
This paper proposes a Bayesian approach to estimate both real-time traffic state and underlying traffic parameters at signalized intersections using low penetration rate vehicle trajectory data. The method provides distributional estimation results that explicitly quantify the uncertainty caused by limited available data.


coremsg

bayesian-estimation-of-traffic-state-and-parameters-at-signalized-intersections-with-low-penetration-vehicle-trajectory-data


Bayesian Estimation of Traffic State and Parameters at Signalized Intersections with Low Penetration Vehicle Trajectory Data
