Article (Scientific journals)
A utility-based dynamic demand estimation model that explicitly accounts for activity scheduling and duration
CANTELMO, Guido; VITI, Francesco; Nigro, Marialisa et al.
2018In Transportation Research. Part A, Policy and Practice
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Abstract :
[en] This paper proposes a Dynamic Demand Estimation (DODE) framework that explicitly accounts for activity scheduling and duration. By assuming a Utility-Based departure time choice model, the time-dependent OD flow becomes a function, whose parameters are those of the utility function(s) within the departure time choice model. In this way, the DODE is solved using a parametric approach, which, on one hand, has less variables to calibrate with respect to the classical bi-level formulation while, on the other hand, it accounts for different trip purposes. Properties of the model are analytically and numerically discussed, showing that the model is more suited for estimating the systematic component of the demand with respect to the standard GLS formulation. Differently from similar approaches in literature, which rely on agent-based microsimulators and require expensive survey data, the proposed framework is applicable with all those DTA models, which are based on OD matrix, and do not necessarily need any data at user level. This has been proven by applying the proposed approach with a standard macroscopic realistic Dynamic Traffic Assignment (DTA)
Disciplines :
Civil engineering
Author, co-author :
CANTELMO, Guido ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
VITI, Francesco  ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
Nigro, Marialisa
Cipriani, Ernesto
External co-authors :
yes
Language :
English
Title :
A utility-based dynamic demand estimation model that explicitly accounts for activity scheduling and duration
Publication date :
August 2018
Journal title :
Transportation Research. Part A, Policy and Practice
ISSN :
0965-8564
eISSN :
1879-2375
Publisher :
Elsevier, United Kingdom
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBilu :
since 05 December 2018

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