07,22,2026 0 views
【Smart CityAttention to online enterprises】Recently, the new AI emergency intelligent agent system for Guangdong Guangzhongjiang Expressway was officially launched. The system relies on big model technology to create exclusive "digital employees" and comprehensively reconstruct the emergency response mode of the entire chain of highway emergencies.
At 18:24 on July 4th, a small car suddenly collided with the guardrail on the Chicao Interchange ramp of Guangzhongjiang Expressway, occupying the right lane. The traffic flow on site is dense, and if there is a slight delay in handling it, it is highly likely to trigger a chain of rear end collisions, and the risk of large-scale road congestion is imminent.
However, this time, there were no continuous phone ringing in the monitoring center, only a light touch of the Alt key, and the digital employees were synchronized on duty, completing the closed-loop disposal of the accident in 40 minutes.
With one Alt key, three "digital employees" will be on duty simultaneously
The monitoring personnel press the Alt shortcut key to initiate voice interaction, and the system's built-in event assistant, AI assistant, and management intelligent agent three digital employees synchronize to their posts, fully automating the disposal work.
The event assistant intelligent agent receives voice descriptions in real-time, automatically extracts accident time, station number, license plate, location and other information, generates standardized initial reports in a structured manner, automatically annotates missing information and reminds to supplement; Synchronize the retrieval of surveillance footage from the affected road section, match it with a dedicated digital contingency plan for ramp accidents, decompose and handle tasks step by step, and automatically generate notification templates.
The AI assistant intelligent agent synchronously retrieves the global emergency resource topology map, matches the nearest road administration, rescue, and collision buffer vehicle teams based on the accident location, calculates the optimal arrival route and expected duration, and outputs accurate scheduling suggestions.
One click management of intelligent agents to launch a "multi-party" online collaborative team, with traffic police, road administration, fire protection, medical, and maintenance units synchronously receiving disposal instructions. The arrival time and on-site disposal screen of each unit are transmitted in real-timemonitoring dashboardThe system automatically synchronizes with information boards along the route, Gaode, Baidu, and Tencent Maps to release speed reduction and lane change prompts, and diverts remote traffic in advance.
The entire scheduling process is seamless, with automatic tracking of all notifications, reports, and scheduling operations, and clear and traceable rescue sequences. After 40 minutes, the on-site dangerous situation was completely resolved, and the road resumed normal traffic. There were no manual forms or cross system switching operations throughout the entire process.
From "making phone calls" to "pressing the keyboard", what has changed is not only the operation mode, but also a deep reconstruction of the entire emergency logic
In the past, in case of emergencies, duty personnel had to switch back and forth between multiple independent systems, manually input and repeatedly verify; After a dangerous situation occurs, make phone calls one by one and repeatedly send notifications in WeChat groups. Information is scattered, the chain is lengthy, omissions, incorrect filling, and no trace of the process occur, and secondary accidents and compliance risks are closely related.
The newly launched AI intelligent agent system adopts intranet deployment and lightweight interfaces to adapt to existing mechanical and electrical equipment, which can be quickly implemented without large-scale hardware replacement. It covers three core operational scenarios: accident alarm duty, cross departmental linkage scheduling, and dual line prevention and control of road risks. It reconstructs emergency response logic from the bottom layer and realizes the transformation from "manual errand" to "automatic data flow".
Six sets of numbers to quantify the hard core effectiveness of this digital upgrade:
A new AI intelligent system has been established to build a fully closed-loop intelligent system of "perception, decision-making, execution, and review". It has six core automation capabilities: vectorized matching of contingency plans, automatic event registration, multi-party collaborative notification, multi-level intelligent reporting, resource mapping scheduling, and one click report generation
The disposal efficiency has been significantly accelerated: the entire process of event disposal has been shortened by more than 30%, and the cross departmental collaborative response time has been increased by 40%;
Manual operation significantly reduces workload: event registration steps are reduced by 50%, reporting and filling time is reduced by 70%, and over 60% of repetitive mechanical work is undertaken by AI;
Comprehensive improvement of process standardization: The standardization rate of event handling processes has increased by over 60%, and the entire process data is 100% traceable and 90% quantifiable for assessment;
Effective reduction of safety risks: events are detected earlier, remote traffic flow is diverted in advance, and the risk of secondary road accidents is significantly reduced;
Human value transformation and upgrading: Automatically complete monthly, quarterly, and annual event statistics and review reports, allowing monitoring personnel to detach from mechanical form filling work and focus on high-value tasks such as road surface analysis and on-site command;
Lower deployment threshold: Lightweight and compatible with existing video, gantry, meteorological, and telephone equipment, data can be stored privately within the intranet without leaving the domain, meeting the requirements of security, information and innovation compliance in the transportation industry.
