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Description
Vehicle type choice is a significant determinant of fuel consumption and energy sustainability; larger, heavier vehicles consume more fuel, and expel twice as many pollutants, than their smaller, lighter counterparts. Over the course of the past few decades, vehicle type choice has seen a vast shift, due to many households making more trips in larger vehicles with lower fuel economy. During the 1990s, SUVs were the fastest growing segment of the automotive industry, comprising 7% of the total light vehicle market in 1990, and 25% in 2005. More recently, due to rising oil prices, greater awareness to environmental sensitivity, the desire to reduce dependence on foreign oil, and the availability of new vehicle technologies, many households are considering the use of newer vehicles with better fuel economy, such as hybrids and electric vehicles, over the use of the SUV or low fuel economy vehicles they may already own. The goal of this research is to examine how vehicle miles traveled, fuel consumption and emissions may be reduced through shifts in vehicle type choice behavior. Using the 2009 National Household Travel Survey data it is possible to develop a model to estimate household travel demand and total fuel consumption. If given a vehicle choice shift scenario, using the model it would be possible to calculate the potential fuel consumption savings that would result from such a shift. In this way, it is possible to estimate fuel consumption reductions that would take place under a wide variety of scenarios.
ContributorsChristian, Keith (Author) / Pendyala, Ram M. (Thesis advisor) / Chester, Mikhail (Committee member) / Kaloush, Kamil (Committee member) / Ahn, Soyoung (Committee member) / Arizona State University (Publisher)
Created2013
Description
Cordon pricing strategies attempt to charge motorists for the marginal social costs of driving in heavily congested areas, lure them out of their vehicles and into other modes, and thereby reduce vehicle miles traveled and congestion-related externalities. These strategies are gaining policy-makers` attention worldwide. The benefits and costs of such strategies can potentially lead to a disproportionate and inequitable burden on lower income commuters, particularly those commuters with poor accessibility to alternative modes of transportation. Strategies designed to mitigate the impacts of cordon pricing for disadvantaged travelers, such as discount and exemptions, can reduce the effectiveness of the pricing strategy. Transit improvements using pricing fee revenues are another mitigation strategy, but can be wasteful and inefficient if not properly targeted toward those most disadvantaged and in need. This research examines these considerations and explores the implications for transportation planners working to balance goals of system effectiveness, efficiency, and equity. First, a theoretical conceptual model for analyzing the justice implications of cordon pricing is presented. Next, the Mobility Access and Pricing Study, a cordon pricing strategy examined by the San Francisco County Transportation Authority is analyzed utilizing a neighborhood-level accessibility-based approach. The fee-payment impacts for low-income transportation-disadvantaged commuters within the San Francisco Bay area are examined, utilizing Geographic Information Systems coupled with data from the Longitudinal Employment and Household Dynamics program of the US Census Bureau. This research questions whether the recommended blanket 50% discount for low-income travelers would unnecessarily reduce the overall efficiency and effectiveness of the cordon pricing system. It is proposed that reinvestment of revenue in transportation-improvement projects targeted at those most disproportionately impacted by tolling fees, low-income automobile-dependent peak-period commuters in areas with poor access to alternative modes, would be a more suitable mitigation strategy. This would not only help maintain the efficiency and effectiveness of the cordon pricing system, but would better address income, modal and spatial equity issues. The results of this study demonstrate how the spatial distribution of the toll-payment impacts may burden low-income residents in quite different ways, thereby warranting the inclusion of such analysis in transportation planning and practice.
