Cloud Map Data Delivery for Autonomous Vehicle Navigation
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Solution Overview
Problem
Current autonomous vehicle navigation systems face difficulties in updating and coordinating high-definition map data across numerous vehicles, requiring complex coordination between OEMs, map suppliers, and backend servers, and are challenged by connectivity issues that affect continuous and safe operation.
Innovation Solution
A cloud-based system stores and updates map data centrally, allowing autonomous vehicles to request and receive map data levels with varying detail and duration, dynamically joining multicast groups to adapt to connectivity problems by pre-fetching less-detailed data and modifying operating modes to ensure continuous navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-definition map data is stored and updated in each autonomous vehicle, then navigation precision is improved, but device complexity and coordination requirements increase significantly
Solution Approach 1:
The patent extracts the map data storage and update functionality from individual autonomous vehicles and relocates it to a centralized cloud-based server. This allows each vehicle to receive map data updates without needing complex coordination with other vehicles or centralized management systems, thereby reducing device complexity while maintaining navigation precision through access to updated map data.
Solution Approach 2:
The cloud-based server serves multiple autonomous vehicles simultaneously, providing map data updates to all connected vehicles through a single centralized system. This universal approach eliminates the need for separate update mechanisms for each vehicle, reducing overall system complexity while ensuring all vehicles access the same high-definition map data for precise navigation.
2Measurement precision
If detailed map data is continuously transmitted to autonomous vehicles, then navigation accuracy is improved, but connectivity requirements and data transmission complexity increase
Solution Approach 1:
The system dynamically adjusts the level of map data detail transmitted to autonomous vehicles based on their specific needs, location, and connectivity conditions. Instead of continuously transmitting full detailed map data to all vehicles, the server selectively provides appropriate data levels, reducing transmission complexity while maintaining navigation accuracy where needed.
Solution Approach 2:
The patent implements local quality by providing different levels of map data detail to different vehicles or different regions of map data based on specific requirements. Critical navigation areas receive high-detail data, while less critical areas receive simplified data, optimizing transmission efficiency while maintaining necessary navigation accuracy.
3Productivity
If autonomous vehicles operate with full capabilities, then navigation performance is improved, but reliability decreases during connectivity failures
Solution Approach 1:
The system performs preliminary actions by pre-fetching and storing map data in autonomous vehicles before connectivity issues occur. When connected, vehicles receive and cache detailed map data and updates in advance, ensuring they maintain full navigation capabilities even when connectivity is lost, thereby improving reliability during connectivity failures.
Solution Approach 2:
The patent implements beforehand cushioning by preparing backup navigation capabilities in vehicles before connectivity problems arise. The system anticipates potential connectivity issues and ensures vehicles have sufficient local map data cached, providing a cushion that allows continued operation with reduced but adequate capabilities during connectivity failures.
Data Source
AI summary
A system and method for providing a map via a cloud-based system is disclosed. The method includes requesting, by a controller of an autonomous vehicle, a map data from a cloud-based server. The map data is stored on the cloud-based server. The method also includes receiving map data from the cloud-based server. The method also includes autonomously navigating the autonomous vehicle based on the received map data.