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Information 2017, 8(3), 95; doi:10.3390/info8030095

Decentralized State-Observer-Based Traffic Density Estimation of Large-Scale Urban Freeway Network by Dynamic Model

1,2,3
,
1,2,3,* and 1,2,3
1
College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China
2
Beijing Key Laboratory of Transportation Engineering, Beijing 100124, China
3
Beijing Collaborative Innovation Center for Metropolitan Transportation, Beijing 100124, China
*
Author to whom correspondence should be addressed.
Received: 27 June 2017 / Revised: 24 July 2017 / Accepted: 31 July 2017 / Published: 3 August 2017
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Abstract

In order to estimate traffic densities in a large-scale urban freeway network in an accurate and timely fashion when traffic sensors do not cover the freeway network completely and thus only local measurement data can be utilized, this paper proposes a decentralized state observer approach based on a macroscopic traffic flow model. Firstly, by using the well-known cell transmission model (CTM), the urban freeway network is modeled in the way of distributed systems. Secondly, based on the model, a decentralized observer is designed. With the help of the Lyapunov function and S-procedure theory, the observer gains are computed by using linear matrix inequality (LMI) technique. So, the traffic densities of the whole road network can be estimated by the designed observer. Finally, this method is applied to the outer ring of the Beijing’s second ring road and experimental results demonstrate the effectiveness and applicability of the proposed approach. View Full-Text
Keywords: urban freeway network; traffic densities estimation; decentralized state observer; Lyapunov function; S-procedure urban freeway network; traffic densities estimation; decentralized state observer; Lyapunov function; S-procedure
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Guo, Y.; Chen, Y.; Zhang, C. Decentralized State-Observer-Based Traffic Density Estimation of Large-Scale Urban Freeway Network by Dynamic Model. Information 2017, 8, 95.

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