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Cooperative Localization Improvement Using Distance Information in Vehicular Ad Hoc Networks.

Felipe Lobo1, Danilo Grael2, Horacio Oliveira3

  • 1Computer Science Department, Federal University of Roraima, Boa Vista 69310-000, Brazil.

Sensors (Basel, Switzerland)
|December 5, 2019
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Summary
This summary is machine-generated.

This study introduces CoVaLID, a new method for vehicular ad hoc networks (VANets) that improves Global Positioning System (GPS) accuracy using cooperative distance information. CoVaLID significantly reduces localization errors for enhanced vehicle safety applications.

Keywords:
data fusiondistance informationlocalization systemsvehicular ad hoc networks

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Area of Science:

  • Vehicular Ad Hoc Networks (VANets)
  • Localization Systems
  • Sensor Fusion

Background:

  • Precise localization is critical for vehicular safety applications.
  • Global Positioning System (GPS) errors are significant in urban canyons and indoor environments.
  • Existing methods struggle with GPS inaccuracies in challenging VANet scenarios.

Purpose of the Study:

  • To develop a novel cooperative localization method (CoVaLID) to enhance GPS accuracy in VANets.
  • To fuse GPS data with inter-vehicle distance information for improved position estimation.
  • To assess the impact of vehicle density, trajectory, and distance error on localization accuracy.

Main Methods:

  • Implemented an extended Kalman filter for data fusion of GPS and distance information.
  • Utilized a weighted average method, prioritizing closer neighbors' distance data.
  • Evaluated the CoVaLID method using real-world vehicular data.

Main Results:

  • CoVaLID demonstrated a significant reduction in GPS error.
  • Achieved a 63% error reduction compared to the VLOCI algorithm.
  • Showcased a 53% error reduction compared to the state-of-the-art VANet location improve (VLOCI) algorithm.

Conclusions:

  • CoVaLID effectively improves GPS accuracy in VANets through cooperative localization.
  • The method's performance is influenced by the number of vehicles, trajectory, and distance sensor quality.
  • CoVaLID offers a robust solution for critical safety applications requiring precise vehicle positioning.