Overview
The use of Dynamic Traffic Assignment (DTA) in transportation modeling is an emerging analysis approach around the world. The benefits of applying DTA in transportation analysis increase with network size and level of congestion. This guidebook presents principles and direction that can be consistently applied when using DTA regardless of application platforms or software packages.
The major benefit of using DTA is the capability of the modeling method to take into account the spatial and temporal effects of congestion in determining route choice, time of departure choice, and mode choice. DTA is suitable for analyses involving incidents, construction zones, Active Transportation and Demand Management (ATDM) strategies, Integrated Corridor Management (ICM) strategies, Intelligent Transportation Systems (ITS), and other operational strategies, as well as capacity increasing strategies.
The purpose of this guide is to provide practitioners with guidance on how to apply DTA within transportation models. This guide provides a set of proven approaches to model building, calibration, and alternatives analysis.
The intended audience for this guidebook includes practitioners, program managers, and software developers. The first four chapters will be of primary interest to program managers while the entire guidebook will be useful to practitioners. Software developers should consider this guide when preparing documentation for their modeling software and providing instruction to their customers.
Macroscopic, mesoscopic, and microscopic simulation models can incorporate DTA methods. Multi-resolution modeling (MRM) is discussed in this guidebook as an effective method for linking analysis tools with different resolutions to enhance DTA. Within the MRM framework, results from one model are fed to another in an iterative process so that overall analysis results are improved and consistency between model assumptions is maintained.
This guidebook also discusses the data required to develop, calibrate, validate, and apply a DTA model. The guide provides a systematic process for DTA model error and validity checking, as well as model calibration that is considerate of project objectives and the variability of traffic conditions in the field.
This guidebook consists of two main parts. Part I: DTA Overview (Chapters 1 through 3) provides background on DTA modeling principles and software capabilities. Part II: DTA Applications (Chapters 4 through 9) provides guidance on how to apply DTA within transportation models.