Autonomy System Lane Indexing for Vehicle Detection
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Solution Overview
Problem
Automated vehicles face challenges in accurately detecting vehicles and lanes on roadways, which is crucial for safe navigation and interaction with other road users.
Innovation Solution
The system employs an autonomy system that uses image inputs from cameras or sensors to identify vehicles and lanes by assigning index values and generating data segments, allowing for the detection of vehicles within lanes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated vehicles collect large amounts of data regarding the surrounding environment to improve safety and navigation accuracy, then the reliability of automated vehicle operation is improved, but the complexity of data processing and system architecture increases
Solution Approach 1:
The patent segments the image data into multiple data segments, where each segment corresponds to a specific region of interest (e.g., lanes, vehicles, pedestrians). This segmentation allows the system to process and analyze specific elements independently, improving detection accuracy without overwhelming the processing system with raw image data as a whole.
Solution Approach 2:
The patent introduces an intermediary processing layer that generates data segments from image data. These segments act as intermediaries between the raw sensor input and the higher-level autonomous driving decisions, enabling more efficient and targeted analysis of environmental elements.
2Measurement precision
If the autonomy system segments image data into multiple data segments to improve detection accuracy, then the measurement precision of object location is improved, but the processing time and computational complexity increase
Solution Approach 1:
By dividing the image into targeted data segments based on detected features (lane lines, vehicle boundaries), the system focuses computational resources only on relevant regions rather than processing the entire image uniformly, thereby improving precision without proportionally increasing processing time.
Solution Approach 2:
The system performs preliminary detection of key features (such as lane lines and vehicle contours) before generating detailed data segments. This preliminary action allows the system to pre-identify regions of interest, reducing the scope of subsequent detailed analysis and minimizing overall processing time.
3Reliability
If the system assigns index values to lanes and vehicles to improve location tracking, then the reliability of position identification is improved, but the complexity of data management increases
Solution Approach 1:
The patent creates simplified index representations (data segments) that copy only the essential location and identification information from the complex image data. These index copies enable efficient tracking and reference of objects without managing the full complexity of the original sensor data.
Data Source
AI summary
Embodiments herein include an automated vehicle performing for identifying vehicles and lanes in roadway by an autonomy system of an automated vehicle. The autonomy system gathers image inputs from cameras or other sensors. The autonomy system assigns index values to the driving lanes and shoulder lanes, and then assigns the index values to the vehicles. The autonomy system generates data segments from the image data, corresponding to creating segments of an image, such that a single image is segmented for portions of the image, such as segmented outputs of each lane line or segmented outputs of portions of the vehicle. The autonomy system compares the segmented portions of the image to detect that a lane contains a vehicle.