Map inference in the face of noise and disparity

  title={Map inference in the face of noise and disparity},
  author={James Biagioni and Jakob Eriksson},
This paper describes a process for automatically inferring maps from large collections of opportunistically collected GPS traces. In this type of dataset, there is often a great disparity in terms of coverage. For example, a freeway may be represented by thousands of trips, whereas a residential road may only have a handful of observations. Additionally, while modern GPS receivers typically produce high-quality location estimates, errors over 100 meters are not uncommon, especially near tall… CONTINUE READING
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