Traffic Flow Signal based Traffic Event Reconstruction using Sequential Monte Carlo Methods

DOI

10.2991/iiicec-15.2015.385How to use a DOI?

Keywords

Traffic Flow Signal; SMC; DDDAS; event reconstruction

Abstract

According to the nonlinear and non-Gaussian characteristics of the traffic flow, we propose a SMC based traffic flow congestion event reconstruction framework based on traffic flow signals. The simulation states can get close to the real scene continuously along with the data assimilation model assimilates the real-time traffic signals constantly. The congestion event in real scene can be estimated based on the simulation data. Thus, we can estimate the congestion in different particles and finally reconstruct the congestion event. This framework can evaluate the current roads’ states based on the reconstruction results, and then the range and the start position of the congestion can be determined. Related experimental results are presented and analyzed.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiangwen Feng
AU  - Song Xu
AU  - Xuefeng Yan
PY  - 2015/03
DA  - 2015/03
TI  - Traffic Flow Signal based Traffic Event Reconstruction using Sequential Monte Carlo Methods
BT  - Proceedings of the 2015 International Industrial Informatics and Computer Engineering Conference
PB  - Atlantis Press
SP  - 1771
EP  - 1774
SN  - 2352-538X
UR  - https://doi.org/10.2991/iiicec-15.2015.385
DO  - 10.2991/iiicec-15.2015.385
ID  - Feng2015/03
ER  -