Emergency control method and system for emergency event in exit direction, medium and product

Abstract

The invention discloses an exit direction emergency event emergency control method and system, a medium and a product, and relates to the field of intelligent traffic Internet of Things, and the method comprises the steps: obtaining event alarm data uploaded by a user terminal, and recognizing an event position and an event type in the event alarm data; acquiring traffic flow data of an exit area corresponding to the event position, and generating an event influence result according to the event type and the traffic flow data; generating a traffic guidance scheme and a signal timing adjustment scheme according to the event influence result and the traffic flow data; generating navigation guidance corresponding to a plurality of sections around the event position based on the traffic guidance scheme, and sending the navigation guidance to the user terminal; and adjusting the traffic signal device of the exit area corresponding to the event position according to the signal timing adjustment scheme. According to the invention, the traffic jam alleviation control efficiency can be improved.

Description

Technical Field

[0001] This application relates to the field of intelligent transportation Internet of Things, and in particular to an emergency control method, system, medium and product for emergency events in the exit direction. Background Art

[0002] With the acceleration of the urbanization process, the traffic flow continues to grow, and problems such as traffic congestion and traffic accidents on urban roads have become increasingly prominent, seriously affecting the operation efficiency and safety of urban traffic. Especially when sudden emergency events (such as traffic accidents, natural disasters, road construction, etc.) occur, whether the traffic signal control system can respond quickly and adjust effectively plays a crucial role in alleviating traffic pressure and ensuring road safety.

[0003] In the related art, some systems adjust the signal timing plan through a preset event response mode. When a specific traffic event is detected, the system will make a fixed adjustment to the signal lights according to the pre-programmed rules to preferentially guide the traffic flow in a specific direction. Generally, the yellow light is used to flash instead of the red and green lights on the main line for warning, and cooperate with on-site staff to conduct traffic guidance.

[0004] However, the fixed signal timing in the related art lacks accurate perception of real-time traffic flow changes, and there is a delay in the arrival of staff, resulting in low efficiency in alleviating traffic congestion. Summary of the Invention

[0005] This application provides an emergency control method, system, medium and product for emergency events in the exit direction, which is used to improve the efficiency of alleviating traffic congestion.

[0006] In a first aspect, this application provides an emergency control method for emergency events in the exit direction, which is applied to a traffic control system. The method includes: obtaining event alarm data uploaded by a user terminal, and identifying the event location and event type in the event alarm data; obtaining traffic flow data of the exit area corresponding to the event location, and generating an event impact result according to the event type and the traffic flow data; generating a traffic guidance plan and a signal timing adjustment plan according to the event impact result and the traffic flow data; generating navigation guidance for multiple sections around the event location based on the traffic guidance plan, and sending the navigation guidance to the user terminal; adjusting the traffic signal device of the exit area corresponding to the event location according to the signal timing adjustment plan.

[0007] In the above embodiment, the traffic control system realizes rapid response and precise control of emergency events by obtaining event alarm data in real time, identifying the location type, generating impact assessment and response plans in combination with traffic flow data, and coordinating navigation guidance and signal timing at the same time; it can dynamically adjust the guidance strategy according to the actual situation, avoid the limitations of the traditional fixed mode, and improve the traffic management efficiency and road passing capacity.

[0008] In some embodiments in combination with some embodiments of the first aspect, the steps of obtaining the event alarm data uploaded by the user terminal and identifying the event location and event type in the event alarm data specifically include: obtaining the event alarm data uploaded by the user terminal and identifying the initial location in the event alarm data; cross-verifying the event alarm data with the real-time monitoring data of the initial location and the traffic event information provided by the third-party platform to obtain a verification result; determining a credibility score for the event alarm data based on the verification result, screening out the event alarm data with a credibility score higher than a preset credibility threshold as the alarm marked event; and determining the event location and event type corresponding to the alarm marked event according to the real-time monitoring data and the traffic event information.

[0009] In the above embodiments, the traffic control system ensures the accuracy and reliability of the event alarm data through a multi-source data cross-verification and credibility scoring mechanism, combining real-time monitoring and third-party platform information; effectively reduces the impact of false alarms, and improves the pertinence and timeliness of the system response.

[0010] In some embodiments in combination with some embodiments of the first aspect, the steps of obtaining the traffic flow data of the exit area corresponding to the event location and generating an event impact result according to the event type and the traffic flow data specifically include: obtaining the traffic flow data and road characteristics of the exit area corresponding to the event location, inputting the traffic flow data and road characteristics into a traffic state assessment model to obtain an estimated impact range; determining the event occurrence time according to the event alarm data, and determining the corresponding secondary traffic wave effect in combination with the historical traffic data of the exit area according to the event type, event location and event occurrence time; and generating an event impact result according to the estimated impact range and the secondary traffic wave effect.

[0011] In the above embodiments, the traffic control system realizes a comprehensive assessment of the event impact by integrating traffic flow data, road characteristics and historical data, using an assessment model to predict the impact range, and combining the secondary traffic wave effect, improving the accuracy and predictability of the early warning.

[0012] In some embodiments in combination with some embodiments of the first aspect, before the steps of obtaining the event alarm data uploaded by the user terminal and identifying the event location and event type in the event alarm data, the method further includes: obtaining the real-time traffic state data of multiple exit areas; determining emergencies based on the real-time traffic state data and historical traffic flow data; and sending a prompt message including the emergencies to the management terminal.

[0013] In the above embodiments, the traffic control system realizes the active identification and early warning of emergencies by continuously monitoring the real-time traffic state of multiple exit areas and analyzing and comparing with historical data, improving the prevention ability and management efficiency of the system.

[0014] In some embodiments in combination with some embodiments of the first aspect, after the step of determining an emergency event based on real-time traffic status data and historical traffic flow data, the method further includes: obtaining license plate information of the vehicle corresponding to the emergency event; determining owner information based on the license plate information, and connecting the mobile terminal corresponding to the owner information to the management terminal.

[0015] In the above embodiments, the traffic control system realizes precise docking and efficient communication for emergency event handling by quickly locating the involved vehicle and establishing a direct connection channel with the vehicle owner, thereby improving the efficiency of emergency event handling.

