Experimental Validation of LiDAR Sensors Used in Vehicular Applications by Using a Mobile Platform for Distance and...

Area of Science:

• Automotive Engineering
• Sensor Technology
• Robotics

Background:

• LiDAR (Light Detection and Ranging) sensors are vital for automotive safety systems, especially in low-light conditions.
• Accurate dynamic response testing of long-range LiDAR is essential for vehicles with long braking distances, like trams, facing varied operational challenges.
• Existing testing methods may not adequately address real-world complexities such as adverse weather or spurious targets.

Purpose of the Study:

• To develop an indoor experimental model for testing LiDAR sensors in vehicular applications.
• To validate the measurement of distances and speeds relative to static and dynamic obstacles using a scaled vehicle model.
• To confirm the reliability of LiDAR measurements under varying operational conditions.

Main Methods:

• Development of a scaled vehicle model equipped with a LiDAR sensor for indoor testing.
• Implementation of variable speed capabilities within the experimental setup.
• Repeated testing to validate software functions for distance and speed measurement.

Main Results:

• Successful validation of the methodology for measuring frontal distance and relative speed using the scaled LiDAR model.
• Demonstrated independence of LiDAR measurements from obstacle color.
• Confirmed reliability of LiDAR measurements irrespective of ambient light conditions.

Conclusions:

• The developed experimental model effectively validates LiDAR sensor performance for automotive applications.
• The validated measurement methodology is robust and applicable to full-scale vehicle systems.
• LiDAR technology shows promise for enhancing vehicle safety systems, particularly for trams and other large vehicles.