Macroscopic Fundamental Diagram Based Discrete Transportation Network Design

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dc.contributor.authorHu, Guojing
dc.contributor.authorLu, Weike
dc.contributor.authorWang, Feng
dc.contributor.authorWhalin, Robert
dc.date.accessioned2020-02-19T20:25:49Z
dc.date.available2020-02-19T20:25:49Z
dc.date.issued2020-01-20
dc.description.abstractThe presence of demand uncertainty brings challenges to network design problems (NDP), because fluctuations in origin-destination (OD) demand have a prominent effect on the corresponding total travel time, which is usually adopted as an index to evaluate the network design problem. Fortunately, the macroscopic fundamental diagram (MFD) has been proved to be a property of the road network itself, independent of the origin-destination demand. Such characteristics of an MFD provide a new theoretical basis to assess the traffic network performance and further appraise the quality of network design strategies. Focusing on improving network capacity under the NDP framework, this paper formulates a bi-level programming model, where at the lower level, flows are assigned to the newly extended network subject to user equilibrium theory, and the upper level determines which links should be added to achieve the maximum network capacity. To solve the proposed model, we design an algorithm framework, where traffic flow distribution of each building strategy is calculated under the dynamic user equilibrium (DUE), and updated through the VISSIM-COM-Python interaction. Then, the output data are obtained to shape MFDs, and k-means clustering algorithm is employed to quantify the MFD-based network capacity. Finally, the methodology is implemented in a test network, and the results show the benefits of using the MFD-based method to solve the network design problem under stochastic OD demands. Specifically, the capacity paradox is also presented in the test results.
dc.description.departmentEngineering
dc.formatText
dc.format.extent14 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationHu, G., Lu, W., Wang, F., & Whalin, R. W. (2020). Macroscopic fundamental diagram based discrete transportation network design. Journal of Advanced Transportation, 2020, pp. 1-14.
dc.identifier.doihttps://doi.org/10.1155/2020/4951953
dc.identifier.issn0197-6729
dc.identifier.urihttps://hdl.handle.net/10877/9317
dc.language.isoen
dc.publisherHindawi
dc.rights.holder© 2020 Guojing Hu et al.
dc.rights.licenseThis work is licensed under a Creative Commons Attribution 3.0 United States License.
dc.sourceJournal of Advanced Transportation, 2020, Article ID 4951953, pp. 1-14.
dc.subjectk-means clustering
dc.subjectstochastic systems
dc.subjecttravel time
dc.subjectalgorithm framework
dc.subjecttraffic control
dc.subjectbilevel programming models
dc.subjectIngram School of Engineering
dc.titleMacroscopic Fundamental Diagram Based Discrete Transportation Network Design
dc.typeArticle

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