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Integrity Monitoring of Multimodal Perception System for Vehicle Localization.

Arjun Balakrishnan1, Sergio Rodriguez Florez1, Roger Reynaud1

  • 1CNRS, ENS Paris-Saclay, Université Paris-Saclay, 91190 Gif-sur-Yvette, France.

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This study introduces a new integrity monitoring framework for autonomous vehicles. It assesses sensor data quality in various environments, ensuring reliable localization and navigation for safer self-driving.

Keywords:
Protection Level markersintegrity assessmentintelligent vehicleslocalizationmultimodal data source

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Area of Science:

  • Autonomous Driving Systems
  • Sensor Data Fusion
  • Robotics Perception

Background:

  • Autonomous driving systems depend critically on high-quality sensor data for localization and navigation.
  • Existing systems face challenges in assessing data integrity across diverse driving scenarios (highway, urban).

Purpose of the Study:

  • To develop and evaluate a novel integrity monitoring framework for multimodal exteroceptive sensor data.
  • To ensure the reliability and safety of autonomous vehicle localization and navigation systems.

Main Methods:

  • A multisource coherence-based integrity assessment framework was developed.
  • A semantic-grid data representation was employed for efficient environmental representation and scalability.
  • The framework was tested on complex, real-world scenarios from public datasets.

Main Results:

  • The framework successfully assesses the integrity of multimodal sensor data in various scenarios.
  • Integrity markers were generated to identify and quantify unreliable data.
  • Protection Level markers (Horizontal, Lateral, Longitudinal) were provided for perception systems.

Conclusions:

  • The proposed integrity assessment framework is crucial for context-based localization in autonomous vehicles.
  • The method adapts aviation integrity concepts for ground vehicle applications, enhancing perception system reliability.
  • The framework demonstrates proof-of-concept for ensuring reliable autonomous navigation in complex environments.