[0016] In some embodiments in combination with some embodiments of the first aspect, after the step of adjusting the traffic signal devices in the exit area corresponding to the event location according to the signal timing adjustment plan, the method further includes: obtaining traffic flow adjustment data of the exit area corresponding to the event location; correcting the signal timing adjustment plan according to the traffic flow adjustment data.

[0017] In the above embodiments, the traffic control system realizes continuous optimization and fine adjustment of the control strategy by obtaining traffic flow adjustment data in real time and dynamically correcting the signal timing plan, ensuring the real-time performance and effectiveness of traffic control.

[0018] In some embodiments in combination with some embodiments of the first aspect, after the step of obtaining traffic flow adjustment data of the exit area corresponding to the event location, the method further includes: determining the traffic guidance effect of the exit area based on the traffic flow adjustment data; generating a traffic guidance record after the traffic guidance effect indicates that the event handling is completed.

[0019] In the above embodiments, the traffic control system establishes a complete file of the event handling process through real-time evaluation and recording of the traffic guidance effect, provides data support for subsequent optimization, and improves the continuous improvement ability of the system.

[0020] In a second aspect, an embodiment of the present application provides a traffic control system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, and the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the traffic control system to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product containing instructions, when the above computer program product runs on a traffic control system, enabling the above traffic control system to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0022] Fourthly, an embodiment of the present application provides a computer-readable storage medium, including instructions that, when running on a traffic control system, cause the traffic control system to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0023] It can be understood that the traffic control system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiments of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, and will not be elaborated here.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Due to the adoption of a multi-dimensional dynamic response mechanism based on real-time event alarm data, combined with accurate location recognition, traffic flow analysis, and adaptive control strategies, it is possible to achieve rapid perception and accurate positioning of emergency events, and generate the optimal evacuation plan according to the actual situation, effectively solving the problems of response lag and rough regulation caused by relying on preset modes in the related art. Furthermore, the real-time, accuracy, and efficiency of traffic control are realized, and the processing efficiency of emergency events and the road passing capacity are improved.

[0025] 2. Due to the adoption of an active early warning mechanism based on multi-region real-time traffic state monitoring and historical data comparison, combined with the function of pushing emergency event recognition and management terminals, it is possible to detect abnormalities in a timely manner and take corresponding measures at the initial stage of the event, effectively solving the problems of passive waiting for alarms and missing the best disposal opportunity in the related art. Furthermore, the early warning and rapid response of emergency events are realized, and the predictability and initiative of traffic management are improved.

[0026] 3. Due to the adoption of a dynamic optimization mechanism based on real-time traffic flow adjustment data, combined with the function of continuously correcting the signal timing plan, it is possible to continuously adjust and optimize the control strategy according to the actual traffic conditions, effectively solving the problems of fixed control schemes and inability to adapt to dynamic changes in the related art. Furthermore, the refinement and self-adaptability of traffic control are realized, and the continuous effectiveness of control measures is ensured. Description of the Drawings

[0027] Figure 1 is a flowchart of an emergency event emergency control method in the exit direction in an embodiment of the present application; Figure 2 is another flowchart of an emergency event emergency control method in the exit direction in an embodiment of the present application; Figure 3 is a schematic structural diagram of an entity device of a traffic control system in an embodiment of the present application. Detailed Embodiments

[0028] The terms used in the following embodiments of this application are only for the purpose of describing specific embodiments and are not intended to limit this application. As used in the specification of this application, the singular forms "a", "an", "above-mentioned", "the", and "this" are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in this application refers to any or all possible combinations including one or more of the listed items.

[0029] Hereinafter, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as implying or suggesting relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the embodiments of this application, unless otherwise specified, the meaning of "a plurality" is two or more.

[0030] For ease of understanding, the application scenarios of the embodiments of this application are introduced below.

[0031] At the exit ramp of the urban expressway, congestion problems often occur due to traffic accidents or vehicle failures. Especially during the morning and evening rush hours, once an accident occurs, it will quickly cause large-scale traffic delays. For example, after a traffic accident at the exit ramp of the South Second Ring Road in a certain city, due to the inability to dredge in time, it led to large-area congestion on the main road and the ramp, and the delay time exceeded 2 hours, affecting tens of thousands of commuters. In this case, how to quickly respond to emergencies and achieve efficient dredging has become an urgent problem to be solved.

[0032] In the related art, the emergency disposal of emergencies in the exit area can be achieved by adopting a preset signal timing scheme and on-site manual dredging. The following introduces the scenario of using the emergency control method for exit direction emergencies in the related art.

[0033] In the related art, when an accident occurs at the exit ramp of the South Second Ring Road, the system can only activate a preset emergency plan: switch the upstream signal lights on the main road to yellow flashing, and at the same time wait for the traffic police to arrive at the scene for manual dredging. This method has obvious defects: the preset plan cannot be flexibly adjusted according to the actual traffic conditions, and the yellow flashing may cause the traffic to be more chaotic; and it takes time for the manual dredging to arrive at the scene, missing the best disposal opportunity, resulting in the continuous expansion of the congestion range.

[0034] By using the emergency control method for exit direction emergencies in the embodiments of this application, through multi-source data verification, real-time traffic flow analysis, and dynamic optimization control, accurate and rapid emergency response is achieved, which not only improves the disposal efficiency but also prevents the occurrence of secondary congestion. The following introduces the scenario of using the emergency control method for exit direction emergencies in this application.

[0035] After adopting the solution of this application, after the system receives an accident alarm, it immediately verifies the accident location and type through multi-source data, and at the same time analyzes the real-time traffic conditions of the surrounding road network. Based on the traffic flow characteristics, the system automatically generates an optimal diversion plan: adjust the signal timing of multiple upstream intersections to guide some traffic flows to divert in advance; push personalized navigation suggestions to vehicles on surrounding roads to avoid congested areas; at the same time, predict the risk of secondary congestion and adjust the traffic capacity of relevant sections in advance. This intelligent collaborative control improves the diversion efficiency.

[0036] It can be seen that by adopting the emergency event emergency control method in the exit direction in the embodiment of this application, while achieving fast response, it can also effectively solve the problem of low disposal efficiency of the traditional fixed mode, and thus realize the intelligence and refinement of traffic management.

[0037] For ease of understanding, the method provided in this embodiment will be described in terms of its process in combination with the above scenario. Please refer to Figure 1 , which is a schematic flowchart of the emergency event emergency control method in the exit direction in the embodiment of this application.

