Self-Learning Vehicle Nodes for Route-Based Data Preloading
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Solution Overview
Problem
Existing vehicle communication systems struggle to efficiently manage data transfer between vehicles and infrastructure nodes, particularly in dynamic environments where vehicle speed and location significantly impact data transmission.
Innovation Solution
A method and system that determine data to be provided to or retrieved from a vehicle based on its speed, location, and the proximity to computing nodes, optimizing data transfer by preloading data onto nodes along the vehicle's predicted route.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If data transfer is performed in real-time between vehicle and infrastructure nodes, then data freshness is improved, but data transmission completeness deteriorates due to vehicle movement and limited communication window
Solution Approach 1:
The system pre-loads data from the target vehicle onto intermediate infrastructure nodes before the source vehicle arrives. This preliminary action ensures that when the source vehicle passes through the infrastructure network, all required data is already available at the destination node, eliminating transmission delays and ensuring complete data transfer regardless of the vehicle's speed or communication window duration.
Solution Approach 2:
Infrastructure nodes serve as intermediaries that relay data between vehicles. Instead of direct vehicle-to-vehicle transmission, data is transferred from the source vehicle to intermediate nodes, which then forward it to the destination node. This intermediary approach allows data to be staged and forwarded systematically, ensuring completeness even when vehicles move quickly through the network.
2Productivity
If vehicle speed is increased to improve transportation efficiency, then productivity is improved, but data transfer reliability deteriorates due to reduced communication time with infrastructure nodes
Solution Approach 1:
The system performs data pre-loading at infrastructure nodes before the vehicle reaches them. This preliminary action decouples data transfer reliability from vehicle speed, allowing vehicles to maintain high speeds while data is systematically prepared and staged at intermediate nodes for reliable transmission when the vehicle is in range.
Solution Approach 2:
The system establishes continuous data transfer operations across multiple infrastructure nodes along the vehicle's route. Data transfer is not a single discrete event but a continuous process that begins at the first node and progresses through subsequent nodes, ensuring that data transfer reliability is maintained throughout the vehicle's journey regardless of speed variations.
3Productivity
If data is pre-loaded onto infrastructure nodes along the predicted route, then data transfer efficiency is improved, but system complexity increases due to route prediction and coordination requirements
Solution Approach 1:
The system determines the vehicle's predicted route and pre-loads data onto infrastructure nodes along that route in advance. This preliminary route planning and data staging simplifies the actual data transfer process, as nodes only need to execute predetermined transfer operations when the vehicle arrives, rather than making complex real-time decisions.
Solution Approach 2:
The system monitors vehicle location and communicates with infrastructure nodes to coordinate data transfers. This feedback mechanism allows the system to adapt to actual vehicle movements while maintaining the overall pre-loaded data structure, balancing automation with real-time adjustments without requiring overly complex centralized control.
Data Source
AI summary
An example operation includes one or more of determining, by a first node, that an event has occurred in a geographic area, predicting, by the first node, a severity of the event, a duration of the event, and at least one vehicle associated with the event, sending, by the first node, the prediction to a second node and a time the at least one vehicle will be proximate the second node, and sending by the second node, notifications to other vehicles proximate the second node to maneuver based on the prediction, prior to the time.