Autonomous Vehicle Mesh Network for Reliable Mobile Node Communication
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Solution Overview
Problem
Current communication networks are inadequate for supporting communication environments involving mobile and static nodes, particularly failing to effectively communicate among and with autonomous vehicles.
Innovation Solution
A dynamically configurable network of autonomous vehicles utilizing a combination of fixed and mobile communication nodes, including Mobile Access Points (MAPs) that can connect to both cellular networks and other vehicles, forming a mesh of communication links to provide robust, scalable, and secure connectivity anywhere and anytime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current communication networks are used to support autonomous vehicles, then existing infrastructure can be maintained, but communication reliability and connectivity among mobile nodes deteriorates
Solution Approach 1:
The patent implements a dynamic network architecture where access points can transition between fixed and mobile states. Mobile access points (MAPs) enable the network to adapt to moving autonomous vehicles, allowing nodes to join and leave the network dynamically while maintaining communication reliability through seamless handoffs and mesh routing protocols.
Solution Approach 2:
The network architecture supports both fixed and mobile access points within the same system, allowing infrastructure to serve multiple functions. Fixed APs provide stable backbone connectivity while MAPs extend coverage to mobile vehicles, creating a universal network that handles both stationary and moving nodes effectively.
2Adaptability or versatility
If a mesh network of mobile access points is deployed to improve connectivity among autonomous vehicles, then communication coverage and adaptability improve, but network complexity and device configuration difficulty increases
Solution Approach 1:
The mesh network implements self-configuration capabilities where mobile access points automatically discover other nodes, establish optimal routing paths, and adjust their network roles dynamically. This self-organizing behavior eliminates manual configuration requirements and reduces operational complexity despite the network's adaptive capabilities.
Solution Approach 2:
The network dynamically adjusts its topology based on the positions and capabilities of participating vehicles. Mobile access points automatically transition between routing modes and connectivity states, allowing the network to maintain optimal performance without complex manual intervention or configuration management.
3Measurement precision
If real-time data collection from multiple autonomous vehicles is implemented to enable urban living optimizations, then data quality and decision-making accuracy improve, but energy consumption and processing requirements increase
Solution Approach 1:
The data collection and processing system is segmented across multiple autonomous vehicles, with each vehicle acting as an independent data node. This distributed architecture allows local processing and filtering of data at the source, reducing the energy required for centralized processing and enabling scalable data collection without linearly increasing overall system energy consumption.
Data Source
AI summary
Methods and systems are provided for detecting anomalies and forecasting optimizations to improve urban living management using networks of autonomous vehicles. An autonomous vehicle may receive initial information relating to infrastructure utilized by a plurality of autonomous vehicles, and may obtain, during operation in the infrastructure, real-time information relating to the infrastructure, to other ones of the plurality of autonomous vehicles, and/or to various conditions or operations pertinent to urban living and management thereof in an area corresponding to and/or associated with the infrastructure. The real-time information may be processed, and based on the processing of the real-time information and the initial information, anomalies and/or problems affecting the infrastructure and/or operation of the plurality of autonomous vehicles in the infrastructure may be detected, and one or more adjustments to improve management of urban living within the area may be determined.