MS Thesis

California Statewide Commodity-Based Truck Activity and Population Forecast and the Transition Towards Zero Emissions

Abstract

Statewide travel forecasting models are developed by state agencies for different purposes such as forecasting network congestion, fuel consumption and air pollution. But in the end, they model the same travel activity from different procedures. Among those models and surveys, the California Statewide Freight Forecasting and Travel Demand Model (CSF2TDM), California Vehicle Inventory and Use Survey (CA-VIUS) from the California Department of Transportation (Caltrans), and the Emission Factor (EMFAC) model from the California Air Resources Board (CARB), are the most well-known ones in California. This thesis compared these models based on results such as Vehicle Miles Traveled (VMT) and vehicle inventory for heavy duty class 8 trucks. In addition, it connected the commodity-based activity of CSF2TDM to the CA-VIUS class 8 truck inventory and forecasted this population for future years. CSF2TDM and CA-VIUS forecasted 17, 19 and 27 percent less class 8 trucks for 2030, 2040 and 2050 target years compared to the EMFAC model. This difference is due to the different procedures and inputs these models have. EMFAC is good at capturing all truck activity while lacking detailed characteristics such as geographical resolution, while CSF2TDM provides a detailed profile of truck activity on the network with no truck inventory associated with truck activity. Moreover, new policies in California are raising questions about the infrastructure impact of zero emission vehicles and electrification of vehicles. The second part of this thesis investigated a framework for feasibility of electric class 8 trucks in California by analyzing the optimal locations of charging stations and their impact on grid infrastructure based on forecasted travel demand from CSF2TDM. The framework would determine the fraction of truck trips that are not feasible for electrification. Feasible trips would be analyzed under two scenarios: charge at origin and charge at destination. Charge at origin means truck gets charged for the trip at the origin and charge at destination means a truck is fully charged at the origin, makes the trip and then gets charged at the destination to get the battery full. Since the OD matrix is not symmetrical, there would be a difference in charging demand on the grid network under these two scenarios.

Suggested Citation
Esmaeil Sina Dabbagh (2022) California Statewide Commodity-Based Truck Activity and Population Forecast and the Transition Towards Zero Emissions. MS Thesis. UC Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/u4evf/cdi_cdl_escholarship_oai_escholarship_org_ark_13030_qt5p40m6qs.

published journal article

Transit Service Contracting: Experiences and Issues

Transportation Research Record

Publication Date

January 1, 1985

Author(s)

Abstract

This paper contains a review of available evidence on transit service contracting with a particular focus on: (a) the extent of service contracting, including who practices it and the types of services involved, (b) the motivations for contracting, (c) the estimated costs and subsidy savings that can be realized from contracting, and (d) the major obstacles to this strategy. Available information indicates that transit contracting is a widely used strategy for supplemental DRT service and for small transit systems in states where state funds are available to subsidize transit.

Suggested Citation
Roger Teal (1985) “Transit Service Contracting: Experiences and Issues”, Transportation Research Record, 1036, pp. 28–36.

Phd Dissertation

Agglomeration, production externalities, and the firm location decision

Publication Date

June 30, 2006

Author(s)

Abstract

TBD

Suggested Citation
Richard Funderburg (2006) Agglomeration, production externalities, and the firm location decision. PhD Dissertation. UC Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/1go3t9q/alma991033463839704701.