ContributorsKelley, Jason L (Author) / Golub, Aaron (Thesis advisor) / Boone, Christopher (Committee member) / Guhathakarta, Subhrahit (Committee member) / Arizona State University (Publisher)
Created2013
Description
A methodology is developed that integrates institutional analysis with Life Cycle Assessment (LCA) to identify and overcome barriers to sustainability transitions and to bridge the gap between environmental practitioners and decisionmakers. LCA results are rarely joined with analyses of the social systems that control or influence decisionmaking and policies. As a result, LCA conclusions generally lack information about who or what controls different parts of the system, where and when the processes' environmental decisionmaking happens, and what aspects of the system (i.e. a policy or regulatory requirement) would have to change to enable lower environmental impact futures. The value of the combined institutional analysis and LCA (the IA-LCA) is demonstrated using a case study of passenger transportation in the Phoenix, Arizona metropolitan area. A retrospective LCA is developed to estimate how roadway investment has enabled personal vehicle travel and its associated energy, environmental, and economic effects. Using regional travel forecasts, a prospective life cycle inventory is developed. Alternative trajectories are modeled to reveal future "savings" from reduced roadway construction and vehicle travel. An institutional analysis matches the LCA results with the specific institutions, players, and policies that should be targeted to enable transitions to these alternative futures. The results show that energy, economic, and environmental benefits from changes in passenger transportation systems are possible, but vary significantly depending on the timing of the interventions. Transition strategies aimed at the most optimistic benefits should include 1) significant land-use planning initiatives at the local and regional level to incentivize transit-oriented development infill and urban densification, 2) changes to state or federal gasoline taxes, 3) enacting a price on carbon, and 4) nearly doubling vehicle fuel efficiency together with greater market penetration of alternative fuel vehicles. This aggressive trajectory could decrease the 2050 energy consumption to 1995 levels, greenhouse gas emissions to 1995, particulate emissions to 2006, and smog-forming emissions to 1972. The potential benefits and costs are both private and public, and the results vary when transition strategies are applied in different spatial and temporal patterns.
ContributorsKimball, Mindy (Author) / Chester, Mikhail (Thesis advisor) / Allenby, Braden (Committee member) / Golub, Aaron (Committee member) / Arizona State University (Publisher)
Created2014
ContributorsShi, Ge (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-25
Description
It has been identified in the literature that there exists a "spatial mismatch" between geographical concentrations of lower-income or minority people who have relatively lower rates of car ownership, lower skills or educational attainment and who mainly rely on public transit for their travel, and low-skilled jobs for which they more easily qualify. Given this situation, various types of transportation projects have been constructed to improve public transit services and, alongside other goals, improve the connection between low-skilled workers and jobs. As indicators of performance, measures of job accessibility are commonly used in to gauge how such improvements have facilitated job access. Following this approach, this study investigates the impact of the Phoenix Metro Light Rail on job accessibility for the transit users, by calculating job accessibility before and after the opening of the system. Moreover, it also investigates the demographic profile of those who have benefited from improvements in job accessibility----both by income and by ethnicity. Job accessibility is measured using the cumulative opportunity approach which quantifies the job accessibility within different travel time limits, such as 30 and 45 minutes. ArcGIS is used for data processing and results visualization. Results show that the Phoenix light rail has improved job accessibility of the traffic analysis zones that are along the light rail line and Hispanic and lower-income groups have benefited more than their counterparts.
ContributorsLiu, Liyuan (Author) / Golub, Aaron (Thesis advisor) / Wentz, Elizabeth (Committee member) / Kuby, Michael (Committee member) / Arizona State University (Publisher)
Created2014
Description
Contrary to many previous travel demand forecasts there is increasing evidence that vehicle travel in developed countries may be peaking. The underlying causes of this peaking are still under much debate and there has been a mobilization of research, largely focused at the national scale, to study the explanatory drivers but research focused at the metropolitan scale, where transportation policy and planning are frequently decided, is relatively thin. Additionally, a majority of this research has focused on changes within the activity system without considering the impact transportation infrastructure has on overall travel demand. Using Los Angeles County California, we investigate Peak Car and whether the saturation of automobile infrastructure, in addition to societal and economic factors, may be a suppressing factor. After peaking in 2002, vehicle travel in Los Angeles County in 2010 was estimated at 78 billion and was 20.3 billion shy of projections made in 2002. The extent to which infrastructure saturation may contribute to Peak Car is evaluated by analyzing social and economic factors that may have impacted personal automobile usage over the last decade. This includes changing fuel prices, fuel economy, population growth, increased utilization of alternate transportation modes, changes in driver demographics , travel time and income levels. Summation of all assessed factors reveals there is at least some portion of the 20 billion VMT that is unexplained in all but the worst case scenario. We hypothesize that the unexplained remaining VMT may be explained by infrastructure supply constraints that result in suppression of travel. This finding has impacts on how we see the role of hard infrastructure systems in urban growth and we explore these impacts in the research.
