Travel time reliability in transportation networks: a review of methodological developments
The unavoidable travel time variability in transportation networks, resulted from the widespread supply side and demand side uncertainties, makes travel time reliability (TTR) be a common and core interest of all the stakeholders in transportation systems, including planners, travelers, service prov...
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| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/163854 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | The unavoidable travel time variability in transportation networks, resulted from the widespread supply side and demand side uncertainties, makes travel time reliability (TTR) be a common and core interest of all the stakeholders in transportation systems, including planners, travelers, service providers, and managers. This common and core interest stimulates extensive studies on modeling TTR. Researchers have developed a range of theories and models of TTR,
many of which have been incorporated into transportation models, policies, and
project appraisals. Adopting the network perspective, this paper aims to
provide an integrated framework for reviewing the methodological developments
of modeling TTR in transportation networks, including its characterization,
evaluation and valuation, and traffic assignment. Specifically, the TTR
characterization provides a whole picture of travel time distribution in
transportation networks. TTR evaluation and TTR valuation (known as the value
of reliability, VOR) simply and intuitively interpret abstract characterized
TTR to be well understood by different stakeholders of transportation systems.
TTR-based traffic assignment investigates the effects of TTR on the individual
users travel behavior and consequently the collective network flow pattern. As
the above three topics are mainly separately studied in different disciplines
and research areas, the integrated framework allows us to better understand
their relationships and may contribute to developing possible combinations of
TTR modeling philosophy. Also, the network perspective enables to focus on
common challenges of modeling TTR, especially the uncertainty propagation from
the uncertainty sources to the TTR at spatial levels including link, route, and
the entire network. Some directions for future research are discussed in the
era of new data environment, applications, and emerging technologies. |
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