Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/73950
Title: | Network-wide on-line travel time estimation with inconsistent data from multiple sensor systems under network uncertainty | Authors: | Shao, H Lam, WHK Sumalee, A Chen, A |
Issue Date: | 2018 | Source: | Transportmetrica. A, Transport science, 2018, v. 14, no. 1-2, p. 110-129 | Abstract: | This paper proposes a new modeling approach for network-wide on-line travel time estimation with inconsistent data from multiple sensor systems. It makes full use of both the available data from multiple sensor systems (on-line data) and historical data (off-line data). The first- and second-order statistical properties of the on-line data are investigated together with the data inconsistency issue to estimate network-wide travel times. The proposed model is formulated as a generalized least squares problem with non-linear constraints. A solution algorithm based on the penalty function method is adopted to solve the proposed model, whose application is illustrated by numerical examples using a local road network in Hong Kong. | Keywords: | Generalized least squares Intelligent Transportation Systems Off-line data On-line data Travel time estimation |
Publisher: | Taylor & Francis | Journal: | Transportmetrica. A, Transport science | ISSN: | 2324-9935 | EISSN: | 2324-9943 | DOI: | 10.1080/23249935.2017.1323039 | Rights: | © 2017 Hong Kong Society for Transportation Studies Limited This is an Accepted Manuscript of an article published by Taylor & Francis in Transportmetrica A: Transport Science on 15 May 2017 (Published online), available at: http://www.tandfonline.com/10.1080/23249935.2017.1323039. |
Appears in Collections: | Journal/Magazine Article |
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File | Description | Size | Format | |
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Shao_Network-Wide_On-Line_Travel.pdf | Pre-Published version | 713.33 kB | Adobe PDF | View/Open |
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