[0038] S101. Obtain the event alarm data uploaded by the user terminal, and identify the event location and event type in the event alarm data.

[0039] Among them, the user terminal refers to a mobile device installed with a traffic event alarm application program, such as a smart phone, a vehicle-mounted device, etc.; the event alarm data refers to a data packet containing information such as the event occurrence time, location, type, etc. uploaded by the user through the terminal, and is used to report traffic events to the traffic control system; the event location represents the specific geographical coordinate location where the traffic event occurs, including longitude and latitude information, road name, kilometer post number, etc.; the event type refers to the specific category of traffic events, such as traffic accidents, vehicle failures, road construction, etc.

[0040] When the traffic control system detects that the user terminal triggers the event alarm function, it starts to execute this step. Specifically, the traffic control system first receives the event alarm request sent by the user terminal, and parses the initial event information contained in the request; then combines the real-time data collected by devices such as video surveillance and electronic police at the accident location to verify the event information; at the same time, queries whether the third-party platform (such as traffic police, rescue, etc.) has received relevant alarms; then through multi-source data comparison and analysis, confirms the authenticity of the event; finally, based on the verification result, accurately locates the event occurrence location and determines the event type according to the actual situation on the site.

[0041] In some embodiments, the acquisition and recognition processing of event alarm data can be implemented in various ways: Optionally, the traffic control system receives the structured event data uploaded by the user terminal through a dedicated API, extracts the location and type fields in the data packet, performs location mapping in combination with the geographic information system, and determines the event type through a preset event classification model; Optionally, the traffic control system analyzes the monitoring video images using a deep learning model, identifies abnormal events, extracts event features, and performs cross-verification in combination with the user alarm information to finally determine the event location and type. It can be understood that the event alarm data can also be simple call data, and other data collection and analysis methods can also be used to implement the acquisition and recognition of event information, which is not limited here.

[0042] S102. Obtain the traffic flow data of the exit area corresponding to the event location, and generate an event impact result according to the event type and the traffic flow data.

[0043] Among them, the exit area refers to the traffic section where the event occurs and its upstream and downstream related sections, including the main road, ramp, and surrounding road network; the traffic flow data refers to various data indicators reflecting the traffic operation status of the area, including traffic volume, vehicle speed, occupancy rate, density, etc.; the event impact result refers to the comprehensive evaluation result of the possible traffic impact range, degree, and duration of the event.

[0044] After the traffic control system completes the identification of the event location and type, it immediately starts to evaluate the event impact. Specifically, the traffic control system first collects real-time traffic flow data through devices such as vehicle detectors and video monitoring in the area; then constructs a traffic state evaluation model in combination with static parameters such as road geometric features and traffic capacity; at the same time, analyzes similar event cases in historical data and extracts impact features; then predicts the spatio-temporal impact range of the event based on a deep learning algorithm; finally, generates a multi-dimensional impact evaluation result by integrating external factors such as weather and time period.

[0045] It should be noted that the traffic state evaluation model is trained based on historical traffic flow data (traffic volume, vehicle speed, density, etc.) and road characteristic data (number of lanes, design speed, etc.), and optimizes the parameters by minimizing the error between the predicted state and the actual state. The model adopts a deep neural network structure including a time series feature extraction layer, a spatial feature extraction layer, and a multi-layer perceptron, and captures feature correlations through an attention mechanism. When in use, real-time traffic flow data and road parameters are input, and evaluation indicators such as traffic state level, congestion degree, and traffic capacity, as well as short-term evolution trends, are output to provide support for traffic control decisions. The training criteria include state classification accuracy (≥95%), congestion prediction accuracy (error ≤ 10%), and evolution trend prediction accuracy (≥90%).

[0046] In some embodiments, the evaluation of the event impact can be achieved in various ways: Optionally, based on the traffic wave propagation theory, an event impact propagation model is established, and the Monte Carlo simulation method is used to predict the impact scope and degree under different scenarios. Combining factors such as traffic flow density and vehicle speed distribution, the congestion risk of key sections is calculated. Optionally, a spatio-temporal big data analysis method is adopted. Combining with the historical case library, the impact patterns of similar events are extracted, and the impact evolution process of the current event is predicted through machine learning algorithms. It can be understood that other mathematical models and algorithms can also be used to achieve accurate evaluation of event impacts, which are not limited here.

[0047] It should be noted that the event impact propagation model is trained using a historical event case library (including information such as event type, location, impact scope, and duration). The parameters are optimized by comparing the predicted impact scope with the actual records. The model adopts a hybrid architecture combining physical-driven and data-driven, including a traffic wave propagation theory module and a machine learning module, and combines factors such as road network topology, traffic flow characteristics, and external conditions. When used, the basic information of the event and the current road network state are input, and the spatio-temporal evolution process of the impact is output, including the diffusion speed, congestion degree, and prediction of secondary effects. The training criteria include the prediction accuracy of the spatial range (≥90%) and the prediction error of the time duration (≤15 minutes).

[0048] S103. Generate a traffic guidance plan and a signal timing adjustment plan according to the event impact result and traffic flow data.

[0049] Among them, the traffic guidance plan represents the traffic flow diversion strategy formulated to relieve traffic congestion, including diversion routes, detour suggestions, etc.; the signal timing adjustment plan refers to the timing and phase adjustment plan for traffic lights in the affected area; the process of generating the plan involves solving multi-objective optimization problems.

[0050] After obtaining the event impact evaluation result, the traffic control system starts to formulate a response plan. Specifically, the traffic control system first divides the control area based on the impact result and determines the key control nodes; then combines the regional road network topology structure to design a feasible diversion plan; at the same time, comprehensively considers the remaining traffic capacity of each section to optimize the signal timing parameters; then verifies the feasibility of the plan through traffic simulation; finally, forms a complete control plan including specific implementation steps.

[0051] In some embodiments, the generation of the control scheme can be achieved in various ways: Optionally, a multi-objective optimization model is constructed using a heuristic algorithm, and the optimal signal timing scheme and diversion strategy are solved according to objectives such as minimizing the overall delay and maximizing the service level of key road sections; Optionally, based on the reinforcement learning method, a regional traffic collaborative control model is established, and the control strategy is continuously optimized through online learning to achieve the intelligent management of complex road networks. It can be understood that other intelligent optimization algorithms can also be used to generate the control scheme, which is not limited here.

