Download or read book A Hybrid Approach to Enhancing a Travel Demand Model s Response to Dynamic Traffic Conditions written by Mohammad Hasan Naser and published by . This book was released on 2006 with total page 94 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 Modeling Traveler Behavior Via Day to day Learning Dynamics written by Ozlem Yanmaz-Tuzel and published by . This book was released on 2010 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Travel behavior lies at the core of analysis and evaluation of transportation related measures aiming to improve urban mobility, environmental quality and a wide variety of social objectives. A better understanding of travel behavior will improve travel demand forecasting and the assessment of emerging transport policies, and will improve our means to increase road safety. The day-to-day models reflect the travelers' learning and forecasting mechanisms. These models predict travelers' choices for any given day based on their experienced choices in the previous days. Day-to-day approaches allow the use of wide range of behavioral rules, and levels of aggregation, and capture the heterogeneity in users' learning and adaptation processes, and behavioral characteristics. This thesis aims to develop a novel framework to model the interdependence between travelers' choice decisions, learning and adaptation behavior and the day-to-day update mechanism of traffic flows. The novelty of this thesis is that the proposed approach combines traveler heterogeneity and rationality in a single framework to predict travelers' day-to-day departure time and route decisions, and develops a novel day-to-day dynamic traffic assignment approach. The empirical results obtained from real transportation network, New Jersey Turnpike, confirm that the proposed day-to-day learning and dynamic traffic assignment framework model can successfully capture the significant learning dynamics, demonstrating the possibility of developing a psychological framework (i.e., learning models) as a viable approach to represent travel behavior. The other contributions of this thesis include a novel route choice set generation approach based on stochastic integer programming approach. The proposed methodology takes into account travel time variability and reliability in the transportation network. The path relevance criteria are directly incorporated into the optimization model by minimizing mean travel time, travel time variability and path overlap. Unlike previous approaches in the literature, proposed methodology eliminates the filtering step from the choice set generation and generates paths sets at desired dissimilarity level while minimizing the travel time and variability of these paths. Several case studies show the applicability of the proposed methodology on real transportation networks.

Download or read book Dynamic Framework for the Analysis of User Responses to Traffic System Disruptions and Control Actions written by Thomas Joseph and published by . This book was released on 1992 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Major planned disruptions, such as those caused by highway reconstruciton, impose major costs on system users. The consideration of user responses is important in planning reconstruction activities and developing control strategies. A methodology is developed to capture the day-to-day responses of commuters to control actions, including supply-side measures (such as ramp control) and demand-side measures (such as information dissemination strategies). The methodology integrates a user-decisions component with a traffic simulation model for freeway corridor systems. Extensive surveys of actual commuter behavior in the North Central Expressway Corridor in Dallas were conducted to characterize the day-to-day dynamics of commuter decisions and to calibrate the user-decision models. The resulting data provide unique information that is of value to a wide array of travel demand measures and traffic operations measures, including IVHS.

Download or read book Hybrid Predictive Control for Dynamic Transport Problems written by Alfredo Nunez and published by Springer Science & Business Media. This book was released on 2012-10-03 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hybrid Predictive Control for Dynamic Transport Problems develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed integer optimization problems dynamically, is readily extendable to other industrial processes. The main topics of this book are: · hybrid predictive control (HPC) design based on evolutionary multiobjective optimization (EMO); · HPC based on EMO for dial-a-ride systems; and · HPC based on EMO for operational decisions in public transport systems. Hybrid Predictive Control for Dynamic Transport Problems is a comprehensive analysis of HPC and its application to dynamic transport systems. Introductory material on evolutionary algorithms is presented in summary in an appendix. The text will be of interest to control and transport engineers working on the operational optimization of transport systems and to academic researchers working with hybrid systems. The potential applications of the generic methods presented here to other process fields will make the book of interest to a wider group of researchers, scientists and graduate students working in other control-related disciplines.

Download or read book Master s Theses Directories written by and published by . This book was released on 2006 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Education, arts and social sciences, natural and technical sciences in the United States and Canada".

Download or read book Advanced Practices in Travel Forecasting written by Rick Donnelly and published by Transportation Research Board. This book was released on 2010 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: TRB's National Cooperative Highway Research Program (NCHRP) Synthesis 406: Advanced Practices in Travel Forecasting explores the use of travel modeling and forecasting tools that could represent a significant advance over the current state of practice. The report examines five types of models: activity-based demand, dynamic network, land use, freight, and statewide.

