Probabilistic model for estimating vehicle trajectories using sparse mobile sensor data

@article{Hao2014ProbabilisticMF,
  title={Probabilistic model for estimating vehicle trajectories using sparse mobile sensor data},
  author={Peng Hao and Kanok Boriboonsomsin and Guoyuan Wu and Matthew J. Barth},
  journal={17th International IEEE Conference on Intelligent Transportation Systems (ITSC)},
  year={2014},
  pages={1363-1368}
}
Mobile sensors have emerged as a promising tool for traffic data collection and performance measurement, but most mobile sensor data today are sparse with low sampling rates, i.e., they are collected from a small subset of vehicles in the traffic stream every 10 to 60 seconds. Therefore, it is challenging to estimate the traffic states in both space and… CONTINUE READING