published journal article

Joint Planning of Dynamic Wireless Charging Lanes and Power Delivery Infrastructure for Heavy-duty Drayage Trucks

Publication Date

August 5, 2024

Author(s)

Ran Wei, Nanpeng Yu, Zuzhao Ye, Mikhail A. Bragin

Areas of Expertise

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

Abstract

Heavy-duty drayage trucks pose a considerable emission burden and health risk, primarily due to their operation in densely populated areas around seaports and intermodal terminals. In response to these concerns, governments are setting ambitious targets for zero-emissions drayage truck transition. As such, the widespread adoption of electric drayage trucks is on the horizon. However, one of the main challenges hindering the mass electrification of drayage trucks is the low readiness of charging infrastructure. Traditional charging stations can lead to long waiting times for truck drivers, which can be detrimental to an industry where timely pickup and delivery are crucial. Dynamic wireless charging lanes (DWCLs) have emerged as a promising alternative or supplement to stationary charging stations by enabling charging-on-the-move. Although electric drayage trucks are potentially the most benefited vehicles from DWCLs, the optimal deployment of DWCLs for them is rarely studied. To address this problem, this project proposes a framework that focuses on the deployment of DWCLs with special attention paid to drayage trucks, while jointly planning the associated power delivery infrastructure. The proposed planning model identifies the optimal locations of DWCLs in a given transportation network and determines how they will be powered by nearby electrical substations. Additionally, the framework also evaluates whether an upgrade of the electrical substation is needed. A large-scale Global Positioning System (GPS) dataset and an electrical substation dataset, which contain more than 7,000 heavy-duty drayage trucks that span over a period of 12 months and over 255 substations, are utilized to provide the necessary input to the proposed framework. Research findings demonstrate the effectiveness of the proposed framework through a case study conducted on a highway network of more than 1,000 miles around the Greater Los Angeles area, home to two of the world’s busiest seaports, Port of Los Angeles and Port of Long Beach.

published journal article

Impact of Electric Vehicle Charging Demand on Power Distribution Grid Congestion

Publication Date

April 22, 2024

Author(s)

Yanning Li, Alan Jenn

Areas of Expertise

Zero-Emission Vehicles & Low-Carbon Fuels

Abstract

California, a pioneer in EV adoption, has enacted ambitious electric vehicle (EV) policies that will generate a large burden on the state’s electric distribution system. We investigate the statewide impact of uncontrolled EV charging on the electric distribution networks at a large scale and high granularity, by employing an EV charging profile projection that combines travel demand model, EV adoption model, and real-world EV charging data. We find a substantial need for infrastructure upgrades in 50% of feeders by 2035, and 67% of feeders by 2045. The distribution system across California must upgrade its capacity by 25 GW by 2045, corresponding to a cost between $6 and $20 billion. While the additional infrastructure cost drives the electricity price up, it is offset by the downward pressure from the growth of total electricity consumption and leads to a reduction in electricity rate between $0.01 and $0.06/kWh by 2045. We also find that overloading conditions are highly diverse spatially, with feeders in residential areas requiring twice as much upgrade compared to commercial areas. Our study provides a framework for evaluating EVs’ impact on the distribution grid and indicates the potential to reduce infrastructure upgrade costs by shifting home-charging demand. The imminent challenges confronting California serve as a microcosm of the forthcoming obstacles anticipated worldwide due to the prevailing global trend of EV adoption.

published journal article

Fleet Operator Perspectives on Alternative Fuels for Heavy-duty Vehicles

Areas of Expertise

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

Abstract

Despite the deployment of alternative fuel vehicles (AFVs) being one of the promising measures to reduce air pollutants and greenhouse gas emissions, AFVs still represent a very small share in the heavy-duty vehicle (HDV) sector. Understanding HDV fleet operator perspectives on alternative fuels is critical to developing effective demand-side strategies to facilitate wider and more rapid adoption of heavy-duty AFVs. This study explored California HDV fleet operator perspectives on viable alternative fuel options in the next 10–20 years, along with motivators for, and barriers to, such adoption. Eighteen in-depth qualitative interviews were conducted, after which thematic analysis was employed to analyze the interview data. Electric, hydrogen, compressed natural gas (CNG), and hybrid options were commonly perceived as viable in the 2030s by the participating organizations. Various optimistic aspects were addressed, including advanced technologies and emission reduction benefits (electric/hydrogen), continued fuel commitments due to their fleet or infrastructure investments already made (CNG), and lower complexity in fleet routing along with favorable driver acceptance (hybrid options). However, many concerns and uncertainties were also reported, including functional unsuitability (electric), uncompetitive upfront costs (hydrogen), unready infrastructure, perceived unavailability of vehicles, uncertain return on investment (electric/hydrogen), and unpromising support from state government (CNG). The study findings help fill a key knowledge gap in AFV fleet adoption research regarding HDV fleet operator perspectives, and contribute to developing demand-side strategies to aid the success of AFV diffusion throughout the HDV market.

