MS Thesis

Changes in Travel Patterns of Two-person Households in California between 2001 and 2012

Publication Date

December 30, 2015

Author(s)

Dhanya Pranab Kumar

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment

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Abstract

The main objective of this thesis is to highlight the travel patterns of two-person households in California as captured in the 2000-2001 and 2010-2012 California Household Travel Surveys (CHTS). The intent is to present basic travel characteristics of households with two peoples who are couples, are employed and do not have kids at home (denoted as DINK – Dual Income No Kids at home) along with comparisons with two-person households who does not belong to the aforementioned category (NON-DINK) using the CHTS 2000-2001 and 2010-2012 datasets. The results highlight significant differences in travel patterns between the two categories, DINKs and NON-DINKs during the eleven years from 2001 to 2012. The average number of daily trips is higher for DINKs compared to NON-DINKs and the trip rate has reduced in 2012 compared to 2001 for both categories. Auto (driver of auto/truck/van) trips is the primary mode of travel for DINKs and NON_DINKs in CHTS 2001 and 2012. During the eleven years, there has been a decrease in auto trips and an increase in the percentages of passenger, bike, walk and transit trips. The primary trip purpose for DINKs are work or work-related, whereas the primary trip purpose for NON-DINKs are shopping/maintenance trips according to both survey results.

MS Thesis

Assessing the Impact of SB743 on Transportation Planning, Traffic Impact Analysis, and Level-of-Service

Publication Date

December 30, 2015

Author(s)

Oluseyi Ojuri

Areas of Expertise

Infrastructure Delivery, Operations, & Resilience Travel Behavior, Land Use, & the Built Environment

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Abstract

Since the implementation of CEQA in 1970, traffic impact analyses have been a key component in California’s land development. A current paradigm shift towards building and living sustainably has caused policy makers, engineers and planners to reexamine the policies that have been instituted. It has also influenced exploration of solutions that can change future developments. We must first analyze the established system of traffic impact analysis to determine the viability and potential benefits of measuring transportation network efficiency through factors highlighted in Senate Bill (SB) 743. These factors include vehicle miles travelled (VMT), fuel use or automobile trips generated. For the purpose of this paper, the focus will be on the VMT. When VMT analysis is applied on a project level, a list of key questions arise that are related to SB 743’s goals of reducing greenhouse gases, increasing multimodal transportation and developing appropriate metrics to conduct transportation analysis. A review of Senate Bill 743 text along with the Governor’s Office of Planning and Research report on the Bill paints a picture of what California’s future development will look like. Furthermore, an examination of travel trends and literature about current transportation analysis helps to evaluate the potential success of Senate Bill 743. In summary, Senate Bill 743 symbolizes a huge step towards carbon emission reduction and an excellent opportunity to start a conversation about making land development more sustainable in California. However, the bill leaves out the essential components of existing traffic impact analyses and employs a measure of environmental impact that does not reflect accessibility or multi-modal transportation.

Phd Dissertation

Modeling Shared-use Urban Mobility Systems to Increase System Performance

Publication Date

September 14, 2015

Author(s)

Robert Regue Grino

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

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Abstract

Shared-use mobility systems, which enable users to have short-term access to transportation modes on an on-demand basis, have experienced tremendous growth over the last decade. However, most of the existing systems suffer from two confounding issues: the lack of modeling tools to understand, simulate and predict their behavior and the lack of integration with the existing transit network. To address those issues, this dissertation focuses on investigating the operational challenges of bikesharing systems, with an emphasis on the rebalancing operations and the modeling of a new mobility concept, Car2work, which builds upon existing carsharing ideas and successfully integrates with existing transit networks. A methodological framework to solve the bikesharing rebalancing problem is proposed. The novelties of the approach are that it is proactive instead of reactive, as the bike redistribution occurs before inefficiencies are observed, and uses the outputs of a demand-forecasting technique to decompose the inventory and the routing problem. The decomposition makes the problem scalable, responsive to operator inputs, and able to accommodate user-specific models. Simulation results based on data from the Hubway bikesharing system show that system performance improvements of 7% in the afternoon peak could be achieved.

