Vehicle trajectory reconstruction for signalized intersections using mobile traffic sensors

Mobile traffic sensors - those move with the flow they are monitoring - have quickly emerged as an important means for traffic monitoring and data collection. In this paper, we propose methods to reconstruct short vehicle trajectories for the entire traffic flow at arterial intersections using sample vehicle trajectories obtained from mobile traffic sensors. The motivation for this work is that once the trajectories for all vehicles are available, a complete picture of the traffic flow will be obtained. Such information can then be applied for arterial performance measurement and other related applications. This paper presents optimization-based and delay-based models to estimate shockwave boundaries at signalized intersections, which are used to reconstruct short vehicle trajectories by applying the variation formulation (VF) of traffic flow. The models are tested using the NGSIM data and micro-simulation data. The results indicate that the proposed models are not very sensitive to penetration rates. In general, the optimization-based model outperforms the delay-based model.