Motor Vehicle Data Transmission Abstraction for Parking Assistance
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Solution Overview
Problem
Modern motor vehicles face challenges in efficiently transmitting large amounts of data from sensors to backend systems, particularly in parking assistance systems, which results in high data rates that are difficult to manage effectively.
Innovation Solution
The method involves dividing the data profile into segments, identifying features and contextual information, and combining them into a route message, reducing the data volume by abstracting the data into features and context information, such as object presence and distances, rather than transmitting raw distance measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If raw sensor data is transmitted to the backend, then complete information is available for analysis, but the data transmission volume becomes excessively large
Solution Approach 1:
The patent divides the continuous sensor data stream into discrete segments representing specific parking space characteristics. Instead of transmitting all raw measurements, the data is segmented into relevant features such as parking space detection, occupancy status, and dimensional information, thereby reducing transmission volume while preserving essential information.
Solution Approach 2:
The patent extracts only the essential features from the raw sensor data for transmission to the backend. By identifying and extracting key parameters such as parking space presence, occupancy state, and relevant dimensions, the system transmits minimal necessary data while maintaining information completeness for backend analysis.
2Quantity of substance
If data is processed and abstracted into features, then data transmission volume is reduced, but processing complexity in the vehicle increases
Solution Approach 1:
The patent performs preliminary processing of sensor data in the vehicle before transmission to the backend. By pre-identifying and pre-extracting relevant features such as parking space characteristics and occupancy status, the system reduces the burden on backend processing while maintaining data utility, effectively shifting some processing complexity to the vehicle side in advance.
3Measurement precision
If measurement frequency is increased, then detection precision is improved, but data rate increases making transmission difficult to manage
Solution Approach 1:
The patent extracts only the essential features from frequent measurements rather than transmitting all measurement data. By identifying key parameters such as parking space detection status and occupancy changes from high-frequency sensor data, the system maintains detection precision while significantly reducing the data rate for transmission and backend management.
Data Source
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AI summary
The invention relates to a method, a device and a computer-readable storage medium with instructions for processing data in a motor vehicle for transmission to a back end. In a first step, sensor data are recorded along a stretch of road travelled by the motor vehicle (10). On the basis of the sensor data, features and context information for the features are then identified within segments of the stretch of road (11). Finally, the features and the context information for the features are combined into a message for the stretch of road (12).