A stochastic Bayesian update and logistic growth mapping of travel-time flow relationship
General Material Designation
[Thesis]
First Statement of Responsibility
Mohammad Mofigul Islam Molla
Subsequent Statement of Responsibility
Stone, Matthew L.
.PUBLICATION, DISTRIBUTION, ETC
Name of Publisher, Distributor, etc.
North Dakota State University
Date of Publication, Distribution, etc.
2017
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
224
GENERAL NOTES
Text of Note
Committee members: Bai, Yong; Huang, Ying; Siddiqui, Chowdhury K. A.
NOTES PERTAINING TO PUBLICATION, DISTRIBUTION, ETC.
Text of Note
Place of publication: United States, Ann Arbor; ISBN=978-1-369-62327-7
DISSERTATION (THESIS) NOTE
Dissertation or thesis details and type of degree
Ph.D.
Discipline of degree
Civil Engineering
Body granting the degree
North Dakota State University
Text preceding or following the note
2017
SUMMARY OR ABSTRACT
Text of Note
The travel-time flow relationship is not always increasing in nature, it is very difficult to predict precisely. Traditional method fails to replicate this unique conditions. Until millennium, although various researchers and practitioners have given much attention to develop travel-time flow relationships, the advancement to improve travel-time flow relationships was not substantial. The knowledge about the travel-time flow relationship is not commensurate with or parallel to the advancement of new knowledge in other fields. After millennium, most investigators did not devote enough attention to create new knowledge, except for application and performance evaluation of the existing knowledge. Therefore, it is necessary to provide a new theoretical and methodological advancement in travel-time flow relationship.
Social sciences;Applied sciences;Travel -time prediction;Travel data collection;Travel time delay;Travel time flow;Virtual sensor;Volume delay function