LiDAR Road Edge Matching for Precise Vehicle Positioning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle control systems struggle to accurately identify road edge portions, especially on curved roads, which is crucial for generating precise vehicle paths and maintaining stable driving systems.
Innovation Solution
A vehicle control device and method that utilize LiDAR sensor data and map information to accurately identify road edge portions by filtering datasets, dividing line segments, and identifying closest partial line segments in a vehicle coordinate system, thereby enabling precise vehicle positioning and control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LiDAR and map information are used to identify road edge portions, then positioning precision is improved, but device complexity increases due to multiple sensors and data processing requirements
Solution Approach 1:
The patent combines LiDAR sensor data with pre-stored map information to identify road edge portions. The processor integrates real-time LiDAR point cloud data with offline map datasets, merging multiple information sources to achieve accurate positioning without requiring complex individual sensor systems
Solution Approach 2:
Map information including road edge portions is pre-stored in the memory before vehicle operation. This preliminary preparation allows the system to quickly compare real-time LiDAR data with known map data, reducing real-time processing complexity while maintaining high positioning precision
2Manufacturing precision
If line segments are divided into multiple partial line segments, then manufacturing precision of path identification is improved, but device complexity increases due to increased data processing
Solution Approach 1:
The patent divides line segments representing road edges into multiple smaller partial line segments. This segmentation allows for more precise matching between LiDAR data and map information, improving path identification accuracy by enabling finer-grained comparison and alignment of road geometry
3Measurement precision
If multiple datasets are processed to identify road edge portions, then measurement precision is improved, but loss of time increases due to extensive data processing
Solution Approach 1:
The patent processes multiple datasets but applies filtering criteria to focus on relevant portions. By identifying and processing only the necessary partial line segments that match LiDAR observations, the system achieves accurate road edge identification without unnecessarily processing all available data, reducing time loss
4Measurement precision
If coordinate system transformation is performed for vehicle positioning, then positioning precision is improved, but device complexity increases due to calibration requirements
Solution Approach 1:
The calibration amount for coordinate system transformation is pre-determined and stored. This preliminary calibration of the relationship between vehicle coordinate system and map coordinate system eliminates the need for complex real-time calibration operations, maintaining positioning precision while reducing operational complexity
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 solution enables accurate and rapid identification of road edge portions, improving positioning performance and ensuring stable vehicle control in both driver assistance and autonomous driving modes.
Implementation Method 1
External objects may be identified using a Light Detection and Ranging (LiDAR) while the vehicle is driving
Data Source
AI summary
A vehicle control device includes a Light Detection and Ranging (LiDAR), a memory that stores map information, and a processor. The processor may filter datasets including a road edge portion associated with a position of a vehicle from the map information according to a first specified condition, obtain a plurality of first partial line segments, identify a plurality of second partial line segments from a plurality of line segments formed by contour points corresponding to the road edge portion through the LiDAR, identify pairs of the plurality of second partial line segments and the plurality of first partial line segments, output a position of the vehicle in a second coordinate system different from a first coordinate system based on applying a specified algorithm to each of the pairs, and control the vehicle based on the position of the vehicle in the second coordinate system.