Top-View Sensor Fusion Layout for Vehicle Footprint-Aware Grids
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle sensor data analysis techniques, such as sensor fusion, inefficiently utilize computational resources due to the vehicle's footprint occupying significant grid space in top view representations, reducing detection and processing efficiency.
Innovation Solution
Adjusting top view representations using amplitude modulation to match the vehicle's shape and sensor coverage, employing polar coordinates and flexible cell definitions to optimize grid utilization and reduce computational overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional sensor fusion with uniform grid top view representation is used, then comprehensive environmental coverage is achieved, but computational resources are inefficiently utilized due to vehicle footprint occupying significant grid space
Solution Approach 1:
The top view representation is segmented into multiple non-uniform grid cells of varying sizes. Grid cells are smaller near the vehicle where detailed detection is needed and larger in distant regions where less detail is required. This segmentation reduces the total number of grid cells while maintaining detection accuracy in critical areas, thereby improving computational efficiency.
Solution Approach 2:
Different regions of the top view representation are assigned different grid cell sizes based on their importance and distance from the vehicle. Areas closer to the vehicle use smaller grid cells for higher precision detection, while distant areas use larger grid cells to reduce computational load. This local quality approach optimizes the balance between detection accuracy and computational resources.
2Measurement precision
If uniform grid top view representation is used, then simple processing is achieved, but detection accuracy is reduced due to unnecessary processing of areas outside sensor coverage
Solution Approach 1:
The patent extracts and processes only the relevant portions of the environment that fall within sensor coverage areas. By using non-uniform grid cells that are concentrated in regions of interest and smaller in size where detection precision is critical, the system eliminates unnecessary processing of areas outside sensor coverage, reducing power consumption while improving detection accuracy.
Solution Approach 2:
Instead of uniformly processing the entire top view representation, the system applies partial processing by focusing computational resources on specific regions with smaller, denser grid cells where detection accuracy is most important, while using larger, sparser grid cells in less critical areas. This selective processing reduces overall power consumption while maintaining high detection accuracy where needed.
Data Source
AI summary
This disclosure provides systems, methods, and devices for vehicle driving assistance systems that support image processing. In a first aspect, a method is provided that includes a receiving sensor data from one or more sensors. The sensor data may be determined for an area surrounding a vehicle, and features may be determined based on the sensor data and projected into a top view representation of the area surrounding the vehicle. The top view representation may be defined by an inner contour and an outer contour. The inner contour may be determined based on an exterior contour of the vehicle, sensing capabilities of one or more sensors, or a combination thereof. Vehicle instructions may then be determined based on the features within the top view representation. Other aspects and features are also claimed and described.