|
Title: Computation of Skims for Large-Scale Implementations of Integrated Activity-Based and Dynamic Traffic Assignment Models
Accession Number: 01594296
Record Type: Component
Record URL: Availability: Find a library where document is available Abstract: Integrated activity-based model (ABM) and dynamic traffic assignment (DTA) frameworks have emerged as promising tools to support transportation planning and operations, particularly in the context of novel technologies and data sources. This research proposes an approach to characterize the implementation of integrated ABM-DTA models and seeks to facilitate the interpretation and comparison of frameworks and, ultimately, the selection of appropriate tools. The importance of the dimensions considered in this characterization is illustrated through a detailed analysis of the computation of skims. Skims are the level of service (LOS) metric produced by DTA models, and the computation of skims may impact the performance and convergence of ABM-DTA applications. Numerical results from experiments on a regional ABM-DTA model in Austin, Texas, suggest that skims produced at relatively small time steps (10 to 30 min) may lead to a faster integrated model convergence. Finer time-grained skims are also observed to capture sharper temporal peaking patterns in the LOS. This work considers two skim computation methods; the analysis of the results suggests that simpler techniques are adequate, as the inherent variability of travel times from simulation overshadows any gain in precision from more complex methods. This study also uses promising techniques to visualize and analyze the model results, a challenging task in the context of highly disaggregate models and the subject of further research. The insights from this research effort can inform future research on the implementation of ABM-DTA methods and practical applications of existing frameworks.
Monograph Title: Monograph Accession #: 01595160
Report/Paper Numbers: 16-5948
Language: English
Authors: Juri, Natalia RuizJames, Rachel MJiang, NanDuthie, JenniferPinjari, AbdulBhat, Chandra RPagination: pp 134–143
Publication Date: 2016
ISBN: 9780309441223
Media Type: Print
Features: Figures
(5)
; References
(17)
; Tables
(3)
TRT Terms: Subject Areas: Data and Information Technology; Highways; Planning and Forecasting
Files: TRIS, TRB, ATRI
Created Date: Jan 12 2016 6:38PM
More Articles from this Serial Issue:
|