An expressway intelligent emergency disposal system and method

Abstract

This invention relates to the field of intelligent transportation technology and proposes an intelligent emergency response system and method for highways. The system includes a multi-source fusion analysis module, an emergency resource query module, a dynamic contingency plan generation module, a hierarchical instruction deconstruction module, an event archive fusion module, and a scheme backtracking optimization module. It performs multi-source fusion analysis on video stream data and traffic flow data to obtain abnormal event alarm information; queries the emergency resource database to obtain a list of available resources; retrieves basic contingency plans from the contingency plan knowledge base and projects resources onto these plans to obtain dynamic response schemes; deconstructs the dynamic response schemes to obtain hierarchical response instructions; fuses event chains of abnormal event trigger signals to obtain dynamic event archives; and performs backtracking analysis on the dynamic response schemes to obtain optimization adjustment parameters. This invention can improve the efficiency of intelligent emergency response on highways.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation technology, and in particular to an intelligent emergency response system and method for highways. Background Technology

[0002] Current highway emergency response technologies rely solely on video streams or traffic flow data for processing road condition data, failing to achieve multi-source data fusion and analysis. This results in a one-sided perception of abnormal events, an inability to accurately capture the true state of events, and a high risk of missed or false alarms, compromising the accuracy and completeness of abnormal event alarm information. Furthermore, the lack of dynamic querying and matching of resource status during emergency response, relying solely on pre-set resource lists for allocation, without considering the event's geographical coordinates, real-time resource location, load status, and other information for comprehensive assessment, leads to a mismatch between resource allocation and actual response needs, resulting in low efficiency in emergency resource utilization.

[0003] Traditional highway emergency response plans are mostly standardized and cannot be tailored to the specific type of emergency, available resources, and geographical coordinates of the incident. This results in poor adaptability and makes it difficult to provide effective guidance for handling different emergency scenarios. Furthermore, the lack of effective retrospective analysis mechanisms after implementation prevents a systematic review of the entire process, including time consumption and key milestones. This hinders the identification of network bottlenecks and resource allocation issues, preventing the optimization of subsequent emergency response plans and hindering continuous improvement in overall emergency response efficiency. Summary of the Invention

[0004] This invention provides an intelligent emergency response system and method for highways to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides an intelligent emergency response system for highways, characterized in that the system includes a multi-source fusion analysis module, an emergency resource query module, a dynamic contingency plan generation module, a hierarchical instruction deconstruction module, an event archive fusion module, and a plan backtracking and optimization module, wherein: The multi-source fusion analysis module is used to perform multi-source fusion analysis on video stream data and traffic flow data of real-time road conditions in the target highway to obtain abnormal event alarm information of the target highway. The emergency resource query module is used to perform a status query on the emergency resource database of the target highway based on the abnormal event alarm information, and obtain a list of available resources for the target highway. The dynamic contingency plan generation module is used to retrieve basic contingency plans from the contingency plan knowledge base of the target highway based on the event type of the abnormal event alarm information, and to perform resource projection on the basic contingency plans based on the available resource list and the geographical coordinates in the alarm information to obtain a dynamic handling plan for the target highway. The hierarchical instruction deconstruction module is used to deconstruct the dynamic handling scheme to obtain the hierarchical handling instructions for the target highway. The event file fusion module is used to perform event chain fusion on the abnormal event trigger signal based on the on-site real-time bitstream of the execution of the graded handling instructions, so as to obtain the dynamic event file of the target highway. The scheme backtracking and optimization module is used to perform backtracking analysis on the dynamic handling scheme based on the total processing time of the dynamic event archive, and obtain the optimization adjustment parameters of the target highway.

[0006] In a preferred embodiment, when the multi-source fusion analysis module performs multi-source fusion analysis on the video stream data and traffic flow data of real-time traffic conditions in the target highway to obtain the abnormal event alarm information of the target highway, it is specifically used for: Frame-by-frame image recognition is performed on the video stream data of the target highway to obtain the first sensing device identifier of the target highway. The traffic flow data of the target highway is scanned using cross-sectional parameters to obtain the second sensing device identifier of the target highway; The first sensing device identifier and the second sensing device identifier are matched and verified to obtain the preliminary associated event signal of the target highway; Based on the preliminary associated event signal, the device installation coordinates of the first sensing device are retrieved, and the device installation coordinates are used as the geographical coordinates of the abnormal event alarm information to obtain the abnormal event alarm information of the target highway.

[0007] In a preferred embodiment, when the emergency resource query module performs a status query on the emergency resource database of the target highway based on the abnormal event alarm information to obtain the available resource list of the target highway, it is specifically used for: Based on the event attribute parameters of the abnormal event alarm information, the spatial range of resource records in the emergency resource database of the target highway is delineated to obtain a candidate resource list for the target highway. The status feedback message of the candidate resource list is received, and the current location data, task load status and equipment integrity identifier of the resource node are parsed from the status feedback message to obtain the real-time dynamic attribute parameters of the target highway. Based on the event geographic coordinates of the event attribute parameters and the current location data, a path is connected to the target highway to obtain the path passage parameters of the target highway. By associating and binding the real-time dynamic attribute parameters and the path access parameters, a list of available resources for the target highway is obtained.

[0008] In a preferred embodiment, when the dynamic contingency plan generation module executes the event type based on the abnormal event alarm information, retrieves the basic contingency plan from the contingency plan knowledge base of the target highway, and projects the basic contingency plan based on the available resource list and the geographical coordinates in the alarm information to obtain the dynamic handling plan for the target highway, it is specifically used for: Based on the triggering feature parameters of the abnormal event alarm information, the contingency plan entries in the contingency plan knowledge base of the target highway are traversed and matched to obtain the basic contingency plan of the target highway. The resource requirement list of the basic plan is compared item by item with the resource records in the available resource list to obtain the matching resource pool of the target expressway; Task codes are assigned to the resource nodes in the matching resource pool to obtain the execution plan for the target highway; The traffic link is calculated for the contingency plan to be executed, and the obtained optimal guidance trajectory is bound to the disposal node in the contingency plan to be executed to obtain the dynamic disposal plan for the target highway.

[0009] In a preferred embodiment, when the hierarchical instruction deconstruction module performs task deconstruction on the dynamic handling scheme to obtain the hierarchical handling instructions for the target highway, it is specifically used for: The sequence of disposal nodes in the dynamic disposal plan is analyzed item by item to obtain the disposal task list of the target highway; Based on the resource node identifiers of the task list, the preset organizational responsibility list is indexed and retrieved to obtain the mapping table of the target highway. Based on the mapping relationship and the task list, the general handling content in the dynamic handling plan is translated into the action outline of the target highway to obtain the original instruction text of the target highway. The original instruction text is structured and encapsulated to obtain the graded handling instructions for the target highway.

