Autonomous Driving Data Parsing Without IDL Text
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Solution Overview
Problem
Automatic driving systems face challenges in accurately parsing driving data collected in a binary number system due to the inability to obtain Interactive Data Language (IDL) text from the driving system, leading to failed data processing and monitoring.
Innovation Solution
A driving data processing method that collects binary driving data, determines a target descriptor from a description pool to describe member information, parses the descriptor to obtain decimal member information, and performs data processing operations using the parsed data, enabling accurate data parsing and monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If driving data is collected in binary number system from the driving system, then data transmission efficiency is improved, but data parsing capability deteriorates because the server cannot obtain IDL text to determine object members
Solution Approach 1:
The patent introduces a descriptor as an intermediary between the binary driving data and the parsing system. The descriptor contains structure information that enables the server to parse binary data without needing the original IDL text. This mediator bridges the gap between efficient binary transmission and reliable data interpretation.
Solution Approach 2:
The patent performs preliminary encoding of structure information into descriptors before data transmission. By pre-processing the structure definitions into portable descriptor formats, the system prepares all necessary parsing information in advance, eliminating the need for IDL text at the receiving end.
2Adaptability or versatility
If IDL text is used to define communication structure in the driving system, then data structure definition capability is improved, but system complexity increases because the server cannot access the IDL text
Solution Approach 1:
The patent extracts the essential structure information from the IDL text and encapsulates it in descriptors. By separating the critical structural metadata from the complete IDL definition, the system retains data structure definition capability while reducing the complexity burden on the server side.
Solution Approach 2:
The patent creates simplified copies of structure information in the form of descriptors. These descriptors replicate the essential structural characteristics needed for parsing without requiring the full IDL text, thus maintaining adaptability while reducing system complexity.
Data Source
AI summary
The present disclosure provides a driving data processing method, an apparatus, a device, an automatic driving vehicle, a medium and a product, including: collecting first driving data generated by using a target structure in a driving system of a target vehicle, where the first driving data uses a binary number system; determining a target descriptor corresponding to the target structure, where the target descriptor is used to describe member information of the target structure; parsing the target descriptor to obtain at least one piece of member information of the target structure; parsing the first driving data according to the at least one piece of the member information to obtain target data corresponding to each of the at least one piece of the member information; and performing a data processing operation based on the target data corresponding to each of the at least one piece of the member information.