Train Obstacle Detection Using Gap-Compensated LIDAR Scanning
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Solution Overview
Problem
Existing obstacle detection systems fail to accurately detect obstacles on or near a trajectory due to gaps in laser beam detection, leading to potential non-detection and unstable tracking of objects, especially in railway vehicles with longer braking distances.
Innovation Solution
An obstacle detection system that complements gaps in sensor detection regions by using a monitoring area setting processing unit and a front obstacle monitoring unit to enhance detection accuracy, utilizing sensors that horizontally scan the front of a train.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If a LIDAR with angular resolution of 0.125 deg and laser beam spot diameter of 0.08 deg is used to detect obstacles at 200 m distance, then the detection distance is sufficient for railway braking requirements, but gaps of about 60 cm occur between laser beams causing missed detections
Solution Approach 1:
The system dynamically changes the scanning pattern based on detected objects. When an object is detected within a laser beam, the scanning density is increased in that region by performing additional scans at different angles, transforming the static uniform scanning into a dynamic adaptive scanning process that concentrates measurement resources where needed
Solution Approach 2:
The detection space is segmented into regions based on detection results. The monitoring area is divided into a first monitoring area (where objects are detected) and a second monitoring area (gaps between laser beams). Different scanning densities are applied to different segments, with higher density in the first area and lower density in the second area, optimizing both detection accuracy and resource usage
2Measurement precision
If the monitoring area is divided into two regions with different scanning densities, then detection accuracy in critical areas is improved, but the device complexity increases
Solution Approach 1:
The scanning control is made dynamic and adaptive rather than static. The system starts with uniform scanning and automatically adjusts scanning density based on real-time detection results. When objects are detected, the system dynamically increases scanning frequency in those regions, eliminating the need for pre-configured complex scanning patterns
Solution Approach 2:
The system performs self-adjustment based on its own detection results. The detection unit identifies objects within laser beams, and this information automatically triggers increased scanning density in the first monitoring area. The system serves itself by using its detection output to control its scanning input, reducing the need for external complex control mechanisms
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enables high-accuracy detection of obstacles on and around a trajectory, preventing collisions by accurately identifying and tracking obstacles.
Implementation Method 1
a LIDAR that further irradiates the inside of the short distance
Implementation Method 2
a LIDAR having an angular resolution of 0.125 deg and a laser beam spot diameter of 0.08 deg
Data Source
AI summary
An object of the present invention is to provide an obstacle detection system and an obstacle detection method for a trajectory traveling vehicle, which are capable of detecting a front obstacle on a trajectory and around the trajectory with high accuracy. The system includes: a monitoring area setting processing unit that sets an obstacle monitoring area for detecting an obstacle; a front obstacle monitoring unit that monitors an obstacle in the obstacle monitoring area using a sensor that horizontally scans the front of the train; and an obstacle detection unit that detects an obstacle in the obstacle monitoring area based on a monitoring result by the front obstacle monitoring unit, in which the front obstacle monitoring unit complements a gap in a detection region of the sensor at a first position with a detection region of the sensor while the train moves from the first position to a second position.