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Subway Active Safety

Urban rail transit lines are prone to safety hazards such as foreign object intrusions. While fully automated lines employ contact-based obstacle detection, they fall short in long-distance preemptive warning capabilities. Semi-automated lines rely on driver vigilance, which can lead to collisions due to human error. Hence, the emergence of train autonomous obstacle detection systems, utilizing LiDAR's high-precision scanning capabilities, becomes imperative. These systems enable real-time detection of obstacles within tunnels, preventing collisions with subway trains. Integrated with the train's automatic driving system, subway trains can autonomously make safety decisions based on obstacle information obtained from LiDAR scans, promptly taking evasive actions.

Benewake's high-performance 3D LiDAR endows trains with the "eye of intelligence," possessing point cloud characteristics conducive to algorithms. It enables precise detection of obstacles within the vehicle's clearance limits, mitigating accidents and ensuring safety for both personnel and train operations.

Core Advantages



Ultra-High Hine Count

256 lines, equipped with track detection capabilities exceeding 60 meters

Ultra-high Resolution

0.1°x0.1°, with more than 4 points detected for a 30*30cm cardboard box at a distance of 70 meters



All-Weather Operational Capability

Working 24/7, equipped with dirt detection functionality, unafraid of day, night, or adverse environmental conditions

Customizable ROI

Allows for precise monitoring of specific areas, accurately detecting trackside elements such as equipment boxes and cable racks

Active Safety

The train's active safety system, based on Benewake's high-performance three-dimensional LiDAR, enables real-time scanning of the track area ahead of the vehicle. It generates high-precision three-dimensional point clouds and employs intelligent algorithms to detect obstacles such as sandbags, track inspection trolleys, pedestrians, and vehicle profiles. With its image-level ultra-high resolution, it can detect pedestrians up to 200m away and vehicle profiles up to 300m away. Therefore, it finds wide application in various scenarios including subway trains, subway maintenance vehicles, tunnel maintenance vehicles, and railway locomotives, providing robust support for the safe operation of trains.


Point Cloud Effect

Success Cases


The XuZhou Metro Line 6 Project                                  Beijing Subway Winter Olympics Line Project

Product Recommendation


Headquarters:3rd Floor, Haiguo Jiaye Sci-Tech Park, Haidian District, Beijing, China
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