published journal article

Integrating Autonomous Vehicles in Multimodal Peer-to-peer Shared Mobility Systems and its Network Impacts

Areas of Expertise

Intelligent Transportation Systems, Emerging Technologies, & Big Data Public Transit, Shared Mobility, & Active Transportation

Abstract

As public perception of sharing economy in transportation has changed, mobilephone-hailed ridesharing is gaining prominence. The key aspect of capitalizing and promoting better shared-mobility systems depends on the matching rate between the supply and demand for rides. Peer-to-peer (P2P) ridesharing systems devise higher matching rate than pure ridesharing systems by attracting more drivers. Even relaxing the spatiotemporal constraints for participants could increase the chances to be matched. However, we notice that sole P2P ridesharing systems still do not guarantee matching when the number of drivers is limited. We propose the utilization of a fleet service to cover the unmatched riders in P2P ridesharing. While it can be any type of fleet services such as taxis, Uber/Lyft, or paratransit, we explore the idea of utilizing shared autonomous vehicles as a fleet, as they can be dispatched without labor. We model an integrated system for P2P ridesharing and shared autonomous fleet vehicles (SAFVs). The proposed algorithm is designed to maximize matching ratio while optimizing the number of required SAFVs. Based on a simulated study on the northern Los Angeles, the integrated shared-mobility system is shown to have high potential to serve a high fraction of riders.

research report

A Data-Driven Approach to Manage High-Occupancy Toll Lanes in California

Publication Date

June 1, 2024

Author(s)

Michael Zhang, Hang Gao, Di Chen, Yanlin Qi

Areas of Expertise

Infrastructure Delivery, Operations, & Resilience Transportation Economics, Funding, & Finance

Abstract

Managing traffic flow in high-occupancy toll (HOT) lanes is a tough balancing act and current tolling schemes often lead to either under- or over-utilization of HOT lane capacity. The inherent linear/nonlinear relationship between flow and tolls in HOT lanes suggests that recent advances in machine learning and the use of a data-driven model may help set toll rates for optimal flow and lane use. In this research project, a data-driven model was developed, using long short-term memory (LSTM) neural networks to capture the underlying flow-toll pattern on both HOT and general-purpose lanes. Then, a dynamic control strategy, using a linear quadratic regulator (LQR) feedback controller was implemented to fully utilize the HOT lane capacity while maintaining congestion-free conditions. A case study of the I-580 freeway in Alameda County, California was carried out. The control system was evaluated in terms of vehicle hours traveled and person-hours traveled for solo drivers and carpoolers. Results show that the tolling strategy helps to mitigate congestion in HOT and general-purpose lanes, benefiting every traveler on the I-580.

research report

Cars and Chargers in the Country: Rural PEV Owner Accounts of Charging and Travel in California

Areas of Expertise

Zero-Emission Vehicles & Low-Carbon Fuels

Abstract

Under the Advanced Clean Cars II (ACC II) rule, California must move to 100% zero-emission vehicle (ZEV) sales by 2035. To make this transition equitable, it is important to understand how we can support ZEV adoption in all communities–including rural communities. The aim of this study is to explore the experiences and perceptions of current rural plug-in electric vehicle (PEV) owners, identify barriers to charging and ownership, and suggest factors to guide the development of infrastructure in rural areas. (PEVs include battery-electric vehicles [BEVs] and plug-in hybrid vehicles.) Semi-structured interviews were conducted with rural PEV owners and included questions related to travel behavior, at-home and public charging experiences, and motivation for household vehicle purchases. Major themes were extracted from the interviews including that PHEV owners tend to have minimal at-home and public charging requirements, while battery-electric vehicle owners require access to Level 2 charging at home and reliable fast charging in public spaces. Additionally, the magnitude of public charging reliability and availability issues appear to be greater in rural than non-rural areas. Grid reliability issues and specific vehicle requirements were also points of discussion among rural PEV owners. The findings of this report could inform policymakers, car manufacturers, and PEV charging companies to better serve rural communities in the transition to 100% PEV sales.

policy brief

Using Real-Time Crowding Data as a Rider Communication Strategy in the COVID-19 Pandemic

Publication Date

October 1, 2020

Author(s)

Eric Dasmalch

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation Safety, Public Health, & Mobility Justice

