Predicting the Ownership, Use, and Environmental Impacts of New Vehicle Technologies with a Focus on the Relationship Between Travel Behavior and the Built Environment

Predicting the Ownership, Use, and Environmental Impacts of New Vehicle Technologies with a Focus on the Relationship Between Travel Behavior and the Built Environment PDF Author: Adam Taylan Nodjomian
Publisher:
ISBN:
Category :
Languages : en
Pages : 246

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Book Description
The field of transportation is on the cusp of major change. Innovations in how vehicles operate and are powered have the potential to elicit changes not seen since the introduction of the interstate highway system more than half a century ago. Predicting the impacts of new vehicle technologies has interested researchers and practitioners across disciplines and continents. This thesis makes a handful of such predictions. It is divided into three parts. In the first part, the results of two large-scale preference surveys and data from the U.S. Environmental Protection Agency’s (EPA) Smart Location Database (EPA, 2014) are used to estimate how land use characteristics impact Americans’ perceptions of, interest in, and willingness to pay for new vehicle technologies, while controlling for demographic attributes. The surveys were conducted by Quarles and Kockelman (2018) and Gurumurthy and Kockelman (2018) in 2017 and together represented over 4,000 U.S. households. Statistical models like the ordered probit and multinomial logit are used to estimate the impacts of demographics and land use characteristics on vehicle-related behavior. Various land use variables arise as significant depending on the question being asked of the respondents. For example, poor job accessibility via automobile is associated with higher levels of interest in automated vehicles (AVs), higher anticipated use of AV technology, a willingness-to-pay (WTP) for self-driving capability, and a greater reliance on AVs for some long-distance travel. No land use variable arises as significantly more predictive than the others at this national-level scale of analysis. The results emphasize the fact that land use policy must be considered at the local level, and that there is no “one size fits all” solution for managing future transportation behavior with land use action. The second part of this thesis evaluates the connection between land use and current travel behavior. Census tract-level measures of population and employment density (provided once again by the EPA’s Smart Location Database [EPA, 2014]) are evaluated across the nation to investigate the connection between the development conditions one experiences and his or her travel behavior. Travel data comes from the 2009 National Household Travel Survey (NHTS). The results highlight a stronger connection between population density and vehicle-miles traveled (VMT) and vehicle ownership, than with employment density. For both VMT and vehicle ownership, an improvement of only two to one can be expected by changing population density conditions in a census tract. In other words increasing population from the lowest density conditions to the highest results in a decline of VMT per capita per day from 20 miles to 10 miles. Similarly, vehicle ownership per capita generally ranges from 0.4 to 0.8. Notably, these improvements are not realized until the highest decile of population density (18 people per acre), thus indicating that simply building homes in rural or low-density suburban regions will likely have a negligible impact on transportation demand. Employment density was found to be less indicative of travel behavior. The third and final piece of the thesis predicts how an evolving light-duty vehicle (LDV) fleet will impact the amount of energy consumed by Americans and the emissions they create. Here, the results of a fleet evolution simulation, developed by Quarles et al. (2019), are used to project what a vehicle fleet with more electric (and fewer gasoline-powered) vehicles will mean for energy consumption and emissions on a per capita basis. Projections are based on historic fuel efficiency data and emission production rates from the Bureau of Transportation Statistics (BTS) and EPA (BTS, 2018b; BTS, 2018c; EPA, 2018a). Conclusions from these findings highlight the need for more efficient vehicles, better emissions control technologies on existing vehicle models and power plants, and a decreased reliance on highly-polluting energy sources for power generation. Policies aimed at achieving these objectives will help ensure that Americans’ future vehicle behavior and ownership will not create an undue burden on themselves or the environment in which they live. Although the analyses discussed in this thesis cover diverse topics such as human behavior, urban planning, and air quality, they establish the need for a proactive approach to cutting-edge vehicle technologies. If left to develop without any oversight or action, transportation network congestion will worsen, development will continue to sprawl, and the environment and public health will suffer. Policies aimed at limiting “empty” driving with AVs, increasing population density, and curbing vehicle and power plant emissions can help ensure the benefits of vehicle technology innovation are not realized at the expense of other considerations.

