Multi-Camera Vehicle Posture Estimation for Cornering Stability
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Solution Overview
Problem
Existing vehicle control systems struggle to accurately identify and maintain the posture of a vehicle, especially in driving assistance and autonomous driving modes, particularly when navigating corners.
Innovation Solution
A vehicle control apparatus and method utilizing multiple cameras to identify the vehicle posture by matching images with templates, calculating pitch angular velocities, and determining the vehicle posture based on the differences between these velocities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single camera is used to identify vehicle posture, then the device complexity is reduced, but the measurement precision of vehicle posture deteriorates
Solution Approach 1:
The patent divides the vehicle into multiple regions of interest (front, rear, left, right) and assigns different cameras to capture specific regions. The processor then integrates information from these segmented views to determine overall vehicle posture, achieving high measurement precision while managing device complexity through functional division
Solution Approach 2:
The patent combines data from multiple cameras (front camera, rear camera, left camera, right camera) to comprehensively identify vehicle posture. By merging information from different viewing angles and positions, the system achieves accurate three-dimensional posture determination that would be impossible with a single camera
2Measurement precision
If multiple sensors (camera, gyro sensor, acceleration sensor) are used to identify vehicle posture, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent makes the camera system perform multiple functions: capturing images for posture identification, detecting vanishing points for orientation analysis, and providing visual data for navigation decisions. This multi-functionality reduces the need for separate dedicated sensors, thereby improving measurement precision without proportionally increasing device complexity
Solution Approach 2:
The processor acts as an intermediary that integrates and fuses data from multiple sensors (camera, gyro sensor, acceleration sensor). It combines the visual information from cameras with motion data from gyro and acceleration sensors to produce a unified and accurate vehicle posture determination, managing the complexity of multiple sensors through centralized processing
3Measurement precision
If the vehicle operates in autonomous driving mode with complex sensor integration, then the vehicle posture identification accuracy improves, but the ease of operation decreases
Solution Approach 1:
The system automatically performs posture identification, vanishing point detection, and navigation decisions without requiring manual intervention. The processor continuously monitors sensor data, self-corrects posture estimates, and autonomously adjusts navigation, making the complex operation transparent to the user and maintaining ease of operation despite high measurement precision
Data Source
AI summary
A vehicle control apparatus may include cameras, a memory, and a processor. The processor may identify matching between a first image obtained by a first camera, from among images and templates based on obtaining the images through the cameras, may obtain a first pitch angular velocity of the first camera based on matching the first image and at least one of the templates, may obtain a second pitch angular velocity of a second camera based on at least one of a line included in a second image obtained by the second camera, from among the images, or a vanishing point of the second image, or any combination thereof, and may identify a posture of a vehicle by using one of the first pitch angular velocity or the second pitch angular velocity based on a difference between the first pitch angular velocity and the second pitch angular velocity.