scholarly journals The queue length estimation for congested signalized intersections based on shockwave theory

2013 ◽  
Author(s):  
Li Yu ◽  
Zhao Dan-pu ◽  
Tai Xian-qing ◽  
Liu Zhi-li
Keyword(s):  
Queue Length ◽  
Signalized Intersections ◽  
Length Estimation

scholarly journals Queue length estimation at signalized intersections based on magnetic sensors by different layout strategies

2017 ◽  
Vol 25 ◽  
pp. 1626-1644 ◽  
Author(s):  
Haijian Li ◽  
Na Chen ◽  
Lingqiao Qin ◽  
Limin Jia ◽  
Jian Rong
Keyword(s):  
Queue Length ◽  
Signalized Intersections ◽  
Magnetic Sensors ◽  
Length Estimation

Real-time queue length estimation for congested signalized intersections

2009 ◽  
Vol 17 (4) ◽  
pp. 412-427 ◽  
Author(s):  
Henry X. Liu ◽  
Xinkai Wu ◽  
Wenteng Ma ◽  
Heng Hu
Keyword(s):  
Real Time ◽  
Queue Length ◽  
Signalized Intersections ◽  
Length Estimation

Real-Time Queue Length Estimation for Signalized Intersections Using Vehicle Trajectory Data

2017 ◽  
Vol 2623 (1) ◽  
pp. 49-59 ◽  
Author(s):  
Fuliang Li ◽  
Keshuang Tang ◽  
Jiarong Yao ◽  
Keping Li
Keyword(s):  
Shock Waves ◽  
Queue Length ◽  
Penetration Rate ◽  
Signalized Intersections ◽  
Signal Timing ◽  
Probe Vehicle ◽  
Vehicle Trajectories ◽  
Length Estimation ◽  
Inflection Points ◽  
Sampling Intervals

Queue length is one of the most important performance measures for signalized intersections. Many methods for queue length estimation based on various data sources have been proposed in the literature. With the latest developments and applications of probe vehicle systems, cycle-by-cycle queue length estimation based only on probe data has become a promising research topic. However, most existing methods assume that information such as signal timing, arrival pattern, and penetration rate is known, an assumption that constrains their applicability in practice. The objective of this study was to propose a cycle-by-cycle queue length estimation method using only probe data without the foregoing assumption. Based on the shock wave theory, the proposed method is capable of reproducing the dynamic queue forming and dissipating process cycles at signalized intersections by using probe vehicle trajectories. To reproduce the queuing processes, the inflection points of probe vehicle trajectories representing the changes of arrival patterns are identified and extracted from the trajectory points of vehicles joining and leaving the queue. A piecewise linear function is then used to fit all the inflection points to estimate the stopping and discharging shock waves. Finally, signal timing data and queue lengths can be calculated on the basis of the estimated shock waves. Under both saturated and oversaturated traffic conditions, the performance of the method is comprehensively evaluated through 60 simulation scenarios, which cover sampling intervals from 5 s to 60 s and penetration rates ranging from 5% to 100%. Results show that compared with the method proposed by Ramezani and Geroliminis in 2015, the proposed method has more robustness for all the sampling intervals and displays more estimation accuracy of queue length and a higher success rate under conditions of low penetration rate.

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