Intelligent Traffic Cloud Control System Edge Computing Bottleneck
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Solution Overview
Problem
The existing intelligent traffic cloud control systems face a significant workload and burden on the central system, leading to ineffective real-time handling of traffic conditions across intersections, as all calculation and control functions are centralized, resulting in poor coordinated control among control servers.
Innovation Solution
The system distributes IP-enabled field devices to acquire and process real-time traffic data locally at each control server, allowing for local coordinated control and edge computing, which reduces the data transmission burden on the central system and enables real-time traffic management by allowing control servers to generate and enforce coordinated control strategies independently or through cloud computing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If all calculation and control functions are centralized in the central system, then unified traffic management is achieved, but the workload and burden on the central system increase significantly
Solution Approach 1:
The patent divides the centralized control system into multiple distributed control servers, each responsible for specific geographic regions or traffic zones. This segmentation allows the system to maintain unified traffic management capabilities while distributing the computational workload across multiple independent servers, thereby reducing the burden on any single central system and improving overall system scalability and reliability.
2Extent of automation
If all field real-time information is transmitted to the central system for processing, then centralized decision-making is achieved, but data transmission time increases and real-time response is delayed
Solution Approach 1:
The patent enables control servers to process and analyze field real-time information locally without requiring complete transmission to a central system. Each control server has the capability to independently process traffic data, generate control decisions, and enforce them in real-time. This local processing approach significantly reduces data transmission time while maintaining effective centralized coordination through inter-server communication.
3Device complexity
If control servers only act as data transmission nodes, then system structure is simplified, but coordinated control effect among control servers is poor
Solution Approach 1:
The patent merges multiple functions including data collection, local processing, control decision-making, and coordination communication within each control server. This functional integration transforms control servers from simple data transmission nodes into intelligent distributed control units that can independently make control decisions while coordinating with other servers through standardized communication protocols, thereby significantly improving coordinated control effectiveness across the entire traffic management system.
Data Source
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AI summary
The invention relates to the field of controlling road traffic, and particularly to a method for coordinated control in an intelligent traffic cloud control system, and in the method, a central system can perform global coordinated control, or a control server can perform local coordinated control, and if the control server performs local coordinated control, then the control server can distribute a pertinent coordinated control strategy for a particular condition in a service area, thus alleviating the burden on the central system, and reducing the overall amount of data information to be transmitted in the intelligent traffic system, and also shortening the period of time for transmitting the data information so as to improve the efficiency of generating and enforcing the coordinated control strategy, and to address the problem of a traffic jam at a crossing effectively in a real-time manner.