Freeway Traffic State Estimation with Floating-Car-Data

2001 ◽  
Vol 34 (9) ◽  
pp. 291-296 ◽  
Author(s):  
Georg Böker ◽  
Jan Lunze
PLoS ONE ◽  
2016 ◽  
Vol 11 (7) ◽  
pp. e0157420 ◽  
Author(s):  
Bin Ran ◽  
Li Song ◽  
Jian Zhang ◽  
Yang Cheng ◽  
Huachun Tan

2016 ◽  
Vol 80 ◽  
pp. 2008-2018 ◽  
Author(s):  
Abhinav Sunderrajan ◽  
Vaisagh Viswanathan ◽  
Wentong Cai ◽  
Alois Knoll

2018 ◽  
Vol 23 (6) ◽  
pp. 525-540
Author(s):  
Han Yang ◽  
Peter J. Jin ◽  
Bin Ran ◽  
Dongyuan Yang ◽  
Zhengyu Duan ◽  
...  

2013 ◽  
Vol 2013 ◽  
pp. 1-6
Author(s):  
Jun Bi ◽  
Can Chang ◽  
Yang Fan

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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