Schedule-Based Dynamic Transit Modeling: Theory and Applications outlines the new schedule-based dynamic approach to mass transit modeling. In the last ten years the schedule-based dynamic approach has been developed and applied especially for operational planning. It allows time evolution of on-board loads and travel times for each run of each line to be obtained, and uses behavioral hypotheses strictly related to transit systems and user characteristics. It allows us to open new frontiers in transit modelling to support network design, timetable setting, investigation of congestion effects, as well as the assessment of new technologies introduction, such as information to users (ITS technologies). The contributors and editors of the book are leading researchers in the field of transportation, and in this volume they build a solid foundation for developing still more sophisticated models. These future models of mass transit systems will continue to add higher levels of accuracy and sensitivity desired in forecasting the performance of public transport systems.

The growing mobility needs of travellers have led to the development of increasingly complex and integrated multi-modal transit networks. Hence, transport agencies and transit operators are now more urgently required to assist in the challenging task of effectively and efficiently planning, managing, and governing transit networks. A pre-condition for the development of an effective intelligent multi-modal transit system is the integration of information and communication technology (ICT) tools that will support the needs of transit operators and travellers. To achieve this, reliable real-time simulation and short-term forecasting of passenger demand and service network conditions are required to provide both real-time traveller information and successfully synchronise transit service planning and operations control. Modelling Intelligent Multi-Modal Transit Systems introduces the current trends in this newly emerging area. Recent developments in information technology and telematics have enabled a large amount of data to become available, thus further attracting transport researchers to set up new models outside the context of the traditional data-driven approach. The alternative demand-supply interaction or network assignment modelling approach has improved greatly in recent years and has a crucial role to play in this new context.

"This book provides a rigorous and comprehensive coverage of transportation models and planning methods and is a must-have to anyone in the transportation community, including students, teachers, and practitioners." Moshe Ben-Akiva, Massachusetts Institute of Technology.

"Schedule-Based Modeling of Transportation Networks: Theory and Applications" follows the book Schedule-Based Dynamic Transit Modeling, published in this series in 2004, recognizing the critical role that schedules play in transportation systems. Conceived for the simulation of transit systems, in the last few years the schedule-based approach has been expanded and applied to operational planning of other transportation schedule services besides mass transit, e.g. freight transport. This innovative approach allows forecasting the evolution over time of the on-board loads on the services and their time-varying performance, using credible user behavioral hypotheses. It opens new frontiers in transportation modeling to support network design, timetable setting, and investigation of congestion effects, as well as the assessment of such new technologies, such as users system information (ITS technologies).

"This book provides a rigorous and comprehensive coverage of transportation models and planning methods and is a must-have to anyone in the transportation community, including students, teachers, and practitioners." Moshe Ben-Akiva, Massachusetts Institute of Technology.

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.

A history of urban travel demand modeling (UTDM) and its enormous influence on American life from the 1920s to the present. For better and worse, the automobile has been an integral part of the American way of life for decades. Its ascendance would have been far less spectacular, however, had engineers and planners not devised urban travel demand modeling (UTDM). This book tells the story of this irreplaceable engineering tool that has helped cities accommodate continuous rise in traffic from the 1950s on. Beginning with UTDM’s origins as a method to help plan new infrastructure, Konstantinos Chatzis follows its trajectory through new generations of models that helped make optimal use of existing capacity and examines related policy instruments, including the recent use of intelligent transportation systems. Chatzis investigates these models as evolving entities involving humans and nonhumans that were shaped through a specific production process. In surveying the various generations of UTDM, he delves into various means of production (from tabulating machines to software packages) and travel survey methods (from personal interviews to GPS tracking devices and smartphones) used to obtain critical information. He also looks at the individuals who have collectively built a distinct UTDM social world by displaying specialized knowledge, developing specific skills, and performing various tasks and functions, and by communicating, interacting, and even competing with one another. Original and refreshingly accessible, Forecasting Travel in Urban America offers the first detailed history behind the thinkers and processes that impact the lives of millions of city dwellers every day.