Real-Time Map Error Detection Using Vehicle Environmental Features
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Solution Overview
Problem
Existing autonomous driving technologies face safety risks due to outdated or incorrect map data, which cannot be corrected in a timely manner, leading to inefficiencies in detecting map errors.
Innovation Solution
A method and apparatus for real-time detection of map errors using environmental feature information from sensors such as cameras, radar, and laser radars, allowing for immediate correction of map data during vehicle travel, including reporting errors to a server for data updates and implementing fault tolerance measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If map data is corrected by periodically collecting feature information, then the correction process is simple and resource-efficient, but the map data cannot be corrected in time, causing safety risks
Solution Approach 1:
The system performs preliminary actions by continuously acquiring environmental feature information during vehicle operation and pre-comparing it with map data. This allows the system to detect map errors as they occur rather than waiting for periodic updates, thus resolving the contradiction between timely detection and resource efficiency.
Solution Approach 2:
The system implements a feedback mechanism where detected map errors are reported to a server, which then updates the map data. This closed-loop feedback enables real-time correction of map errors while maintaining efficient resource utilization by only triggering updates when actual errors are detected, rather than continuously updating.
2Productivity
If real-time detection of map errors is implemented during vehicle travel, then the timeliness and efficiency of map error detection is improved, but the system complexity and computational requirements increase
Solution Approach 1:
The system uses the vehicle's existing environmental sensing capabilities (cameras, radar, etc.) for multiple purposes: both for navigation and for map error detection. This multi-functionality approach enables real-time detection without adding dedicated complex detection hardware, thus resolving the contradiction between detection efficiency and system complexity.
Solution Approach 2:
The system performs self-service by automatically comparing environmental feature information with map data and autonomously detecting errors. This automated self-diagnosis eliminates the need for complex manual verification processes and reduces the overall system complexity while maintaining high detection efficiency.
Data Source
AI summary
The present application provides a method for detecting map error information, an apparatus, a device, a vehicle and a storage medium, where the method includes: acquiring current environmental feature information around a vehicle; and detecting, according to the current environmental feature information and map data, whether the map data is erroneous. Whether the map data is erroneous is detected in real time based on the current environmental feature information during the process of the actual traveling of the vehicle, which improves timeliness and efficiency for the map error detection, thereby the map data can be corrected in time and the traveling safety of the vehicle may be improved.