Vehicle Lane Path Control Using Map-Lane Deviation Checks
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Solution Overview
Problem
Existing vehicle control systems inaccurately select a smaller road width based on potentially incorrect information, leading to inappropriate vehicle travel control when lane markings cannot be detected.
Innovation Solution
A vehicle control system that recognizes road lane markings using both detection devices and map information, determines deviations, and adjusts the travel path center based on the smaller of the detected widths to ensure accurate vehicle control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a smaller road width is always selected regardless of information correctness, then the system can handle cases where lane markings cannot be detected, but inappropriate vehicle travel control may be performed when the selected information is incorrect
Solution Approach 1:
The system compares detection device information with map information and uses deviation detection to feedback on information quality. When deviations exceed thresholds, the system adjusts its selection strategy, creating a closed-loop verification mechanism that improves reliability without requiring complete system redesign
Solution Approach 2:
The system performs partial verification by checking only critical deviations (lateral distance and angle) rather than complete information validation. This selective approach provides sufficient reliability for safety-critical decisions while avoiding the complexity of exhaustive verification of all road width parameters
2Measurement precision
If both detection device and map information are used and compared, then the correctness of information can be verified, but the system complexity increases
Solution Approach 1:
The verification process is segmented into distinct components: lateral distance deviation check, angle deviation check, and width-based selection. Each segment handles a specific aspect of information validation, making the overall complex process manageable and maintainable while achieving high measurement precision
Solution Approach 2:
The system applies different verification strictness to different information aspects. Critical parameters like lateral distance and angle deviations use threshold-based rejection, while width selection uses comparative analysis. This localized quality approach optimizes measurement precision without uniformly increasing complexity across all processing stages
Data Source
AI summary
A device recognizes road lane markings and outputs first left road lane markings and first right road lane markings, recognizes the road lane markings based on map information and outputs second left road lane markings and second right road lane markings, determines deviations between first left road lane markings and second left road lane markings and deviations between first right road lane markings and second right road lane markings, determines that deviations are present only in one of the first left road lane markings and the second left road lane markings and the first right road lane markings and the second right road lane markings, sets a position at which a predetermined width is offset as a center of a travel path on which the vehicle is to travel in the future, and generates the travel path based on the center of the travel path.