[0052] It should be noted that the traffic control system adopts the objective optimization method, constructs a mathematical optimization model by comprehensively considering the constraints such as the road capacity, traffic demand distribution, and safety margin within the event impact area. The objective function of the model includes multiple dimensions such as minimizing the overall delay and maximizing the service level of key road sections. First, the current saturation of each road section is determined based on the flow-density relationship, and the remaining traffic capacity is calculated. Then, the priority diversion levels are divided according to the event impact results, and the traffic flow is allocated to different paths according to the priority. Next, the optimal diversion path combination is solved through the genetic algorithm, and at the same time, the corresponding signal timing parameters, including the cycle length, green ratio, and phase difference, are calculated using the Webster method. Finally, the feasibility of the scheme is verified through simulation, and parameter fine-tuning will be carried out if necessary. For example, when an accident occurs on a certain ramp, the system will first calculate the remaining capacity of the surrounding road network, select 3-4 diversion channels with the best traffic conditions, and cooperate with the signal timing adjustment to guide the vehicles to divert reasonably.

[0053] S104. Generate navigation guidance for multiple sections around the corresponding event location based on the traffic guidance scheme, and send the navigation guidance to the user terminal.

[0054] Among them, the navigation guidance refers to the personalized route suggestion information provided to the user, including the optimal detour route, estimated travel time, real-time traffic conditions, etc.; the surrounding sections refer to the relevant road sections affected by the event, including the upstream merging section, downstream diversion section, etc.; the user terminal includes in-vehicle navigation devices, mobile phone navigation APPs, etc.

[0055] After the traffic control system determines the traffic guidance scheme, it starts to push personalized navigation suggestions. Specifically, the traffic control system first screens the applicable diversion routes according to the vehicle's current location and destination information; then calculates the real-time traffic conditions of each route, including congestion status, estimated travel time, etc.; at the same time, based on the user's personalized needs, such as preference for highways or surface roads; then generates navigation guidance containing detailed paths and key tips; finally, sends the guidance information to the relevant user terminals through the message push mechanism.

[0056] In some embodiments, the generation and push of navigation guidance can be achieved in various ways: Optionally, a multi-source traffic condition data fusion technology is adopted, combined with historical travel patterns, to formulate differentiated navigation strategies for different types of vehicles, and the timeliness of navigation suggestions is ensured through real-time traffic condition updates; Optionally, based on swarm intelligence algorithms, a collaborative navigation model is established, and by optimizing the overall road network load distribution, the formation of new congestion points is avoided. It can be understood that other intelligent navigation algorithms can also be used to generate personalized guidance, which is not limited here.

[0057] It should be noted that the traffic control system constructs an accurate path planning model based on the travel time reliability theory, comprehensively considering factors such as the real-time traffic state of sections, historical travel time distribution, and user personalized needs. First, the Bayesian estimation method is used to calculate the expected travel time and its reliability index of each section at the current time period in combination with historical data. Then, based on the multi-constrained shortest path algorithm, with the goal of minimizing the total travel time and combining the path reliability requirements, several candidate path plans are generated. Next, according to the user's historical trajectory characteristics, their path preferences are extracted, such as the tendency to take the highway or the feeder road, etc., and the candidate plans are sorted personalizedly. Finally, the recommended path is converted into segmented navigation instructions, including key turning points, estimated travel time and other information. For example, the system will push 2-3 suitable detour routes according to the destinations of different vehicles and update the traffic conditions in real time.

[0058] S105. Adjust the traffic signal devices in the exit area corresponding to the event location according to the signal timing adjustment plan.

[0059] Among them, the traffic signal device refers to the signal lamp equipment that controls vehicle traffic, including main road signal lamps, ramp signal lamps, etc.; the signal timing adjustment involves the dynamic adjustment of parameters such as cycle, phase, and green signal ratio; the exit area includes all signal-controlled intersections within the scope affected by the event.

[0060] After the traffic control system generates the timing plan, it immediately executes signal adjustment. Specifically, the traffic control system first confirms the control authority of the affected signal intersections; then, in the order of priority, gradually adjusts the signal parameters of each intersection; at the same time, monitors the actual control effect after the parameter adjustment; then dynamically optimizes the timing plan according to the feedback data; finally, on the premise of ensuring safety, realizes the coordinated control of regional signal timing.

[0061] In some embodiments, signal timing adjustment can be achieved in a variety of ways: optionally, an adaptive control algorithm is used to dynamically adjust the signal cycle and phase ratio based on real-time detection data, and the control effect is continuously optimized through a feedback mechanism; optionally, a regional coordinated control model is established to achieve timing linkage between multiple intersections, and the regional traffic efficiency is improved through a signal optimization algorithm. It is understandable that other traffic control algorithms can also be used to achieve intelligent adjustment of signal timing, which is not limited here.

[0062] In the above embodiment, efficient handling of emergency events is achieved through real-time data analysis and multi-dimensional collaborative control. In practical applications, this method can dynamically adjust the control strategy according to different scenarios to ensure the pertinence and effectiveness of the handling plan. The following is a supplement to the scenario of this embodiment.

[0063] In a specific application, the system not only realized the basic diversion function, but also demonstrated strong scalability. When it was detected that a ramp accident might affect the exit of a subway station, the system automatically linked up with the subway operation department to adjust the passenger diversion plan for the relevant stations; at the same time, based on the historical case library, the system predicted possible chain reactions and deployed emergency resources at key nodes in advance. The system also evaluated the diversion effect in real time and dynamically optimized the control strategy, ultimately shortening the diversion time originally expected to be 2 hours to 45 minutes, fully demonstrating the advanced nature of this solution.

[0064] After combining the above scenarios, the following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the emergency control method for emergency events in the exit direction in an embodiment of the present application.

[0065] S201. Acquire real-time traffic status data of multiple exit areas.

[0066] Among them, the exit area refers to the intersection of the city's main roads and expressways and its surrounding areas, including ramps, auxiliary roads and connecting lines; real-time traffic status data refers to various dynamic data reflecting the current traffic operation conditions, including traffic flow, average speed, vehicle density, queue length, etc.; data acquisition equipment includes coil detectors, video surveillance, radar detectors, etc.

