Smart city tunnel traffic emergency supervision internet of things large model system and method

The IoT-based big data model system for emergency traffic monitoring in smart cities tunnels solves the passive response problem of existing tunnel traffic monitoring systems by constructing vehicle fusion feature vectors and predicting congestion, proactively adjusting traffic lights and issuing detour routes, and realizing an efficient transformation from event identification to traffic management, thereby improving the initiative and emergency response capabilities of traffic management.

CN122116644APending Publication Date: 2026-05-29CHENGDU QINCHUAN IOT TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHENGDU QINCHUAN IOT TECH CO LTD
Filing Date
2026-04-21
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

The existing urban tunnel traffic monitoring system has limited means of traffic incident perception and passive response, making it difficult to proactively prevent and fundamentally alleviate congestion. Its control measures are limited to local road sections and cannot effectively predict and regulate regional traffic conditions.

Method used

By using the IoT big data model system for emergency monitoring of tunnel traffic in smart cities, a fusion feature vector of vehicles is constructed to identify abnormal events, predict upstream congestion, and proactively prevent congestion through traffic light control and detour route prompts. Combined with real-time traffic conditions, guidance information is released to achieve proactive traffic management.

Benefits of technology

Accurately identify minor anomalies within tunnels, predict congestion spread trends in advance, proactively adjust traffic lights to restrict traffic flow, shorten reaction time, reduce the risk of regional traffic paralysis, and improve regional road network efficiency and emergency response capabilities.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application relates to the field of traffic supervision, and provides a smart city tunnel traffic emergency supervision Internet of Things large model system and method, the method comprising the following steps: constructing a fusion feature vector of a vehicle in a target tunnel according to multidimensional data of the target tunnel; determining an abnormal event according to the fusion feature vector and congestion data of the target tunnel; predicting an upstream congestion condition of the target tunnel according to the abnormal event, the congestion data and surrounding traffic flow data of the target tunnel; and generating a signal control instruction comprising a passing time length according to the upstream congestion condition, the signal control instruction being configured to control a target signal lamp to maintain a target state for the passing time length, the target signal lamp being a signal lamp on a key road section in a direction leading to the target tunnel. The application can realize a leap from passive control of 'getting stuck at the source' to active dredging of 'avoiding the congestion point', provide clear and feasible alternative solutions for drivers, and significantly improve the overall passing efficiency and emergency disposal capability of a regional road network.
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