Discrete--continuous Model of Household Vehicle Ownership and Trip Generation PDF Download

Author: Kiranmai Chirumamilla
Publisher:
ISBN:
Category : Automobile ownership
Languages : en
Pages : 148

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Book Description

Author: Thomas F. Golob
Publisher:
ISBN:
Category : Automobile ownership
Languages : en
Pages : 42

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Book Description

Author: David A. Hensher
Publisher: Elsevier
ISBN: 1483291197
Category : Business & Economics
Languages : en
Pages : 296

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Book Description
This unique book is the first attempt to fully integrate automobile ownership (by fleet size and vehicle type) and vehicle use in an intertemporal setting which recognises the durable nature of automobiles using extensive longitudinal panel data on each household (over 5 years). The book presents: the theoretical and econometric development of a joint discrete-continuous choice longitudinal model system of household and automobile ownership and use, bringing together 9 years of research;the application of the model system for the period 1981-1985 in Australia;the forecasting of the model system up to 2020; particular emphasis on the development and application of a longitudinal data base which is unique to the topic - to capture the dynamic (intertemporal) impacts of technological change, life-style change, fuel prices etc. The book not only extends the reader's knowledge of the dimensions of automobile demand but it also adds important new ideas on handling dynamics of choice, as well as new empirical evidence on elasticities of demand for vehicles and vehicle kilometres. Energy and transport planning specialists will find the book essential reading.

Author: Ron Eash
Publisher:
ISBN:
Category : Traffic surveys
Languages : en
Pages : 100

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Book Description

Author: Yafei Han
Publisher:
ISBN:
Category :
Languages : en
Pages : 162

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Book Description
In the last few decades, travel demand models have undergone tremendous development and, today, are routinely used to support planning and policy decisions. But uncertainty in forecasting with such models is often overlooked, and its impact on forecast accuracy is rarely evaluated. My thesis is motivated to understand behavior uncertainty and model uncertainty in travel demand modeling. In particular, I assess the temporal transferability of vehicle ownership models and trip generation models for Boston metropolitan area from 1990 to 2010. Through statistical tests, I find significantly changed preferences in household vehicle ownership choice and trip production. For vehicle ownership choice, the effects of most socio-economic and demographic factors, and regional location factor have evolved; while the effects of local built environment factors and transit access are stable. Trip rates have changed over time, with decreased home-based work, home-based shopping, home-based bank and personal business, home-based social, home-based eating and non-home-based work trips; and increased home-based recreational and home-based work-related trips. The prediction tests suggest that failing to consider preference changes cause significant bias in forecasts. The transferred vehicle ownership model of 1991 under-predicts 0- vehicle households by 42.5%, and over-predicts 2-vehicle households by 14.8% in 2010. The transferred trip rates from 1991 overestimate total trips in 2010 by 7% to 9%. Homebased work-related, home-based pick-up and drop-off, and home-based recreational trips are significantly unpredicted by 34%, 12% and 27%; while home-based work, home-based shopping, home-based social, and non-home-based work trips are significantly overpredicted by 9%, 20%, 31%, and 69%. Different model specifications have shown a modest range of variability in prediction outcomes, suggesting model specification uncertainty has less influence on forecasts than behavior uncertainty. In vehicle ownership modeling, children, seniors, and local built environment variables improve the prediction accuracy for 0-vehicle group. But all model specifications cannot well distinguish between 0- and 1-vehicle households, and between 2- and 3-vehicle households. Household characterization affects the prediction accuracy for certain trip purposes. Including more detailed household information may lead to worse forecasts because of large sampling variance. Future works are suggested to incorporate behavior uncertainty in forecast, explore uncertainty in model structure, and evaluate the practical implications of the lack of model transferability.

Author: Wilbur Smith and Associates
Publisher:
ISBN:
Category : Automobile ownership
Languages : en
Pages : 352

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Author: Travel Model Improvement Program (U.S.)
Publisher:
ISBN:
Category : Federal aid to transportation
Languages : en
Pages : 44

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Book Description

Author: Aurélie Glerum
Publisher:
ISBN:
Category :
Languages : en
Pages : 26

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Book Description

Author: Joanna M. Brunso
Publisher:
ISBN:
Category : Trip generation
Languages : en
Pages : 574

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Book Description

Author: Rajesh Paleti Ravi Venkata Durga
Publisher:
ISBN:
Category :
Languages : en
Pages : 348

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Book Description
Activity-based travel demand model systems are increasingly being deployed to microsimulate daily activity-travel patterns of individuals. However, a critical dimension that is often missed in these models is that of vehicle type choice. The current dissertation addresses this issue head-on and contributes to the field of transportation planning in three major ways. First, this research develops a comprehensive vehicle micro-simulation framework that incorporates state-of-the-art household vehicle type choice, usage, and evolution models. The novelty of the framework developed is that it accommodates all the dimensions characterizing vehicle fleet/usage decisions, as well as accommodates all dimensions of vehicle transactions (i.e., fleet evolution) over time. The models estimated are multiple discrete-continuous models (vehicle type being the discrete component and vehicle mileage being the continuous component) and spatial discrete choice models that explicitly accommodate for multiple vehicle ownership and spatial interactions among households. More importantly, the vehicle fleet simulator developed in this study can be easily integrated within an activity-based microsimulation framework. Second, the vehicle fleet evolution and composition models developed in this dissertation are used to predict the vehicle fleet characteristics, annual mileage, and the associated fuel consumption and green-house gas (GHG) emissions for future years as a function of the built environment, demographics, fuel and related technology, and policy scenarios. This exercise contributes in substantial ways to the identification of promising strategies to increase the penetration of alternative-fuel vehicles and fuel-efficient vehicles, reduce energy consumption, and reduce greenhouse gas emissions. Lastly, this research captures several complex interactions between vehicle ownership, location, and activity-travel decisions of individuals by estimating 1) a joint tour-based model of tour complexity, passenger accompaniment, vehicle type choice, and tour length, and 2) an integrated model of residential location, work location, vehicle ownership, and commute tour characteristics. The methodology used for estimating these models allows the specification and estimation of multi-dimensional choice model systems covering a wide spectrum of dependent variable types (including multinomial, ordinal, count, and continuous) and may be viewed as a major advance with the potential to lead to redefine the way activity-based travel model systems are structured and implemented.