VANET based traffic estimation: A matrix completion approach

Traffic information is important for drivers and the traffic monitoring center (TMC) to avoid traffic congestions. VANET based systems use probe vehicles (PVs) to sense and upload the traffic information. However, due to the uneven distribution of the PVs, only a small part of the real-time traffic data can be gathered. Also, it is not efficient to estimate the traffic conditions at TMC and then publish to vehicles. We consider a service oriented algorithm for both PVs and TMC to estimate the missing traffic conditions, and propose a Matrix Completion (MC) based algorithm, HaTTEM, to estimate the missing traffic data in the traffic condition matrix (TCM). Temporal continuity and the bounds of the traffic data are introduced to reduce the error of estimation. To reduce the computational time, we propose the L_0.5-based Iterative MC Algorithm so that the TCM can be fast estimated by the PVs and TMC. The simulations with real world data show the effectiveness and efficiency of HaTTEM even when the PVs can only sense 20% of the traffic data.