Adaptive Vehicle Network Architecture for Predictive Data Prioritization
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Solution Overview
Problem
Vehicle networks often experience congestion, leading to reduced performance in communication with remote computing devices, resulting in suboptimal data transmission and potential safety concerns during autonomous vehicle operations.
Innovation Solution
An adaptive multi-network architecture that allows vehicles to connect to multiple networks, prioritizing data transmission based on real-time network parameters and predictive mapping, ensuring optimal data transfer by utilizing available bandwidth and minimizing network congestion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle connects to a single network, then the device complexity is reduced, but the network performance and reliability deteriorate due to congestion
Solution Approach 1:
The patent divides the network communication function into multiple independent modems (first modem for first network, second modem for second network). Each modem operates independently on a separate network, allowing the system to segment network traffic and avoid congestion on a single network. This segmentation enables reliable data transmission by distributing load across multiple network paths.
Solution Approach 2:
The vehicle system is designed with multi-functionality by incorporating multiple modems that can operate on different networks simultaneously. The system can universally communicate across multiple network types (e.g., cellular networks with different carriers), making the communication system adaptable and reliable regardless of which network experiences congestion or failure.
2Productivity
If the vehicle uses multiple networks simultaneously, then the network performance improves, but the device complexity increases
Solution Approach 1:
The patent implements dynamic network selection and data routing based on real-time network conditions. The system monitors parameters such as signal strength, data rate, and latency for each network, and dynamically adjusts which modem transmits which data packets. This dynamic adaptation optimizes data transmission efficiency while managing the complexity of having multiple networks through intelligent control.
Solution Approach 2:
The system incorporates feedback mechanisms where network performance parameters are continuously monitored and used to adjust transmission decisions. Based on feedback from network condition assessments, the system determines optimal data transmission paths, prioritizes critical data, and switches networks when necessary, thereby improving productivity while systematically managing multi-network complexity.
3Reliability
If the vehicle prioritizes data transmission based on network parameters, then the communication reliability improves, but the system complexity increases
Solution Approach 1:
The patent applies local quality by assigning different priority levels to different types of data (e.g., high priority for safety-critical data, low priority for non-critical telemetry). Each data packet is tagged with priority information, and the system applies quality-based routing where high-priority data is transmitted on the most reliable network while low-priority data can tolerate network variations. This resolves the contradiction by making the prioritization system manageable through clear categorization.
Data Source
AI summary
A vehicle can connect to multiple networks and can determine network parameters (e.g., available bandwidth, latency, signal strength, etc.) associated with the multiple networks. Additionally, the vehicle can access network map data associated with the multiple networks. As the vehicle traverses an environment, the vehicle can collect sensor data of the environment and/or vehicle data (e.g., vehicle pose, diagnostic data, etc.). Based on the network parameters and the network map data, the vehicle can optimize the use of the networks determine portions of the sensor data and/or vehicle data to transmit via the one or more of the multiple networks.