Intelligent Traffic Cloud Control System Edge Computing
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Solution Overview
Problem
The existing urban traffic management systems face inefficiencies due to data overload at central control systems and slow data transfer between traffic signal controllers and field devices via serial buses, leading to delayed control instructions and inefficient data processing.
Innovation Solution
Implementing an intelligent traffic cloud control system with IP-enabled field devices communicating over a broadband bus, utilizing edge computing for local traffic control and self-learning for coordinated control strategies, and cloud computing for data sharing between control servers to alleviate central system burden and improve data processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a central control system processes all traffic data from all intersections, then centralized control can be achieved, but the central control system becomes overloaded and processing efficiency decreases
Solution Approach 1:
The patent divides the centralized control system into distributed control nodes at each intersection. Each control node independently processes local traffic data and generates control instructions, eliminating the bottleneck of centralized processing. This segmentation allows parallel processing across multiple nodes, significantly improving overall system productivity while reducing the load on any single device.
Solution Approach 2:
The patent implements edge computing by deploying control nodes directly at intersections, enabling local data processing and control decision-making. Each control node processes traffic data locally rather than transmitting all data to a central system, reducing communication overhead and processing delays. This local quality approach improves response time and processing efficiency while minimizing central system burden.
2Speed
If traffic signal controllers communicate with field devices over a serial bus, then system simplicity is maintained, but data transfer speed is relatively low
Solution Approach 1:
The patent replaces traditional serial bus communication with Ethernet-based IP network communication. This substitution transitions from serial mechanical/electrical signaling to packet-based network protocols, enabling significantly higher data transfer speeds. The Ethernet infrastructure provides robust, high-speed communication while maintaining system modularity and ease of deployment through standardized networking components.
3Loss of time
If the central control system processes and controls all traffic intersections, then unified traffic management is achieved, but control instruction issuance is delayed due to system overload
Solution Approach 1:
The patent segments the monolithic central control system into autonomous control nodes distributed across intersections. Each node independently processes local traffic data and generates control instructions without waiting for central system processing. This segmentation eliminates the sequential processing bottleneck, reducing control instruction delays while maintaining unified traffic management through standardized protocols and cloud-based coordination.
Solution Approach 2:
The patent implements preliminary action by pre-deploying control nodes at intersections with pre-configured processing capabilities. These nodes are ready to immediately process traffic data and generate control instructions without waiting for central system authorization or processing. This preliminary preparation of distributed control capabilities significantly reduces response time and eliminates delays associated with centralized decision-making.
Data Source
AI summary
The application relates to an intelligent traffic cloud control system configured to acquire and centrally analyze a large amount of field data in a traffic system, and to control the traffic system. Unlike a traditional traffic directing and controlling system in such an operating mode that data are acquired and transmitted respectively by different sensing devices, and then collected, analyzed, and processed by a central system, the intelligent traffic cloud control system according to the invention analyzes and processes centrally a large amount of data through field control servers communicating over IP address based broadband buses, and performs adaptive traffic control, traffic regulation enforcement, position tracking, coordinated control, and other service functions through integrating edge computing and cloud computing at a plurality of adjacent field control servers.