V2X Sensor Data Filtering for Selective Object Message Decoding
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Solution Overview
Problem
The increasing number of V2X vehicles necessitates improved processes for handling the associated increase in V2X related messaging, particularly in terms of processing load, power consumption, and thermal considerations, as vehicles transmit and receive sensor data sharing messages (SDSMs) and collective perception messages (CPMs).
Innovation Solution
Implementing methods for filtering SDSMs based on host data and operating context, including decoding or discarding portions of the messages, and utilizing Basic Safety Messages (BSMs) to associate and filter detected object data into relevant groups, thereby reducing processing requirements and improving power consumption and thermal management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vehicles transmit and receive all sensor data sharing messages from increasing number of V2X vehicles, then comprehensive object detection information is available, but processing load and power consumption increase significantly
Solution Approach 1:
The patent segments sensor data sharing messages into multiple portions (e.g., header portion, first data portion, second data portion) that can be independently processed. The receiving vehicle decodes only the header portion to determine relevance, and selectively decodes subsequent portions based on this assessment, thereby reducing overall processing load and power consumption while maintaining comprehensive detection capability for relevant objects
Solution Approach 2:
The patent extracts and prioritizes critical identification information (such as object ID, location, velocity) from sensor data messages for rapid assessment. By extracting only the essential header information first, the system can quickly determine message relevance without processing the entire data set, thus reducing power consumption while preserving access to comprehensive detection information when needed
2Reliability
If vehicles process all received sensor data sharing messages, then complete object detection data is obtained, but processing time and computational resources increase
Solution Approach 1:
The patent implements preliminary action by decoding and assessing the header portion of sensor data messages before processing the full message content. This preliminary assessment determines message relevance based on critical parameters such as object location, velocity, and detection type, allowing the system to avoid time-consuming processing of irrelevant messages while ensuring complete processing of relevant ones
Solution Approach 2:
The patent applies partial action by selectively decoding only the portions of sensor data messages that are relevant to the receiving vehicle's operating context. Instead of uniformly processing all messages in full, the system performs partial decoding based on relevance assessment, reducing processing time while maintaining complete object detection data for relevant messages
3Measurement precision
If all sensor data sharing messages are decoded and processed, then maximum detection accuracy is achieved, but thermal generation increases
Solution Approach 1:
The patent segments message processing into hierarchical stages (header decoding, relevance assessment, selective full decoding) that distribute computational workload. This segmentation allows the system to maintain high detection accuracy for relevant messages by fully decoding them, while minimizing thermal generation by avoiding full decoding of irrelevant messages
Solution Approach 2:
The patent changes processing parameters dynamically based on message characteristics and vehicle operating context. By adjusting the level of processing (partial vs. full decoding) according to relevance criteria, the system optimizes the balance between detection accuracy and thermal management, achieving maximum accuracy only when necessary
4Productivity
If filtering is applied to sensor data sharing messages, then processing load is reduced, but risk of discarding relevant data increases
Solution Approach 1:
The patent performs preliminary decoding of message header portions containing critical identification information before filtering decisions are made. This preliminary action ensures that relevance assessment is based on accurate, decoded data rather than raw message content, minimizing the risk of discarding relevant messages while still achieving processing load reduction through selective filtering
Solution Approach 2:
The system implements feedback mechanisms where decoding results and operating context information are used to dynamically adjust filtering criteria. By continuously monitoring detection needs and message characteristics, the system optimizes the balance between processing efficiency and data relevance, ensuring that filtering decisions are based on current operational requirements
Data Source
AI summary
Techniques are provided for filtering object detection information provided via V2X communication links. An example method for partially filtering a sensor data sharing message includes receiving the sensor data sharing message from a vehicle, decoding a first portion of the sensor data sharing message to determine an area of interest associated with the vehicle, determine a relative position of the area of interest, and decoding or discarding a second portion of the sensor data sharing message based on the relative position of the area of interest.