Intersection signal control mobile tuning device and method based on edge calculation

Abstract

The invention provides an intersection signal control mobile tuning device based on edge calculation. The device comprises a multi-source information receiving and storing unit, an edge calculation unit and a signal tuning unit based on a deep neural network. The multi-source information receiving and storing unit receives intersection real-time state data sent by roadside sensing equipment in real time through an edge 5G communication network and stores the intersection real-time state data; the edge calculation unit is used for receiving the intersection real-time state information acquiredby the multi-source information receiving and storing unit and processing the intersection real-time state information; and the signal tuning unit based on the deep neural network adjusts and optimizes the intersection signal based on the data processing result. The mobile tuning device provided by the invention can tune and optimize the intersection of a traffic system, and when the traffic system is jammed, the signal tuning unit of the key intersection at the moment can be built in the mobile tuning device and moved to the intersection to be tuned and optimized, so that the operation efficiency of the key intersection is improved, and the jam of the traffic system is relieved.

Description

technical field [0001] The invention belongs to the field of traffic control, and in particular relates to an intersection signal control mobile optimization device and method based on edge computing. Background technique [0002] With the development of economy, the number of urban motor vehicles has increased significantly, and urban traffic congestion and congestion often occur. As a key node of traffic flow convergence and evacuation, intersections greatly affect the safety and efficiency of urban traffic system operation. Traditional intersection signal control is mostly timing signal control based on experience. Faced with the dynamics and complexity of traffic flow at intersections, traditional signal control schemes often cannot meet the requirements for safety and efficiency at intersections, and are likely to cause congestion. Congestion will affect the safety and overall operating efficiency of the traffic system. [0003] At present, in the face of problems such...

AI Technical Summary

Problems solved by technology

Traditional intersection signal control is mostly timing signal control based on experience. Facing the dynamics and complexity of traffic flow at intersections, traditional signal control schemes often cannot meet the requirements for safety and efficiency at intersections, and are likely to cause congestion. Congestion, which affects the safety and overall operational efficiency of the traffic system

[0003]Currently facing problems such as congestion and congestion at intersections, traffic management departments often adopt the method of manual adjustment of signal lights on site, although the method of manual adjustment of signal lights has certain effects , but manual adjustment of signal lights is not stable and will increase safety hazards at intersections

In order to better solve the traffic congestion problem in the traffic system, there is an existing method of controlling key intersections using cloud-based control. The control cannot meet the real-time requirements of intersection control

In order to enable the intersection signal optimization device to respond to the intersection status information in real time, it is necessary to install a signal optimization device on the edge of the intersection, but installing a signal optimization device on each intersection edge will result in a great waste of resources. For the entire city's traffic system, key intersections are dynamically changing, and fixed signal optimization devices at the edge of some intersections cannot meet the needs of traffic system optimization

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