LiDAR Parking Control for Slope-Aware Collision Filtering
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Solution Overview
Problem
LiDAR-based parking control systems face errors in determining collision likelihood due to incomplete information about objects on slopes, leading to potential braking errors.
Innovation Solution
A processor-based system that generates cell-by-cell position and slope information, performs clustering, and determines object positions relative to virtual slope boundaries, comparing bumper and object angles to delete irrelevant data, ensuring accurate collision detection and preventing braking errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LiDAR sensor is used to detect objects and slopes for parking control, then the ability to detect smaller objects and distances is improved, but the accuracy of slope identification and collision likelihood determination deteriorates due to incomplete information
Solution Approach 1:
The space around the vehicle is divided into multiple cells, and slope information is generated for each cell independently. This segmentation allows the system to process slope data in discrete units, improving the reliability of slope identification by analyzing each cell's characteristics separately rather than treating the entire environment as a single unit.
Solution Approach 2:
The system introduces a new dimension of analysis by generating slope information as a separate parameter alongside position coordinates. By adding slope angle data for each object and cell, the system enhances slope identification reliability without compromising the existing object detection precision in the three-dimensional space.
2Reliability
If the system processes information for all detected objects to ensure safety, then the reliability of collision detection is improved, but the complexity of the processing system increases
Solution Approach 1:
The system extracts only the necessary information for collision assessment by generating slope information specifically for each detected object and cell. Instead of processing all available sensor data, the system selectively extracts position coordinates and slope angles, reducing processing complexity while maintaining reliable collision detection through targeted data analysis.
Solution Approach 2:
The system applies different processing approaches based on local conditions by evaluating slope information and position data for each individual object and cell. By tailoring the analysis to local characteristics rather than applying a uniform processing method to all objects, the system reduces overall complexity while maintaining high reliability in collision detection for each specific scenario.
3Measurement precision
If the system uses detailed cell-by-cell position information and slope information for each object, then the accuracy of parking control is improved, but the quantity of data to be processed increases
Solution Approach 1:
The system performs preliminary processing by generating cell-by-cell position information and slope information for each object before the main collision assessment process. By preparing this structured data in advance, the system enables accurate parking control through efficient querying and comparison during the actual decision-making process, reducing the computational burden of detailed analysis.
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
Enhances the accuracy of autonomous parking by reducing false collision detections and braking errors by processing LiDAR data to identify objects on slopes effectively.
Implementation Method 1
LiDAR uses laser pulses whose wavelength ranges from 0.25 to 1 μm which is shorter than the wavelength range of radar. Accordingly, LiDAR is able to detect smaller objects than radar.
Data Source
AI summary
An apparatus for controlling a vehicle is introduced. The apparatus may comprise a processor, and memory storing instructions, when executed by the processor, may cause the apparatus to: receive information associated with a plurality of objects on a ground, generate cell-by-cell position information and slope information for each of the plurality of objects, generate, based on performing a clustering process on each piece of the cell-by-cell position information and slope information, clustering information, generate slope angle information and boundary information, determine whether one of the plurality of objects is behind a boundary, compare a bumper angle of the vehicle and an object angle of the one of the plurality of objects, determine whether the vehicle is likely to collide with the one of the plurality of objects, and delete a piece of the cell-by-cell position information and slope information associated with the one of the plurality of objects.