Download or read book Behavioral Travel demand Models written by Peter R. Stopher and published by . This book was released on 1976 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Modeling of Transport Demand written by V.A Profillidis and published by Elsevier. This book was released on 2018-10-23 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling of Transport Demand explains the mechanisms of transport demand, from analysis to calculation and forecasting. Packed with strategies for forecasting future demand for all transport modes, the book helps readers assess the validity and accuracy of demand forecasts. Forecasting and evaluating transport demand is an essential task of transport professionals and researchers that affects the design, extension, operation, and maintenance of all transport infrastructures. Accurate demand forecasts are necessary for companies and government entities when planning future fleet size, human resource needs, revenues, expenses, and budgets. The operational and planning skills provided in Modeling of Transport Demand help readers solve the problems they face on a daily basis. Modeling of Transport Demand is written for researchers, professionals, undergraduate and graduate students at every stage in their careers, from novice to expert. The book assists those tasked with constructing qualitative models (based on executive judgment, Delphi, scenario writing, survey methods) or quantitative ones (based on statistical, time series, econometric, gravity, artificial neural network, and fuzzy methods) in choosing the most suitable solution for all types of transport applications. Presents the most recent and relevant findings and research - both at theoretical and practical levels - of transport demand Provides a theoretical analysis and formulations that are clearly presented for ease of understanding Covers analysis for all modes of transportation Includes case studies that present the most appropriate formulas and methods for finding solutions and evaluating results

Download or read book Issues in Behavioral Demand Modeling and the Valuation of Travel Time written by and published by . This book was released on 1973 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Urban Travel Demand Modeling written by Norbert Oppenheim and published by Wiley-Interscience. This book was released on 1995-02-06 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: In addition, models for optimal transportation supply decisions are integrated with the demand models. Transit travel and goods movements are specifically addressed.

Download or read book Behavioural Travel Modelling written by David A. Hensher and published by Taylor & Francis. This book was released on 2021-05-11 with total page 872 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originally published in 1979, this study deals on a fully comprehensive level with both passenger and freight travel. The 40 chapters deal with an extensive range of related topics, including equilibrium modelling, theoretical and conceptual developments in demand modelling, goods movement and forecasting and policy. It outlines approaches to understanding travel behaviour, which move beyond the individual choice theory towards a broader consideration of activities.

Download or read book Behavioral Travel demand Models written by Peter R. Stopher and published by . This book was released on 1976 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Behavioural Travel Modelling written by David A. Hensher and published by Routledge. This book was released on 2021-05-11 with total page 844 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originally published in 1979, this study deals on a fully comprehensive level with both passenger and freight travel. The 40 chapters deal with an extensive range of related topics, including equilibrium modelling, theoretical and conceptual developments in demand modelling, goods movement and forecasting and policy. It outlines approaches to understanding travel behaviour, which move beyond the individual choice theory towards a broader consideration of activities.

Download or read book Ictis 2013 written by Xinping Yan and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Urban Travel Demand written by Thomas A. Domencich and published by . This book was released on 1975 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Charles River Associates research study.

Download or read book Travel Demand Forecasting Parameters and Techniques written by and published by Transportation Research Board. This book was released on 2012 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: TRB’s National Cooperative Highway Research Program (NCHRP) Report 716: Travel Demand Forecasting: Parameters and Techniques provides guidelines on travel demand forecasting procedures and their application for helping to solve common transportation problems.

Download or read book Mapping the Travel Behavior Genome written by Konstadinos G. Goulias and published by . This book was released on 2019-10-26 with total page 734 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mapping the Travel Behavior Genome covers the latest research on the biological, motivational, cognitive, situational, and dispositional factors that drive activity-travel behavior. Organized into three sections, Retrospective and Prospective Survey of Travel Behavior Research, New Research Methods and Findings, and Future Research, the chapters of this book provide evidence of progress made in the most recent years in four dimensions of the travel behavior genome. These dimensions are Substantive Problems, Theoretical and Conceptual Frameworks, Behavioral Measurement, and Behavioral Analysis. Including the movement of goods as well as the movement of people, the book shows how traveler values, norms, attitudes, perceptions, emotions, feelings, and constraints lead to observed behavior; how to design efficient infrastructure and services to meet tomorrow's needs for accessibility and mobility; how to assess equity and distributional justice; and how to assess and implement policies for improving sustainability and quality of life. Mapping the Travel Behavior Genome examines the paradigm shift toward more dynamic, user-centric, demand-responsive transport services, including the "sharing economy," mobility as a service, automation, and robotics. This volume provides research directions to answer behavioral questions emerging from these upheavals. Offers a wide variety of approaches from leading travel behavior researchers from around the world Provides a complete map of the methods, skills, and knowledge needed to work in travel behavior Describes the state of the art in travel behavior research, providing key directions for future research

