Physical Route Adjustment Using Real-Time Connectivity Data
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Solution Overview
Problem
Existing wireless communication systems fail to ensure reliable connectivity for autonomous vehicles (AVs) and remotely operated vehicles (ROVs) due to unpredictable network connectivity issues, especially in scenarios where uplink capacity is constrained, and existing QoS mechanisms are ineffective in managing transmitter power limitations and resource allocation.
Innovation Solution
A system that adjusts physical routes based on real-time connectivity data by using a route predictor to analyze intent dissatisfaction reports from AVs/ROVs, leveraging distributed data sources and adaptive network selection to improve connectivity, even in multi-CSP and multi-SIM scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing QoS mechanisms are used to manage connectivity, then network resource allocation is maintained, but connectivity reliability for AVs/ROVs deteriorates due to unpredictable network issues and transmitter power limitations
Solution Approach 1:
The system dynamically adjusts the physical route of AVs/ROVs based on real-time connectivity conditions. Instead of static route planning, the system continuously monitors connectivity quality and reroutes vehicles to areas with better network coverage, making the routing adaptable to changing network conditions and unpredictable connectivity issues.
Solution Approach 2:
The system implements a feedback mechanism where connectivity performance data from AVs/ROVs is collected and analyzed. This feedback loop enables the system to identify problematic areas and adjust routes proactively, improving connectivity reliability by learning from past performance and adapting to recurring issues.
2Reliability
If network capacity is increased to improve connectivity, then more data can be transmitted, but the cost and complexity of network upgrades becomes excessive
Solution Approach 1:
Instead of upgrading the entire network infrastructure, the system segments the problem by focusing on route adjustments for specific vehicles experiencing connectivity issues. This targeted approach improves reliability for affected vehicles without requiring comprehensive network upgrades, reducing overall complexity and cost.
Solution Approach 2:
The system introduces an intermediary routing layer between the vehicle and the network infrastructure. By adjusting routes to avoid problematic network areas, the system mediates connectivity issues without modifying the underlying network infrastructure, avoiding excessive complexity and upgrade costs.
3Reliability
If real-time route adjustments are implemented, then connectivity reliability improves, but the complexity of route management increases
Solution Approach 1:
The system enables autonomous vehicles to self-adjust their routes based on connectivity conditions. The vehicles independently monitor their own connectivity quality and receive automated route recommendations, reducing the need for complex centralized route management and simplifying operations.
Solution Approach 2:
The system changes the parameter being optimized from traditional route efficiency (distance, time) to connectivity quality. By prioritizing connectivity parameters over other route considerations, the system simplifies route management decisions while improving reliability, as the primary optimization criterion becomes network performance rather than multiple competing factors.
Data Source
AI summary
A node can be configured to manage physical routes associated with one or more communication devices. The node can receive (1110) information associated with a performance of a communication network connecting a first communication device with a second communication device as the first communication device moves along a physical route. The node can, responsive to receiving the information, determine (1120) instructions for improving a connection between the first communication device and the second communication device. The node can transmit (1140) an indication of the instructions to the first communication device.