[0067] The traffic control system continuously performs this step during daily operation. Specifically, the traffic control system first collects basic traffic parameters in real time through multiple types of detection equipment distributed in each exit area; then cleans, verifies and completes the collected raw data; at the same time, it integrates floating vehicle data from a third-party platform; then organizes and stores the processed data according to the time and space dimensions; and finally establishes a real-time data stream to ensure the continuous update of traffic status information.

[0068] In some embodiments, the acquisition and processing of real-time traffic state data can be achieved in various ways: Optionally, a distributed data acquisition architecture is adopted. By establishing a dynamic self-organizing network of data acquisition nodes, intelligent scheduling of acquisition devices and real-time transmission of data are realized. At the same time, outlier values are removed using data cleaning algorithms, and multi-source information is integrated through data fusion algorithms. Optionally, based on edge computing technology, an intelligent processing unit is deployed at the data acquisition end to achieve preprocessing and preliminary analysis of data, reduce the transmission load through data compression algorithms, and optimize the data acquisition efficiency using an adaptive sampling strategy. It can be understood that other data acquisition and processing methods can also be used to achieve real-time monitoring of traffic states, which are not limited here.

[0069] S202. Determine an emergency event based on the real-time traffic state data and historical traffic flow data.

[0070] Among them, the historical traffic flow data represents the traffic operation data collected by the system in the long term, including traffic flow characteristics under different time periods, weather conditions, holidays, etc. An emergency event refers to various events that cause abnormal traffic states, including traffic accidents, vehicle failures, traffic jams, etc. The determination process involves anomaly detection and event recognition.

[0071] After obtaining the real-time traffic state data, the traffic control system continuously executes this step. Specifically, the traffic control system first performs time series analysis on the real-time data to extract the change characteristics of key traffic parameters; then compares with the historical data of the same period to establish a benchmark model of the normal traffic state; at the same time, combines external factors such as weather and activities to establish a multi-dimensional anomaly discrimination model; then identifies abnormal patterns through deep learning algorithms; finally, determines whether an emergency event is formed according to the degree and duration of the anomaly.

[0072] In some embodiments, the detection and determination of emergency events can be achieved in various ways: Optionally, a time series prediction model based on a long short-term memory network (LSTM) is constructed. By comparing the deviation between the actual traffic state and the predicted value, an adaptive threshold is set for anomaly detection, and event classification and recognition are performed in combination with multi-dimensional feature vectors. Optionally, an inference mechanism based on a knowledge graph is adopted. Historical event cases are constructed into a knowledge base, and event attribution analysis of the current abnormal state is realized through similarity matching and causal reasoning. It can be understood that other intelligent analysis methods can also be used to achieve automatic identification of emergency events, which are not limited here.

[0073] In some embodiments, the traffic control system will contact the vehicle owner for processing, that is, the traffic control system will obtain the license plate information of the vehicle corresponding to the emergency event; determine the vehicle owner information according to the license plate information, and connect the mobile terminal corresponding to the vehicle owner information to the management terminal.

[0074] Among them, the license plate information represents the unique identification code of a motor vehicle, including the license plate number, vehicle type, etc.; the vehicle owner information refers to the data of all owners registered for the vehicle, including contact information, identity information, etc.; the mobile terminal represents the communication device used by the vehicle owner, such as a mobile phone, in-vehicle device, etc.; the management terminal refers to the control device used by the traffic management department.

[0075] The traffic control system executes this process after identifying the involved vehicle. Specifically, the traffic control system first collects clear license plate images through high-definition cameras or electronic police devices; then calls the vehicle management database for license plate recognition and information matching; at the same time, queries the valid contact information of the vehicle owner; then tries to establish contact with the vehicle owner through multiple channels; finally, on the premise of ensuring information security, establishes a real-time communication link between the vehicle owner's mobile terminal and the management terminal to achieve remote negotiation and processing.

[0076] In some embodiments, the vehicle owner contact and communication establishment can be achieved in multiple ways: Optionally, build a license plate automatic recognition system based on intelligent recognition technology, accurately extract license plate characters through deep learning algorithms, quickly locate vehicle owner information in combination with the vehicle database, and push contact requests through an encrypted channel; Optionally, adopt a multimodal communication system, establish a contact mechanism including multiple methods such as text messages, phone calls, APP push, etc., and ensure communication security through identity authentication to achieve instant communication between the management terminal and the vehicle owner. It can be understood that other communication methods can also be used to establish vehicle owner contact, which is not limited here.

[0077] S203. Send a prompt message including the emergency event to the management terminal.

[0078] Among them, the prompt message represents the detailed description data of the emergency event, including key information such as event type, location, time, impact degree, etc.; the management terminal refers to the control device used by the traffic management department, including workstations in the traffic command center, mobile law enforcement terminals, etc.; the information sending process involves data transmission and display.

[0079] The traffic control system immediately executes this step after confirming the emergency event. Specifically, the traffic control system first integrates the multi-dimensional information of the emergency event to generate an event description report in a standard format; then determines the priority of information push according to the event level; at the same time, generates differentiated information content for different levels of management personnel; then pushes the information to the relevant management terminal through a secure channel; finally, tracks the information reception status to ensure that important information is processed in a timely manner.

[0080] In some embodiments, the generation and transmission of prompt information can be achieved in various ways: Optionally, a multi-level early warning mechanism based on the severity of events is constructed, the event description is automatically compiled through intelligent text generation technology, a visual display is generated in combination with the geographic information system, and an encrypted channel is adopted to ensure the security of information transmission; Optionally, a distributed message push system is established to achieve targeted push to management terminals at different levels, the message confirmation mechanism is used to ensure the delivery of information, and at the same time, real-time update and interactive feedback of information are supported. It can be understood that other information processing methods can also be adopted to achieve intelligent push of event prompts, which are not limited herein.

[0081] S204. Obtain the event alarm data uploaded by the user terminal, and identify the event location and event type in the event alarm data.

[0082] Referring to step S101, the traffic control system will identify the event location and event type.

[0083] In some embodiments, the traffic control system will perform alarm verification, that is, the traffic control system will obtain the event alarm data uploaded by the user terminal and identify the initial location in the event alarm data; cross-verify the event alarm data with the real-time monitoring data of the initial location and the traffic event information provided by the third-party platform to obtain a verification result; determine the credibility score of the event alarm data based on the verification result, screen out the event alarm data with a credibility score higher than the preset credible threshold as the alarm marked event; determine the event location and event type corresponding to the alarm marked event according to the real-time monitoring data and traffic event information.