Predicting the Ownership, Use, and Environmental Impacts of New Vehicle Technologies with a Focus on the Relationship Between Travel Behavior and the Built Environment

Predicting the Ownership, Use, and Environmental Impacts of New Vehicle Technologies with a Focus on the Relationship Between Travel Behavior and the Built Environment PDF Author: Adam Taylan Nodjomian
Publisher:
ISBN:
Category :
Languages : en
Pages : 246

Get Book Here

Book Description
The field of transportation is on the cusp of major change. Innovations in how vehicles operate and are powered have the potential to elicit changes not seen since the introduction of the interstate highway system more than half a century ago. Predicting the impacts of new vehicle technologies has interested researchers and practitioners across disciplines and continents. This thesis makes a handful of such predictions. It is divided into three parts. In the first part, the results of two large-scale preference surveys and data from the U.S. Environmental Protection Agency’s (EPA) Smart Location Database (EPA, 2014) are used to estimate how land use characteristics impact Americans’ perceptions of, interest in, and willingness to pay for new vehicle technologies, while controlling for demographic attributes. The surveys were conducted by Quarles and Kockelman (2018) and Gurumurthy and Kockelman (2018) in 2017 and together represented over 4,000 U.S. households. Statistical models like the ordered probit and multinomial logit are used to estimate the impacts of demographics and land use characteristics on vehicle-related behavior. Various land use variables arise as significant depending on the question being asked of the respondents. For example, poor job accessibility via automobile is associated with higher levels of interest in automated vehicles (AVs), higher anticipated use of AV technology, a willingness-to-pay (WTP) for self-driving capability, and a greater reliance on AVs for some long-distance travel. No land use variable arises as significantly more predictive than the others at this national-level scale of analysis. The results emphasize the fact that land use policy must be considered at the local level, and that there is no “one size fits all” solution for managing future transportation behavior with land use action. The second part of this thesis evaluates the connection between land use and current travel behavior. Census tract-level measures of population and employment density (provided once again by the EPA’s Smart Location Database [EPA, 2014]) are evaluated across the nation to investigate the connection between the development conditions one experiences and his or her travel behavior. Travel data comes from the 2009 National Household Travel Survey (NHTS). The results highlight a stronger connection between population density and vehicle-miles traveled (VMT) and vehicle ownership, than with employment density. For both VMT and vehicle ownership, an improvement of only two to one can be expected by changing population density conditions in a census tract. In other words increasing population from the lowest density conditions to the highest results in a decline of VMT per capita per day from 20 miles to 10 miles. Similarly, vehicle ownership per capita generally ranges from 0.4 to 0.8. Notably, these improvements are not realized until the highest decile of population density (18 people per acre), thus indicating that simply building homes in rural or low-density suburban regions will likely have a negligible impact on transportation demand. Employment density was found to be less indicative of travel behavior. The third and final piece of the thesis predicts how an evolving light-duty vehicle (LDV) fleet will impact the amount of energy consumed by Americans and the emissions they create. Here, the results of a fleet evolution simulation, developed by Quarles et al. (2019), are used to project what a vehicle fleet with more electric (and fewer gasoline-powered) vehicles will mean for energy consumption and emissions on a per capita basis. Projections are based on historic fuel efficiency data and emission production rates from the Bureau of Transportation Statistics (BTS) and EPA (BTS, 2018b; BTS, 2018c; EPA, 2018a). Conclusions from these findings highlight the need for more efficient vehicles, better emissions control technologies on existing vehicle models and power plants, and a decreased reliance on highly-polluting energy sources for power generation. Policies aimed at achieving these objectives will help ensure that Americans’ future vehicle behavior and ownership will not create an undue burden on themselves or the environment in which they live. Although the analyses discussed in this thesis cover diverse topics such as human behavior, urban planning, and air quality, they establish the need for a proactive approach to cutting-edge vehicle technologies. If left to develop without any oversight or action, transportation network congestion will worsen, development will continue to sprawl, and the environment and public health will suffer. Policies aimed at limiting “empty” driving with AVs, increasing population density, and curbing vehicle and power plant emissions can help ensure the benefits of vehicle technology innovation are not realized at the expense of other considerations.

Driving and the Built Environment

Driving and the Built Environment PDF Author: National Research Council
Publisher: National Academies Press
ISBN: 030915054X
Category : Transportation
Languages : en
Pages : 178

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Book Description
TRB Special Report 298: Driving and the Built Environment: Effects of Compact Development on Motorized Travel, Energy Use, and CO2 Emissions examines the relationship between land development patterns and vehicle miles traveled (VMT) in the United States to assess whether petroleum use, and by extension greenhouse gas (GHG) emissions, could be reduced by changes in the design of development patterns. The report estimates the contributions that changes in residential and mixed-use development patterns and transit investments could make in reducing VMT by 2030 and 2050, and the impact this could have in meeting future transportation-related GHG reduction goals.

