Incorporation of Lagrangian measurements in freeway traffic state estimation

2010 ◽  
Vol 44 (4) ◽  
pp. 460-481 ◽  
Author(s):  
Juan C. Herrera ◽  
Alexandre M. Bayen
Keyword(s):  
State Estimation ◽  
Freeway Traffic ◽  
Traffic State ◽  
Traffic State Estimation ◽  
Lagrangian Measurements

Freeway traffic state estimation: A Lagrangian-space Kalman filter approach

2018 ◽  
Vol 23 (6) ◽  
pp. 525-540
Author(s):  
Han Yang ◽  
Peter J. Jin ◽  
Bin Ran ◽  
Dongyuan Yang ◽  
Zhengyu Duan ◽  
...  
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Freeway Traffic ◽  
Traffic State ◽  
Traffic State Estimation ◽  
Filter Approach

scholarly journals Particle Filter for Estimating Freeway Traffic State in Beijing

2013 ◽  
Vol 2013 ◽  
pp. 1-6
Author(s):  
Jun Bi ◽  
Can Chang ◽  
Yang Fan
Keyword(s):  
Particle Filter ◽  
State Estimation ◽  
Estimation Error ◽  
Nonlinear Problems ◽  
The West ◽  
Freeway Traffic ◽  
Traffic State ◽  
Traffic Characteristics ◽  
Traffic State Estimation ◽  
Traffic Guidance

Freeway traffic state estimation is useful for intelligent traffic guidance, control, and management. The freeway traffic state is featured with rapid and dramatic fluctuations, which presents a strong nonlinear feature. In theory, a particle filter has good performance in solving nonlinear problems. This paper proposes a particle filter based approach to estimate freeway traffic state. The freeway link between the west of Peace Bridge and the west of San Yuan Bridge of the third ring in Beijing is used as the experimental object. According to the traffic characteristics and measurement mode of the link, the second-order validated macroscopic traffic flow model is adopted to set up the link model. The implementation steps of the particle filter for freeway traffic state estimation are described in detail. The estimation error analysis for the experiments proves that the proposed approach has an encouraging estimation performance.

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