D03-1

Jason Lee
An Economic Analysis of the Good Roads Movement
Advisor: Alan Olmstead

This study fills a research void in the transportation history of the United States by examining the construction of the road network in the early 20th century. The roads were the backbone of the transportation network at the turn of the century, and the movement to improve them had lasting economic consequences. This project addresses several questions: (1) What were the economic factors that led to the improvement of the road network? (2) What were the economic and social consequences that resulted from the roads movement? (3) How was the coordination problem between local, state and federal governments resolved? and (4) Who were the groups for and against the construction of good roads? Basic economic demand-side modeling will be employed to answer the questions posed above. By examining the economic effects of road improvement in early 20th century America, we may glean some insights on the relationship between infrastructure investment and economic growth and development which can be applied in creating a sustainable transportation plan for developing countries.

D03-2

Zhen Qian
Holistic Dynamic Congestion Pricing (HDCP) With Heterogeneous Travelers in Corridor Networks
Advisor: Michael Zhang

Holistic dynamic congestion pricing plays an important role in sustainable transportation. An efficient pricing scheme optimizes route choices and departure time of travelers at the network level, and it may also lead private car travelers to shift to the public transit, or alternatively to reduce the total demand. Hence, congestion may be largely mitigated under an efficient pricing scheme. In this dissertation, we shall first establish a dynamic equilibrium among three groups of people, i.e. non-carpooled private car users (solo-drivers), carpooled private car users (carpoolers) and transit users. Then, transit fares, parking fees and road pricing are generally considered as three major forms of time-varying pricing schemes. More importantly, unlike the traditional research based on a homogenous population, we would like to study dynamic congestion pricing upon users with continuously distributed values of time (VOT). We shall start from a typical single-origin-single-destination (SOSD) network, and extend it to a “pure” freeway network and eventually a general combined corridor network. We expect to propose a dynamic pricing solution framework and find a realistic and efficient way of holistic dynamic pricing for sustainable transportation systems. More particularly, relying on this solution framework, sensitivity analysis, with respect to some critical parameters (such as pricing, bottleneck capacity, etc), will be conducted to show how changes in a critical factor will affect the network performances.

D03-3

David Vernon
Hydrogen Enriched Internal Combustion Via Thermochemical Recuperation to Increase Efficiency and Reduce Emissions
Advisor: Paul Erickson

In internal combustion engines the majority of the chemical energy held in the original fuel is exhausted as waste heat. This exhaust heat represents a significant potential source of energy to be taped. Endothermic reformation reactions can convert a portion of this exhaust heat into chemical energy by breaking fuel molecules apart producing hydrogen rich gas in a process called thermochemical recuperation. The hydrogen rich gas can be used to enrich the primary fuel air mixture. Hydrogen enrichment of the primary fuel mixture enables combustion with very lean or dilute mixtures resulting in low temperature combustion and thereby achieving higher efficiency and lower emissions than standard combustion regimes. This project will experimentally investigate the use of ethanol autothermal reformation for on-board hydrogen generation using waste heat.

Hydrogen enrichment via chemical recuperation is a hydrogen technology that does not require hydrogen refueling station infrastructure nor significant on-board hydrogen storage and therefore has the potential to be commercialized in the near term. This technology would increase efficiency and reduce emissions in ICE vehicles while also laying the groundwork for smaller scale hydrogen production technologies and eventually for fuel cell vehicles.

D02-1

Christopher Congleton, TTP  
The Collective Calculus of Travel Mode Choice: Are Drivers Free-Riding on Lower Impact Modes?
Advisor: Susan Handy

This study develops and tests a model of mode choice that incorporates the logic of collective action.  I test the hypothesis that travelers consider externalities of their travel choices and their ability to influence changes in the collective outcomes of their travel behavior when choosing their mode of travel.  I hypothesize that ordinary travelers vary predictability in the degree to which they are involved in efforts to increase positive externalities, reduce negative externalities, and attempt to produce collective goods using a model of collective action.  Should these considerations prove to be present in mode choice, this has widespread implications for travel demand modeling, travel demand management, and transportation policy and praxis.  We test a collective interest model of mode choice, adapted from studies of protest behavior and environmental activism; and the individual rational choice model as commonly used in travel mode choice studies.

D02-2

Yongxi Huang, CEE  
Optimal Design of Hydrogen Production, Storage and Delivery System under Uncertainty
Advisor: Yueyue Fan

This study aims to minimize the total cost of the entire hydrogen pathway using optimization techniques, and simultaneously satisfy all the demand requirements and feedstock resource constraints.  In an uncertain decision environment, rigorous stochastic modeling methods are incorporated in order to improve the efficiency and reliability of hydrogen systems.  Due to the time-dependent availability of most of the renewable feedstock, a multistage model that has built-in temporal dimension is required.  A multistage stochastic model is proposed in this study.  We will also integrate engineering-economic models into the optimization model framework to make the modeling more realistic.  Engineering-economic models will be used to estimate the primary inputs of feedstock and capital equipment, and also to estimate the resulting outputs (e.g. hydrogen and carbon).