[0084] Among them, the initial location represents the geographical location information when the user reports the event; the real-time monitoring data refers to information such as video images collected by on-site monitoring devices; the third-party platform refers to the information systems of relevant departments such as traffic police and rescue; the credibility score represents a quantitative evaluation value of the event authenticity; the preset credible threshold refers to the lowest score standard for determining the credibility of the event.

[0085] The traffic control system executes this process immediately after receiving the event alarm. Specifically, the traffic control system first analyzes the location information contained in the alarm data; then calls all the monitoring resources around this location; at the same time, queries the real-time information of the third-party platform; then performs information integration through the multi-source data fusion algorithm; further calculates the credibility score based on the evidence theory; finally, accurately locates and classifies high-credibility events to form a standardized event description.

[0086] In some embodiments, the verification and processing of alarm information can be achieved in various ways: Optionally, a multi-source information fusion model based on D-S evidence theory is constructed. By setting the credibility weights of different information sources, the comprehensive credibility score is calculated, and the exact location of the event is determined by combining the spatial clustering algorithm; Optionally, a deep learning method is adopted to establish a multi-modal verification system including video analysis and text understanding. Through feature extraction and pattern matching, the accurate discrimination of the event type is realized. It can be understood that other data analysis methods can also be used to evaluate the credibility of alarm information, which is not limited here.

[0087] S205. Obtain the traffic flow data and road characteristics of the exit area corresponding to the event location, and input the traffic flow data and road characteristics into the traffic state assessment model to obtain the estimated influence range.

[0088] Among them, the road characteristics represent the static attribute parameters of the road, including the number of lanes, design speed, traffic capacity, etc.; the traffic state assessment model refers to a mathematical model for analyzing the traffic operation state, including the flow-density relationship, wave propagation characteristics, etc.; the estimated influence range is used to represent the spatial range and degree that the event may affect.

[0089] The traffic control system executes this step immediately after determining the event location. Specifically, the traffic control system first extracts the static feature data of the road network around the event location; then obtains the real-time traffic flow parameters of all detection points in the area; at the same time, combines topological features such as road grade and interchange type; then inputs these data into the pre-trained assessment model; finally, through simulation calculation, the spatio-temporal distribution prediction of the event impact is obtained.

[0090] In some embodiments, the traffic state assessment and influence range prediction can be achieved in various ways: Optionally, a traffic flow evolution model based on cellular automata is established. By setting different boundary conditions and parameters, the disturbance propagation process of the event on the traffic flow is simulated, and the change of the service level of the key section is calculated; Optionally, a road network state prediction model is constructed by using graph neural networks. Taking the road sections as nodes and the intersections as edges, the spatial correlation of the traffic flow is simulated through the message passing mechanism, and the diffusion range of the event impact is predicted. It can be understood that other traffic flow theories and models can also be used to accurately predict the influence range, which is not limited here.

[0091] It should be noted that the traffic control system will establish a hybrid evaluation model including macroscopic and microscopic characteristics based on the traffic flow propagation theory. At the macroscopic level, the LWR model is used to describe the relationship among traffic flow density, speed, and flow rate, and the basic flow characteristics are obtained through numerical solution. At the microscopic level, the cellular automaton model is introduced to depict the car-following behavior and lane-changing characteristics of individual vehicles. The model inputs include road geometric parameters (number of lanes, slope, etc.), traffic flow parameters (flow rate, speed, occupancy, etc.), and environmental parameters (weather, road conditions, etc.). The Kalman filter algorithm is used to achieve real-time parameter correction and improve the prediction accuracy. The model outputs include key indicators such as spatial influence range, congestion degree, and propagation speed. For example, when an accident occurs at a certain place on the main road, the system can accurately predict the specific range where the congestion will spread within 10 - 15 minutes.

[0092] S206. Determine the event occurrence time according to the event alarm data, and determine the corresponding secondary traffic wave effect in combination with the historical traffic data in the exit area according to the event type, event location, and event occurrence time.

[0093] Among them, the event occurrence time represents the exact occurrence moment of the traffic event; the secondary traffic wave effect refers to the chain reaction triggered by the initial event, including the congestion spread in the upstream section, the load transfer of the surrounding road network, etc.; the historical traffic data includes traffic operation records under similar conditions.

[0094] The traffic control system executes this step after obtaining the basic information of the event. Specifically, the traffic control system first determines the accurate event occurrence time through cross-validation of multi-source data; then retrieves similar cases in the historical database; at the same time, combines the current road network load status and the available capacity of the surrounding area; then establishes an event impact propagation model; finally, simulates and predicts various chain reactions that the event may trigger.

[0095] In some embodiments, the prediction of the secondary effect can be achieved in various ways: Optionally, a shock wave propagation model is constructed based on the traffic flow theory, and by calculating the upstream queue growth rate and the downstream evacuation capacity, combined with the road network topology structure, the congestion spread process is predicted, and the spillover risk of key nodes is evaluated; Optionally, a Bayesian network is used to establish an event impact causal chain model, and the conditional probability distribution is trained through historical data to achieve the probability prediction of the chain reaction. It can be understood that other prediction methods can also be used to achieve the evaluation of the secondary effect, which is not limited here.

[0096] It should be noted that the traffic control system adopts an event impact propagation model based on a causal network. First, a Bayesian network including nodes such as road network topology, traffic demand, and operating status is constructed, and the conditional probability distribution between nodes is learned through historical data. Then, based on information such as event type, location, and time, the initial state of the network is set, and a probability inference algorithm is used to predict the state transition probability of each associated road section. The model particularly focuses on the spillover risk of key nodes (such as interchange ramps, major intersections, etc.), and verifies the evolution process under different scenarios through simulation. Finally, a complete prediction result including elements such as the impact propagation path, impact degree, and duration is obtained. For example, the system can predict that the congestion on the main road may lead to a 30% increase in the traffic volume on the ground road, and accordingly adjust the signal control strategy.

[0097] S207. Generate event impact results according to the estimated impact scope and secondary traffic wave effect.

