Roadside Unit Data Prioritization for Connected Vehicles
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Solution Overview
Problem
Current connected vehicle systems face challenges in efficiently prioritizing and processing large amounts of data exchanged in transit networks, which can lead to delays in critical safety messages and inefficient traffic management.
Innovation Solution
A method that prioritizes vehicle data based on urgency and available computing resources, allowing for immediate transmission of critical safety messages and processing at appropriate servers, while adapting intersections in real-time using signal phase and timing data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all vehicle data is processed equally without prioritization, then comprehensive data analysis is achieved, but critical safety messages experience delays and processing efficiency decreases
Solution Approach 1:
The patent segments vehicle data into different priority levels (critical safety messages, important operational data, routine information) and processes them through different channels. Critical safety messages are identified and routed immediately with highest priority, while other data is processed in sequence or batched, eliminating the bottleneck of uniform processing and ensuring timely delivery of safety-critical information.
Solution Approach 2:
The system changes the processing parameter of data by assigning different priority levels and urgency flags to different types of vehicle data. This parameter change enables the system to dynamically adjust processing behavior, allocating computing resources and transmission bandwidth differently based on data urgency, thereby reducing latency for critical messages while maintaining comprehensive data collection.
2Productivity
If more computing resources are allocated to process all vehicle data in real-time, then processing completeness is improved, but system complexity and infrastructure requirements increase
Solution Approach 1:
The patent divides the data processing workload into segmented tasks based on priority and urgency. Critical safety messages receive dedicated real-time processing resources, while non-critical data is processed in batches or with lower resource allocation. This segmentation allows the system to achieve high productivity for essential functions without requiring excessive computing infrastructure for all data types.
Solution Approach 2:
The system applies partial processing action by focusing computing resources on the most critical portions of data processing rather than attempting to process all data with equal depth and urgency. Critical safety messages receive full real-time processing attention, while other data receives appropriate but reduced processing intensity, optimizing productivity without proportionally increasing infrastructure complexity.
3Loss of information
If vehicle data is transmitted to remote servers for processing, then centralized analysis capability is improved, but network latency and transmission time increase
Solution Approach 1:
The patent segments data transmission by routing different types of vehicle data to different destinations based on urgency. Critical safety messages are transmitted immediately to both local edge computing nodes and remote servers simultaneously, ensuring low-latency processing at the edge while maintaining centralized analysis capability. Non-critical data is transmitted to remote servers in batches, reducing network latency for time-sensitive operations while preserving comprehensive centralized data collection for thorough analysis.
Data Source
AI summary
A method may be implemented to prioritize and analyze data exchanged in a connected vehicle transit network. The method may include receiving, at a roadside unit, vehicle data from a connected vehicle. The method may further include prioritizing the vehicle data received from the connected vehicle based on a level of urgency, network latency or available computing resources.