Autonomous Vehicle Position Control for Occluded Landmark Detection
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Solution Overview
Problem
In autonomous vehicle navigation, large obstacles such as large vehicles in front can obstruct the camera's field of view, leading to decreased accuracy in landmark detection and subsequent vehicle positioning.
Innovation Solution
A vehicle control system that includes a processor to acquire and analyze peripheral object data, calculate landmark positions, and adjust the vehicle's relative position to the obstacle to facilitate easier landmark detection by the monitoring sensor, thereby improving landmark detection frequency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the vehicle maintains a fixed position relative to the obstacle, then the obstacle monitoring is simplified, but the landmark detection accuracy decreases due to obstruction
Solution Approach 1:
The vehicle's position is dynamically adjusted based on real-time detection of obstacles and landmarks. The processor continuously monitors the detection frequency of landmarks and modifies the vehicle's relative position to the obstacle accordingly, transforming a static positioning problem into a dynamic optimization process that maximizes landmark visibility while maintaining simplified obstacle monitoring
2Measurement precision
If the vehicle changes position frequently to optimize landmark detection, then the detection accuracy improves, but the system complexity and processing load increase
Solution Approach 1:
The system implements a feedback mechanism where the processor monitors landmark detection frequency and uses this information to determine whether position adjustment is necessary. This feedback-based approach allows the vehicle to maintain optimal positioning without excessive adjustments, balancing detection accuracy with processing efficiency by only acting when detection metrics indicate a need for change
Data Source
AI summary
A system for autonomously driving a vehicle along a road segment includes at least one processor. The processor is configured to: acquire at least one piece of peripheral object data indicating information about an object disposed around the vehicle from a peripheral monitoring sensor; analyze the peripheral object data to calculate a position of the landmark with respect to the road on which the vehicle travels; determine position coordinates of the vehicle based on the position of the landmark calculated from the peripheral object data and the map data; and change a relative position of the vehicle with respect to an obstacle so as to easily detect the landmark by the peripheral monitoring sensor when the obstacle is disposed within a detection range of the peripheral monitoring sensor.