research report

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

Abstract

The upcoming Connected Vehicles (CV) technology shows great promise in effectively managing traffic congestion and enhancing mobility for users along transportation corridors. Data analysis powered by sensors in Connected Vehicles allows us to implement optimized traffic management strategies optimizing the efficiency of transportation infrastructure resources. In this study, the research team introduces a novel Integrated Corridor Management (ICM) methodology, which integrates underutilized Park-And-Ride (PAR) facilities into the global optimization strategy. To achieve this, the team uses vehicle-to-infrastructure (V2I) communication protocols, namely basic safety messages (BSM) and traveler information messages (TIM) to help gather downstream traffic information and share park and ride advisories with upstream traffic, respectively. Next, the team develops a model that assesses potential delays experienced by vehicles in the corridor. Based on this model, the research team employs a novel centralized deep reinforcement learning (DRL) solution to control the timing and content of these messages. The ultimate goal is to maximize throughput, minimize carbon emissions, and reduce travel time effectively. To evaluate the Integrated Corridor Management strategy, the paper includes simulations on a realistic model of Interstate 5 using the Veins simulation software. The deep reinforcement learning agent converges to a strategy that marginally improves throughput, travel speed, and freeway travel time, at the cost of a slightly higher carbon footprint.

Suggested Citation
Y Moghaddas, M Fakih, T Zhang, M Odema and MA Al Faruque (2023) ‪An Integrated Corridor Management for Connected Vehicles and Park and Ride Structures using Deep Reinforcement Learning‬. Technical Report 23-03. Center for Embedded & Cyber-Physical Systems, UCI. Available at: https://cecs.uci.edu/files/2023/08/An-Integrated-Corridor-Management-for-Connected-Vehicles-and-Parkand-Ride-Structures-using-Deep-Reinforcement-Learning.pdf (Accessed: October 5, 2023).

Phd Dissertation

Rural identity and attitudes toward growth management in the Rocky Mountains : an exploration of state, county, and municipal officials in Idaho

Publication Date

January 1, 1997

Author(s)

Gayla Smutny
Suggested Citation
Gayla Smutny (1997) Rural identity and attitudes toward growth management in the Rocky Mountains : an exploration of state, county, and municipal officials in Idaho. PhD Dissertation. University of California, Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/17uq3m8/alma991020297819704701.

published journal article

Heuristic vehicle classification using inductive signatures on freeways

Transportation Research Record

Publication Date

January 1, 2000
Suggested Citation
Carlos Sun and Stephen G. Ritchie (2000) “Heuristic vehicle classification using inductive signatures on freeways”, Transportation Research Record, 1717(1), pp. 130–136. Available at: 10.3141/1717-16.

policy brief

Communities Are Experimenting with Microtransit to Fill Critical Gaps in Public Transit Service – What Have We Learned so Far?

Publication Date

September 1, 2024

Author(s)

Susan Shaheen, Elliot Martin, "Brooke (Schmidt) Wolfe ", Adam Cohen

Abstract

This brief provides an overview of microtransit service as deployed across California. Microtransit is a technology-enabled transit service that typically employs shuttles or vans to provide on-demand transportation with dynamic routing. While many rides are dispatched and paid via a smartphone, many services also provide a telephone booking option. A few services accept cash payment and street hails (similar to taxis). Variations of microtransit can include fixed schedules and routes and larger or smaller vehicles. Typically, microtransit services are operated by or provided on behalfof a government entity or nonprofit organization, although privately operated microtransit programs also might exist.

Suggested Citation
Susan Shaheen, Elliot Martin, "Brooke (Schmidt) Wolfe " and Adam Cohen (2024) Communities Are Experimenting with Microtransit to Fill Critical Gaps in Public Transit Service – What Have We Learned so Far?. Policy Brief. UC ITS. Available at: https://doi.org/10.7922/g2w957jf.

book/book chapter

Road Pricing for Congestion Management: The Transition from Theory to Policy

Publication Date

January 1, 1997

Author(s)

Kenneth Small, Jose A. Gomez-Ibanez
Suggested Citation
Kenneth A. Small and Jose A. Gomez-Ibanez (1997) “Road Pricing for Congestion Management: The Transition from Theory to Policy”, in Transport Economics. 1st ed. Routledge. Available at: https://www.taylorfrancis.com/chapters/edit/10.4324/9780203985359-20/road-pricing-congestion-management-transition-theory-policy-kenneth-small-jose-gomez-ibanez.

working paper

When Do Consumers Favor Price Increases: With Applications to Congestion and to Regulation

Publication Date

December 1, 1992

Associated Project

Author(s)

Amihai Glazer, Esko Niskanen

Working Paper

No. 193

Areas of Expertise

Abstract

For a conventional good, an increase in price reduces the consumer surplus of both those who no longer buy the good, and of those who continue to buy it. If, however, consumers must spend real resources to obtain rights for the good, or if the quality depends on the number of other consumers trying to obtain the same good, then a price increase may have different effects. Both these characteristics apply to congestible goods: a consumer’s utility decreases in the price he pays and in the number of other persons who use the good. Some users may gain from a price increase which reduces demand. Therefore, even if the revenue is not returned to the users, their welfare can increase.

Suggested Citation
Amihai Glazer and Esko Niskanen (1992) When Do Consumers Favor Price Increases: With Applications to Congestion and to Regulation. Working Paper No. 193. Institute of Transportation Studies, UC Irvine: University of California Transportation Center. Available at: https://escholarship.org/uc/item/3w17n1bc.

Phd Dissertation

Electrification, Connectivity, & Active Demand Management: Addressing the traffic, health, and environmental justice impacts of drayage trucks in Southern California

Abstract

Trucking electrification combined with connected and automated technologies promises to cut the cost of freight transportation, reduce its environmental footprint, and make roads safer. If electric trucks are powerful enough to cease behaving as moving bottlenecks, they could also increase road capacity and reduce the demand for new infrastructure, a consequence that has so far been overlooked by the literature. In this dissertation, I study the traffic and infrastructure demand impacts of electrifying and connecting (via cooperative adaptive cruise control, CACC) heavy-duty drayage trucks (HDDTs) that serve the San Pedro Bay Ports (SPBP; the ports of Los Angeles and Long Beach, which is the largest port complex in the U.S), quantify the resulting health, environmental, and Environmental Justice impacts, and explore how to maximize the benefits of connected vehicles with active demand management.In Chapter 2, I explore the potential traffic and infrastructure implications of replacing conventional HDDTs that serve the SPBP with electric and/or connected HDDTs. I rely on microscopic simulation on a freeway and arterial network centered on I-710, the country’s most important economic artery. My results show that 1,000-hp electric/hydrogen trucks can be a substitute for additional road capacity. Accounting for the traffic impacts of new vehicle technologies is critical in infrastructure planning, and my results suggest shifting funding from building new capacity to financing zero-emission (ZE) 1,000 hp HDDTs until the market for these vehicles has matured. In Chapter 3, I quantify the health and GHG reduction benefits of replacing the HDDTs serving the SPBP with ZE-HDDTs. I simulate ZE-HDDTs on a regional freeway network to analyze their PM2.5 and CO2 emissions in 2012 and 2035 using MOVES3 emission factors. I then estimate their contribution to PM2.5 concentrations with InMAP and health impacts with BenMAP. I find that despite technology improvements and air quality regulations, SPBP HDDTs would still cause 106 premature deaths (valued at $1.3 billion in $2022) and 2,142 asthma attacks (over two thirds of which would accrue to disadvantaged communities) in 2035 due to population and drayage traffic growth, not to mention at least $220 million in climate costs. With ZE-HDDTs becoming attractive in the next few years from a total cost of ownership point-of-view, the main cost of achieving ZE road drayage is a scrappage program for non-ZE-HDDTs. My results justify implementing this program by 2035. In Chapter 4, I study the performance impacts of lane management strategies implemented on I-710 to support the deployment of CACC-enabled vehicles and their potential to absorb the 2035 projected growth in cargo demand at the SPBP. I find that a designated lane for CACC-enabled vehicles can decrease congestion by creating more platooning opportunities, thus maximizing CACC benefits.

Suggested Citation
Monica Ramirez-Ibarra (2022) Electrification, Connectivity, & Active Demand Management: Addressing the traffic, health, and environmental justice impacts of drayage trucks in Southern California. Ph.D.. UC Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/u4evf/cdi_proquest_journals_2729127485 (Accessed: October 12, 2023).