자료유형  

 학위논문

Control Number  

0016931299

International Standard Book Number  

9798380619561

Dewey Decimal Classification Number  

385

Main Entry-Personal Name  

Lazarus, Jessica.

Publication, Distribution, etc. (Imprint  

[S.l.] : University of California, Berkeley., 2023

Publication, Distribution, etc. (Imprint  

Ann Arbor : ProQuest Dissertations & Theses, 2023

Physical Description  

1 online resource(203 p.)

General Note  

Source: Dissertations Abstracts International, Volume: 85-04, Section: B.

General Note  

Advisor: Bayen, Alexandre;Shaheen, Susan.

Dissertation Note  

Thesis (Ph.D.)--University of California, Berkeley, 2023.

Restrictions on Access Note  

This item must not be sold to any third party vendors.

Summary, Etc.  

요약The digitization and automation of transportation systems is fundamentally transforming the transportation landscape, creating important opportunities and challenges for improving the sustainability of transportation worldwide. There are more travel options to choose from than ever before, with real-time information on the cost and time trade-offs between alternative routes and modes of travel available in the palm of a hand. In particular, shared on-demand mobility services such as transportation network companies (TNC) (e.g., Lyft, Uber), bikesharing, and microtransit offer affordable and convenient alternatives to personal auto ownership that can complement or supplement existing public transit services. In addition, these services may aid in reducing existing inequities in access to fast and reliable transportation. However, despite the potential that innovative shared mobility service models bring forth to improve the sustainability of transportation, the inefficiencies of fleet-based services such as TNCs and the low adoption rates of pooled rides that transport multiple travelers in the same vehicle have contributed to worsening congestion in several regions across the United States. Meanwhile, the design and deployment of transportation demand management (TDM) strategies has not kept pace of disruption nor the corresponding evolution in travel behavior.In light of the pressing need to improve the sustainability of a rapidly evolving transportation ecosystem, this dissertation contributes to the theory, methodology, and state of knowledge of optimal mechanism design for multi-faceted TDM strategies. With a focus on congestion pricing strategies, this research aims to facilitate the design and analysis of data-driven TDM strategies that incorporate a multitude of policy levers (e.g., congestion pricing, multi-modal incentives, public transit operations) using a simulation-based multi-objective optimization approach to inform decision-makers about the inherent trade-offs between congestion and emission reductions, economic feasibility, and transportation equity.In particular, I focus on the optimization of congestion pricing and targeted incentive schemes in multi-modal transportation networks including pooled ride options. Congestion pricing aims to reduce congestion by charging road users for driving on congested roads. A review of the various aspects of the transportation pricing optimization problem as studied in the literature is presented in Chapter 2, including the specification and analysis of various dimensions of demand sensitivity, congestion pricing structure and charging zone design, optimization objectives, optimization approaches, and transportation equity analysis. Studies of the optimization of pricing structures and charging zones for congestion pricing schemes have established that greater toll levels and charging zone coverage produce greater reductions in driving, which is deemed beneficial with respect to total system-wide travel time reductions. However, as is pointed out by public acceptance studies and literature on the equity implications of congestion pricing, the cost burden of congestion mitigation is disparately borne by lower-income individuals who are the most likely to be financially incentivized to adopt less desirable alternatives to driving. Few congestion pricing optimization studies have incorporated transportation equity objectives; none have included equity in addition to other efficiency and environmental objectives. The contributions of this dissertation to the literature on congestion pricing optimization span the theory of optimal mechanism design for multi-objective congestion pricing strategies, methodology for simulation-based multi-objective optimization of multi-faceted TDM strategies, and empirical understanding of congestion pricing strategies optimized with respect to multiple policy objectives.Mechanism Design for Optimal Congestion Pricing PoliciesChapter 3 establishes that equity-based objectives and the inclusion of monetary incentives for the adoption of driving alternatives are feasible strategies for tackling the equity issues inherent in congestion pricing optimization (i.e., the disparate distributions of increased costs for lower income drivers and reduced travel times for higher income drivers). In this chapter, I formulate a bi-level optimization problem to compute optimal link- and mode-specific tolls and targeted mode-specific incentives (i.e., direct monetary transfers) using aggregate-level information on the flows of network users using various modes of transportation. This work contributes to the theory of congestion pricing optimization by proving the existence of optimal multi-modal congestion pricing schemes including both tolls and monetary incentives that are optimized with respect to equity-focused objectives defined on the basis of the distributional impacts of the pricing scheme across travelers. Several functions inspired by different theories of justice are presented as alternative social objective functions, including:1. Utilitarian: maximize the sum of individual utility (i.e., a quasilinear function of travel time, cost, and other factors weighted by the individual demand sensitivity to each) of travel,2. Egalitarian: maximize the sum of individual utility using the average demand sensitivity to weight travel time cost,3. Equality of Opportunity: maximize a weighted sum of the individual utility, again using the average demand sensitivity. (Abstract shortened by ProQuest).

Subject Added Entry-Topical Term  

Transportation.

Subject Added Entry-Topical Term  

Sustainability.

Subject Added Entry-Topical Term  

Public policy.

Subject Added Entry-Topical Term  

Environmental engineering.

Index Term-Uncontrolled  

Carpooling

Index Term-Uncontrolled  

Congestion pricing

Index Term-Uncontrolled  

Multi-objective optimization

Index Term-Uncontrolled  

Transportation demand management

Index Term-Uncontrolled  

Transportation equity

Index Term-Uncontrolled  

Transportation sustainability

Added Entry-Corporate Name  

University of California, Berkeley Civil and Environmental Engineering

Host Item Entry  

Dissertations Abstracts International. 85-04B.

Host Item Entry  

Dissertation Abstract International

Electronic Location and Access  

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Control Number  

joongbu:642381