Car2work main goal is to connect commuters with workplaces while leveraging the line-haul capabilities of existing public transit systems and guaranteeing a trip back home, efficiently tackling the “last mile” problem that is a limiting characteristic of public transit. It differs from the traditional dynamic-ridesharing approaches because it is designed for recurrent commuting trips where commuters announce their (multiple) trips in advanced and an automated all-or-nothing matching strategy is performed, guaranteeing a ride home. The problem is formulated as a pure binary problem that is solved using an aggregation/disaggregation algorithm that renders optimal solutions. The solution approach is based on decomposing the problem into a master problem and a sub-problem, reducing the number of decision variables and constraints. As a result, various instances of the problem can be solved in reasonable amount of time, even when considering the transit network. The model can be used to simulate a widespread implementation of the concept.

Phd Dissertation

Inequality in Accessibility to Amenities and Exposure to Hazards

Publication Date

September 14, 2015

Author(s)

Dongwoo Yang

Areas of Expertise

Safety, Public Health, & Mobility Justice Travel Behavior, Land Use, & the Built Environment

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Abstract

This dissertation proposes a heuristic theoretical framework for understanding dynamics that impact environmental health including social/built environmental settings, individual residents’ behavioral patterns, location activity spaces (LAS), environmental quality, exposure, and health outcomes. I examined the relationships between factors included in the framework based on individuals’ LASs, and represent a hypothetical geographic boundary in which an individual is expected to spend his/her time in daily life. In addition to the individual level exposure, I characterized built environmental quality for subsidized housing neighborhoods in Los Angeles and Orange Counties, which have not been the focus of previous affordable housing studies. In Chapter 2 and Chapter 4, I empirically demonstrated the framework for residents in neighborhoods near the Expo Right Rail Transit line and the Boyle Heights community in Los Angeles. With OLS regression analysis, I found that bigger LAS were associated with lower walkability, more non-residential land use, higher transit stop density, shorter length of residency, working out of home, and higher income. I examined the relationship between the probability of a census block group (BG) having at least one subsidized unit and associated BG built environmental qualities. Based on logistic regression models, I found that subsidized housing units tended to be located in BGs with better transit access, lower walkability, more mixed-use, and lower air pollution concentrations.

Phd Dissertation

Technology, Trade and the Environment

Publication Date

August 19, 2015

Author(s)

Paul Stroik

Areas of Expertise

Transportation Economics, Funding, & Finance

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Abstract

The three chapters in this dissertation use firm-level data from Vietnam, Chile, and a set of Eastern-European countries to understand the importance of foreign direct investment in technology diffusion and subsequent environmental implications of changes in the production process. Chapter 1 investigates whether increased within-firm or within-industry foreign exposure, or foreign exposure from domestic downstream industry increases technology adoption. Chapters 2 and 3 look beyond technology spillovers of foreign investment, considering whether increased foreign investment affects domestic firm energy intensities. Chapter 2 studies whether domestic Vietnamese firms that become suppliers of domestic foreign-owned firms experience differential technology adoption and changes in energy intensity. Chapter 3 studies whether increased within-firm or within-industry foreign exposure, or foreign exposure from domestic downstream industry in Chile affects firm-level energy intensities.

Studying manufacturing and service firms in Eastern-European countries, Chapter 1 finds that technology gains from domestic foreign exposure differ between lower-income and higher-income countries. In higher-income countries, increased within-industry foreign exposure and increased foreign exposure from downstream industries on average increases technology adoption.

Studying Vietnamese manufacturing firms, Chapter 2 finds that firms that become suppliers of domestic foreign firms are on average more likely to have innovated than their non-supplier peers. These technology gains are found not to translate into short-run changes in energy intensity.

Studying Chilean manufacturing firms, Chapter 3 finds as firms experience increased within-firm foreign investment, they on average increase their electricity intensity. Moreover, increased within-industry foreign exposure on average increases electricity intensity for all firms, and fuel intensity for firms in “dirty” industries.

