The schedule-based modeling of transportation systems: recent developments. -- Passenger delay models for rail networks -- Multi-day dynamic transit assignment -- Schedule-based dynamic transit assignment -- The potential impact of automated data collection systems on urban public transport planning. -- Using automated fare collection data, GIS, and dynamic schedule queries to improve transit data and transit assignment model. -- Large-scale schedule-based transit assignment - further optimization of the solution algorithms -- Schedule-based transit assignment: new dynamic equilibrium model with vehicle capacity constraints -- MILATRAS: a new modeling framework for the transit assignment problem -- Simulation-based evaluation of Advanced Public Transportation Information Systems (APTIS) -- The build-up of capacity problems during the peak hour -- Schedule-based passenger and freight mode choice models for ex- urban trips -- A schedule-based methodology proposal for Sea Motorways feasibility evaluation -- Estimation of target time distribution for agri-food products by road transport -- A macroscopic model of a container terminal based on diachronic networks.

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). 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 scheduled transportation systems will continue to improve the accuracy and sensitivity desired in forecasting the performance of public transport systems.