INARI project

Project Objectives

• Explore the effectiveness of different modalities for multi-sensor data fusion
• Utilize unconventional polarization imaging for detecting pavement conditions

Key Features

• Multi-Sensor Data Fusion
  • Focuses on combining data from various sensors to improve detection
  • accuracy
  • Considers only high response modalities based on weather conditions,
  • enhancing fusion efficiency
  • Automates the selection of modalities for merging based on external data
  • acquisition conditions
• Uncertainty and Reliability
  • Estimates sensor uncertainty and reliability in degraded weather
  • conditions
  • Ensures robust data fusion by dynamically adapting to weather changes.

Technological Impact

• Enhances road safety by providing accurate pavement condition data
• Improves vehicle control systems, leading to safer and more reliable
• navigation.