[0010] In a preferred embodiment, when the event file fusion module executes the on-site live stream based on the execution of the graded handling instructions and performs event chain fusion on the abnormal event trigger signals to obtain the dynamic event file of the target highway, it is specifically used for: The system captures the live bitstream of the graded handling instructions and performs protocol parsing on the live bitstream to obtain the original live handling record of the target highway. Based on the event chain identifier of the original on-site handling record, the event chain of the abnormal event triggering signal is traced to obtain the event source file of the target highway. Using the initial alarm time in the event source file as the time reference zero point, the original on-site handling records are arranged in chronological order to obtain the event evolution sequence of the target highway; Spatially anchor the video clips of the handling process in the event evolution sequence with the event geographic coordinates of the original on-site handling record to obtain the spatiotemporal related event clips of the target highway; The spatiotemporal related event fragments are compositely encapsulated to obtain a multi-dimensional event record chain of the target highway; Add anti-tamper verification mark and file seal to the multi-dimensional event record chain and store it in the target highway event archive database to obtain the dynamic event archive of the target highway.

[0011] In a preferred embodiment, when the event archive fusion module performs composite encapsulation of the spatiotemporally related event fragments to obtain a multi-dimensional event record chain of the target highway, it is specifically used for: Keyframe interpolation is performed on the video evidence units of the spatiotemporally related event segments to obtain the labeled video data of the target highway; The labeled video data is serially spliced ​​to obtain the event video sequence of the target highway; The event video sequence is encapsulated using a protocol to obtain the dynamic event recording chain of the target highway; The dynamic event record chain is hashed and digested, and an archive timestamp and file version number are added to the initially encapsulated dynamic event record chain to obtain the multi-dimensional event record chain of the target highway.

[0012] In a preferred embodiment, when the scheme backtracking optimization module performs backtracking analysis on the dynamic handling scheme based on the total processing time of the dynamic event archive to obtain the optimization adjustment parameters of the target highway, it is specifically used for: The total processing time of the dynamic event archive is calibrated by time interval to obtain the full process time interval of the target highway; The entire process time interval is compared with a preset standard processing time threshold for threshold determination. When the entire process time interval exceeds the standard processing time threshold, a timeout alarm flag for the target highway is obtained. In response to the timeout alarm, the resource allocation record and execution sequence window of the dynamic handling plan are retrieved back, and the actual arrival timestamp of the handling node in the dynamic handling plan is extracted from the dynamic event archive. The deviation nodes are located by comparing the resource allocation record with the actual arrival timestamp to obtain the list of delay nodes of the target highway. By tracing the path of delay handling nodes in the delay node list, a list of road network bottlenecks of the target expressway is obtained. Based on the list of delayed nodes and the list of road network bottlenecks, the compensation parameters of the dynamic handling scheme are calibrated to obtain the optimized adjustment parameters of the target expressway.

[0013] In a preferred embodiment, the calculation formula for the optimization adjustment parameter is as follows: , ; In the formula, This refers to the resource quota correction coefficient in the optimization adjustment parameters. The path detour weight in the optimization adjustment parameters is used to... This represents the total number of delayed nodes in the list of delayed nodes. For the first The delay duration of each delayed node, For the first Bottleneck correlation factors corresponding to each delay node The preset delay attenuation coefficient, The length of the road segment affected by the incident, The preset bottleneck congestion coefficient, The total number of bottlenecks. For the first The rate of capacity loss at each bottleneck point This is the preset standard traffic capacity.

[0014] To address the above problems, the present invention also provides an intelligent emergency response method for highways, the method comprising: Pt.1. Perform multi-source fusion analysis on the video stream data and traffic flow data of real-time road conditions in the target highway to obtain the abnormal event alarm information of the target highway. Pt.2. Based on the abnormal event alarm information, perform a status query on the emergency resource database of the target highway to obtain the available resource list of the target highway; Pt.3. Based on the event type of the abnormal event alarm information, retrieve the basic contingency plan from the contingency plan knowledge base of the target highway, and perform resource projection on the basic contingency plan based on the available resource list and the geographical coordinates in the alarm information to obtain the dynamic handling plan of the target highway. Pt.4. Deconstruct the dynamic handling scheme to obtain the hierarchical handling instructions for the target highway; Pt.5. Based on the real-time bitstream of the execution of the graded handling instructions, the event chain fusion of the abnormal event triggering signal is performed to obtain the dynamic event file of the target highway. Pt.6. Based on the total processing time of the dynamic event archive, a retrospective analysis is performed on the dynamic processing scheme to obtain the optimized adjustment parameters of the target highway.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. This technology achieves collaborative processing of video streams and traffic flow data through multi-source fusion analysis, accurately pinpointing the geographical coordinates of abnormal events, thus enhancing the accuracy and completeness of abnormal event alarm information. Simultaneously, relying on dynamic queries of the emergency resource database, it combines event attributes to complete the spatial delineation and real-time status analysis of resources, achieving precise matching of resources with response needs and improving the efficiency of emergency resource allocation and utilization. Based on event type, it retrieves basic contingency plans and combines them with available resource lists and geographical coordinates to complete resource projection, ensuring that dynamic response plans are tailored to actual emergency response scenarios. Hierarchical instruction deconstruction enables the refined breakdown and structured encapsulation of response tasks, making the transmission and execution of response instructions more targeted and efficient.

[0016] 2. This technology integrates event chains of abnormal events through live on-site bitstreams, constructing a dynamic event archive containing spatiotemporal information. It comprehensively preserves data from the entire emergency response process, providing a complete and accurate basis for reviewing the response. Based on the total response time in the dynamic event archive, retrospective analysis is conducted to accurately locate delay nodes and road network bottlenecks, generating optimization and adjustment parameters. This enables continuous optimization of the dynamic response plan, constantly improving the highway emergency response process, significantly enhancing overall efficiency, and making emergency response decisions more scientific and rational. Attached Figure Description

[0017] Figure 1 This is a system architecture diagram of an intelligent emergency response system for highways provided in an embodiment of the present invention; Figure 2 This is a flowchart illustrating an intelligent emergency response method for highways, provided as an embodiment of the present invention.

[0018] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments belong to some, but not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “said” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0021] Depending on the context, the word "if" or "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0022] Furthermore, the timing of the steps in the following method embodiments is merely an example and not a strict limitation.

[0023] In practice, the server-side equipment deployed in a highway intelligent emergency response system may consist of one or more devices. This highway intelligent emergency response system can be implemented as: a business instance, a virtual machine, or hardware devices. For example, it can be implemented as a business instance deployed on one or more devices in a cloud node. Simply put, it can be understood as software deployed on a cloud node, providing a highway intelligent emergency response system to various user terminals. Alternatively, it can be implemented as a virtual machine deployed on one or more devices in a cloud node, with application software installed to manage various user terminals. Or, it can also be implemented as a server composed of numerous identical or different types of hardware devices, with one or more hardware devices configured to provide a highway intelligent emergency response system to various user terminals.

[0024] In terms of implementation, the intelligent emergency response system for highways and the user terminal are mutually compatible. That is, if the intelligent emergency response system for highways is implemented as an application installed on a cloud service platform, then the user terminal is a client that establishes a communication connection with the application; or if the intelligent emergency response system for highways is implemented as a website, then the user terminal is implemented as a webpage; or if the intelligent emergency response system for highways is implemented as a cloud service platform, then the user terminal is implemented as a mini-program in an instant messaging application.

