Headway Estimation of Platooned Vehicles by Dual Filter Integrated with Car-Following Model

Abstract

This paper applies a dual Unscented Kalman filter (DUKF) and a dual particle filter (DPF) for estimating the headway distance of vehicles traveling in a longitudinal platoon. Assuming that prior knowledge on the car-following model parameter is different from what is observed in a real car-following, DUKF and DPF attempt to estimate the headway by measuring the acceleration rate and velocity of all vehicles in the platoon. Numerical analysis showed that DUKF and DPF estimated the headway accurately with a satisfactorily level of estimation precision.