[0098] Among them, the event impact result represents the comprehensive evaluation result of the overall impact of the event, including quantitative indicators such as the impact scope, duration, and severity; the process of generating the impact result involves the fusion analysis of multi-dimensional data.

[0099] The traffic control system executes this step after completing the impact scope estimation and secondary effect analysis. Specifically, the traffic control system first integrates the spatial impact scope and time evolution characteristics; then evaluates the change in the service level of each affected road section; calculates the overall increase in regional delay; analyzes the risk level of key nodes; and finally generates a comprehensive impact report including multiple evaluation dimensions.

[0100] In some embodiments, the generation of the impact result can be achieved in various ways: Optionally, a multi-level evaluation index system is constructed, the weights of each index are determined through the analytic hierarchy process, and combined with the fuzzy comprehensive evaluation method to achieve the quantitative characterization of the impact degree; Optionally, based on the scenario analysis method, multiple possible impact development scenarios are designed, and the occurrence probability and impact degree of each scenario are calculated through Monte Carlo simulation. It can be understood that other evaluation methods can also be used to achieve the quantitative expression of the impact result, which is not limited here.

[0101] S208. Generate a traffic guidance plan and a signal timing adjustment plan according to the event impact result and traffic flow data.

[0102] Referring to step S103, the traffic control system will generate a traffic guidance plan and a signal timing adjustment plan.

[0103] S209. Generate navigation guidance for multiple sections around the corresponding event location based on the traffic guidance plan, and send the navigation guidance to the user terminal.

[0104] Referring to step S104, the traffic control system will send the navigation guidance to the user terminal.

[0105] S210. Adjust the traffic signal device in the exit area corresponding to the event location according to the signal timing adjustment plan.

[0106] Referring to step S105, the traffic control system will control and adjust the traffic signal device.

[0107] S211. Obtain the traffic flow adjustment data in the exit area corresponding to the event location.

[0108] Among them, the traffic flow adjustment data represents the traffic state change data after implementing control measures, including changes in traffic volume, speed, queue length, etc.; the data acquisition process involves real-time monitoring and effect evaluation.

[0109] The traffic control system continuously executes this step after implementing traffic control measures. Specifically, the traffic control system first collects real-time traffic parameters through the regional detector network; then calculates the change amount of each index relative to before the control; at the same time, monitors the load transfer situation of the surrounding road network; then evaluates the actual effect of the control measures; and finally forms a detailed traffic state adjustment report.

[0110] In some embodiments, the monitoring of the traffic flow adjustment effect can be achieved in multiple ways: Optionally, establish a real-time evaluation system based on multi-source data fusion, set multiple effect evaluation indicators, calculate the improvement degree after implementing the measures in real time, and conduct achievement analysis in combination with the expected goals; Optionally, adopt a comparative analysis method, establish a dynamic comparison model including data before and after control, and quantify the control effect through spatio-temporal evolution analysis. It can be understood that other evaluation methods can also be used to accurately quantify the traffic adjustment effect, which is not limited here.

[0111] In some embodiments, the traffic control system will perform data recording, that is, the traffic control system will determine the traffic guidance effect in the exit area based on the traffic flow adjustment data; after the traffic guidance effect indicates that the event processing is completed, a traffic guidance record is generated.

[0112] Among them, the traffic guidance effect represents the actual improvement degree after implementing traffic control measures; the completion of event processing means that the traffic order returns to the normal state; the traffic guidance record is a data document that completely records the whole process of event processing, including information such as time nodes, disposal measures, and effect evaluation.

[0113] The traffic control system continuously executes this process after implementing control measures. Specifically, the traffic control system first collects the traffic state data of all detection points in the area; then calculates the change amount of key indicators relative to before the event occurs; at the same time, evaluates the actual effect of implementing the measures; then judges whether the traffic order has returned to normal; and finally standardizes and arranges various data of the entire disposal process to form a complete guidance record.

[0114] In some embodiments, the effect evaluation and record generation can be achieved in various ways: Optionally, a multi-dimensional evaluation index system is established. By setting quantitative indexes such as traffic efficiency and delay reduction, combined with time-series data analysis, the overall improvement effect is evaluated, and an evaluation report is automatically generated; Optionally, knowledge graph technology is adopted to construct a complete process chain for event handling, and through semantic analysis, the structured storage of information is realized to support subsequent experience summary and pattern mining. It can be understood that other data processing methods can also be used to achieve the generation of effect evaluation and records, which are not limited here.

[0115] S212. Modify the signal timing adjustment plan according to the traffic flow adjustment data.

[0116] Among them, the modification process means dynamically optimizing and adjusting the original timing plan based on the actual effect, including the update of parameters such as cycle length, phase difference, and green signal ratio; the plan modification involves multi-objective optimization solution.

[0117] The traffic control system executes this step after obtaining the traffic flow adjustment data. Specifically, the traffic control system first evaluates the actual control effect of the existing timing plan; then identifies the key parameters that need to be optimized; at the same time, combines the coordination requirements of upstream and downstream intersections; then calculates a new timing plan through an optimization algorithm; finally, gradually implements parameter adjustment to ensure a smooth transition.

[0118] In some embodiments, the dynamic modification of the timing plan can be achieved in various ways: Optionally, an adaptive control algorithm is adopted to establish a feedback regulation mechanism based on the real-time traffic state. By setting multiple control objective functions, the signal timing parameters are optimized in real time to achieve a rapid response to traffic demand changes; Optionally, based on the reinforcement learning method, the signal timing optimization is modeled as a sequential decision-making problem, and through continuous interaction with the environment, the control strategy is continuously improved. It can be understood that other optimization algorithms can also be used to achieve the dynamic adjustment of the timing plan, which are not limited here.

[0119] It should be noted that the traffic control system realizes the dynamic optimization of the timing plan based on the reinforcement learning method. The control area is modeled as a Markov decision process, the state space contains traffic flow parameters of each road section, and the action space is adjustable signal timing parameters. By designing a reward function based on factors such as vehicle delay and stop times, the deep Q-learning algorithm is used to continuously optimize the control strategy. The system evaluates the control effect every 3 - 5 minutes and adjusts the parameters according to the actual improvement degree. To ensure control stability, a soft update mechanism is adopted to gradually adjust the timing plan. For example, when it is detected that the diversion effect is not as expected, the system will appropriately increase the green signal ratio, but the change range does not exceed 15% of the original plan.