[0025] like Figure 1 The diagram shown is a system architecture diagram of an intelligent emergency response system for highways provided in an embodiment of the present invention.

[0026] The intelligent emergency response system for highways described in this invention can be hosted on a cloud server. In terms of implementation, it can function as one or more service devices, or as an application installed in the cloud (e.g., a mobile service operator's server, server cluster, etc.), or it can be developed into a website. Depending on the functions implemented, the intelligent emergency response system for highways may include a multi-source fusion analysis module, an emergency resource query module, a dynamic contingency plan generation module, a hierarchical instruction deconstruction module, an event archive fusion module, and a plan backtracking and optimization module. The modules described in this invention can also be referred to as units, which are a series of computer program segments that can be executed by the processor of an electronic device and perform a fixed function, stored in the memory of the electronic device.

[0027] In this embodiment of the invention, in a highway intelligent emergency response system, each of the above-mentioned modules can be implemented independently and can call other modules. Here, "calling" can be understood as one module connecting to multiple modules of another type and providing corresponding services to those connected modules. In the highway intelligent emergency response system provided by this embodiment of the invention, without modifying the program code, the applicability of the highway intelligent emergency response system architecture can be adjusted by adding modules and directly calling them, achieving cluster-based horizontal expansion to quickly and flexibly expand the highway intelligent emergency response system. In practical applications, the above-mentioned modules can be set in the same device or different devices, or they can be set in virtual devices, such as service instances in a cloud server.

[0028] The following describes, with reference to specific embodiments, the various components and specific workflows of a highway intelligent emergency response system: The multi-source fusion analysis module is used to perform multi-source fusion analysis on video stream data and traffic flow data of real-time road conditions in the target highway to obtain abnormal event alarm information of the target highway. In this embodiment of the invention, when the multi-source fusion analysis module performs multi-source fusion analysis on the video stream data and traffic flow data of real-time road conditions in the target highway to obtain the abnormal event alarm information of the target highway, it is specifically used for: Frame-by-frame image recognition is performed on the video stream data of the target highway to obtain the first sensing device identifier of the target highway. The traffic flow data of the target highway is scanned using cross-sectional parameters to obtain the second sensing device identifier of the target highway; The first sensing device identifier and the second sensing device identifier are matched and verified to obtain the preliminary associated event signal of the target highway; Based on the preliminary associated event signal, the device installation coordinates of the first sensing device are retrieved, and the device installation coordinates are used as the geographical coordinates of the abnormal event alarm information to obtain the abnormal event alarm information of the target highway.

[0029] At a standard of 30 frames per second, continuous frame image acquisition is performed on the video stream data of the target highway. For each frame of the acquired image, a device feature extraction operation is performed to extract the physical identification features of the sensing device in the image. The extracted features are then matched with a preset sensing device feature library in all dimensions. When the matching result is that the features completely overlap, the unique identification information of the device is extracted. This identification information is the first sensing device identifier of the target highway.

[0030] The traffic flow data of the target highway is fully scanned at 500-meter road cross-section intervals. The traffic flow data features collected by the sensing devices at each cross-section are obtained by scanning. The device identifier exclusive field bound to the data features is extracted. The field is formatted according to the preset character format standard. When the field format fully conforms to the standard, the unique identification information is extracted. This identification information is the second sensing device identifier of the target highway.

[0031] The character sequence of the first sensing device identifier is compared character by character with the character sequence of the second sensing device identifier. When the matching rate of the two sets of identifier character sequences reaches 100%, the matching verification of the set of sensing device identifiers is determined to be successful. After the matching verification is successful, signal data containing the identification information of the set of sensing devices is generated. This signal data is the preliminary associated event signal of the target highway.

[0032] A precise search is performed in the preset basic information database of sensing devices, using the identifier of the first sensing device in the preliminary associated event signal as the unique search keyword. After retrieving the device installation coordinate information corresponding to the identifier, the coordinate information is calibrated according to the WGS-84 geographic coordinate system format. The calibrated geographic coordinate information is then fully integrated with the preliminary associated event signal data to generate standardized alarm data containing geographic coordinates and sensing device identifiers. This standardized alarm data is the abnormal event alarm information of the target highway.

[0033] The beneficial effects are as follows: by obtaining the corresponding sensing device identifiers through frame-by-frame image recognition of video stream data and cross-sectional parameter scanning of traffic flow data, it is possible to accurately collect and extract features from multi-source data on real-time road conditions on highways. Then, through matching and verification of sensing device identifiers, effective association and fusion of multi-source data can be achieved, ensuring the accuracy of associated signals from the data source. Subsequently, based on the matched identifiers, the installation coordinates of the devices can be retrieved and the geographic coordinates can be calibrated, so that the alarm information of abnormal events can be accompanied by accurate geographic location information. This ensures that the alarm information of abnormal events is both complete and accurate, providing reliable and effective basic data support for all aspects of subsequent emergency response on highways, and ensuring that subsequent emergency response operations are carried out based on the actual abnormal event situation.

[0034] The emergency resource query module is used to perform a status query on the emergency resource database of the target highway based on the abnormal event alarm information, and obtain a list of available resources for the target highway. In this embodiment of the invention, when the emergency resource query module performs a status query on the emergency resource database of the target highway based on the abnormal event alarm information to obtain the available resource list of the target highway, it is specifically used for: Based on the event attribute parameters of the abnormal event alarm information, the spatial range of resource records in the emergency resource database of the target highway is delineated to obtain a candidate resource list for the target highway. The status feedback message of the candidate resource list is received, and the current location data, task load status and equipment integrity identifier of the resource node are parsed from the status feedback message to obtain the real-time dynamic attribute parameters of the target highway. Based on the event geographic coordinates of the event attribute parameters and the current location data, a path is connected to the target highway to obtain the path passage parameters of the target highway. By associating and binding the real-time dynamic attribute parameters and the path access parameters, a list of available resources for the target highway is obtained.

[0035] The event attribute parameters recorded in the abnormal event alarm information are extracted, and the relevant content of the event's geographical coordinates and impact type is extracted. Taking the event's geographical coordinates as the center, the corresponding resource retrieval space range is defined according to the preset emergency resource allocation space threshold. The geographical attribute information of resource records is retrieved line by line in the emergency resource database of the target highway. All resource records whose geographical attribute information is within the retrieval space range and whose resource type matches the event impact type are selected. The selected resource records are organized in an orderly manner according to the resource node identifier to form a structured data list. This structured data list is the candidate resource list of the target highway.

[0036] A resource status query command is sent to the terminal control device corresponding to each resource node in the candidate resource list. The status feedback messages returned by each terminal control device in response to the query command are received. The data packets of the status feedback messages are disassembled layer by layer according to the preset message data parsing rules. The original data of the current location data field, task load status field and equipment integrity identifier field corresponding to each resource node are extracted in sequence. The three types of data extracted from each resource node are classified and integrated according to the resource node identifier. The integrated structured resource status data is the real-time dynamic attribute parameters of the target highway.

