Matching Items (15)

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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. Over the course of the past few decades, vehicle type

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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2013

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Experience in data quality assessment on archived historical freeway traffic data

Description

Concern regarding the quality of traffic data exists among engineers and planners tasked with obtaining and using the data for various transportation applications. While data quality issues are often understood by analysts doing the hands on work, rarely are the

Concern regarding the quality of traffic data exists among engineers and planners tasked with obtaining and using the data for various transportation applications. While data quality issues are often understood by analysts doing the hands on work, rarely are the quality characteristics of the data effectively communicated beyond the analyst. This research is an exercise in measuring and reporting data quality. The assessment was conducted to support the performance measurement program at the Maricopa Association of Governments in Phoenix, Arizona, and investigates the traffic data from 228 continuous monitoring freeway sensors in the metropolitan region. Results of the assessment provide an example of describing the quality of the traffic data with each of six data quality measures suggested in the literature, which are accuracy, completeness, validity, timeliness, coverage and accessibility. An important contribution is made in the use of data quality visualization tools. These visualization tools are used in evaluating the validity of the traffic data beyond pass/fail criteria commonly used. More significantly, they serve to educate an intuitive sense or understanding of the underlying characteristics of the data considered valid. Recommendations from the experience gained in this assessment include that data quality visualization tools be developed and used in the processing and quality control of traffic data, and that these visualization tools, along with other information on the quality control effort, be stored as metadata with the processed data.

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Date Created
2011

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Integrated model of the urban continuum with dynamic time-dependent activity-travel microsimulation: framework, prototype, and implementation

Description

The development of microsimulation approaches to urban systems modeling has occurred largely in three parallel streams of research, namely, land use, travel demand and traffic assignment. However, there are important dependencies and inter-relationships between the model systems which need to

The development of microsimulation approaches to urban systems modeling has occurred largely in three parallel streams of research, namely, land use, travel demand and traffic assignment. However, there are important dependencies and inter-relationships between the model systems which need to be accounted to accurately and comprehensively model the urban system. Location choices affect household activity-travel behavior, household activity-travel behavior affects network level of service (performance), and network level of service, in turn, affects land use and activity-travel behavior. The development of conceptual designs and operational frameworks that represent such complex inter-relationships in a consistent fashion across behavioral units, geographical entities, and temporal scales has proven to be a formidable challenge. In this research, an integrated microsimulation modeling framework called SimTRAVEL (Simulator of Transport, Routes, Activities, Vehicles, Emissions, and Land) that integrates the component model systems in a behaviorally consistent fashion, is presented. The model system is designed such that the activity-travel behavior model and the dynamic traffic assignment model are able to communicate with one another along continuous time with a view to simulate emergent activity-travel patterns in response to dynamically changing network conditions. The dissertation describes the operational framework, presents the modeling methodologies, and offers an extensive discussion on the advantages that such a framework may provide for analyzing the impacts of severe network disruptions on activity-travel choices. A prototype of the model system is developed and implemented for a portion of the Greater Phoenix metropolitan area in Arizona to demonstrate the capabilities of the model system.

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2012

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Sensitivity of synthetic population generation procedures in transportation models, implications of alternative constraints

Description

The growing use of synthetic population, which is a disaggregate representation of the population of an area similar to the real population currently or in the future, has motivated the analysis of its sensitivity in the population generation procedure. New

The growing use of synthetic population, which is a disaggregate representation of the population of an area similar to the real population currently or in the future, has motivated the analysis of its sensitivity in the population generation procedure. New methods in PopGen have enhanced the generation of synthetic populations whereby both household-level and person-level characteristics of interest can be matched in a computationally efficient manner. In the process of set up, population synthesis procedures need sample records for households and persons to match the marginal totals with a specific set of control variables for both the household and person levels, or only the household level, for a specific geographic resolution. In this study, an approach has been taken to analyze the sensitivity by changing and varying this number of controls, with and without taking person controls. The implementation of alternative constraints has been applied on a sample of three hundred block groups in Maricopa County, Arizona. The two datasets that have been used in this study are Census 2000 and a combination of Census 2000 and ACS 2005-2009 dataset. The variation in results for two different rounding methods: arithmetic and bucket rounding have been examined. Finally, the combined sample prepared from the available Census 2000 and ACS 2005-2009 dataset was used to investigate how the results differ when flexibility for drawing households is greater. Study shows that fewer constraints both in household and person levels match the aggregate total population more accurately but could not match distributions of individual attributes. A greater number of attributes both in household and person levels need to be controlled. Where number of controls is higher, using bucket rounding improves the accuracy of the results in both aggregate and disaggregates level. Using combined sample gives the software more flexibility as well as a rich seed matrix to draw households which generates more accurate synthetic population. Therefore, combined sample is another potential option to improve the accuracy in matching both aggregate and disaggregate level household and person distributions.

