Vehicle Communication Apparatus Feature Extraction
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Solution Overview
Problem
Vehicle-to-vehicle communication systems face challenges in efficiently transmitting vehicle status information due to high data volumes, leading to communication difficulties and increased processing loads when transmitting and analyzing travel information from multiple vehicles.
Innovation Solution
A communication apparatus and system that acquire and create feature information with a smaller data amount than the original status information, using methods like Deep Learning to convert multiple types of information into fewer feature amounts, and transmit this feature information along with correspondence data to efficiently convey vehicle status, reducing data transmission and processing loads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If vehicle status information is transmitted in original format, then complete vehicle status data is available, but data transmission volume increases and communication efficiency decreases
Solution Approach 1:
The patent extracts essential feature information from comprehensive vehicle status data using deep learning models. Instead of transmitting all original status parameters, the system identifies and transmits only the most critical feature amounts that represent vehicle status, thereby reducing data volume while preserving essential information content.
Solution Approach 2:
The patent transforms vehicle status information from raw parameter format to feature amount format through deep learning processing. This parameter transformation compresses multiple status parameters into fewer feature amounts, reducing transmission data volume while maintaining the ability to reconstruct vehicle status information at the receiving end.
2Quantity of substance
If feature information is created to reduce data amount, then data transmission volume decreases, but information completeness may be compromised
Solution Approach 1:
The patent implements a feedback mechanism where the receiving end uses correspondence information to interpret feature amounts and reconstruct vehicle status. The system continuously refines the feature extraction process based on the effectiveness of status determination, ensuring that transmitted feature information maintains sufficient completeness for accurate vehicle status assessment.
Solution Approach 2:
The patent introduces correspondence information as an intermediary element that bridges the gap between compressed feature information and complete vehicle status. This intermediary data structure enables the receiving end to accurately interpret feature amounts and reconstruct comprehensive vehicle status information without receiving the original large-volume status data.
3Adaptability or versatility
If multiple types of status information are transmitted, then comprehensive vehicle status is captured, but processing load at receiving end increases
Solution Approach 1:
The patent segments the processing workload between transmitting and receiving ends. The transmitting end performs complex deep learning-based feature extraction to convert multiple status parameters into compact feature amounts, while the receiving end only needs to perform simpler interpretation of these feature amounts using correspondence information, thereby reducing overall processing load.
Solution Approach 2:
The patent performs preliminary processing of vehicle status information at the transmitting end by pre-computing feature amounts using deep learning models before transmission. This preliminary action consolidates multiple status parameters into essential feature information in advance, so the receiving end does not need to perform complex analysis on raw status data, reducing its processing burden.
Data Source
AI summary
Provided is a communication apparatus installed in a vehicle, the communication apparatus including: an acquisition unit configured to acquire, via a network installed in the vehicle, a plurality of types of status information each indicating a status of the vehicle; an information creation unit configured to create, on the basis of each piece of the status information acquired by the acquisition unit, feature information having a data amount smaller than a total of data amounts of the respective pieces of the status information, the feature information including a feature amount of a traveling status of the vehicle; and a transmission unit configured to transmit vehicle information based on the feature information created by the information creation unit, to another communication apparatus.