Vehicle Data Classification and Transmission Filtering
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Solution Overview
Problem
Existing data transmission systems in vehicles face challenges in managing large data volumes, leading to information overload for drivers, as they transmit all sensor data without filtering, which can distract drivers and reduce their attention to relevant information.
Innovation Solution
A method and system for data classification and transmission that filters data packets based on pre-defined driving or event categories in the receiving vehicle, ensuring only relevant information is displayed, using physical event data and driving-specific data from the transmitting vehicle, with options for manual or automatic category specification and standardized data packets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all sensor data is transmitted without filtering, then complete information is available, but driver attention is reduced due to information overload
Solution Approach 1:
The patent extracts and transmits only the essential characteristics of sensor data (physical event data) rather than all raw sensor data. By identifying and transmitting only the most relevant features that characterize environmental events, the system maintains information completeness while reducing data volume and preventing driver distraction from excessive information.
Solution Approach 2:
The patent applies different quality levels of data transmission based on the specific event type and driving context. Different physical quantities and event categories are transmitted with appropriate detail levels matched to their relevance for the current driving situation, ensuring each type of information receives the appropriate level of processing and transmission priority.
2Object-affected harmful factors
If data filtering is applied based on driver category, then driver distraction is reduced, but system complexity increases
Solution Approach 1:
The patent segments the filtering system into distinct functional modules: event detection module, physical quantity extraction module, category matching module, and data transmission module. Each module handles a specific aspect of the filtering process, making the overall complex system manageable through clear separation of concerns and modular design.
Solution Approach 2:
The patent performs preliminary classification of sensor data into event categories and extraction of physical quantities before transmission. By pre-processing and categorizing the data in advance at the transmitting vehicle, the receiving vehicle receives already-filtered, categorized information that requires minimal additional processing, thus reducing overall system complexity.
3Productivity
If standardized data packets are used, then data transmission efficiency is improved, but adaptability to different driving scenarios is reduced
Solution Approach 1:
The patent implements a dynamic data packet structure where the content and characteristics of transmitted data are adapted based on the current driving situation, event type, and driver category. While the packet format itself is standardized for efficient transmission, the actual data content within the standardized structure dynamically adjusts to match the specific driving scenario, combining transmission efficiency with scenario adaptability.
Data Source
AI summary
In a method for data classification and data transmission in vehicles, event data which characterize an event that occurs in a first vehicle are stored in a data packet. Event data of the data packet are transmitted from the first to a second vehicle and displayed there if at least a portion of the event data and/or driving-specific data from the first vehicle corresponds to a driving or event category that is determined in the second vehicle.