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Experimental Study Regarding Long Range LiDAR Capabilities in Sensing Safety Distance for Vehicle Application
Gabriel Popa1, Marius-Alin Gheți1, Emil Tudor2
1Rolling Stock Department from Faculty of Transport, University "Politehnica" of Bucharest, 060042 Bucharest, Romania.
Sensors (Basel, Switzerland)
|August 12, 2022
Summary
This study evaluated LiDAR sensors for tram collision avoidance. Findings show LiDAR is sensitive to fake targets and blind spots, requiring integration with other sensors for reliable safety distance sensing.
Area of Science:
- Automotive Engineering
- Robotics and Automation
- Sensor Technology
Background:
- Vehicle safety is a key goal in driving automation.
- Rail vehicles like trams require longer safety distances due to wheel-rail adherence limits.
- Fixed frontal sensing faces challenges including fake targets, blind spots, and variable lighting.
Purpose of the Study:
- To evaluate the effectiveness of LiDAR sensors for collision-avoidance systems in rail applications.
- To assess LiDAR performance in sensing safety distances for trams under various conditions.
Main Methods:
- Experimental study using a scaled tram model with a narrow field-of-view LiDAR sensor.
- Distance measurements conducted under varied illumination, target size, reflectivity, and track configurations.
Main Results:
- LiDAR sensors demonstrated sensitivity to fake targets and blind spots.
- Optical interferences and reflectivity variations impacted sensor performance.
- Effectiveness in sensing safety distance was evaluated under diverse conditions.
Conclusions:
- LiDAR sensors alone are insufficient for comprehensive tram anti-colliding systems.
- Integration with additional sensors is necessary for reliable safety tasks.
- Identified sensor limitations can guide the development of dedicated tram collision prevention systems and high-risk zone identification.
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