Autonomous Vehicle Routing for Bandwidth-Constrained Network Areas
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Solution Overview
Problem
Autonomous vehicles in densely populated areas often cause reduced bandwidth due to capacity constraints in routers, leading to decreased data speeds and connectivity issues, as they consume high network resources, necessitating a solution to minimize density and optimize bandwidth usage.
Innovation Solution
A method that determines the bandwidth requirements of autonomous vehicles and passengers, identifies areas with oversubscribed bandwidth, and dynamically reroutes vehicles to avoid these areas without significantly increasing travel time, using a neural network-based routing system to optimize network bandwidth by distributing traffic to areas with available capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If autonomous vehicles are routed through densely populated areas to minimize travel time, then delivery speed is improved, but network bandwidth capacity deteriorates due to oversubscription
Solution Approach 1:
The system performs preliminary routing decisions by predicting future bandwidth requirements of autonomous vehicles before they reach congested areas. The neural network analyzes current vehicle positions, destinations, and network conditions to proactively assign routes that will optimize bandwidth usage before congestion occurs, preventing oversubscription rather than reacting to it
Solution Approach 2:
The patent introduces a centralized server as an intermediary that acts as a traffic controller between autonomous vehicles and the wireless network. This server receives bandwidth capacity data from network nodes, processes routing decisions using neural networks, and communicates optimized routes back to vehicles, thereby mediating the conflict between vehicle movement and network resource allocation
2Productivity
If autonomous vehicles concentrate in high-traffic areas to optimize delivery routes, then productivity is improved, but network reliability deteriorates due to bandwidth oversubscription
Solution Approach 1:
The routing system dynamically adjusts vehicle routes based on real-time network conditions. As bandwidth availability changes across different geographic areas and time periods, the neural network continuously recalculates optimal paths, allowing the system to adapt to varying network capacity and maintain reliable connectivity while preserving delivery productivity
Solution Approach 2:
The system implements a feedback loop where bandwidth capacity data from network nodes is continuously monitored and fed back to the routing server. This feedback enables the neural network to learn from past routing decisions and network conditions, progressively optimizing routes to maintain both productivity and reliability by avoiding areas where bandwidth demand exceeds capacity
Data Source
AI summary
Aspects of the present invention disclose a method for routing one or more autonomous vehicles to minimize a density of autonomous vehicles and passengers passing through network areas with oversubscribed bandwidth. The method includes one or more processors determining a bandwidth requirement of a first autonomous vehicle. The method further includes determining respective bandwidth requirement for one or more additional autonomous vehicles utilizing a wireless network. The method further includes determining a total bandwidth capacity of one or more nodes of the wireless network. The method further includes determining routing instructions from a current location of the first autonomous vehicle to a destination of the first autonomous vehicle based at least in part on the bandwidth requirement of the first autonomous vehicle and the total bandwidth capacity of the one or more nodes of the wireless network.