[0037] The calibrated geographic coordinates of the event are extracted from the event attribute parameters, and the current location data of each resource node is extracted from the real-time dynamic attribute parameters. Based on the electronic map of the target highway network, the path connection operation is completed by drawing the path between the two points with the current location data of each resource node as the starting point and the geographic coordinates of the event as the ending point. The basic road information and real-time traffic status of each drawn path are collected in all dimensions. After the collection is completed, the relevant information is organized according to the corresponding path. The organized structured path information is the path traffic parameters of the target highway.

[0038] Using the unique identifier of each resource node as a unified association keyword, the current location data, task load status, and equipment integrity identifier of each resource node in the real-time dynamic attribute parameters are matched and bound with the path information corresponding to the same resource node in the path access parameters. The validity of all resource node data after binding is verified, and resource node data with a task load status of full load or an equipment integrity identifier of non-intact are removed. The valid resource node data that has passed the verification is classified and arranged according to resource type to form a structured resource list. This structured resource list is the available resource list of the target highway.

[0039] The beneficial effects are as follows: By defining the spatial scope of resource records in the emergency resource database based on event attribute parameters from abnormal event alarm information, the selection of candidate resources can be aligned with the actual handling needs of abnormal events, achieving accurate initial screening of emergency resources. Receiving and parsing status feedback messages from the candidate resource list to obtain real-time dynamic attribute parameters allows for a comprehensive understanding of the actual status of each resource node, ensuring that the understanding of resource conditions aligns with the actual situation on-site. Path access parameters are obtained by connecting paths based on event geographic coordinates and current resource location data, providing information on the actual path from the resource to the event location, thus providing a basis for path planning for resource allocation. By associating and binding real-time dynamic attribute parameters with path access parameters, a list of available resources is formed, encompassing both resource status information and path access information, making the list comprehensive and practical. This provides accurate and effective resource data support for the generation of subsequent dynamic handling plans, ensuring the scientific and rational allocation of emergency resources.

[0040] The dynamic contingency plan generation module is used to retrieve basic contingency plans from the contingency plan knowledge base of the target highway based on the event type of the abnormal event alarm information, and to perform resource projection on the basic contingency plans based on the available resource list and the geographical coordinates in the alarm information to obtain a dynamic handling plan for the target highway. In this embodiment of the invention, when the dynamic contingency plan generation module executes the event type based on the abnormal event alarm information, retrieves the basic contingency plan from the contingency plan knowledge base of the target highway, and projects the basic contingency plan based on the available resource list and the geographical coordinates in the alarm information to obtain the dynamic handling plan for the target highway, it is specifically used for: Based on the triggering feature parameters of the abnormal event alarm information, the contingency plan entries in the contingency plan knowledge base of the target highway are traversed and matched to obtain the basic contingency plan of the target highway. The resource requirement list of the basic plan is compared item by item with the resource records in the available resource list to obtain the matching resource pool of the target expressway; Task codes are assigned to the resource nodes in the matching resource pool to obtain the execution plan for the target highway; The traffic link is calculated for the contingency plan to be executed, and the obtained optimal guidance trajectory is bound to the disposal node in the contingency plan to be executed to obtain the dynamic disposal plan for the target highway.

[0041] The trigger feature parameters encapsulated in the abnormal event alarm information are extracted. These parameters include features related to event type, scope of impact, and handling level. Using these trigger feature parameters as the matching basis, all contingency plan entries in the target highway contingency plan knowledge base are compared one by one according to their target features. During the comparison process, the preset features of the contingency plan entries and the features of the trigger feature parameters are verified to be identical in all dimensions. When the preset features of the contingency plan entries are completely identical to the features of the trigger feature parameters, the contingency plan entries are determined to be successfully matched. The successfully matched contingency plan entries are fully extracted and standardized according to the preset contingency plan format. The standardized contingency plan content is the basic contingency plan for the target highway.

[0042] Extract the pre-set resource requirement list from the basic contingency plan. This list contains information such as the types, specifications, and quantities of various resources required for disposal. At the same time, extract all resource records from the available resource list. Compare each resource requirement in the resource requirement list with the resource records in the available resource list item by item, using resource type as the first comparison dimension, resource specification as the second comparison dimension, and available resource quantity as the third comparison dimension. When a resource record in the available resource list is completely consistent with the corresponding item in the resource requirement list in terms of type and specification, and the available quantity is not less than the required quantity, the resource item is considered to have successfully matched. Extract all successfully matched resource records and classify and integrate them according to resource function. The integrated structured resource set is the matching resource pool for the target highway.

[0043] Based on the emergency response process preset in the basic plan, the specific task requirements, task priorities, and resource responsibility division standards for each response stage are broken down. To match each resource node in the resource pool, a unique task code is assigned according to the combination rule of "response stage code + priority code + resource identifier code". The assigned task code is bound one-to-one with the corresponding resource node. At the same time, the task codes of each resource node are arranged in an orderly manner according to the time sequence of the response process. The entire process is integrated by combining the response requirements of the basic plan with the resource node information after binding the task codes. The integrated response plan, which includes the correspondence between task codes and resource nodes, is the response plan to be executed for the target highway.

[0044] Based on the electronic map of the target highway network and combined with the acquired route traffic parameters, for each resource node corresponding to the disposal node in the contingency plan to be executed, all feasible traffic links from the current location of the resource node to the geographical coordinates of the disposal node are planned. The passage distance, smoothness, and time of each feasible link are evaluated in all dimensions. The traffic link with the best evaluation result is selected as the optimal guidance trajectory from the resource node to the corresponding disposal node. Each disposal node is bound to its corresponding optimal guidance trajectory in a one-to-one task. At the same time, the bound disposal node, resource node, and optimal guidance trajectory information are fully integrated with the disposal process of the contingency plan to be executed. The integrated content is standardized and encapsulated. The encapsulated standardized disposal plan is the dynamic disposal plan for the target highway.

[0045] The beneficial effects are as follows: By traversing and matching contingency plan entries in the contingency plan knowledge base based on the trigger feature parameters of abnormal event alarm information to obtain basic contingency plans, the basic contingency plans can be highly matched with the actual characteristics of abnormal events, ensuring the accuracy and relevance of contingency plan retrieval. By comparing the resource requirement list of the basic contingency plans with the available resource list item by item to obtain a matching resource pool, precise adaptation between resource requirements and actual available resources can be achieved, ensuring that resource allocation conforms to contingency plan requirements. Finally, by assigning task codes to resource nodes in the matching resource pool to obtain contingency plans to be executed, the handling tasks of each resource node can be clearly defined. By using standardized identification and marking, the allocation of emergency response tasks is ensured to be clear and orderly. The traffic flow calculation of the emergency response plan is performed, and the optimal guidance trajectory is bound to the response node to obtain a dynamic response plan. This allows the response plan to integrate resource adaptability and path rationality. At the same time, the geographical coordinates of alarm information are combined to complete resource projection, so that the dynamic response plan is fully adapted to the actual response scenario of abnormal events. This makes the plan highly practical and provides accurate and feasible plan support for the subsequent issuance and execution of emergency response instructions, which greatly improves the adaptability and execution efficiency of highway emergency response plans.