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Date Created
2012

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An assessment of stochastic variability and convergence characteristics in travel microsimulation models

Description

In the middle of the 20th century in the United States, transportation and infrastructure development became a priority on the national agenda, instigating the development of mathematical models that would predict transportation network performance. Approximately 40 years later, transportation planning

In the middle of the 20th century in the United States, transportation and infrastructure development became a priority on the national agenda, instigating the development of mathematical models that would predict transportation network performance. Approximately 40 years later, transportation planning models again became a national priority, this time instigating the development of highly disaggregate activity-based traffic models called microsimulations. These models predict the travel on a network at the level of the individual decision-maker, but do so with a large computational complexity and processing time requirement. The vast resources and steep learning curve required to integrate microsimulation models into the general transportation plan have deterred planning agencies from incorporating these tools. By researching the stochastic variability in the results of a microsimulation model with varying random number seeds, this paper evaluates the number of simulation trials necessary, and therefore the computational effort, for a planning agency to reach stable model outcomes. The microsimulation tool used to complete this research is the Transportation Analysis and Simulation System (TRANSIMS). The requirements for initiating a TRANSIMS simulation are described in the paper. Two analysis corridors are chosen in the Metropolitan Phoenix Area, and the roadway performance characteristics volume, vehicle-miles of travel, and vehicle-hours of travel are examined in each corridor under both congested and uncongested conditions. Both congested and uncongested simulations are completed in twenty trials, each with a unique random number seed. Performance measures are averaged for each trial, providing a distribution of average performance measures with which to test the stability of the system. The results of this research show that the variability in outcomes increases with increasing congestion. Although twenty trials are sufficient to achieve stable solutions for the uncongested state, convergence in the congested state is not achieved. These results indicate that a highly congested urban environment requires more than twenty simulation runs for each tested scenario before reaching a solution that can be assumed to be stable. The computational effort needed for this type of analysis is something that transportation planning agencies should take into consideration before beginning a traffic microsimulation program.

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2010

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Modeling the role and influence of children in household activity-based rravel model systems

Description

Rapid developments are occurring in the arena of activity-based microsimulation models. Advances in computational power, econometric methodologies and data collection have all contributed to the development of microsimulation tools for planning applications. There has also been interest in modeling child

Rapid developments are occurring in the arena of activity-based microsimulation models. Advances in computational power, econometric methodologies and data collection have all contributed to the development of microsimulation tools for planning applications. There has also been interest in modeling child daily activity-travel patterns and their influence on those of adults in the household using activity-based microsimulation tools. It is conceivable that most of the children are largely dependent on adults for their activity engagement and travel needs and hence would have considerable influence on the activity-travel schedules of adult members in the household. In this context, a detailed comparison of various activity-travel characteristics of adults in households with and without children is made using the National Household Travel Survey (NHTS) data. The analysis is used to quantify and decipher the nature of the impact of activities of children on the daily activity-travel patterns of adults. It is found that adults in households with children make a significantly higher proportion of high occupancy vehicle (HOV) trips and lower proportion of single occupancy vehicle (SOV) trips when compared to those in households without children. They also engage in more serve passenger activities and fewer personal business, shopping and social activities. A framework for modeling activities and travel of dependent children is proposed. The framework consists of six sub-models to simulate the choice of going to school/pre-school on a travel day, the dependency status of the child, the activity type, the destination, the activity duration, and the joint activity engagement with an accompanying adult. Econometric formulations such as binary probit and multinomial logit are used to obtain behaviorally intuitive models that predict children's activity skeletons. The model framework is tested using a 5% sample of a synthetic population of children for Maricopa County, Arizona and the resulting patterns are validated against those found in NHTS data. Microsimulation of these dependencies of children can be used to constrain the adult daily activity schedules. The deployment of this framework prior to the simulation of adult non-mandatory activities is expected to significantly enhance the representation of the interactions between children and adults in activity-based microsimulation models.

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Date Created
2010

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A network-sensitive integrated travel model for simulating impacts of real-time traveler information

Description

Real-time information systems are being used widely around the world to mitigate the adverse impacts of congestion and events that contribute to network delay. It is important that transportation modeling tools be able to accurately model the impacts of real-time

Real-time information systems are being used widely around the world to mitigate the adverse impacts of congestion and events that contribute to network delay. It is important that transportation modeling tools be able to accurately model the impacts of real-time information provision. Such planning tools allow the simulation of the impacts of various real-time information systems, and the design of traveler information systems that can minimize impacts of congestion and network disruptions. Such modeling tools would also be helpful in planning emergency response services as well as evacuation scenarios in the event of a natural disaster. Transportation modeling tools currently in use are quite limited in their ability to model the impacts of real-time information provision on travel demand and route choices. This dissertation research focuses on enhancing a previously developed integrated transportation modeling system dubbed SimTRAVEL (Simulator of Transport, Routes, Activities, Vehicles, Emissions, and Land) to incorporate capabilities that allow the simulation of the impacts of real-time traveler information systems on activity-travel demand. The first enhancement made to the SimTRAVEL framework involves the ability to reflect the effects of providing information on prevailing (as opposed to historical) network conditions on activity-travel behavior choices. In addition, the model system is enhanced to accommodate multiple user information classes (pre-trip and enroute) simultaneously. The second major contribution involves advancing the methodological framework to model enroute decision making processes where a traveler may alter his or her travel choices (such as destination choice) while enroute to an intended destination. Travelers who are provided up-to-date network information may choose to alter their destination in response to congested conditions, or completely abandon and reschedule an activity that offers some degree of flexibility. In this dissertation research, the model framework is developed and an illustrative demonstration of the capabilities of the enhanced model system is provided using a subregion of the Greater Phoenix metropolitan area in Arizona. The results show that the model is able to simulate adjustments in travel choices that may result from the introduction of real-time traveler information. The efficacy of the integrated travel model system is also demonstrated through the application of the enhanced model system to evaluate transportation policy scenarios.

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2014

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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 of university population travel characteristics in understanding and modeling activity-travel

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.

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Date Created
2014

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Demographic evolution modeling system for activity-based travel behavior analysis and demand forecasting

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,

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.

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Date Created
2014

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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 tour-based model systems in practice. Activity-based travel demand forecasting model

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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Date Created
2014