Vehicle Positioning Data Error Convergence for High-Accuracy Mapping
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Solution Overview
Problem
Driverless vehicles require high-accuracy maps, but low-cost sensors used for map data collection introduce significant positioning errors, leading to low map accuracy.
Innovation Solution
A method and apparatus for processing positioning data by controlling a vehicle through five stages: dynamic alignment, traveling along a path of a character '8', collecting map data, and performing dynamic alignment, followed by error convergence using forward and backward filtering to reduce positioning errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If low-cost sensors are used for map data collection, then device cost is reduced, but positioning accuracy deteriorates
Solution Approach 1:
The system performs preliminary dynamic alignment stages before actual map data collection to pre-calibrate and correct sensor errors. By conducting error convergence processing in advance through multiple alignment stages, the system compensates for low-cost sensor inaccuracies before they affect map formation, thereby maintaining positioning accuracy without requiring expensive sensors.
Solution Approach 2:
The system implements feedback mechanisms by continuously collecting positioning data during dynamic alignment stages and using this information to correct errors in subsequent map data collection. The error convergence processing uses feedback from multiple measurement stages to iteratively improve positioning accuracy, allowing low-cost sensors to achieve performance comparable to expensive sensors through continuous error correction.
2Measurement precision
If dynamic alignment and error convergence processing are performed, then positioning accuracy is improved, but processing time increases
Solution Approach 1:
The error convergence processing is segmented into five distinct stages: initial dynamic alignment, first path following, map data collection, second path following, and final dynamic alignment. By dividing the processing into manageable segments, the system can perform error correction continuously throughout data collection rather than as a single time-consuming batch process, reducing overall processing time while maintaining accuracy.
Solution Approach 2:
The system performs error convergence processing continuously across all five stages rather than as discrete separate operations. Positioning data is collected and processed in real-time throughout the entire map formation process, eliminating idle time between data collection and error correction. This continuous processing approach maintains positioning accuracy while minimizing time loss compared to batch processing methods.
Data Source
AI summary
Embodiments of the present disclosure provide a method and apparatus for processing positioning data, a device, a storage medium and a vehicle. In the method according to the embodiments of the present disclosure, the vehicle is controlled to collect positioning data continuously in the five stages including a first stage for performing dynamic alignment, a second stage for traveling along a path of a character “8”, a third stage for collecting map data, a fourth stage for traveling along a path of the character “8”, and a fifth stage for performing the dynamic alignment, and processing of error convergence is performed on the positioning data collected in the third stage, according to the positioning data collected in the first stage, the second stage, the fourth stage and the fifth stage, to obtain the final positioning data after the error convergence.