Cloud-side collaborative expressway cloud control system and control method

Abstract

The invention relates to an intelligent traffic cloud control system, and provides a cloud-side-end collaborative road traffic cloud control platform technical architecture by fully applying technologies such as cloud computing, edge computing, big data and artificial intelligence, which can overcome the defects of the existing traffic operation management and monitoring system technical architecture. According to the highway cloud control platform designed and developed by the technical architecture, the road network operation efficiency can be improved on the premise that the safety is ensured, so that highway users can obtain more timely, effective and personalized driving and travel auxiliary information, and the functions of supporting vehicle-road cooperative automatic driving practical application and the like are achieved.

Description

technical field [0001] This application relates to the field of smart transportation technology, in particular to a cloud-edge-device collaborative road traffic cloud control platform technical architecture and a control method thereof. Background technique [0002] Build smart transportation, promote the deep integration of big data, Internet of Things, artificial intelligence, blockchain and other technologies with the transportation industry, realize the integrated development of transportation infrastructure network, transportation service network, energy and information network, and improve transportation system management and operation It is one of the important starting points for building a safe, convenient, efficient, green and economical modern comprehensive transportation system. [0003] As an important part of my country's transportation infrastructure and the backbone network of passenger and cargo transportation, expressways have become an important field of m...

AI Technical Summary

Problems solved by technology

The existing expressway electromechanical system is a closed system based on a private communication network. It mainly collects information such as traffic flow and environment through roadside cameras, weather detectors, vehicle detectors and other field monitoring facilities. There is a lack of external information input channels for vehicle information and road user status information; at the same time, subsystems such as toll collection, monitoring, and emergency communication within the system are also independent and closed, and the openness of the system needs to be improved

[0006] Second, the challenge of accurate and timely information service

The basic data of the existing expressway electromechanical system is basically reported layer by layer. Information calculation and processing are mainly deployed in the TOCC or monitoring center on the upper layer. The computing power of each layer of TOCC is not fully utilized, and the information release is mainly "top-down". Level-by-level release mode; at the same time, the information service is mainly based on statistical reports, and the timely information service ability to accurately locate different road users and managers needs to be improved urgently

[0007] The third is the challenge of intelligent decision-making control

[0010] First, there are obvious differences between low-level devices and high-level devices in their working modes and operating states. For example, in addition to transmitting raw data to the upper layer, the lowest-level end device also needs to obtain high-speed, short-latency control of the upper layer. Instructions (such as based on the uploaded data), and in the prior art due to the setting of multi-layer cloud devices, this caused a long delay in response and transmission. When instructions are sent to the end device step by step, it often cannot meet its high-speed and short-latency requirements

[0011] In the second aspect, the current cloud architecture, because cloud devices are set up based on cloud computing architecture, generally adopts data sharing management in the process of data transmission and processing, while in the field of traffic management, because low-level devices are directly connected to The equipment directly related to traffic conditions needs to collect, analyze and give instructions in real time in a timely and rapid manner. Therefore, the computing power concentration of the equipment is required to be higher. If the distributed computing power is used for data sharing between cloud devices , often resulting in insufficient resources to meet the needs of real-time data processing

However, if the solution of centralized data storage and processing is adopted between cloud devices, it will inevitably lead to high equipment deployment and maintenance costs, and the contradiction between the two needs to be overcome urgently

[0012] In the third aspect, in the existing traffic control cloud architecture, it often only focuses on the construction of a large control closed-loop from the top-level cloud device to the bottom-end device, while ignoring the consideration of the differences between low-level devices and high-level devices from the perspective of "side". High-efficiency transmission, fast processing, and short-latency response requirements

If the low-level equipment is only generally included in the entire large control closed loop, its resources are usually occupied by the high-level equipment (sometimes not in the running state, but in the waiting state for instructions to the high-level equipment), causing the low-level equipment to be unable to give full play to their high efficiency. Dealing with the role of "edge" level tasks

And based on this, the inventor of the present application further considered that if a small control closed loop on the "side" side is constructed, it will easily cause delays in the response to the entire large control closed loop control, and the contradiction between the two also needs to be resolved urgently

Images