[0120] In the embodiments of the present application, due to the adoption of innovative technologies such as an event verification mechanism based on multi-source data fusion, an impact assessment model for real-time traffic flow analysis, a dynamically optimized signal control strategy, and personalized navigation guidance push, etc., it is possible to achieve rapid perception, accurate positioning, precise assessment, and collaborative disposal of emergency events, effectively solving the problems of response lag, inaccurate assessment, and rough control existing in traditional technologies. Furthermore, it realizes the intelligentization, precision, and high efficiency of traffic management, improves the disposal efficiency of emergency events in the exit area, and provides strong support for ensuring the safe and smooth operation of urban traffic.

[0121] The traffic control system in the embodiments of the present invention application will be described from the perspective of hardware processing. Please refer to Figure 3 , which is a schematic structural diagram of an entity device of the traffic control system in the embodiments of the present application.

[0122] It should be noted that Figure 3 the structure of the traffic control system shown is only an example and should not bring any limitations to the functions and usage scopes of the embodiments of the present invention.

[0123] As Figure 3 shown, the traffic control system includes a CPU 301, which can perform various appropriate actions and processes according to the program stored in the ROM 302 or the program loaded into the RAM 303 from the storage section 308, such as executing the method described in the above embodiments. In the RAM 303, various programs and data required for system operation are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other via a bus 304. The I / O interface 305 is also connected to the bus 304.

[0124] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD), an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. The drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that the computer program read from it can be installed into the storage section 308 as needed.

[0125] In particular, according to an embodiment of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment of the present invention includes a computer program product that includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from the removable medium 311. When the computer program is executed by the CPU 301, various functions defined in the present invention are executed.

[0126] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. Among them, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the above-mentioned module, program segment, or part of code includes one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order from that marked in the accompanying drawings.

[0127] Specifically, the traffic control system of this embodiment includes a processor and a memory. A computer program is stored on the memory. When the computer program is executed by the processor, the emergency event emergency control method for the exit direction provided in the above embodiment is implemented.

[0128] As another aspect, the present invention also provides a computer-readable storage medium. This storage medium may be included in the traffic control system described in the above embodiment; or it may exist separately and not be assembled into the traffic control system. The above storage medium carries one or more computer programs. When the above one or more computer programs are executed by a processor of the traffic control system, the traffic control system is enabled to implement the emergency event emergency control method for the exit direction provided in the above embodiment.

[0129] As described above, the above embodiments are only used to illustrate the technical solutions of the present application and are not intended to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0130] As used in the foregoing embodiments, depending on the context, the term "when" can be interpreted to mean "if" or "after" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "upon determining" or "if (the stated condition or event) is detected" can be interpreted to mean "if determined" or "in response to determining" or "when (the stated condition or event) is detected" or "in response to detecting (the stated condition or event)".

Claims

1. An emergency control method for the exit direction, characterized in that, Applied to a traffic control system, the method includes: Obtain event alarm data uploaded by a user terminal, and identify the event location and event type in the event alarm data; Obtain traffic flow data of the exit area corresponding to the event location, and generate an event impact result according to the event type and the traffic flow data; Generate a traffic guidance plan and a signal timing adjustment plan according to the event impact result and the traffic flow data; Generate navigation guidance for multiple sections around the event location based on the traffic guidance plan, and send the navigation guidance to the user terminal; Adjust the traffic signal device in the exit area corresponding to the event location according to the signal timing adjustment plan.

2. The method according to claim 1, wherein The step of obtaining event alarm data uploaded by a user terminal and identifying the event location and event type in the event alarm data specifically includes: Obtain event alarm data uploaded by a user terminal, and identify the initial location in the event alarm data; Cross-verify the event alarm data with the real-time monitoring data of the initial location and the traffic event information provided by a third-party platform to obtain a verification result; Determine the credibility score of the event alarm data based on the verification result, and filter out the event alarm data with a credibility score higher than a preset credible threshold as an alarm marked event; Determine the event location and event type corresponding to the alarm marked event according to the real-time monitoring data and the traffic event information.

3. The method according to claim 1, characterized in that, The step of obtaining traffic flow data of the exit area corresponding to the event location and generating an event impact result according to the event type and the traffic flow data specifically includes: Obtain the traffic flow data and road characteristics of the exit area corresponding to the event location, and input the traffic flow data and the road characteristics into a traffic state evaluation model to obtain an estimated impact range; Determine the event occurrence time according to the event alarm data, and determine the corresponding secondary traffic wave effect in combination with the historical traffic data of the exit area according to the event type, the event location, and the event occurrence time; Generate an event impact result according to the estimated impact range and the secondary traffic wave effect.

4. The method according to claim 1, wherein Before the step of obtaining event alarm data uploaded by a user terminal and identifying the event location and event type in the event alarm data, the method further includes: Obtain the real-time traffic state data of multiple exit areas; Determine emergencies based on the real-time traffic state data and historical traffic flow data; Send a prompt message including the emergencies to a management terminal.

5. The method according to claim 4, characterized in that, After the step of determining emergencies based on the real-time traffic state data and the historical traffic flow data, the method further includes: Obtain the license plate information of the vehicle corresponding to the emergency; Determine the vehicle owner information according to the license plate information, and connect the mobile terminal corresponding to the vehicle owner information to the management terminal.

6. The method according to claim 1, characterized in that, After the step of adjusting the traffic signal device in the exit area corresponding to the event location according to the signal timing adjustment plan, the method further includes: Obtain the traffic flow adjustment data of the exit area corresponding to the event location; The signal timing adjustment plan is modified according to the traffic flow adjustment data.

7. The method according to claim 6, wherein After the step of obtaining the traffic flow adjustment data of the exit area corresponding to the event location, the method further includes: Determining a traffic guidance effect of the exit area based on the traffic flow adjustment data; After the traffic guidance effect representation event is processed, a traffic diversion record is generated.

8. A traffic control system, characterized in that, The traffic control system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the traffic control system to execute the method described in any one of claims 1-7.

9. A computer-readable storage medium, comprising instructions, characterized in that, When the instruction is executed on a traffic control system, the traffic control system is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that, When the computer program product runs on a traffic control system, the traffic control system is caused to execute the method according to any one of claims 1 to 7.

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