Spatial inference of traffic transition using micro-macro traffic variables
File(s)
Published version
Author(s)
Thajchayapong, S
Barria, JA
Type
Journal Article
Abstract
This paper proposes an online traffic inference algorithm for road segments in which local traffic information cannot be directly observed. Using macro-micro traffic variables as inputs, the algorithm consists of three main operations. First, it uses interarrival time (time headway) statistics from upstream and downstream locations to spatially infer traffic transitions at an unsupervised piece of segment. Second, it estimates lane-level flow and occupancy at the same unsupervised target site. Third, it estimates individual lane-level shockwave propagation times on the segment. Using real-world closed-circuit television data, it is shown that the proposed algorithm outperforms previously proposed methods in the literature.
Date Issued
2015-04-01
Date Acceptance
2014-07-21
Citation
IEEE Transactions on Intelligent Transportation Systems, 2015, 16 (2), pp.854-864
ISSN
1524-9050
Publisher
Institute of Electrical and Electronics Engineers
Start Page
854
End Page
864
Journal / Book Title
IEEE Transactions on Intelligent Transportation Systems
Volume
16
Issue
2
Copyright Statement
© 2015 The Authors. This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/
License URL
Identifier
https://ieeexplore.ieee.org/document/6894580
Subjects
Science & Technology
Technology
Engineering, Civil
Engineering, Electrical & Electronic
Transportation Science & Technology
Engineering
Transportation
Freeway segments
microscopic traffic variables
spatial inference
traffic anomalies
traffic estimation
Logistics & Transportation
0801 Artificial Intelligence and Image Processing
0905 Civil Engineering
1507 Transportation and Freight Services
Publication Status
Published
Date Publish Online
2014-09-09