Dynamic Graphic Information Classification for Autonomous Vehicles
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current high definition electronic maps and 3D point cloud graphic information systems for autonomous vehicles are unable to precisely determine vehicle position without additional technologies and suffer from bulky data volumes, leading to unstable transmission and potential traffic accidents due to delayed data downloads.
Innovation Solution
A dynamic graphic information classification device and method that classifies and downloads local map information based on road curvature, crossroads features, and automatic driving level, storing data in a cloud server and reducing data volume by downloading only necessary information, allowing for advance downloading in complex environments and reducing data volume in simpler ones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high definition electronic map and 3D point cloud graphic information are used to provide abundant and accurate road environment information, then measurement precision and reliability are improved, but data volume increases causing unstable transmission and longer download time
Solution Approach 1:
The patent segments the graphic information into different grades based on road environment complexity and vehicle automatic driving level. Instead of downloading all high definition map data, the system divides the data into multiple quality levels and selects appropriate segments, thereby reducing download time while maintaining sufficient precision for safe autonomous driving.
Solution Approach 2:
The patent applies local quality by dynamically adjusting the grade of map information downloaded based on the specific road environment characteristics (curvature, crossroads features) and vehicle driving level. Different regions receive different quality levels of map data, optimizing the balance between data volume and positioning precision for each local area.
2Reliability
If high definition electronic map and 3D point cloud graphic information are used to provide abundant and accurate road environment information, then reliability is improved, but data volume increases causing unstable transmission
Solution Approach 1:
The patent segments graphic information into different grades and selects appropriate segments based on road environment complexity and driving level, reducing overall data volume while maintaining reliability through strategic selection of critical information segments.
Solution Approach 2:
The patent changes the parameter of data quality grade dynamically based on road environment characteristics and vehicle driving level. By adjusting the grade parameter, the system optimizes the balance between data volume and reliability, ensuring sufficient information for safe driving without excessive data transmission.
3Ease of operation
If all high definition map information is stored locally in the vehicle, then accessibility is improved, but storage capacity requirements increase significantly
Solution Approach 1:
The patent segments map information into different grades and stores only the necessary segments locally based on the vehicle's current driving level and road environment. This reduces the storage capacity requirement while maintaining ease of access to the required map information through the classification system.
Solution Approach 2:
The patent implements preliminary action by pre-classifying and pre-selecting which map information segments need to be stored locally based on predicted driving paths and road environment characteristics. This allows the system to prepare appropriate data in advance without requiring storage of all possible high definition map data.
Data Source
AI summary
A dynamic graphic information classification device which is installed in a vehicle and comprises at least one automatic driving assistant system, a wireless communication interface, a storage device, a GPS module, and a processor. The wireless communication interface is connected with a cloud server where a high definition map and 3D point cloud map information are stored. The GPS module acquires position coordinates of the vehicle from an electronic map. The storage device stores at least one of at least one road curvature and at least one crossroads feature of a road environment of a predetermined driving path of the vehicle. The processor classifies the map information to be downloaded according to at least one of at least one road curvature and at least one crossroads feature and an automatic driving level of the automatic driving assistant system, whereby to reduce the time for download.