Download or read book A Disaggregated Behavioral Model of Urban Travel Demand written by Charles River Associates and published by . This book was released on 1972 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Sources of Error and Uncertainty in Behavioral Travel demand Models written by Joel Horowitz and published by . This book was released on 1980 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Development of an Aggregate Model of Urbanized Area Travel Behavior written by Frank S. Koppelman and published by . This book was released on 1976 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Aggregate Travel Demand Forecasting from Disaggregated Behavioral Models written by Daniel McFadden and published by . This book was released on 1974 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Modeling and Forecasting the Impact of Major Technological and Infrastructural Changes on Travel Demand written by Feras El Zarwi and published by . This book was released on 2017 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: The transportation system is undergoing major technological and infrastructural changes, such as the introduction of autonomous vehicles, high speed rail, carsharing, ridesharing, flying cars, drones, and other app-driven on-demand services. While the changes are imminent, the impact on travel behavior is uncertain, as is the role of policy in shaping the future. Literature shows that even under the most optimistic scenarios, society's environmental goals cannot be met by technology, operations, and energy system improvements only - behavior change is needed. Behavior change does not occur instantaneously, but is rather a gradual process that requires years and even generations to yield the desired outcomes. That is why we need to nudge and guide trends of travel behavior over time in this era of transformative mobility. We should focus on influencing long-range trends of travel behavior to be more sustainable and multimodal via effective policies and investment strategies. Hence, there is a need for developing policy analysis tools that focus on modeling the evolution of trends of travel behavior in response to upcoming transportation services and technologies. Over time, travel choices, attitudes, and social norms will result in changes in lifestyles and travel behavior. That is why understanding dynamic changes of lifestyles and behavior in this era of transformative mobility is central to modeling and influencing trends of travel behavior. Modeling behavioral dynamics and trends is key to assessing how policies and investment strategies can transform cities to provide a higher level of connectivity, attain significant reductions in congestion levels, encourage multimodality, improve economic and environmental health, and ensure equity. This dissertation focuses on addressing limitations of activity-based travel demand models in capturing and predicting trends of travel behavior. Activity-based travel demand models are the commonly-used approach by metropolitan planning agencies to predict 20-30 year forecasts. These include traffic volumes, transit ridership, biking and walking market shares that are the result of large scale transportation investments and policy decisions. Currently, travel demand models are not equipped with a framework that predicts long-range trends in travel behavior for two main reasons. First, they do not entail a mechanism that projects membership and market share of new modes of transport into the future (Uber, autonomous vehicles, carsharing services, etc). Second, they lack a dynamic framework that could enable them to model and forecast changes in lifestyles and transport modality styles. Modeling the evolution and dynamic changes of behavior, modality styles and lifestyles in response to infrastructural and technological investments is key to understanding and predicting trends of travel behavior, car ownership levels, vehicle miles traveled (VMT), and travel mode choice. Hence, we need to integrate a methodological framework into current travel demand models to better understand and predict the impact of upcoming transportation services and technologies, which will be prevalent in 20-30 years. The objectives of this dissertation are to model the dynamics of lifestyles and travel behavior through: " Developing a disaggregate, dynamic discrete choice framework that models and predicts long-range trends of travel behavior, and accounts for upcoming technological and infrastructural changes." Testing the proposed framework to assess its methodological flexibility and robustness." Empirically highlighting the value of the framework to transportation policy and practice. The proposed disaggregate, dynamic discrete choice framework in this dissertation addresses two key limitations of existing travel demand models, and in particular: (1) dynamic, disaggregate models of technology and service adoption, and (2) models that capture how lifestyles, preferences and transport modality styles evolve dynamically over time. This dissertation brings together theories and techniques from econometrics (discrete choice analysis), machine learning (hidden Markov models), statistical learning (Expectation Maximization algorithm), and the technology diffusion literature (adoption styles). Throughout this dissertation we develop, estimate, apply and test the building blocks of the proposed disaggregate, dynamic discrete choice framework. The two key developed components of the framework are defined below. First, a discrete