Autonomous Lane Change Yaw Control Using Camera and Map Lane Width
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Solution Overview
Problem
False recognition of lane markings by a camera during autonomous driving can lead to inappropriate vehicle behavior during lane changes, complicating control and potentially causing unintended vehicle actions.
Innovation Solution
A vehicle control method that utilizes both camera-based and map-based lane width information to control the yaw angle of the vehicle before, during, and after a lane change, ensuring accurate lane positioning and trajectory management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If lane marking information from camera is used for autonomous lane change control, then real-time lane positioning capability is improved, but false recognition of lane markings causes unreliable control
Solution Approach 1:
The patent combines camera-based lane marking recognition with map information (including lane width and curvature data) to perform lane change control. By merging these two information sources, the system achieves both real-time positioning capability and reliability against false recognition, as map information serves as a verification reference when camera recognition is uncertain
Solution Approach 2:
Map information acts as an intermediary element that mediates between camera input and vehicle control output. The control device references map data (lane width, curvature) to verify or correct camera-based lane marking recognition, thereby reducing the direct impact of false recognition on control decisions
2Adaptability or versatility
If camera-based lane width information is used for yaw angle control, then adaptive lane positioning is improved, but false recognition leads to inappropriate vehicle behavior
Solution Approach 1:
The system implements feedback by continuously comparing camera-based lane width measurements with map information during lane change execution. When discrepancies are detected (indicating potential false recognition), the system uses map information as feedback to correct the control input, preventing inappropriate vehicle behavior while maintaining adaptability to actual lane conditions
3Speed
If autonomous lane change control relies on camera recognition, then real-time response capability is improved, but system vulnerability to recognition errors increases
Solution Approach 1:
The system performs preliminary verification by comparing real-time camera recognition results with pre-stored map information before executing lane change control. This preliminary action (verification step) maintains fast response capability while reducing vulnerability to recognition errors, as the map data provides advance reference information for validation
Data Source
AI summary
A controller executes processing including: before a lane change of an own vehicle to an adjacent lane by autonomous driving is started, acquiring lane marking information in front of the own vehicle and first lane width information from a camera and controlling a yaw angle of the own vehicle, based on the lane marking information and the first lane width information so the own vehicle travels within an own vehicle lane; when the lane change is started, acquiring second lane width information from map information and controlling the yaw angle, based on the second lane width information in such a way that the own vehicle performs the lane change; and after the lane change is completed, controlling the yaw angle, based on the lane marking information and the first lane width information in such a way that the own vehicle travels within an own vehicle lane after lane change.