[0046] The hierarchical instruction deconstruction module is used to deconstruct the dynamic handling scheme to obtain the hierarchical handling instructions for the target highway. In this embodiment of the invention, when the hierarchical instruction deconstruction module performs task deconstruction on the dynamic handling scheme to obtain the hierarchical handling instructions for the target highway, it is specifically used for: The sequence of disposal nodes in the dynamic disposal plan is analyzed item by item to obtain the disposal task list of the target highway; Based on the resource node identifiers of the task list, the preset organizational responsibility list is indexed and retrieved to obtain the mapping table of the target highway. Based on the mapping relationship and the task list, the general handling content in the dynamic handling plan is translated into the action outline of the target highway to obtain the original instruction text of the target highway. The original instruction text is structured and encapsulated to obtain the graded handling instructions for the target highway.

[0047] Extract the sequence of disposal nodes encapsulated in the dynamic disposal plan, and decompose the information of each disposal node in the sequence in all dimensions. Extract the disposal content, execution standards, associated resource node identifiers, and execution sequence requirements corresponding to each disposal node one by one. Arrange all the extracted disposal node information in order of execution sequence, and add a unique node code to the disposal information of each node. Standardize and organize the arranged information according to the preset list format. The standardized structured list is the disposal task list of the target highway.

[0048] Extract all associated resource node identifiers from the task list and use each resource node identifier as a unique retrieval index key. Perform precise single-key retrieval in the preset list of organizational authority and responsibility. After the retrieval is completed, extract the execution organization name, organizational authority and responsibility scope, instruction receiving channel, and execution permission level corresponding to each resource node identifier. Bind and organize the resource node identifiers with the extracted organizational authority and responsibility information one by one. Arrange the bound information in a structured manner according to the preset table format. The structured table after arrangement is the mapping relationship table of the target highway.

[0049] Based on the correspondence between resource node identifiers and organizational authority information in the mapping table, and combined with the specific execution requirements of the disposal task list, the general disposal content in the dynamic disposal plan is translated in a targeted manner. The general disposal content is converted into practical expressions that fit the scope of authority and execution authority of each executing organization. The translated practical expressions are hierarchically divided according to the priority of the disposal tasks and sorted into a standardized action outline. The action outline is fully integrated with the execution sequence and execution standards of the disposal task list. The integrated standardized text content is the original instruction text of the target highway.

[0050] According to the preset emergency response instruction classification standards, based on the priority of the response task, the scope of impact, and the administrative level of the implementing body, the contents of the original instruction text are classified into different levels. Each level of instruction is given a unique instruction code, implementing body identifier, execution time limit requirement, and instruction feedback node. The content of each level of instruction is encapsulated separately according to the module structure of "instruction requirements + execution standards + feedback requirements". After completing the modular encapsulation of all levels of instructions, the encapsulated modules of each level are integrated in an orderly manner according to the instruction level. A unified instruction header information and verification identifier are added to the integrated whole. The structured instruction data body after integration and encapsulation is the graded response instruction for the target highway.

[0051] The beneficial effects are as follows: By analyzing the sequence of disposal nodes in a dynamic disposal plan item by item to obtain a disposal task list, the overall disposal plan can be broken down into specific disposal tasks. This clearly presents the disposal requirements, execution sequence, and associated resources, making the disposal tasks more concrete and systematic. Based on the resource node identifier index of the disposal task list, a mapping relationship table is obtained by retrieving the organizational responsibility list. This enables a precise correspondence between resource nodes and the responsibilities of the executing organization, clarifying the scope of responsibilities, instruction receiving and execution authority of each executing entity, providing a clear basis for instruction translation. Combining the mapping relationship and the disposal task list, general disposal content is translated into action. The outline obtains the original instruction text, allowing the instruction content to align with the actual responsibilities and execution scenarios of each implementing entity, eliminating ambiguities caused by generic content, and making the instructions highly practical. By structurally encapsulating the original instruction text to obtain tiered disposal instructions, the disposal instructions can form a standardized hierarchical structure, making the hierarchical division of instructions clear and the execution requirements explicit, ensuring the accuracy of instruction issuance and the efficiency of transmission. Each implementing entity can quickly identify and adapt the instruction content to its own situation, greatly improving the orderly execution and implementation efficiency of emergency disposal instructions, and providing clear and standardized instruction support for the efficient development of subsequent tiered disposal work.

[0052] The event file fusion module is used to perform event chain fusion on the abnormal event trigger signal based on the on-site real-time bitstream of the execution of the graded handling instructions, so as to obtain the dynamic event file of the target highway. In this embodiment of the invention, when the event file fusion module executes the on-site live stream based on the execution of the graded handling instruction and performs event chain fusion on the abnormal event trigger signal to obtain the dynamic event file of the target highway, it is specifically used for: The system captures the live bitstream of the graded handling instructions and performs protocol parsing on the live bitstream to obtain the original live handling record of the target highway. Based on the event chain identifier of the original on-site handling record, the event chain of the abnormal event triggering signal is traced to obtain the event source file of the target highway. Using the initial alarm time in the event source file as the time reference zero point, the original on-site handling records are arranged in chronological order to obtain the event evolution sequence of the target highway; Spatially anchor the video clips of the handling process in the event evolution sequence with the event geographic coordinates of the original on-site handling record to obtain the spatiotemporal related event clips of the target highway; The spatiotemporal related event fragments are compositely encapsulated to obtain a multi-dimensional event record chain of the target highway; Add anti-tamper verification mark and file seal to the multi-dimensional event record chain and store it in the target highway event archive database to obtain the dynamic event archive of the target highway.

[0053] When the event archive fusion module performs composite encapsulation of the spatiotemporally related event fragments to obtain the multi-dimensional event record chain of the target highway, it is specifically used for: Keyframe interpolation is performed on the video evidence units of the spatiotemporally related event segments to obtain the labeled video data of the target highway; The labeled video data is serially spliced ​​to obtain the event video sequence of the target highway; The event video sequence is encapsulated using a protocol to obtain the dynamic event recording chain of the target highway; The dynamic event record chain is hashed and digested, and an archive timestamp and file version number are added to the initially encapsulated dynamic event record chain to obtain the multi-dimensional event record chain of the target highway.

[0054] Audio and video acquisition devices and data acquisition terminals are deployed at all handling nodes for the execution of graded handling instructions. The devices and terminals capture audio and video data, handling operation data, and equipment status data in real time, forming a live bitstream containing multiple types of data. The live bitstream is parsed in a full-process protocol parsing operation, including header parsing, data segment disassembly, and format restoration, according to a preset bitstream transmission protocol. The parsed raw data is classified and collected according to the acquisition device identifier, handling node identifier, and acquisition time. The collected structured on-site handling data set is the original on-site handling record of the target highway.