choice framework for modeling and forecasting the adoption and diffusion of new transportation services. A disaggregate technology adoption model was developed since models of this type can: (1) be integrated with current activity-based travel demand models; and (2) account for the spatial/network effect of the new technology to understand and quantify how the size of the network, governed by the new technology, influences the adoption behavior. We build on the formulation of discrete mixture models and specifically dynamic latent class choice models, which were integrated with a network effect model. We employed a confirmatory approach to estimate our latent class choice model based on findings from the technology diffusion literature that focus on defining distinct types of adopters such as innovator/early adopters and imitators. Latent class choice models allow for heterogeneity in the utility of adoption for the various market segments i.e. innovators/early adopters, imitators and non-adopters. We make use of revealed preference (RP) time series data from a one-way carsharing system in a major city in the United States to estimate model parameters. The data entails a complete set of member enrollment for the carsharing service for a time period of 2.5 years after being launched. Consistent with the technology diffusion literature, our model identifies three latent classes whose utility of adoption have a well-defined set of preferences that are statistically significant and behaviorally consistent. The technology adoption model predicts the probability that a certain individual will adopt the service at a certain time period, and is explained by social influences, network effect, socio-demographics and level-of-service attributes. Finally, the model was calibrated and then used to forecast adoption of the carsharing system for potential investment strategy scenarios. A couple of takeaways from the adoption forecasts were: (1) highest expected increase in the monthly number of adopters arises by establishing a relationship with a major technology firm and placing a new station/pod for the carsharing system outside that technology firm; and (2) no significant difference in the expected number of monthly adopters for the downtown region will exist between having a station or on-street parking. The second component in the proposed framework entails modeling and forecasting the evolution of preferences, lifestyles and transport modality styles over time. Literature suggests that preferences, as denoted by taste parameters and consideration sets in the context of utility-maximizing behavior, may evolve over time in response to changes in demographic and situational variables, psychological, sociological and biological constructs, and available alternatives and their attributes. However, existing representations typically overlook the influence of past experiences on present preferences. This study develops, applies and tests a hidden Markov model with a discrete choice kernel to model and forecast the evolution of individual preferences and behaviors over long-range forecasting horizons. The hidden states denote different preferences, i.e. modes considered in the choice set and sensitivity to level-of-service attributes. The evolutionary path of those hidden states (preference states) is hypothesized to be a first-order Markov process such that an individual's preferences during a particular time period are dependent on their preferences during the previous time period. The framework is applied to study the evolution of travel mode preferences, or modality styles, over time, in response to a major change in the public transportation system. We use longitudinal travel diary from Santiago, Chile. The dataset consists of four one-week pseudo travel diaries collected before and after the introduction of Transantiago, which was a complete redesign of the public transportation system in the city. Our model identifies four modality styles in the population, labeled as follows: drivers, bus users, bus-metro users, and auto-metro users. The modality styles differ in terms of the travel modes that they consider and their sensitivity to level-of-service attributes (travel time, travel cost, etc.). At the population level, there are significant shifts in the distribution of individuals across modality styles before and after the change in the system, but the distribution is relatively stable in the periods after the change. In general, the proportion of drivers, auto-metro users, and bus-metro users has increased, and the proportion of bus users has decreased. At the individual level, habit formation is found to impact transition probabilities across all modality styles; individuals are more likely to stay in the same modality style over successive time periods than transition to a different modality style. Finally, a comparison between the proposed dynamic framework and comparable static frameworks reveals differences in aggregate forecasts for different policy scenarios, demonstrating the value of the proposed framework for both individual and population-level policy analysis. The aforementioned methodological frameworks comprise complex model formulation. This however comes at a cost in terms.

Download or read book Choice and Constraints Oriented Modeling written by Pat Burnett and published by . This book was released on 1978 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Development of Household Interaction Game, pilot-tested on elderly group in Oklahoma City.