Vehicle Sensor Signal Encoding Table for Variable-Length Memory Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle sensor signals, particularly acceleration signals, are not uniformly distributed, leading to high-frequency occurrences near the middle value and requiring large memory for storage, increasing hardware costs.
Innovation Solution
An adaptive encoding table generation method that classifies sensor signals by occurrence frequency, assigning shorter binary codes to high-frequency signals and longer codes to low-frequency signals, optimizing encoding and decoding processes in a lossless manner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed-length binary codes are used to encode sensor signals, then the encoding process is simple and reliable, but the memory requirement increases significantly due to high-frequency occurrences of signals near the middle value
Solution Approach 1:
The patent applies local quality by assigning different code lengths to different signal ranges based on their occurrence frequencies. High-frequency signals near the middle value are assigned shorter codes, while low-frequency signals are assigned longer codes. This creates a non-uniform code distribution that adapts to the local characteristics of signal frequency, thereby reducing overall memory requirements while maintaining encoding reliability.
Solution Approach 2:
The patent changes the parameter of code length from fixed to variable based on signal occurrence frequency. By dynamically adjusting the code length parameter according to the frequency distribution of sensor signals, the system optimizes the balance between encoding simplicity and memory efficiency, resolving the contradiction between reliability and memory requirement.
2Quantity of substance
If variable-length codes are assigned based on occurrence frequency, then the average encoding length is reduced, but the encoding and decoding process becomes more complex
Solution Approach 1:
The patent segments the sensor signal range into multiple intervals based on occurrence frequency. Each interval is assigned a specific code length, creating a structured segmentation of the encoding process. This segmentation allows for systematic implementation of variable-length coding while maintaining manageable complexity through organized categorization of signals.
Solution Approach 2:
The patent performs preliminary action by pre-classifying sensor signals into different frequency categories and pre-assigning appropriate code lengths before actual encoding occurs. This preparation step simplifies the real-time encoding process by eliminating the need for complex calculations during encoding, thereby reducing operational complexity while achieving variable-length code benefits.
3Device complexity
If all sensor signals are encoded with the same code length, then the encoding table is simple and easy to manage, but the storage efficiency decreases due to unnecessary memory allocation for low-frequency signals
Solution Approach 1:
The patent applies local quality to the encoding table by creating different entry structures for different signal frequency categories. High-frequency signals have shorter code assignments while low-frequency signals have longer code assignments. This localized differentiation within the encoding table structure optimizes storage efficiency without requiring complete redesign of the entire encoding system.
Data Source
AI summary
A method of generating an encoding table for sensor signals of a vehicle includes (i) obtaining the frequency at which sensor signals occur, (ii) classifying the sensor signals into different levels according to the occurrence frequency, with the level number related to the number of encoding bits, wherein the higher the occurrence frequency, the smaller the level number and the smaller the number of encoding bits, (iii) assigning binary codes to the sensor signals, wherein the binary code has a single middle bit, front bits before the middle bit, and rear bits after the middle bit, the middle bit is written into a first bit value, the number of the front bits characterizes the level and is written into a second bit value, and the number of the rear bits depends on the number of the front bits and the value of the sensor signal is mapped out by the bit value of the rear bits, and (iv) generating an encoding table to establish corresponding relationships between the sensor signals and the binary codes. A corresponding encoding method, decoding method, computer program product, and processing device are also disclosed. This can reduce the memory required to record sensor signals.