Autonomous Vehicle Mesh Network for Reliable Connectivity
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Solution Overview
Problem
Current communication networks are inadequate for supporting communication environments involving mobile and static nodes, particularly in networks of autonomous vehicles, as they fail to provide robust, scalable, and efficient connectivity and data management.
Innovation Solution
A dynamically configurable network architecture that integrates mobile and static communication nodes, utilizing Mobile Access Points (MAPs) and Fixed Access Points (FAPs) to create a mesh network, enabling seamless communication and data collection across various environments, with built-in redundancies and self-healing capabilities to ensure continuous connectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current communication networks are used to support autonomous vehicles, then existing infrastructure can be leveraged, but robustness and reliability are insufficient for mobile and static node environments
Solution Approach 1:
The patent implements a dynamic network architecture where Mobile Access Points (MAPs) in autonomous vehicles can dynamically join, leave, and move within the network. The system adapts topology changes in real-time, allowing vehicles to serve as moving communication nodes that maintain connectivity despite motion, thereby achieving both reliability and adaptability simultaneously
Solution Approach 2:
The patent introduces MAPs as intermediary nodes between autonomous vehicles and the fixed infrastructure (FAPs). These MAPs relay communications, enabling vehicles to maintain reliable connectivity even when direct connections to FAPs are unavailable, thus bridging the gap between mobile vehicle needs and fixed infrastructure limitations
2Adaptability or versatility
If a mesh network with MAPs and FAPs is implemented, then connectivity and adaptability improve, but system complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where MAPs and FAPs automatically discover each other, negotiate connections, and dynamically configure network topology without manual intervention. The system performs self-healing when nodes fail or move, automatically rerouting communications and reconfiguring the mesh network, thereby reducing operational complexity despite the sophisticated architecture
Solution Approach 2:
The patent segments the communication network into distinct functional components: MAPs in vehicles, FAPs in fixed infrastructure, and cloud-based management systems. Each segment operates semi-independently with defined interfaces, allowing the complex mesh network to be managed through modular, manageable units rather than as a monolithic system
3Reliability
If redundant connections and self-healing capabilities are added, then reliability improves, but energy consumption increases
Solution Approach 1:
The patent implements periodic health checks and connection status monitoring rather than continuous active maintenance of all redundant paths. MAPs periodically assess network conditions and only activate alternative routes when degradation is detected, reducing energy consumption while maintaining reliability through on-demand use of redundant connections
Solution Approach 2:
The patent creates a dynamic balance in redundancy management where the system continuously monitors network conditions and adaptively adjusts the activation of redundant paths. When network conditions are good, redundant paths remain dormant to save energy; when conditions deteriorate, redundant paths are activated to maintain connectivity, achieving reliability without constant energy expenditure
Data Source
AI summary
Communication network architectures, systems and methods for supporting a network of mobile nodes. As a non-limiting example, various aspects of this disclosure provide autonomous vehicle network architectures, systems, and methods for supporting a dynamically configurable network of autonomous vehicles comprising a complex array of both static and moving communication nodes. In particular, systems and methods for data-driven managed services built on top of a network of autonomous vehicles.