TY - JOUR
T1 - Traffic state estimation and uncertainty quantification based on heterogeneous data sources
T2 - A three detector approach
AU - Deng, Wen
AU - Lei, Hao
AU - Zhou, Xuesong
N1 - Funding Information:
The research of the first author was carried out when he was a visiting student at the University of Utah and supported by the Fundamental Research Funds for the Central Universities of China (No. KTJB10003536). The third author was partially supported by an USDOT Regional University Transportation Center grant (NEXTRANS Project No. 040PY02). We would also like to thank anonymous reviewers and Mr. Jeffrey Taylor for his valuable suggestions. The work presented in this paper remains the sole responsibility of the authors.
PY - 2013/11
Y1 - 2013/11
N2 - This study focuses on how to use multiple data sources, including loop detector counts, AVI Bluetooth travel time readings and GPS location samples, to estimate macroscopic traffic states on a homogeneous freeway segment. With a generalized least square estimation framework, this research constructs a number of linear equations that map the traffic measurements as functions of cumulative vehicle counts on both ends of a traffic segment. We extend Newell's method to solve a stochastic three-detector problem, where the mean and variance estimates of cell-based density and flow can be analytically derived through a multinomial probit model and an innovative use of Clark's approximation method. An information measure is further introduced to quantify the value of heterogeneous traffic measurements for improving traffic state estimation on a freeway segment.
AB - This study focuses on how to use multiple data sources, including loop detector counts, AVI Bluetooth travel time readings and GPS location samples, to estimate macroscopic traffic states on a homogeneous freeway segment. With a generalized least square estimation framework, this research constructs a number of linear equations that map the traffic measurements as functions of cumulative vehicle counts on both ends of a traffic segment. We extend Newell's method to solve a stochastic three-detector problem, where the mean and variance estimates of cell-based density and flow can be analytically derived through a multinomial probit model and an innovative use of Clark's approximation method. An information measure is further introduced to quantify the value of heterogeneous traffic measurements for improving traffic state estimation on a freeway segment.
KW - Clark's approximation
KW - Kinematic wave method
KW - Probit model
KW - Three-detector problem
KW - Traffic state estimation
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U2 - 10.1016/j.trb.2013.08.015
DO - 10.1016/j.trb.2013.08.015
M3 - Article
AN - SCOPUS:84885404726
SN - 0191-2615
VL - 57
SP - 132
EP - 157
JO - Transportation Research Part B: Methodological
JF - Transportation Research Part B: Methodological
ER -