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Spatial Inference of Traffic Transition Using Micro-Macro Traffic Variables
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Document Title
Spatial Inference of Traffic Transition Using Micro-Macro Traffic Variables
Author
Thajchayapong S., Barria J.A.
Name from Authors Collection
Affiliations
National Electronic and Computer Technology Center (NECTEC), National Science and Technology Development Agency (NSTDA), Pathumthani, 12120, Thailand; Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, United Kingdom
Type
Article
Source Title
IEEE Transactions on Intelligent Transportation Systems
ISSN
15249050
Year
2015
Volume
16
Issue
2
Page
854-864
Open Access
All Open Access, Bronze
Publisher
Institute of Electrical and Electronics Engineers Inc.
DOI
10.1109/TITS.2014.2345742
Format
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. © 2000-2011 IEEE.
Industrial Classification
Knowledge Taxonomy Level 1
Knowledge Taxonomy Level 2
Knowledge Taxonomy Level 3
License
N/A
Rights
N/A
Publication Source
Scopus