ContributorsFraser, Andrew (Author) / Chester, Mikhail V (Thesis advisor) / Pendyala, Ram M. (Committee member) / Seager, Thomas P (Committee member) / Arizona State University (Publisher)
Created2014
Description
The activity-based approach to travel demand analysis and modeling, which has been developed over the past 30 years, has received tremendous success in transportation planning and policy analysis issues, capturing the multi-way joint relationships among socio-demographic, economic, land use characteristics, activity participation, and travel behavior. The development of synthesizing population with an array of socio-demographic and socio-economic attributes has drawn remarkable attention due to privacy and cost constraints in collecting and disclosing full scale data. Although, there has been enormous progress in producing synthetic population, there has been less progress in the development of population evolution modeling arena to forecast future year population. The objective of this dissertation is to develop a well-structured full-fledged demographic evolution modeling system, capturing migration dynamics and evolution of person level attributes, introducing the concept of new household formations and apprehending the dynamics of household level long-term choices over time. A comprehensive study has been conducted on demography, sociology, anthropology, economics and transportation engineering area to better understand the dynamics of evolutionary activities over time and their impacts in travel behavior. This dissertation describes the methodology and the conceptual framework, and the development of model components. Demographic, socio-economic, and land use data from American Community Survey, National Household Travel Survey, Census PUMS, United States Time Series Economic Dynamic data and United States Center for Disease Control and Prevention have been used in this research. The entire modeling system has been implemented and coded using programming language to develop the population evolution module named `PopEvol' into a computer simulation environment. The module then has been demonstrated for a portion of Maricopa County area in Arizona to predict the milestone year population to check the accuracy of forecasting. The module has also been used to evolve the base year population for next 15 years and the evolutionary trend has been investigated.
ContributorsPaul, Sanjay (Author) / Pendyala, Ram M. (Thesis advisor) / Kaloush, Kamil (Committee member) / Ahn, Soyoung (Committee member) / Arizona State University (Publisher)
Created2014
ContributorsShatuho, Kristina (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-27
Description
To guide the timetabling and vehicle assignment of urban bus systems, a group of optimization models were developed for scenarios from simple to complex. The model took the interaction of prospective passengers and bus companies into consideration to achieve the maximum financial benefit as well as social satisfaction. The model was verified by a series of case studies and simulation from which some interesting conclusions were drawn.
ContributorsHuang, Shiyang (Author) / Askin, Ronald G. (Thesis advisor) / Mirchandani, Pitu (Committee member) / McCarville, Daniel R. (Committee member) / Arizona State University (Publisher)
Created2014
Description
It has been identified in the literature that there exists a link between the built environment and non-motorized transport. This study aims to contribute to existing literature on the effects of the built environment on cycling, examining the case of the whole State of California. Physical built environment features are classified into six groups as: 1) local density, 2) diversity of land use, 3) road connectivity, 4) bike route length, 5) green space, 6) job accessibility. Cycling trips in one week for all children, school children, adults and employed-adults are investigated separately. The regression analysis shows that cycling trips is significantly associated with some features of built environment when many socio-demographic factors are taken into account. Street intersections, bike route length tend to increase the use of bicycle. These effects are well-aligned with literature. Moreover, both local and regional job accessibility variables are statistically significant in two adults' models. However, residential density always has a significant negatively effect on cycling trips, which is still need further research to confirm. Also, there is a gap in literature on how green space affects cycling, but the results of this study is still too unclear to make it up. By elasticity analysis, this study concludes that street intersections is the most powerful predictor on cycling trips. From another perspective, the effects of built environment on cycling at workplace (or school) are distinguished from at home. This study implies that a wide range of measures are available for planners to control vehicle travel by improving cycling-level in California.
ContributorsWang, Kailai, M.U.E.P (Author) / Salon, Deborah (Thesis advisor) / Rey, Sergio (Committee member) / Li, Wenwen (Committee member) / Arizona State University (Publisher)
Created2015