report | Jul 2022

Factors Affecting Development Decisions and Construction Delay of Housing in Transit-Accessible and Jobs-Rich Areas in California

Read more
policy brief | Jul 2022

What Can Be Done to Speed Up Building Approval for Multifamily Housing in Transit-Accessible Locations?

Read more

Tolling lessons learned for road usage charge

Status

Complete

Project Timeline

January 1, 2022 - December 31, 2022

Principal Investigator

David Brownstone

Sponsor, Program & Award Number

SB1 // STRP Faculty Research: PSR-21-40-MATCH

Areas of Expertise

Transportation Economics, Funding, & Finance

Team Departmental Affiliation

Economics

Project Summary

Even though plug-in electric vehicles can reduce the problem of greenhouse gas emissions from the transportation sector, externalities like congestion and road damage will exist. Therefore, state transportation agencies will need pricing mechanisms like a per-mile road user charge (RUC) to deal with these externalities while accounting for the transition to an EV-dominated fleet. In this project, focusing on electronic toll collection (ETC) methods, we aim to conduct a thorough review of lessons learned from established tolling systems across US states and the tolling system in Singapore and London. Post literature review, a multi-criteria performance framework of different tolling mechanisms will be formulated based on criteria such as accuracy of data collection, complexity for regulators and users, compatibility across policy objectives (primarily RUC), and equity. Finally, we aim to identify the best practices in the existing tolling systems for offsetting some of the costs for low-income drivers and demonstrate their effectiveness using travel behavior data from the National Household Travel Survey. A good understanding of the pros and cons of the existing tolling systems will help state transportation agencies investigate the trade-offs of the different tolling systems while designing an RUC.

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

policy brief | Jan 2024

What Does the Prevalence of Telecommuting Mean for Urban Planning?

Read more
research report | Jan 2024

Telecommuting and the Open Future

Read more

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