Conference
Distributed evolutionary estimation of dynamic traffic origin/destination
Abstract
This paper focuses on updating time varying demand matrices using real-time information. An Artificial Intelligence technique based on Distributed Evolutionary Algorithms (DEA), which is capable to exploit the use of grid computing, is developed. This EA-based demand estimation framework is implemented into a model that we call DynODE (Dynyamic O/D Estimator). DynODE provides a direct way of fusing information of varying types, with different …
Authors
Kattan L; Abdulhai B
Pagination
pp. 911-916
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publication Date
September 1, 2010
DOI
10.1109/itsc.2010.5624970
Name of conference
13th International IEEE Conference on Intelligent Transportation Systems
Conference proceedings
17th International IEEE Conference on Intelligent Transportation Systems (ITSC)
ISSN
2153-0009