Autonomous Vehicle Sensor Filtering by Region of Interest
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Solution Overview
Problem
Conventional autonomous vehicle sensor systems collect and process excessive sensor data from all directions, leading to a significant computational burden and unnecessary data transmission, which can be inefficient and resource-intensive.
Innovation Solution
A system that selectively captures and filters sensor data by identifying regions of interest based on the vehicle's parameters, such as position, path, and speed, allowing only relevant data to be captured and transmitted to the central computing system, thereby reducing the amount of data processed and transmitted.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor systems continuously collect sensor data from all around the autonomous vehicle, then complete environmental awareness is achieved, but computational burden and data transmission requirements increase significantly
Solution Approach 1:
The patent divides the surrounding environment into multiple regions (e.g., front, rear, left, right regions) and selectively captures sensor data only from relevant regions based on vehicle behavior, rather than processing all data from all directions. This segmentation reduces computational burden while maintaining necessary environmental awareness.
Solution Approach 2:
The patent applies different data capture strategies to different regions based on their relevance to current vehicle operations. For example, when the vehicle is moving straight, only the front region is monitored; when turning, side regions are monitored. This local quality approach optimizes resource allocation by focusing computational resources on critical areas.
2Loss of information
If all sensor data is transmitted to the central computing system, then complete data availability is achieved, but data transmission bandwidth and processing resources are wasted
Solution Approach 1:
The patent extracts and transmits only the relevant portion of sensor data (from regions of interest) to the central computing system, rather than transmitting all captured data. This extraction principle reduces data transmission bandwidth requirements and energy consumption while ensuring all necessary information for autonomous navigation is available.
3Reliability
If sensors capture data from all regions, then comprehensive monitoring is achieved, but system resource utilization becomes inefficient
Solution Approach 1:
The patent dynamically adjusts which regions are monitored based on real-time vehicle parameters such as direction of travel, speed, and operational state. This dynamic adaptation ensures comprehensive monitoring of relevant areas while avoiding waste of computational resources on irrelevant regions, thereby improving overall system productivity.
Data Source
AI summary
A method comprises obtaining one or more parameters of an autonomous vehicle, the parameters including any of a position, path, and/or speed of the autonomous vehicle. The method further includes identifying, based on the one or more parameters of the autonomous vehicle, a region of interest from a plurality of regions surrounding the autonomous vehicle. The method further includes controlling, based on the region of interest, one or more sensors mounted on a surface of the autonomous vehicle to capture sensor data of the region of interest and not capture sensor data from the one or more other regions of the plurality of regions surrounding the autonomous vehicle. The method further includes providing the captured sensor data to a processor, the processor being capable of facilitating, based on the captured sensor data of the region of interest, one or more autonomous vehicle driving actions.