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gps2roadnetwork's Introduction

GPS2RoadNetwork

Reading list of the topic about utilizing vehicle generated GPS data to update road networks

Waffle.io - Issues in progress

Targets

  1. Discover added or deleted routes
  2. Mine the rich information of routes (e.g., width)
  3. ...

Reading List

  1. Existing Work in Map Updates

    1. MapFuse: Road Network Fusion for Incremental Map Updates
  2. Outlier Detection

    1. Distance-based Outlier Detection in Data Streams
  3. Map Inference from GPS

    1. Inferring Directed Road Networks from GPS Traces by Track Alignment

    2. Automatic Generation and Validation of Road Maps from GPS Trajectory Data Sets

    3. Choosing thresholds for density-based map construction algorithms

    4. Map Custruction Project. The comparison and evaluation of many existing algorithms. Codes and datasets available! Their paper is also avaialbe here.

    5. Inferring Road Maps from Global Positioning System Traces. Eleven papers compared. Three algorithms are open sourced, which are used in the above project.

    6. Constructing street networks from GPS trajectories. In Proc. European Symp. on Algorithms/ slide/ note

    7. Map inference in the face of noise and disparity/ slide/ note

    8. On vehicle tracking data-based road network generation/ note

  4. Map Matching

    1. A critical review of real-time map-matching algorithms: Current issues and future directions
    2. Current map-matching algorithms for transport applications: State-of-the art and future research directions
    3. High accuracy tightly-coupled integrity monitoring algorithm for map-matching

Tools

  1. A tool for matching crowd- sourced and authoritative geospatial data
  2. Map Custruction Project

gps2roadnetwork's People

Contributors

haidaoxiaofei avatar hsmyy avatar

Stargazers

 avatar srforever avatar vugia truong avatar Electra Green avatar  avatar  avatar Denis Laprise avatar  avatar  avatar  avatar  avatar Nanfei Ye avatar Ruslan avatar

Watchers

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gps2roadnetwork's Issues

Road Closure Detection

  1. Turning patterns of end nodes change dramatically in a time window
  2. Destination-aware detection: why not query
  3. Detecting anomalies on low-frequency roads is rather challenging

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