Network Connectivity Road Map for Connected Vehicles
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Solution Overview
Problem
Connected vehicles experience connectivity issues due to high demand for network bandwidth, high loads on back-end servers, and limited or intermittent network coverage, which vary by geographical location and time.
Innovation Solution
An evaluation system that determines a network connectivity performance road map by collecting overall performance metrics from vehicles and back-end servers, storing them in a road map database, and calculating statistical measures to annotate nodes and edges on a map data road graph, enabling vehicles to receive navigational requests and route plans based on network performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vehicles rely on existing wireless network infrastructure for connectivity, then basic communication functionality is achieved, but connectivity quality deteriorates in areas with high demand, limited bandwidth, or intermittent coverage
Solution Approach 1:
The system performs preliminary actions by collecting network performance metrics from multiple vehicles and back-end servers, calculating statistical measures, and generating a connectivity performance road map in advance. This allows vehicles to query and receive connectivity assessments for specific geographic regions before traveling, enabling them to plan routes that avoid areas with poor network performance, thereby preventing connectivity issues rather than reacting to them after they occur.
2Measurement precision
If the system collects performance metrics from all vehicles and servers to create accurate connectivity maps, then connectivity assessment accuracy is improved, but system complexity and data processing requirements increase
Solution Approach 1:
The system segments the data collection and processing functions across multiple components: vehicles collect local network performance metrics, back-end servers aggregate and process this data, and the system generates connectivity assessments for specific geographic regions. This segmentation allows the system to handle large volumes of data from multiple sources without requiring a single complex processing unit, while still achieving accurate connectivity measurements through coordinated data collection and statistical analysis.
3Ease of operation
If the system provides detailed real-time connectivity information to vehicles, then navigation quality is improved, but network bandwidth consumption and server load increase
Solution Approach 1:
The system applies local quality by providing connectivity performance information specific to particular geographic regions rather than uniform global data. Vehicles receive tailored connectivity assessments for the specific areas they are traveling through or planning to visit. This localized approach delivers high-quality, relevant navigation information to each vehicle based on its specific route needs, while avoiding the transmission of unnecessary global data, thereby reducing overall network bandwidth consumption and server processing load.
Data Source
AI summary
An evaluation system that determines a network connectivity performance road map includes one or more back-end servers in wireless communication with a plurality of vehicles located in a geographic region by a wireless communication network and one or more road map databases in electronic communication with the one or more back-end servers. The one or more road map databases store a map data road graph of the geographic region including a plurality of nodes connected by a plurality of edges and one or more statistical measures corresponding to the plurality of overall performance metrics of the wireless communication network for each of the plurality of nodes. The one or more back-end servers determine the network connectivity performance road map of the geographical region based on the statistics corresponding to the plurality of overall performance metrics for each of the plurality of nodes and each of the plurality of edges.