Capturing the Impacts of Land Use on Travel Behavior

Capturing the Impacts of Land Use on Travel Behavior PDF Author: Veronica Adelle Hannan
Publisher:
ISBN:
Category :
Languages : en
Pages : 141

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Book Description
Most urban planning literature suggests that compact and mixed-use neighborhoods correlate with lower vehicle kilometers traveled (VKT), and accordingly, lower energy consumption and transportation-related emissions. However, many of these studies also find that the relationship between urban form and travel behavior is marginal at best, and several commit analytical errors, which may compromise the robustness of parameter estimates. This thesis examines daily travel behavior in Santiago de Chile to understand how demographic structure, neighborhood design, and regional accessibility influence travel behavior as measured through emitted grams of five criteria pollutants (C0 2, VOCs, PM10, CO and NO,). To answer this question, two different modeling techniques are employed to investigate the variables related to car ownership and travel behavior. The first analysis uses a discrete-continuous choice model to understand the attributes that influence car-ownership and travel emissions. The second study uses structural equation modeling to simultaneously estimate latent urban form factors, car-ownership and emitted pollutants. The advantage of each technique is that they both offer the flexibility to address the four major methodological errors identified in the literature review: inulticollinearity, spatial auto-correlation, the modifiable areal unit problem and self-selection. After controlling for the four methods-related gaps, both models find that, although economic and demographic characteristics dominate in explaining travel decisions, the built environment plays a small, but significant, role. The discrete-continuous choice model uses two classes of measures to capture urban form: local attributes and regional accessibility. It finds that neighborhood-level and regional characteristics have an equally important impact on 2 or 3-plus vehicle ownership.Furthermore, the model suggests that regional accessibility attributes dominate among the built environment measures in explaining variations in emitted travel pollutants. The structural equation model uses three latent urban form factors to characterize the built environment: a high-intensity, mixed-use factor; a high-income residential factor; and a non-gridded street factor. It finds that the high-density, mixed-use factor decreases the utility of owning a vehicle, and reduces the likelihood of travel emissions. The latter two factors, on the other hand, both increase the probability of owning a car. Lastly, the non-gridded street factor has a consistently positive effect on travel emissions.

Built Environment and Car Travel

Built Environment and Car Travel PDF Author: C. Maat
Publisher: IOS Press
ISBN: 1607500647
Category : Business & Economics
Languages : en
Pages : 183

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Book Description
Analyses of Interdependencies. An academic and policy debate has been running in recent decades on whetherand to what extent travel behaviour is influenced by the built environment.This dissertation addresses the influence on daily travel distance, chainingbehaviour, car ownershi

Human Mobility, Spatiotemporal Context, and Environmental Health: Recent Advances in Approaches and Methods

Human Mobility, Spatiotemporal Context, and Environmental Health: Recent Advances in Approaches and Methods PDF Author: Mei-Po Kwan
Publisher: MDPI
ISBN: 3039211838
Category : Medical
Languages : en
Pages : 382

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Book Description
Environmental health researchers have long used concepts like the neighborhood effect to assessing people’s exposure to environmental influences and the associated health impact. However, these are static notions that ignore people’s daily mobility at various spatial and temporal scales (e.g., daily travel, migratory movements, and movements over the life course) and the influence of neighborhood contexts outside their residential neighborhoods. Recent studies have started to incorporate human mobility, non-residential neighborhoods, and the temporality of exposures through collecting and using data from GPS, accelerometers, mobile phones, various types of sensors, and social media. Innovative approaches and methods have been developed. This Special Issue aims to showcase studies that use new approaches, methods, and data to examine the role of human mobility and non-residential contexts on human health behaviors and outcomes. It includes 21 articles that cover a wide range of topics, including individual exposure to air pollution, exposure and access to green spaces, spatial access to healthcare services, environmental influences on physical activity, food environmental and diet behavior, exposure to noise and its impact on mental health, and broader methodological issues such as the uncertain geographic context problem (UGCoP) and the neighborhood effect averaging problem (NEAP). This collection will be a valuable reference for scholars and students interested in recent advances in the concepts and methods in environmental health and health geography.

