An Overview of Autonomous Vehicles Sensors and Their Vulnerability to Weather Conditions

Area of Science:

• Autonomous Systems
• Sensor Technology
• Environmental Impact on Perception

Background:

• Autonomous vehicles (AVs) depend on sensor systems for environmental perception and decision-making.
• Real-world conditions, particularly adverse weather, pose significant challenges to AV sensor performance.
• Existing AV perception systems may not accurately account for environmental degradation.

Purpose of the Study:

• To analyze the impact of diverse weather conditions on common AV sensor technologies.
• To quantify performance degradation across RADAR, LiDAR, ultrasonic, camera, and GNSS sensors.
• To enhance the realism of AV simulations and sensor fusion models.

Main Methods:

• Review of physical fundamentals, electromagnetic spectrum, and operational principles of key AV sensors.
• Quantification of weather effects (precipitation, fog, lightning) on sensor performance.
• Analysis of sensor responses for improved object identification and X-in-the-loop (XIL) testing.

Main Results:

• Detailed understanding of how specific weather phenomena affect individual sensor types.
• Methodology for simulating realistic sensor degradation in adverse weather.
• Identification of appropriate attenuation models for XIL experiments.

Conclusions:

• Quantifying weather effects on AV sensors is crucial for developing robust perception systems.
• Improved simulations and sensor fusion based on this quantification will enhance AV safety and reliability.
• This research aids in validating AV perception under realistic, challenging environmental conditions.