[0055] A pre-defined event chain identifier is extracted from the unified data fields of the original on-site handling records. This identifier is a unique identifier for the corresponding abnormal event. Using this event chain identifier as the unique search keyword, a full-domain precise search is performed in the dedicated database of abnormal event trigger signals. All initial trigger-related data bound to this identifier are retrieved, including the data collected by the initial sensing device, the generation data of the first abnormal signal, and the determination data of the initial event characteristics. All retrieved initial trigger-related data are sorted in order according to the time of signal generation. A unique source file code is added to the sorted dataset. The structured initial trigger dataset after sorting and coding is the event source file of the target highway.

[0056] The initial alarm time is accurately recorded from the incident source archives and set as the time reference zero point. The collection timestamp corresponding to each data record in the original on-site handling records is extracted and all collection timestamps are converted into relative time values ​​calculated from the time reference zero point. The original on-site handling records are arranged in a fixed order from small to large relative time values. During the arrangement process, all handling-related information corresponding to each data record is completely preserved. The continuous and structured handling record sequence formed in this order is the event evolution sequence of the target highway.

[0057] The video clips corresponding to all handling processes are extracted from the event evolution sequence. A relative time value matching its acquisition process and the identification of the handling node to which it belongs are added to each video clip. The standardized event geographic coordinates corresponding to each video clip are retrieved from the original on-site handling records. According to the preset geospatial coding rules, the relative time value, handling node identification and the corresponding event geographic coordinates of each video clip are bound one-to-one. A corresponding spatial attribute label is added to each video clip that has been bound. The labeled video clips containing spatiotemporal attributes and the corresponding handling records are the spatiotemporally related event clips of the target highway.

[0058] All spatiotemporally related event segments are arranged continuously in ascending order of relative time values. The data format of each spatiotemporally related event segment is standardized and converted to fit the preset archive storage data format. Multi-dimensional information such as video data, time attributes, spatial attributes, handling operation records, and equipment status data contained in each segment are extracted in sequence. The information of each dimension is integrated and associated layer by layer according to the preset layered encapsulation structure. A continuous and unique segment code is added to the integrated whole to form a complete recording link. The encapsulated recording link containing multi-dimensional information and with continuous time sequence is the multi-dimensional event recording chain of the target highway.

[0059] A unique anti-tampering verification identifier is generated for the multi-dimensional event record chain according to the preset anti-tampering data verification rules. This identifier is deeply bound to all data content of the multi-dimensional event record chain. Any modification to the data content will directly invalidate the identifier. Then, a standardized file seal containing the file generation time, unique file code, and generation subject identifier is added to the multi-dimensional event record chain according to the preset file seal generation rules. The multi-dimensional event record chain with the added anti-tampering verification identifier and file seal is stored in the designated storage directory according to the preset storage rules of the target highway event archive database. After storage is completed, a unique file retrieval identifier is generated for the record chain. The standardized file data containing the file retrieval identifier, anti-tampering verification identifier, file seal, and complete multi-dimensional event record chain is the dynamic event archive of the target highway.

[0060] Video evidence units encapsulated in spatiotemporally related event segments are extracted. The original keyframes of these video evidence units are extracted at fixed points, following a preset time interval rule. Within the time interval between adjacent original keyframes, interpolated frames with natural transitions are generated based on the image features of the preceding and following keyframes. The generated interpolated frames are then precisely inserted into the time positions of the corresponding adjacent original keyframes. After all interpolation operations are completed, standardized annotation information, including the corresponding event geographic coordinates and relative time values, is added to each original keyframe and interpolated frame. The complete video data after adding the annotation information is the annotated video data of the target highway.

[0061] The labeled video data corresponding to each spatiotemporally related event segment is extracted. The encapsulated relative time value is extracted from each labeled video data. All labeled video data are serially spliced ​​without gaps according to a fixed order of relative time values ​​from small to large. During the splicing process, the connection between two adjacent labeled video data segments is double-checked for both image and timestamp to ensure that there are no gaps in the image and no overlap in the timestamps at the connection position. After all splicing operations are completed, the encoding format and resolution parameters of all video data are unified. The resulting continuous video data stream is the event video sequence of the target highway.

[0062] According to the preset highway emergency response archive data transmission protocol, standardized protocol header information is added to the event video sequence. The protocol header information includes basic data such as video encoding format, total video duration, and number of associated spatiotemporal event segments. The serially spliced ​​event video sequence is used as the core data of the protocol body. An integrity check code generated based on the data content is added to the end of the protocol. After the protocol is encapsulated, the encapsulated video data is precisely associated and bound with the corresponding spatiotemporal event segment's handling operation record, resource node status data, and path passage parameters according to the timeline. The resulting time-series continuous and data-associated record link is the dynamic event record chain of the target highway.

[0063] The entire data content in the dynamic event record chain is verified and processed bit by bit to generate a hash digest that uniquely corresponds to the data content of the dynamic event record chain. This hash digest is deeply bound to all the data in the dynamic event record chain. Any change in the data content will directly cause the hash digest to change. The system's real-time standard UTC time is extracted as the archive timestamp. An initial archive version number is assigned to the first generated dynamic event record chain according to the preset archive version number encoding rules. The hash digest, archive timestamp, and archive version number are accurately added to the preset data fields of the dynamic event record chain. The full integration and encapsulation of all additional information and the original record chain data is completed. The complete record chain after integration and encapsulation is the multi-dimensional event record chain of the target highway.

[0064] The beneficial effects include: capturing and parsing the live stream of tiered response command execution; comprehensively collecting and standardizing various data from on-site response, ensuring the integrity and authenticity of the original on-site response records; tracing the trigger signals of abnormal events based on event chain identifiers, accurately retrieving relevant data from the initial trigger of the event, clarifying the source information of the event, and achieving complete tracing of the abnormal event chain; arranging the original on-site response records chronologically with the initial alarm time as the zero point, allowing the response process to be presented in an orderly manner according to the timeline, forming a logically clear sequence of event evolution; spatially anchoring video clips of the response process with the geographical coordinates of the event, achieving deep correlation between the temporal and spatial attributes of the response process, giving the event records precise spatial orientation; and adding standardized annotation information to the video through keyframe interpolation when performing composite encapsulation of spatiotemporally related event clips, improving the integrity and readability of video evidence units. The serial splicing of labeled video data ensures the continuity of the event video sequence without any gaps. Protocol encapsulation enables precise association and binding of video data with various handling-related data. The generated dynamic event record chain possesses temporal continuity and data correlation. Generating a hash digest for the dynamic event record chain and adding an archiving timestamp and file version number ensures the uniqueness and traceability of the multi-dimensional event record chain. Adding anti-tampering verification marks and file seals to the multi-dimensional event record chain and completing the archiving process technically ensures that the archived data is not tampered with, ensuring the authenticity and integrity of the dynamic event archive. The final dynamic event archive completely preserves the multi-dimensional spatiotemporal information of the entire process from triggering to handling of the abnormal event, providing accurate, comprehensive, and effective data support for the retrospective analysis and optimization of subsequent emergency response plans. It also provides standardized and reliable archival evidence for the review of events and process streamlining related to highway emergency response.

[0065] The scheme backtracking and optimization module is used to perform backtracking analysis on the dynamic handling scheme based on the total processing time of the dynamic event archive, and obtain the optimization adjustment parameters of the target highway.

