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 
Keywords: Generalized least squares
Intelligent Transportation Systems
Off-line data
On-line data
Travel time estimation
Issue Date: 2018
Publisher: Taylor & Francis
Source: Transportmetrica. A, Transport science, 2018, v. 14, no. 1-2, p. 110-129 How to cite?
Journal: Transportmetrica. A, Transport science 
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.
URI: http://hdl.handle.net/10397/73950
ISSN: 2324-9935
EISSN: 2324-9943
DOI: 10.1080/23249935.2017.1323039
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

3
Last Week
0
Last month
Citations as of Mar 24, 2019

WEB OF SCIENCETM
Citations

1
Last Week
0
Last month
Citations as of Apr 8, 2019

Page view(s)

36
Citations as of May 21, 2019

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.