Lane Change Control Using Camera-Map Partition Line Priority
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Solution Overview
Problem
In automated driving technologies, road partition lines may not be accurately recognized, leading to inconsistent vehicle control due to variations in camera recognition, map information accuracy, and update timing, which affects the safety and convenience of transportation systems.
Innovation Solution
A vehicle control device and method that employs two recognizers to identify partition lines from camera and map data, with a driving controller prioritizing steering and speed control based on the accuracy of these recognitions, especially during lane changes, by comparing the distance and angle between recognized partition lines to ensure appropriate driving control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If automated driving control is executed based on camera recognition of partition lines, then the system can adapt to real-time road conditions, but recognition accuracy deteriorates due to variations in camera detection and environmental factors
Solution Approach 1:
The patent combines camera-based partition line recognition with map information-based partition line recognition to create a fused recognition result. This merging of multiple recognition sources compensates for the weaknesses of individual methods, maintaining both adaptability to real-time conditions and recognition accuracy.
Solution Approach 2:
The system performs match determination between camera-based and map-based partition lines, using the comparison feedback to identify and correct recognition errors. When discrepancies are detected, the system can adjust or re-evaluate the recognition results to improve accuracy while maintaining real-time adaptability.
2Measurement precision
If automated driving control is executed based on map information of partition lines, then the system maintains stable and accurate lane guidance, but cannot respond to real-time changes in road conditions or actual lane positions
Solution Approach 1:
The patent merges map information-based partition line recognition with camera-based recognition. The map information provides stable and accurate baseline guidance, while the camera input adds real-time adaptability, creating a comprehensive control system that benefits from both sources.
Solution Approach 2:
The system pre-acquires map information about partition lines before automated driving control is executed. This preliminary action ensures that accurate baseline lane guidance is available, which can then be adjusted in real-time based on camera recognition and actual road conditions.
3Adaptability or versatility
If the system prioritizes camera-based partition line recognition, then real-time adaptability is improved, but reliability deteriorates when recognition accuracy is insufficient
Solution Approach 1:
The system uses match determination as a feedback mechanism to verify camera-based recognition against map information. When the camera recognition does not match the expected map-based partition lines, the system can identify potential errors and adjust control reliability accordingly, preventing unreliable camera data from causing unsafe control actions.
Solution Approach 2:
The system performs preliminary match determination between camera-based and map-based partition lines before executing automated driving control. This preliminary verification ensures that only reliable recognition results are used for control, maintaining reliability while still allowing real-time adaptability when recognition is accurate.
4Reliability
If the system prioritizes map information-based partition line recognition, then control stability is improved, but adaptability to actual road conditions deteriorates
Solution Approach 1:
The patent combines map information-based recognition with camera-based recognition to create a fused result. The map information provides stable control foundation, while the camera input introduces real-time adaptability, ensuring that the system responds to actual road conditions without losing control stability.
Solution Approach 2:
The system dynamically adjusts the weight or influence of map information versus camera recognition based on match determination results. When camera recognition matches map information, the system can adapt more dynamically to real-time conditions; when there are discrepancies, the system relies more on the stable map information, creating a dynamic balance between stability and adaptability.
Data Source
AI summary
A vehicle control device according to an embodiment includes a first recognizer that recognizes a first partition line partitioning a traveling lane, a second recognizer that recognizes a second partition line partitioning a lane around from map information, and a driving controller that executes driving control, and the driving controller executes driving control giving priority to the first partition line over the second partition line in a case in which the first partition line does not match the second partition line when a host vehicle travels in a lane change section and a case in which one of the two first partition lines is present in the lane partitioned, a distance between the two second partition lines and the first partition line present in the lane is equal to or greater than a predetermined distance, and another partition line is recognized in an extension direction of the second partition line.