Calibration-free traffic state estimation method using single detector and connected vehicles with Kalman filtering and RTS smoothing

2020 ◽  
Author(s):  
Toru Seo
Keyword(s):  
State Estimation ◽  
Kalman Filtering ◽  
Estimation Method ◽  
Connected Vehicles ◽  
Traffic State ◽  
Traffic State Estimation ◽  
Single Detector ◽  
Calibration Free

Microscopic simulation-based validation of a per-lane traffic state estimation scheme for highways with connected vehicles

2018 ◽  
Vol 86 ◽  
pp. 441-452 ◽  
Author(s):  
Sofia Papadopoulou ◽  
Claudio Roncoli ◽  
Nikolaos Bekiaris-Liberis ◽  
Ioannis Papamichail ◽  
Markos Papageorgiou
Keyword(s):  
State Estimation ◽  
Connected Vehicles ◽  
Microscopic Simulation ◽  
Traffic State ◽  
Traffic State Estimation ◽  
Simulation Based ◽  
Estimation Scheme

scholarly journals Traffic State Estimation Using Connected Vehicles and Stationary Detectors

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Ellen F. Grumert ◽  
Andreas Tapani
Keyword(s):  
State Estimation ◽  
Traffic Management ◽  
Effective Control ◽  
Accurate Estimation ◽  
Connected Vehicles ◽  
Density Estimates ◽  
Promising Alternative ◽  
Traffic Conditions ◽  
Traffic State ◽  
Traffic State Estimation

Real-time traffic state estimation is of importance for efficient traffic management. This is especially the case for traffic management systems that require fast detection of changes in the traffic conditions in order to apply an effective control measure. In this paper, we propose a method for estimating the traffic state and speed and density, by using connected vehicles combined with stationary detectors. The aim is to allow fast and accurate estimation of changes in the traffic conditions. The proposed method does only require information about the speed and the position of connected vehicles and can make use of sparsely located stationary detectors to limit the dependence on the infrastructure equipment. An evaluation of the proposed method is carried out by microscopic traffic simulation. The traffic state estimated using the proposed method is compared to the true simulated traffic state. Further, the density estimates are compared to density estimates from one detector-based method, one combined method, and one connected-vehicle-based method. The results of the study show that the proposed method is a promising alternative for estimating the traffic state in traffic management applications.

scholarly journals Traffic State Estimation Per Lane in Highways with Connected Vehicles

2017 ◽  
Vol 27 ◽  
pp. 921-928
Author(s):  
Nikolaos Bekiaris-Liberis ◽  
Claudio Roncoli ◽  
Markos Papageorgiou
Keyword(s):  
State Estimation ◽  
Connected Vehicles ◽  
Traffic State ◽  
Traffic State Estimation
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