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A predictive continuum dynamic user-optimal model for the simultaneous departure time and route choice problem in a polycentric city
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Publication Year
2018-11-01
Publisher
INFORMS Inst.for Operations Res.and the Management Sciences
Citation
Transportation Science, Vol.52, pp.1496-1508
Keyword
Predictive dynamic user-optimal modelProjection methodSimultaneous departure time and route choiceUnstructured meshesVariational inequality
Mesh Keyword
Predictive dynamicsProjection methodRoute choiceUnstructured meshesVariational inequalities
All Science Classification Codes (ASJC)
Civil and Structural EngineeringTransportation
Abstract
This study develops a predictive continuum dynamic user-optimal model for the simultaneous departure time and route choice problem through a variational inequality (VI) approach. A polycentric urban city with multiple central business districts (CBDs) is considered, and travelers are classified into different classes according to their destinations (i.e., CBDs). The road network within the modeling city is assumed to be sufficiently dense and can be viewed as a continuum. A predictive dynamic user-optimal (PDUO) model has been previously used to model traffic flow with a given traffic demand distribution, in which travelers choose the routes that minimize the actual travel cost to the CBD. In this work, we combine the departure time choice with the PDUO model to study the simultaneous departure time and route choice problem. The user-optimal departure time principle is satisfied, which states that for each origin–destination pair, the total costs incurred by travelers departing at any time are equal and minimized. We then present an equivalent VI and solve it using the projection method after discretization based on unstructured meshes. A numerical experiment for an urban city with two CBDs is presented to demonstrate the effectiveness of the numerical algorithm.
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/30591
DOI
https://doi.org/10.1287/trsc.2017.0785
Fulltext

Type
Article
Funding
This work was jointly supported by grants from the Research Grants Council of the Hong Kong Special Administrative Region, China [17208614], the National Natural Science Foundation of China [11272199 and 11672348], the National Basic Research Program of China [2012CB725404], and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) [NRF-2010-0029446].
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