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@article{Thajchayapong:2015:10.1109/TITS.2014.2345742,
author = {Thajchayapong, S and Barria, JA},
doi = {10.1109/TITS.2014.2345742},
journal = {IEEE Transactions on Intelligent Transportation Systems},
pages = {854--864},
title = {Spatial inference of traffic transition using micro-macro traffic variables},
url = {http://dx.doi.org/10.1109/TITS.2014.2345742},
volume = {16},
year = {2015}
}
TY - JOUR
AB - 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.
AU - Thajchayapong,S
AU - Barria,JA
DO - 10.1109/TITS.2014.2345742
EP - 864
PY - 2015///
SN - 1524-9050
SP - 854
TI - Spatial inference of traffic transition using micro-macro traffic variables
T2 - IEEE Transactions on Intelligent Transportation Systems
UR - http://dx.doi.org/10.1109/TITS.2014.2345742
UR - https://ieeexplore.ieee.org/document/6894580
VL - 16
ER -
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