D02-3

Julia Silvis, TTP  
Social Networks as Transportation Resources: A Survey of Seniors
Advisor: Deb Niemeier

This project investigates the interactions between seniors’ social networks and their travel behavior, and will quantify the transportation-related carbon emissions of seniors.  Using survey data, Julia will assess three primary questions: 1) the transportation-related carbon emissions (including trips made on behalf of respondents) associated with various levels of age and mobility, and 2) how and if seniors are able to use their social networks as transportation resources, through ridesharing, receiving visits, having friends run errands for them and 3) if ridesharing (or other behaviors) allow seniors to maintain mobility at lower emission levels.  In addition, to investigate impacts of the built environment on these relationships, respondents will be divided into four groups, based on where they live (Davis or Roseville) and whether or not they live in a retirement community.  This study will shed light on how transportation-related carbon emissions are likely to change with the coming demographic shift, as well as on how seniors can maintain mobility, independence and quality of life as they age.  The implications of this study will not be limited to seniors, however, but should reveal ways in which mobility in general could be maintained with lower carbon emissions.

D02-4

Adam Henry, TTP  
Social Networks and Learning for Sustainability in Regional Planning
Advisor: Mark Lubell

One of the most important goals of collaborative planning processes is to promote successful learning by and amongst networked groups of actors. "Learning" is the process by which stakeholders collectively hone their abilities to address complex problems, develop common understandings of issues to be addressed, and produce effective policy solutions. Despite the importance of learning to sustainable planning efforts, there is a paucity of research on how and why learning occurs. This dissertation uses social networks as the primary organizing concept through which to study learning in the context of regional land use and transportation planning. Data are collected using a survey instrument from stakeholders involved in five regional planning processes in California. The survey measures belief systems, various social network structures, and individual involvement in collaborative efforts. Exponential random graph models will be used to explore the determinants of network structure and identify signatures of learning. This analysis will be supplemented with agent-based computer simulations to investigate how planning institutions can be better designed to promote desirable network structures and enable learning. Ultimately, this research will contribute to a coherent theory of how collaborative institutions can promote more sustainable transportation and land use planning through learning.

D02-5

Haining Du, CEE  
Development of Dynamic Traffic Management System
Advisor: Michael Zhang

The dissertation study is aimed at establishing a new framework for dynamic traffic control using vehicular ad hoc networks. Real time traffic information will be collected from all the vehicles involved to generate suitable control strategies to make the road safer and less congested. In this research, fCA, a cellular automata (CA) model with finer time-space resolution is proposed and coded as a simulation tool. Algorithms will be developed to make the lane changing maneuver more realistic. Then, this fCA model will be calibrated and validated using field data from NGSIM. After that, control strategies including Variable Speed Limits (VSL) and suggestion for lane changing will be studied and corresponding algorithms will be developed. They will be implemented in the simulation for evaluation. We will also evaluate the impact of the proportion of drivers who do not follow the control strategies. Simulation based on fCA model will be used to generate results for the evaluation. This dynamic traffic management system is expected to make the traffic flow more stable and smooth and lead to higher flow capacities especially for the places where insufficient capacity deteriorates the level of service, i.e. ramps, work zone, etc.

D02-6

Wei Tang, TTP  
The Exploration of E-Shopping Behavior: A Latent Class Approach
Advisor: Patricia Mokhtarian

    Online shopping has increased steadily since its introduction, and could lead to substantial impacts on trip generation, destinations, and timing. Fully understanding the potential transportation impacts requires us to better understand the adoption of this new shopping alternative (or "channel"), and to compare it with the old one (i.e. conventional store shopping).
 
     This study proposes to model e-shopping adoption as a function of numerous factors hypothesized to influence it, such as general and channel-specific shopping attitudes, shopping experiences, and objective characteristics of the consumer. The data were collected from an Internet-based survey conducted in the spring of 2006, in two northern California university communities: Davis and Santa Clara. Since we think different people weight variables affecting channel choice differently, we apply latent class modeling (LCM) to simultaneously segment shoppers and produce segmented discrete choice models. By comparing the LCM approach with the conventional one (i.e. using conventional cluster analysis for market segmentation), we expect the results will show that LCM is superior to the latter approach. And we hope it will also provide important insights into (1) the response to internet shopping, and (2) the efficacy of the LCM approach in understanding human diversity of tastes and values.

D01-1

Nicholas P. Lutsey, TTP  
Prioritization of Technology Alternatives for Cost-Effective Climate Change Mitigation
Advisor: Dan Sperling

Governments worldwide are considering and enacting a variety of measures to reduce greenhouse gas emissions from the transportation sector. But which strategies are most sustainable, effective, and beneficial? This study is a systematic attempt to put climate change emission reduction strategies in context for researchers and policymakers. Current research in this area has deficiencies in three areas: incorporating the experience of the lower-level climate change initiatives, integrating the disparate research studies’ results, and including the ancillary benefits of mitigation policies. This proposed research tackles these issues to prioritize future climate change policy actions. It develops a novel “multi-benefit” cost-effectiveness accounting framework that quantifies, monetizes and bundles private and societal impacts of the mitigation measures into one cost-per-ton metric. It also compares and prioritizes transportation alternatives both within the sector and to options in other sectors.

