Hierarchical Traffic Management via Dynamic Server Assignment
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Solution Overview
Problem
Current traffic management systems face challenges in efficiently managing dynamic vehicle networks and traffic incidents due to high computational resource requirements and impractical utilization of vehicle and server resources, especially when the number of navigable vehicles changes rapidly.
Innovation Solution
A hierarchical computing architecture that dynamically assigns traffic sections to either local section servers or remote management servers based on responsive vehicle rates, traffic conditions, and resource availability, allowing for flexible distribution of computational tasks and optimal resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a centralized computing server is used to perform traffic management computations, then traffic management capability is improved, but computational resource requirements and costs increase significantly
Solution Approach 1:
The patent segments the centralized computing architecture into a hierarchical structure with multiple levels: cloud-based computing servers, edge computing devices (such as roadside units), and onboard vehicle computing systems. Each segment handles specific computational tasks appropriate to its capabilities and proximity to the traffic data, distributing the computational burden and reducing the load on any single centralized server while maintaining overall traffic management capability.
2Adaptability or versatility
If computational resources are distributed across vehicles and servers, then resource utilization flexibility is improved, but system complexity increases
Solution Approach 1:
The patent implements a dynamic resource allocation mechanism where computational tasks are flexibly assigned to different computing entities (vehicles, edge devices, cloud servers) based on real-time conditions such as vehicle density, computational capacity availability, traffic conditions, and communication latency. This dynamic assignment allows the system to adapt to changing conditions while the hierarchical structure and standardized interfaces manage complexity by providing clear task distribution protocols.
3Productivity
If more vehicles are monitored and managed in real-time, then traffic management effectiveness is improved, but communication latency and computational burden increase
Solution Approach 1:
The patent introduces spatial dimensionality into the computing architecture by deploying edge computing devices at strategic locations along the road network and utilizing vehicles themselves as distributed computing nodes. This spatial distribution brings computation closer to the source of traffic data, reducing communication latency. The hierarchical structure organizes these distributed nodes into manageable layers, allowing real-time processing of traffic information from multiple vehicles without overwhelming a single processing point.
Data Source
AI summary
An example method determines a plurality of traffic sections for a geographical traffic area, each traffic section including a road segment and vehicle(s) traveling on the road segment; monitors a responsive vehicle rate for a first traffic section of the plurality of traffic sections; and assigns, based on the responsive vehicle rate of the first traffic section, the first traffic section to one of a first section server dedicated to manage the first traffic section and a remote management server capable of managing the plurality of traffic sections of the geographical traffic area, the first section server comprising computing device(s) of responsive vehicle(s) in the first traffic section.