Effects of Built Environments on Travel Behavior and Emissions

Effects of Built Environments on Travel Behavior and Emissions PDF Author: Jin Hyun Hong
Publisher:
ISBN:
Category : Automobile travel
Languages : en
Pages : 122

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Book Description
Urban transportation researchers have been studying the relationship between land use policy and travel behavior for several decades due to the topic's great importance in public policy-making. Because of the improvements in energy efficiency, large reductions in emissions have been achieved for a given amount of travel. Unfortunately, the rapid growth in total travel distance over the past several decades, especially for light duty vehicles, has reduced the benefits from technological improvements. Therefore, many urban planners have suggested land use planning as an alternative and fundamental way to reduce auto dependency and thereby, transportation emissions. However, several empirical studies about the linkage between built environments and travel behavior produced mixed results. In light of the inconsistent findings, research efforts to reconcile the discrepancy among different studies are required. Several methodological issues are found based on the previous literature and four main challenges are addressed in this study: self-selection, spatial autocorrelation, trip-interdependency, and geographic scale. In addition, two key methodological issues in modeling transportation emissions are found and addressed. First, transportation emissions per person are often estimated by using vehicle miles traveled (VMT) and emissions factors, but these emissions factors do not fully consider variations in travel speed and vehicle characteristics. Second, VMT and emissions factors are associated with travel characteristics, implying that the same methodological challenges existing in the land use-travel behavior analysis can exist in the land use-transportation emissions analysis. This research obtained several important results. First, increasing residential density can reduce VMT and emissions significantly. In addition, the impact of residential density on VMT is higher than that on transportation emissions, indicating that negative externalities such as congestion generated from compact developments should be considered in the land use-transportation emissions analysis. Second, analyses show that the effects of land use factors on VMT and emissions are different according to tour types and geographic scales. These results imply that different land use policies should be implemented according to neighborhoods characteristics. Finally, the sensitivity analyses of built environment factors show that ignoring trip and vehicle characteristics in the emissions calculation can inflate the influences of built environments on emissions.

Using Big Data to Model Travel Behavior

Using Big Data to Model Travel Behavior PDF Author: Gregory Stuart MacFarlane
Publisher:
ISBN:
Category : Choice of transportation
Languages : en
Pages :

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Book Description
The transportation community is exploring how new "big'' databases constructed by companies or public administrative agencies can be used to better understand travelers' behaviors and better predict travelers' responses to various transportation policies. This thesis explores how a large targeted marketing database containing information about individuals' socio-demographic characteristics, current residence attributes, and previous residential locations can be used to investigate research questions related to individuals' transportation preferences and the built environment. The first study examines how household vehicle ownership may be shaped by, or inferred from, previous behavior. Results show that individuals who have previously lived in dense ZIP codes or ZIP codes with more non-automobile commuting options are more likely to own fewer vehicles, all else equal. The second study uses autoregressive models that control for spatial dependence, correlation, and endogeneity to investigate whether investments in public transit infrastructure are associated with higher home values. Results show that willingness-to-pay estimates obtained from the general spatial Durbin model are less certain than comparable estimates obtained through ordinary least squares. The final study develops an empirical framework to examine a housing market's resilience to price volatility as a function of transportation accessibility. Two key modeling frameworks are considered. The first uses a spatial autoregressive model to investigate the relationship between a home's value, appreciation, and price stability while controlling for endogenous missing regressors. The second uses a latent class model that considers all these attributes simultaneously, but cannot control for endogeneity.

The Causal Relationship Between the Built Environment and Personal Travel Choice

The Causal Relationship Between the Built Environment and Personal Travel Choice PDF Author: Xinyu Cao
Publisher:
ISBN:
Category :
Languages : en
Pages : 410

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Book Description


Bulletin of the Atomic Scientists

Bulletin of the Atomic Scientists PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 88

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Book Description
The Bulletin of the Atomic Scientists is the premier public resource on scientific and technological developments that impact global security. Founded by Manhattan Project Scientists, the Bulletin's iconic "Doomsday Clock" stimulates solutions for a safer world.

Autonomous Vehicle Technology

Autonomous Vehicle Technology PDF Author: James M. Anderson
Publisher: Rand Corporation
ISBN: 0833084372
Category : Transportation
Languages : en
Pages : 215

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Book Description
The automotive industry appears close to substantial change engendered by “self-driving” technologies. This technology offers the possibility of significant benefits to social welfare—saving lives; reducing crashes, congestion, fuel consumption, and pollution; increasing mobility for the disabled; and ultimately improving land use. This report is intended as a guide for state and federal policymakers on the many issues that this technology raises.