[0066] In this embodiment of the invention, when the scheme backtracking optimization module performs backtracking analysis on the dynamic handling scheme based on the total processing time of the dynamic event archive to obtain the optimization adjustment parameters of the target highway, it is specifically used for: The total processing time of the dynamic event archive is calibrated by time interval to obtain the full process time interval of the target highway; The entire process time interval is compared with a preset standard processing time threshold for threshold determination. When the entire process time interval exceeds the standard processing time threshold, a timeout alarm flag for the target highway is obtained. In response to the timeout alarm, the resource allocation record and execution sequence window of the dynamic handling plan are retrieved back, and the actual arrival timestamp of the handling node in the dynamic handling plan is extracted from the dynamic event archive. The deviation nodes are located by comparing the resource allocation record with the actual arrival timestamp to obtain the list of delay nodes of the target highway. By tracing the path of delay handling nodes in the delay node list, a list of road network bottlenecks of the target expressway is obtained. Based on the list of delayed nodes and the list of road network bottlenecks, the compensation parameters of the dynamic handling scheme are calibrated to obtain the optimized adjustment parameters of the target expressway.

[0067] The calculation formula for the optimization adjustment parameters is as follows: , ; In the formula, This refers to the resource quota correction coefficient in the optimization adjustment parameters. The path detour weight in the optimization adjustment parameters is used to... This represents the total number of delayed nodes in the list of delayed nodes. For the first The delay duration of each delayed node, For the first Bottleneck correlation factors corresponding to each delay node The preset delay attenuation coefficient, The length of the road segment affected by the incident, The preset bottleneck congestion coefficient, The total number of bottlenecks. For the first The rate of capacity loss at each bottleneck point This is the preset standard traffic capacity.

[0068] Extract the initial alarm time and the completion confirmation time of the abnormal event from the dynamic event archive. Convert both times to standard UTC timestamp format and perform time calibration. Use the calibrated initial alarm time as the start point of the time interval and the completion confirmation time as the end point of the time interval. Define the total processing time interval according to the preset standardized format of "start timestamp - end timestamp". The defined standardized time interval data is the full process time interval of the target highway.

[0069] The total actual processing time is obtained by extracting the time difference between the start and end points of the entire process time interval. A preset standard processing time threshold matching the abnormal event type is retrieved. This threshold is the maximum allowable processing time for the corresponding event type. The total actual processing time is compared with the standard processing time threshold. When the total actual processing time exceeds the standard processing time threshold, it is determined that the entire process time interval exceeds the standard processing time threshold. Standardized identifier data containing a unique event identifier, the total actual processing time, and the standard processing time threshold is generated according to the preset alarm identifier generation rules. This standardized identifier data is the timeout alarm identifier for the target highway.

[0070] Using the unique event identifier in the timeout alarm as the exclusive search keyword, a precise backtracking search is performed in the dedicated storage database of the dynamic handling plan. The complete resource assignment record and execution sequence window corresponding to the event are retrieved. The resource assignment record includes the associated resource node identifier and resource assignment time of each handling node. The execution sequence window includes the preset arrival time and preset completion time of each handling node. Then, from the spatiotemporal related event fragments in the dynamic event archive, the actual timestamps of each resource node arriving at the corresponding handling node are extracted according to the handling node identifier and organized. The time difference between the preset arrival time and the actual arrival timestamp of each handling node is calculated. When the calculated time difference is greater than the preset handling node time deviation threshold, the handling node is determined to be a deviation node. The handling node identifier, preset arrival time, actual arrival timestamp, and time difference information of all deviation nodes are structured and organized according to the preset list format. The standardized list after organization is the delay node list of the target highway.

[0071] Extract the planned travel routes from the resource nodes corresponding to each delayed handling node in the delay node list to that node. Retrieve the full-segment traffic data of each planned travel route during the emergency handling execution period from the traffic status database of the target highway network. This data includes the real-time traffic speed, traffic density, and road traffic status of each segment. Verify the traffic status of each segment of the planned travel route segment by segment. Segments with traffic speeds lower than the preset normal traffic speed, traffic density higher than the preset normal traffic density, or blocked road traffic status are identified as road network bottlenecks. Extract the unique segment identifier, geographic coordinates, and specific traffic anomaly status of all road network bottlenecks. Structure and organize the above information according to the preset list format. The standardized list after organization is the road network bottleneck list of the target highway.

[0072] Extract the time difference, associated resource node identifier, and handling node attribute information of each delayed node in the delayed node list. Simultaneously, extract the road segment location, traffic anomaly type, and impact range information of each bottleneck point in the road network bottleneck point list. Based on the preset resource allocation rules and route planning rules of the target expressway's dynamic handling plan, for each delayed node, combined with its corresponding road network bottleneck point information, parameter calibration is performed sequentially according to the preset compensation parameter calibration rules for the quantity and type of resource allocation, as well as alternative routes and traffic priorities in route planning. At the same time, adaptive time compensation calibration is performed on the execution sequence window of each handling node. All calibrated resource compensation parameters, route compensation parameters, and time sequence compensation parameters are integrated according to the preset parameter structure. Add a unique event identifier and parameter calibration timestamp to the integrated parameter set. The integrated standardized parameter set is the optimization adjustment parameter of the target expressway.

[0073] The number of delay nodes is obtained by counting each delay node in the list of delay nodes of the target highway. This number is the basic statistical data related to the delay nodes, which is directly extracted from the list of delay nodes of the target highway.

[0074] The actual arrival timestamps corresponding to each delay node are extracted from the dynamic event archive of the target highway. Combined with the preset arrival time of the delay node in the dynamic handling plan of the target highway, the two times are converted into standard UTC time and the time difference is calculated. The time difference obtained is the delay duration of each delay node, which is calculated from the corresponding data in the dynamic event archive and the dynamic handling plan.

[0075] For each delay node on the target highway, a standardized calibration is performed based on the impact of its corresponding road network bottleneck and the importance of related road segments. The calibration result is a bottleneck correlation factor for each delay node, which is obtained from the correlation analysis between the delay node list and the road network bottleneck list.

[0076] The delay attenuation coefficient is a fixed standard value preset in the highway emergency response system, which is directly retrieved from the preset highway emergency response standard parameter library.

[0077] The actual length data of the highway segment affected by the abnormal event is extracted from the event attribute parameters of the abnormal event alarm information of the target highway. This data is the length of the road segment affected by the event and is directly extracted from the abnormal event alarm information.

[0078] The bottleneck congestion coefficient is a fixed standard value preset in the highway emergency response system, which is directly retrieved from the preset highway emergency response standard parameter database.

[0079] The total number of bottlenecks is obtained by counting each bottleneck point in the bottleneck list of the target highway network. This data is directly extracted from the bottleneck list of the target highway network.

[0080] The actual capacity data of each bottleneck point is extracted from the bottleneck point list of the target expressway network. Combined with the preset standard capacity data of the expressway section, the ratio of the actual capacity to the standard capacity is calculated. The resulting ratio is the capacity loss rate of each bottleneck point, which is calculated from the bottleneck point list and the preset standard data.