D01-2

Wei Shen, CEE   
Dynamic System Optimal Assignment for Emergency Evacuations
Advisor: Michael Zhang

This dissertation proposes to develop a series of advanced models and corresponding software tools for designing emergency evacuation plans in transportation networks. Given the potential serious effects of man-made and natural disasters, quickly moving people out of harm’s way is critically important. In this research, the evacuation planning problem is formulated as a system optimal dynamic traffic assignment (SO-DTA) model subject to constraints. Existing SO-DTA models involve significant deficiencies and are not ready to be applied in evacuation planning; this project seeks to overcome those deficiencies. Practical constraints such as updating rules for control signals at merging points, direction switching rules for reversible lanes, releasing rules of departure flow at origins will then be added into the base model to derive practical evacuation plans. The research will also develop a case study for the City of Sacramento.

D01-3

Taihyeong Lee, CEE 
The Impact of Structural Changes in U.S. Industry on Relationships between Transportation and Communications
Advisor: Pat Mokhtarian

Many public policies have been developed on the assumption that improved telecommunications correlates with less travel. Many scholars, meanwhile, have suggested that the main effect of telecommunications may be complementary, and actually result in increasing travel. Although most studies and policies have focused on analyzing or affecting the consumer demand for travel, industry accounts for 62.3% of total expenditures on travel, and 48.1% of expenditures on communications. Thus, understanding relationships between transportation and communications for industry is even more important than for consumers. This study will use input-output analysis to examine how those cross-sectional relationships change across time and differ by industry. It will be the first known study across multiple years (the ten benchmark years between 1947 and 1997) at the aggregate level, and includes other methodological refinements. It will provide important new insight into the impact of structural changes in industry on the relationships between transportation and communications.

D01-4

Matthew D. Caldwell, TTP  
Investigation of a Hydrogen Pathway using Distributed Reformation of Unpurified Bio-alcohol Mixtures Derived by Thermochemical Biomass Conversion
Advisor: Paul Erickson

This research focuses on sustainable fuel pathways: the role that biofuels and new biomass conversion technologies can play now and potentially in the future as a low-cost renewable source of hydrogen. A large biofuels industry and infrastructure could lead to a viable and economic hydrogen introduction pathway when low-grade alcohols produced through new thermochemical biomass gasification processes are used. These alcohols are less costly and less energy intensive than ethanol produced from corn. Alcohols will be analyzed for their components, and for their energy and cost lifecycles to inform further research on using autothermal reformation to convert alcohols into hydrogen.

D01-5

Changzheng Liu, CEE  
Stochastic Models for Transportation Network Protection
Advisor: Yueyue Fan

Transportation infrastructure is an important component of a functioning society and is critical to facilitating post-disaster recovery. Smoothly functioning infrastructure is also an important component of sustainable transportation. This research will develop mathematical models and solution algorithms to support efficient and reliable resource allocation for protecting transportation infrastructure systems. The main challenge in modeling retrofit problems is to capture the interdependency of individual transportation facilities and to cope with uncertainties. The proposed work brings in rigorous treatment for modeling uncertainties, filling an important gap in existing literature. This work will benefit society through reduced system loss, improved system reliability under disasters, and effective utilization of limited resources. The general methodologies developed here can be extended to other spatially distributed lifeline systems under risk.

D01-6

Jingtao Ma, CEE
Development of Integrated Traffic Control that Balances Efficiency and Equity
Advisor: Debbie Niemeier

This research seeks to develop traffic control strategies that balance efficiency and equity, two important functions that decision-makers must consider as design criteria for new or updated traffic control systems. As a piece of theoretical work, this study establishes a mathematical model that balances both efficiency and equity requirements, and develops solution and analysis procedures to investigate the properties of the model. The study will develop equity measures to quantify the gains and losses of various user groups under various control schemes, define control objectives and constraints considering both efficiency and equity requirements, develop the mathematical models for equity/efficiency control and solve the models, study the factors that affect the control efficiency and equity. The study will provide the means to carry out traffic control designs that are both efficient and equitable.

D01-7

Pengcheng Fu, CEE   
Discrete Element Modeling of Foamed Asphalt Treated Recycled Asphalt Pavement Materials
Advisor: John Harvey

Pavement researchers and practitioners are exploring options for using recycled asphalt pavement because it is a low-cost, long-life and environmentally friendly strategy. Cold foam in-place recycling reduces energy use, greenhouse gas emissions and construction-induced traffic congestion, and saves new materials. Because the materials are new to the field, however, researchers and practitioners lack in-depth understanding of material behaviors, and face difficulties in linking properties of the mix ingredients to the properties measured in laboratory testing and in the field. Understanding the effects of recycled asphalt pavement is of special importance since engineers have limited flexibility to control the recycled material. This research will develop a discrete element method model representing the mesoscopic structural features of foamed asphalt mixes. It will provide insight into the roles of ingredients of foamed asphalt treated materials and help predict material behaviors, enabling flexible pavement in-place recycling to be implemented with greater confidence.