Matching Items (5)

Decling Car Use in a Megacity: Exploring the Drivers of Peak Car Including Infrastructure Saturation

Description

There is increasing evidence that vehicle travel in developed countries may have peaked, contradicting many historical travel demand forecasts. The underlying causes of this peaking are still under debate and

There is increasing evidence that vehicle travel in developed countries may have peaked, contradicting many historical travel demand forecasts. The underlying causes of this peaking are still under debate and there has been a mobilization of research, largely focused at national scales, to study the explanatory drivers. There is, however, a dearth of research focused at the metropolitan scale where transportation policy and planning are frequently decided.

Using Los Angeles County, California, as a case study, we investigate the Peak Car theory and whether social, economic, and technical factors, including roadways that have become saturated at times, may be contributing to changes in travel behavior. After peaking in 2002, vehicle travel in Los Angeles County declined by 3.4 billion (or 4.1%) by 2010. The effects of changing fuel prices, fuel economy, population growth, increased utilization of alternate transportation modes, changes in driver demographics, income, and freight are first assessed. It is possible, and likely, that these factors alone explain the reduction in travel. However, the growth in congestion raises questions of how a constricting supply of roadway network capacity may contribute to travel behavior changes.

There have been no studies that have directly assessed how the maturing supply of infrastructure coupled with increasing demand affect travel behavior. We explore regional and urban factors in Los Angeles to provide insight into the drivers of Peak Car at city scales where the majority of travel occurs. The results show that a majority of the decline in VMT in Los Angeles can be attributed the rising fuel prices during the 2000s. While overall roadway network capacity is not yet a limiting factor for vehicle travel there is some evidence that suggests that congestion along certain corridors may be shifting some automobile travel to alternatives. The results also suggest that the relative impact of any factor on travel demand is likely to vary from one locale to another and Peak Car analysis across large geographic areas obscures the nuisances of travel behavior at a local scale.

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Conceptualizing social capital and active transportation to school through a social-ecological model

Description

Active transportation to school (ATS) has received an increasing amount of attention over the past decade due to its promising health contributions. Most of the existing research that surrounds ATS

Active transportation to school (ATS) has received an increasing amount of attention over the past decade due to its promising health contributions. Most of the existing research that surrounds ATS investigates factors from the physical environment as well as factors from the individual perspective that influence walking and biking to school. This research attempts to add to the existing knowledge by exploring the impact that social relationships within the neighborhood have on ATS.

A model, based on social ecological theory, was presented and tested to examine elements thought to influence ATS. A logistic regression analysis was run to determine the odds of students walking or biking based on the influence of each construct within the model. Results indicated that the physical and socio-cultural constructs were directly and significantly related to ATS behavior while the construct of safety had an indirect effect. These findings support the idea that there are several factors that operate within and across different ecological levels to influence the mode of transportation to school. Therefore, programs to promote ATS should involve multi-level strategies. In addition to the physical environment, interventions should address interpersonal relationships within the family, school, and neighborhood.

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Created

Date Created
  • 2015

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A tour level stop scheduling framework and a vehicle type choice model system for activity based travel forecasting

Description

This dissertation research contributes to the advancement of activity-based travel forecasting models along two lines of inquiry. First, the dissertation aims to introduce a continuous-time representation of activity participation in

This dissertation research contributes to the advancement of activity-based travel forecasting models along two lines of inquiry. First, the dissertation aims to introduce a continuous-time representation of activity participation in tour-based model systems in practice. Activity-based travel demand forecasting model systems in practice today are largely tour-based model systems that simulate individual daily activity-travel patterns through the prediction of day-level and tour-level activity agendas. These tour level activity-based models adopt a discrete time representation of activities and sequence the activities within tours using rule-based heuristics. An alternate stream of activity-based model systems mostly confined to the research arena are activity scheduling systems that adopt an evolutionary continuous-time approach to model activity participation subject to time-space prism constraints. In this research, a tour characterization framework capable of simulating and sequencing activities in tours along the continuous time dimension is developed and implemented using readily available travel survey data. The proposed framework includes components for modeling the multitude of secondary activities (stops) undertaken as part of the tour, the time allocated to various activities in a tour, and the sequence in which the activities are pursued.

Second, the dissertation focuses on the implementation of a vehicle fleet composition model component that can be used not only to simulate the mix of vehicle types owned by households but also to identify the specific vehicle that will be used for a specific tour. Virtually all of the activity-based models in practice only model the choice of mode without due consideration of the type of vehicle used on a tour. In this research effort, a comprehensive vehicle fleet composition model system is developed and implemented. In addition, a primary driver allocation model and a tour-level vehicle type choice model are developed and estimated with a view to advancing the ability to track household vehicle usage through the course of a day within activity-based travel model systems. It is envisioned that these advances will enhance the fidelity of activity-based travel model systems in practice.

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Created

Date Created
  • 2014

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Estimations of reductions in household vehicle miles traveled under scenarios of shifts in vehicle type choice

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.

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.

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Created

Date Created
  • 2013

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A study of university student travel behavior

Description

Institutions of higher education, particularly those with large student enrollments, constitute special generators that contribute in a variety of ways to the travel demand in a region. Despite the importance

Institutions of higher education, particularly those with large student enrollments, constitute special generators that contribute in a variety of ways to the travel demand in a region. Despite the importance of university population travel characteristics in understanding and modeling activity-travel patterns and mode choice behavior in a region, such populations remain under-studied. As metropolitan planning organizations continue to improve their regional travel models by incorporating processes and parameters specific to major regional special generators, university population travel characteristics need to be measured and special submodels that capture their behavior need to be developed. The research presented herein begins by documenting the design and administration of a comprehensive university student online travel and mode use survey that was administered at Arizona State University (ASU) in the Greater Phoenix region of Arizona. The dissertation research offers a detailed statistical analysis of student travel behavior for different student market segments. A framework is then presented for incorporating university student travel into a regional travel demand model. The application of the framework to the ASU student population is documented in detail. A comprehensive university student submodel was estimated and calibrated for integration with the full regional travel model system. Finally, student attitudes toward travel are analyzed and used as explanatory factors in multinomial logit models of mode choice. This analysis presents an examination of the extent to which attitudes play a role in explaining mode choice behavior of university students in an urban setting. The research provides evidence that student travel patterns vary substantially from those of the rest of the population, and should therefore be considered separately when forecasting travel demand and formulating transport policy in areas where universities are major contributors to regional travel.

Contributors

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Created

Date Created
  • 2014