Phd Dissertation

Human-centered computing and the future of work : lessons from mechanical turk and turkopticon, 2008-2015

Publication Date

June 29, 2015

Author(s)

Michael (Six) Silberman

Areas of Expertise

Other

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Abstract

Online labor markets such as Amazon Mechanical Turk (AMT), Uber, and TaskRabbit are contributing to rapid changes in the nature of work for hundreds of thousands of workers. These markets create significant new economic opportunities, but most currently treat workers as second-class citizens. Take-home pay is often low compared to similar work in traditional employment arrangements, and workers have limited means of influencing market design or management practice. This makes it hard for workers to create reliable livelihoods from the opportunities these markets present. This dissertation uses AMT, an online labor market for small information tasks, as a case through which to examine the consequences of treating workers as second-class citizens, to argue that future platform designs and management practices should treat workers as central stakeholders, and to develop theory and method for doing so. The central argument of the dissertation is that workers’ concerns should be more substantively and systematically addressed in the design and operation of online labor markets. Five messages elaborate this argument. First, in online labor markets, some workers are casual or transient, while others are professionals, providing significant and reliable value to customers and relying on income earned in the market to meet basic needs. Second, workers who rely on income earned through online labor markets should be considered first-class stakeholders, alongside customers and shareholders. Third, workers in online labor markets are rarely the narrowly self-interested profit maximizers of classical economic theory. Workers can be better understood as “situatedly rational” actors: human beings with incomplete information and finite cognitive capabilities whose actions and preferences are shaped by many factors, including rules, norms, and expectations. Fourth, online labor markets are not monolithic, perfectly competitive markets but parts of polycentric economic systems composed of complexly interlinked action situations characterized by imperfect competition and incomplete information. Fifth, institutions supporting crowd work research should develop an interdisciplinary practice-oriented agenda to understand the consequences of current online labor market designs and practices, and to develop new designs and practices that incorporate workers who rely on market income as central stakeholders.

working paper

A Real-Time Algorithm to Solve the Peer-to-Peer Ride-Matching Problem in a Flexible Ridesharing System

Publication Date

June 30, 2015

Author(s)

Neda Masoud, R. (Jay) Jayakrishnan

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

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Abstract

Real-time peer-to-peer ridesharing is a promising mode of transportation that has gained popularity during the recent years, thanks to the wide-spread use of smart phones, mobile application development platforms, and online payment systems. An assignment of drivers to riders, known as the ride-matching problem, is the central component of a peer-to-peer ridesharing system. In this paper, we discuss the features of a flexible ridesharing system, and propose an algorithm to optimally solve the ride-matching problem in a flexible ridesharing system in real-time. We generate random instances of the problem, and perform sensitivity analysis over some of the important parameters in a ridesharing system. Finally, we introduce the concept of peer-to-peer ride exchange, and show how it affects the performance of a ridesharing system.

Phd Dissertation

Development of Dielectric Elastomer Nanocomposites as Stretchable and Flexible Actuating Materials

Publication Date

June 29, 2015

Author(s)

Yu Wang

Areas of Expertise

Other

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Abstract

Dielectric elastomers (DEs) are a new type of smart materials showing promising functionalities as energy harvesting materials as well as actuating materials for potential applications such as artificial muscles, implanted medical devices, robotics, loud speakers, micro-electro-mechanical systems (MEMS), tunable optics, transducers, sensors, and even generators due to their high electromechanical efficiency, stability, lightweight, low cost, and easy processing. Despite the advantages of DEs, technical challenges must be resolved for wider applications. A high electric field of at least 10-30 V/um is required for the actuation of DEs, which limits the practical applications especially in biomedical fields. We tackle this problem by introducing the multiwalled carbon nanotubes (MWNTs) in DEs to enhance their relative permittivity and to generate their high electromechanical responses with lower applied field level. This work presents the dielectric, mechanical and electromechanical properties of DEs filled with MWNTs. The micromechanics-based finite element models are employed to describe the dielectric, and mechanical behavior of the MWNT-filled DE nanocomposites. A sufficient number of models are computed to reach the acceptable prediction of the dielectric and mechanical responses. In addition, experimental results are analyzed along with simulation results. Finally, laser Doppler vibrometer is utilized to directly detect the enhancement of the actuation strains of DE nanocomposites filled with MWNTs. All the results demonstrate the effective improvement in the electromechanical properties of DE nanocomposites filled with MWNTs under the applied electric fields.

Phd Dissertation

Designing Environment-Oriented Pricing and Traffic Rationing Schemes for Travel Demand Management

Publication Date

June 29, 2015

Author(s)

Daniel Rodriguez-Roman

Areas of Expertise

Transportation Economics, Funding, & Finance Travel Behavior, Land Use, & the Built Environment

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Abstract

Optimization-based approaches are presented for the design of environment-oriented road pricing and traffic rationing schemes, particularly with the objective of curbing human exposure to motor vehicle generated air pollutants. In addition, surrogate-based solution algorithms are developed to accelerate the search of good solutions for the problems considered. A toll design problem is proposed for selecting tolling locations and levels that minimize environmental inequality and human exposure to pollutants, subject to budget constraints and pollutant concentration constraints at receptor points. A mixed-integer variant of the metric stochastic response surface algorithm and a hybrid genetic algorithm-metric stochastic heuristic are presented to solve the mixed integer toll design problem. Numerical tests suggest that the proposed algorithms are promising solution methods for transportation network design problems. In addition, an optimization problem is presented for the design of cordon and area-based road pricing schemes subject to environmental constraints. Flexible problem formulations are considered which can be easily utilized with state-of-the-practice transportation planning models. A surrogate-based solution algorithm that utilizes a geometric representation of the charging area boundary is proposed to solve cordon and area pricing problems. Lastly, a bi-objective traffic rationing problem is considered where the planner attempts to maximize auto usage while minimizing pollutant exposure inequality, subject to constraints on the levels of greenhouse gas emissions and pollutant concentration levels. A surrogate-assisted differential evolution algorithm for multiobjective continuous optimization problems with constraints is proposed.

Phd Dissertation

Regional Scale Dispersion Modeling and Analysis of Directly Emitted Fine Particulate Matter from Mobile Source Pollutants Using AERMOD

Publication Date

June 29, 2015

Author(s)

Seth Contreras

Areas of Expertise

Safety, Public Health, & Mobility Justice Travel Behavior, Land Use, & the Built Environment Zero-Emission Vehicles & Low-Carbon Fuels

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Abstract

A large and growing body of literature associates proximity to major roadways with increased risk of many negative health outcomes and suggests that exposure to fine particulate matter may be a substantial factor. Directly emitted and non-reactive mobile source air pollutants such as directly emitted fine particulate matter can form large spatial concentration gradients along major roadways, in addition to causing significantly large temporal and seasonal variation in air pollutant concentrations within urban areas. Current modeling and regulatory approaches for minimizing exposure have limited spatial resolution and do not fully exploit the available data. The objective is to establish a methodology for quantifying fine particulate matter concentration gradients due to mobile source pollutants and to estimate the resulting population exposure at a regional scale. A novel air dispersion modeling framework is proposed using the Environmental Protection Agency’s regulatory model AERMOD with data from a regional travel demand model that can produce a high resolution concentration surface for a considerably large metropolitan area; in our case, Los Angeles County, California. We find that PM2.5 concentrations are highest and most widespread during the morning and evening commutes, particularly during the winter months. This is likely caused by a combination of stable atmospheric conditions during the early morning and after sunset in the evening and higher traffic volumes during the morning and evening commutes. During the midday hours concentrations are at their lowest even though traffic volumes are still much higher than during the evening. This is likely the result of heating during the day time which leads to unstable atmospheric conditions that cause more vertical mixing and lateral dispersion, reducing ground level PM2.5 concentrations by transport and dilution. With respect to roadway centerlines, PM2.5 concentrations drop off quickly, reaching relatively low concentrations between 150m to 200m from the center line of high volume roads. However, during stable atmospheric conditions (e.g., nighttime & winter season) concentrations remain elevated at distances up to 1,000m from roadway centerlines. We will demonstrate the feasibility of our methodology and how integrating the dispersion modeling framework into the travel demand modeling process routinely performed when developing and analyzing regional transportation improvement initiatives can lead to more environmentally and financially sustainable transportation plans. Regional strategies that minimize exposure, rather than inventories, could be established, environmental justice concerns are easily identified, and projects likely to cause local pollution “hotspots” can be proactively screened out, saving time and money for the transportation agency.