Download or read book Traffic Flow Dynamics written by Martin Treiber and published by Springer Science & Business Media. This book was released on 2012-10-11 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive and instructive coverage of vehicular traffic flow dynamics and modeling. It makes this fascinating interdisciplinary topic, which to date was only documented in parts by specialized monographs, accessible to a broad readership. Numerous figures and problems with solutions help the reader to quickly understand and practice the presented concepts. This book is targeted at students of physics and traffic engineering and, more generally, also at students and professionals in computer science, mathematics, and interdisciplinary topics. It also offers material for project work in programming and simulation at college and university level. The main part, after presenting different categories of traffic data, is devoted to a mathematical description of the dynamics of traffic flow, covering macroscopic models which describe traffic in terms of density, as well as microscopic many-particle models in which each particle corresponds to a vehicle and its driver. Focus chapters on traffic instabilities and model calibration/validation present these topics in a novel and systematic way. Finally, the theoretical framework is shown at work in selected applications such as traffic-state and travel-time estimation, intelligent transportation systems, traffic operations management, and a detailed physics-based model for fuel consumption and emissions.

Download or read book Innovations in Travel Demand Modeling Papers written by and published by Transportation Research Board. This book was released on 2008 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 31 individual authored papers from the breakout sessions are contained in Volume 2"--Pub. desc.

Download or read book Transportation Network Modeling 2004 written by and published by . This book was released on 2004 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Predicting Air Quality Effects of Traffic flow Improvements written by Richard Gerhard Dowling and published by Transportation Research Board. This book was released on 2005 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Assessment of Congestion Pricing for Reducing Urban Congestion and Improving Air Quality written by Jorge Acha-Daza and published by . This book was released on 1995 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Systematic Literature Review on Mathematical Models of Humanitarian Logistics written by Ibrahim M. Hezam and published by Infinite Study. This book was released on with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: Humanitarian logistics (HL) is considered one of the most significant issues of disaster operations and management. Thus, HL operation should be viable enough to function well under the uncertain and complex nature of the disaster. Many difficulties in pre-and post-disaster phases bring both human and economic losses. Therefore, it is essential to make sure that the HL operations are designed efficiently. In the last two decades, several publications have emphasized efficient HL operations and proposed several mathematical models and algorithms to increase the efficiency of HL operations and motivated the necessity of a systematic literature review. A systematic literature review is deemed pertinent due to its transparent and detailed article searching procedure. In this study, due to the importance of the mathematical optimization model, we reviewed more than one hundred articles published between 2000 and 2020 to investigate the optimization models in the field of HL.We classified the optimization models into three main problems: facility location problems, relief distribution, and mass evacuation where each of the classified areas includes both deterministic and non-deterministic models.

Download or read book Trends and Applications in Knowledge Discovery and Data Mining written by Xiao-Li Li and published by Springer. This book was released on 2015-11-25 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings at PAKDD Workshops 2015, held in conjunction with PAKDD, the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining in Ho Chi Minh City, Vietnam, in May 2015. The 23 revised papers presented were carefully reviewed and selected from 57 submissions. The workshops affiliated with PAKDD 2015 include: Pattern Mining and Application of Big Data (BigPMA), Quality Issues, Measures of Interestingness and Evaluation of data mining models (QIMIE), Data Analytics for Evidence-based Healthcare (DAEBH), Vietnamese Language and Speech Processing (VLSP).

Download or read book Dissertation Abstracts International written by and published by . This book was released on 2008 with total page 800 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Traffic Management written by Simon Cohen and published by John Wiley & Sons. This book was released on 2016-06-15 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transport systems are facing an impossible dilemma: satisfy an increasing demand for mobility of people and goods, while decreasing their fossil-energy requirements and preserving the environment. Additionally, transport has an opportunity to evolve in a changing world, with new services, technologies but also new requirements (fast delivery, reliability, improved accessibility). The subject of traffic is organized into two separate but complementary volumes: Volume 3 on Traffic Management and Volume 4 on Traffic Safety. Traffic Management, Volume 3 of the 'Research for Innovative Transports' Set, presents a collection of updated papers from the TRA 2014 Conference, highlighting the diversity of research in this field. Theoretical chapters and practical case studies address topics such as cooperative systems, the global approach in modeling, road and railway traffic management, information systems and impact assessment.

Download or read book Transportation Research Record written by and published by . This book was released on 1993 with total page 708 pages. Available in PDF, EPUB and Kindle. Book excerpt: