Sensor Recognition Feedback Loop for Autonomous Driving Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing autonomous vehicle sensors struggle with recognition accuracy due to inconsistent abstract data with the real situation, limiting the improvement of subsequent driving route planning and decision-making.
Innovation Solution
Implementing bidirectional data transmission between sensors and a processing unit to optimize recognition algorithms using feedback data, enhancing sensor accuracy by incorporating attribute description data from multiple sources, including other sensors and cloud sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sensors process raw data using recognition algorithms to obtain abstract data, then data processing efficiency is improved, but recognition accuracy deteriorates when abstract data is inconsistent with the real situation
Solution Approach 1:
The patent implements a feedback mechanism where the processing unit determines whether abstract data from sensors is consistent with the real situation by comparing it with actual scenario data. When inconsistency is detected, the processing unit sends feedback to the sensor to optimize the recognition algorithm. This closed-loop feedback system resolves the contradiction by enabling continuous improvement of recognition accuracy while maintaining efficient data processing through algorithm optimization rather than brute-force reprocessing.
Solution Approach 2:
The patent applies preliminary action by having the processing unit pre-determine the consistency between abstract data and real situations before final decision-making. The processing unit prepares feedback information in advance that indicates what corrections are needed, allowing sensors to optimize their recognition algorithms proactively rather than reactively. This preliminary assessment prevents propagation of inaccurate abstract data through the system.
2Measurement precision
If sensors continuously optimize recognition algorithms to improve accuracy, then recognition accuracy is improved, but device complexity increases
Solution Approach 1:
The patent introduces the processing unit as an intermediary that mediates between sensors and the optimization process. Instead of sensors directly and continuously optimizing their own algorithms (which would increase sensor complexity), the processing unit acts as a central coordinator that receives abstract data, determines consistency with reality, generates optimization feedback, and sends it back to sensors. This distributes complexity to a dedicated processing unit while keeping sensors relatively simple data collection devices.
3Measurement precision
If bidirectional data transmission is implemented between sensors and processing unit, then recognition accuracy is improved through feedback, but loss of time increases due to additional communication overhead
Solution Approach 1:
The patent extracts only the essential feedback information needed for optimization from the full data processing cycle. Instead of continuous bidirectional communication of all data, the processing unit extracts and transmits only the specific consistency determination results and optimization indications back to sensors. This minimal extraction approach reduces communication overhead and time loss while still providing the necessary feedback for accuracy improvement.
Data Source
Figure 1~2
Figure 3
Figure 4
AI summary
A data processing method and apparatus, a chip system, and a medium are provided. The method may be applied to the field of autonomous driving or intelligent driving. The method includes: obtaining first abstract data from first raw data by using a first recognition algorithm, where the first abstract data includes attribute description data of a first target; receiving first feedback data, where the first feedback data includes attribute description data of a second target; and optimizing the first recognition algorithm based on the first feedback data, where the first raw data is measurement data of a scenario, and the first target and the second target are targets in the scenario. According to the method in the foregoing technical solution, bidirectional data transmission can be performed between a sensor and a processing unit, and a recognition algorithm is optimized based on received feedback data. This improves recognition accuracy of the sensor.