Abstract

In response to the COVID-19 Pandemic, many transit agencies have embraced real-time crowding data as a rider communication strategy. These data allow riders to see the current level of crowding on individual transit vehicles in real time. Most operators share these data using GTFS Realtime, an extension to the General Transit Feed Specification that already powers trip-planning applications such as Transit App and Google Maps.Offering these real-time data helps riders make informed travel choices that allow them, for example, to avoid crowded transit vehicles. However, actual implementations vary widely and may not always provide useful information to transit riders or other interested parties. This policy brief summarizes the current state of real-time crowding data in September 2020, and provides recommendations for ongoing improvements.

book/book chapter

The Drive for Dollars: How Fiscal Politics Shaped Urban Freeways and Transformed American Cities

Areas of Expertise

Transportation Economics, Funding, & Finance

Abstract

American cities are distinct from almost all others in the degree to which freeways and freeway travel dominate urban landscapes. In The Drive for Dollars, Brian D. Taylor, Eric A. Morris, and Jeffrey R. Brown tell the largely misunderstood story of how freeways became the centerpiece of U.S. urban transportation systems, and the crucial, though usually overlooked, role of fiscal politics in bringing freeways about. The authors chronicle how the ways that we both raise and spend transportation revenue have shaped our transportation system and the lives of those who use it, from the era before the automobile to the present day. They focus on how the development of one revolutionary type of road–the freeway–was inextricably intertwined with money. With the nation’s transportation finance system at a crossroads today, this book sheds light on how we can best fund and plan transportation in the future. The authors draw on these lessons to offer ways forward to pay for transportation more equitably, provide travelers with better mobility, and increase environmental sustainability and urban livability.

policy brief

What Does Public Health Research Tell Us About the Risks of Riding Public Transit During the COVID-19 Pandemic?

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation Safety, Public Health, & Mobility Justice

Abstract

The COVID-19 pandemic has upended how people travel
and how transportation systems function. Travel is down
across all modes in 2020, though the declines on public
transit have been greater and the recovery slower than on
other travel modes, such as private automobiles and “active”
transportation modes like biking and walking. This shift in
travel mode choice away from transit is likely explained at
least in part by would-be riders’ fears of infection during
this communicable disease outbreak because public transit
congregates people in dense and enclosed environments.
To lower the risk of infection and reduce the spread of
COVID-19, transit agencies worldwide have implemented
measures such as route and service modifications,
improved ventilation and air filtration, increased cleaning
and disinfecting, modifications of seating and boarding
protocols to ensure physical distancing, mask-wearing
requirements, and even screening riders for fevers.
The perception that public transit poses an elevated risk
for the transmission and spread of infectious diseases
influences both people’s reluctance to ride and transit
agencies’ various pandemic response measures. But is
this perception merited, and is transit “safe” to ride? Since
the beginning of the COVID-19 pandemic, this question
has been widely debated. But this is a complex issue that
defies a simple “yes” or “no” answer, as it depends on many
factors (such as ambient infection rates) beyond transit
operators’ control. As we found in our review of the public
health literature, the relative infection risk on public transit
depends not only on how transit operators respond, but
also on the particulars of the communicable disease, rider
and employee adherence to public health guidance, the trip
durations and densities of riders on vehicles, as well as the
effectiveness of the broader public health response. Thus,
arguing in the abstract about whether riding transit is safe
or dangerous during a pandemic is a bit like arguing about
the area of a rectangle knowing only the length of one side.

published journal article

State of the BART: Analyzing the Determinants of Bay Area Rapid Transit Use in the 2010s

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

Abstract

Peaking on public transit—the concentration of ridership in peak times and directions into and out of central areas—has waxed in the U.S. over the past century, as public transit has lost more mode share at off-peak times, in off-peak directions, and among non-commute trips. A notable pre-pandemic manifestation of this chronic problem was on Bay Area Rapid Transit, the San Francisco Bay Area’s regional heavy rail system. While BART staved off an absolute ridership decline longer than most American transit operators in the mid-and late-2010s, it did so almost entirely due to peak gains in riders offsetting off-peak losses. As a result, the system experienced worsening passenger crowding at some times and places, expanding underutilization of capacity at many others, and the prospect of enormous expenditures to accommodate rising transbay passenger demand. To examine the factors driving transit use in the 2010s, we model peak and off-peak BART trips as a function of station area and system characteristics. We uniquely use origin-destination pairs as the unit of analysis in order to separately measure influences at both ends of the trip. We find that transfers and travel time most influence peak and off-peak BART ridership and that station-area employment and time competitiveness with driving particularly influence peak patronage. Over time in our models, the associations between ridership and transit travel time weakened, while the associations between ridership and transfers, employment, and time-competitiveness with driving grew stronger. In sum, we find that the peaking problem plaguing public transit systems for decades worsened in the years leading up to the pandemic—on this one nationally significant U.S. transit system, at least—which poses potentially substantial financial challenges in the years ahead.