[0081] Standard traffic capacity is a fixed standard value preset for each section of the expressway, which is directly retrieved from the preset expressway network standard parameter library.

[0082] The correction coefficient, obtained by integrating data such as delay duration of delay nodes, bottleneck correlation factors, and length of road segments affected by events from the relevant calculations of the optimization adjustment parameters of the target expressway, is used to make adaptive adjustments to the resource allocation quota in the subsequent dynamic handling plan. The calculation result of this correction coefficient can accurately reflect the actual impact of delays and road network bottlenecks on resource allocation.

[0083] The weight values ​​obtained from the optimization and adjustment parameters of the target expressway, by integrating data such as the capacity loss rate of bottleneck points and the total number of bottleneck points, are used to determine the detour weight in the route planning of the subsequent dynamic disposal plan. The calculation results of these weight values ​​can accurately reflect the actual impact of road network bottlenecks on route traffic.

[0084] The optimization adjustment parameter formed by combining the resource quota correction coefficient and the route detour weight can provide a precise compensation calibration basis for the dynamic disposal plan of the target expressway from the two core dimensions of resource allocation and route planning. The calculation result of this parameter directly serves the retrospective optimization of the dynamic disposal plan.

[0085] By integrating and calculating relevant data on delay nodes and road network bottlenecks in all dimensions to obtain optimized adjustment parameters, the optimized dynamic response plan for the target highway can accurately avoid road network bottlenecks, reasonably adjust the quantity and type of resource allocation, scientifically plan detour routes for response paths, and effectively reduce delays at response nodes during subsequent emergency response processes.

[0086] After adjusting the dynamic response plan for the target highway based on optimized parameters, the resource allocation and route planning of the dynamic response plan can better match the actual road network status and emergency response needs of the highway, continuously improving the overall efficiency of intelligent emergency response for the target highway and making subsequent emergency response procedures more scientific and practical.

[0087] Reference Figure 2 The diagram shown is a flowchart illustrating an intelligent emergency response method for highways according to an embodiment of the present invention. In this embodiment, the intelligent emergency response method for highways includes: Pt.1. Perform multi-source fusion analysis on the video stream data and traffic flow data of real-time road conditions in the target highway to obtain the abnormal event alarm information of the target highway. Pt.2. Based on the abnormal event alarm information, perform a status query on the emergency resource database of the target highway to obtain the available resource list of the target highway; Pt.3. Based on the event type of the abnormal event alarm information, retrieve the basic contingency plan from the contingency plan knowledge base of the target highway, and perform resource projection on the basic contingency plan based on the available resource list and the geographical coordinates in the alarm information to obtain the dynamic handling plan of the target highway. Pt.4. Deconstruct the dynamic handling scheme to obtain the hierarchical handling instructions for the target highway; Pt.5. Based on the real-time bitstream of the execution of the graded handling instructions, the event chain fusion of the abnormal event triggering signal is performed to obtain the dynamic event file of the target highway. Pt.6. Based on the total processing time of the dynamic event archive, a retrospective analysis is performed on the dynamic processing scheme to obtain the optimized adjustment parameters of the target highway.

[0088] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0089] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0090] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A smart emergency response system for highways, characterized in that, The system includes a multi-source fusion analysis module, an emergency resource query module, a dynamic contingency plan generation module, a hierarchical instruction deconstruction module, an event archive fusion module, and a plan backtracking and optimization module, wherein: The multi-source fusion analysis module is used to perform multi-source fusion analysis on video stream data and traffic flow data of real-time road conditions in the target highway to obtain abnormal event alarm information of the target highway. The emergency resource query module is used to perform a status query on the emergency resource database of the target highway based on the abnormal event alarm information, and obtain a list of available resources for the target highway. The dynamic contingency plan generation module is used to retrieve basic contingency plans from the contingency plan knowledge base of the target highway based on the event type of the abnormal event alarm information, and to perform resource projection on the basic contingency plans based on the available resource list and the geographical coordinates in the alarm information to obtain a dynamic handling plan for the target highway. The hierarchical instruction deconstruction module is used to deconstruct the dynamic handling scheme to obtain the hierarchical handling instructions for the target highway. The event file fusion module is used to perform event chain fusion on the abnormal event trigger signal based on the on-site real-time bitstream of the execution of the graded handling instructions, so as to obtain the dynamic event file of the target highway. The scheme backtracking and optimization module is used to perform backtracking analysis on the dynamic handling scheme based on the total processing time of the dynamic event archive, and obtain the optimization adjustment parameters of the target highway.

2. The intelligent emergency response system for highways as described in claim 1, characterized in that, When the multi-source fusion analysis module performs multi-source fusion analysis on the video stream data and traffic flow data of real-time road conditions on the target highway to obtain the abnormal event alarm information of the target highway, it is specifically used for: Frame-by-frame image recognition is performed on the video stream data of the target highway to obtain the first sensing device identifier of the target highway. The traffic flow data of the target highway is scanned using cross-sectional parameters to obtain the second sensing device identifier of the target highway; The first sensing device identifier and the second sensing device identifier are matched and verified to obtain the preliminary associated event signal of the target highway; Based on the preliminary associated event signal, the device installation coordinates of the first sensing device are retrieved, and the device installation coordinates are used as the geographical coordinates of the abnormal event alarm information to obtain the abnormal event alarm information of the target highway.

3. The intelligent emergency response system for highways as described in claim 1, characterized in that, When the emergency resource query module performs a status query on the emergency resource database of the target highway based on the abnormal event alarm information to obtain the available resource list of the target highway, it is specifically used for: Based on the event attribute parameters of the abnormal event alarm information, the spatial range of resource records in the emergency resource database of the target highway is delineated to obtain a candidate resource list for the target highway. The status feedback message of the candidate resource list is received, and the current location data, task load status and equipment integrity identifier of the resource node are parsed from the status feedback message to obtain the real-time dynamic attribute parameters of the target highway. Based on the event geographic coordinates of the event attribute parameters and the current location data, a path is connected to the target highway to obtain the path passage parameters of the target highway. By associating and binding the real-time dynamic attribute parameters and the path access parameters, a list of available resources for the target highway is obtained.

4. The intelligent emergency response system for highways as described in claim 1, characterized in that, When the dynamic contingency plan generation module executes the event type based on the abnormal event alarm information, retrieves the basic contingency plan from the contingency plan knowledge base of the target highway, and projects the basic contingency plan based on the available resource list and the geographical coordinates in the alarm information to obtain the dynamic handling plan for the target highway, it is specifically used for: Based on the triggering feature parameters of the abnormal event alarm information, the contingency plan entries in the contingency plan knowledge base of the target highway are traversed and matched to obtain the basic contingency plan of the target highway. The resource requirement list of the basic plan is compared item by item with the resource records in the available resource list to obtain the matching resource pool of the target expressway; Task codes are assigned to the resource nodes in the matching resource pool to obtain the execution plan for the target highway; The traffic link is calculated for the contingency plan to be executed, and the obtained optimal guidance trajectory is bound to the disposal node in the contingency plan to be executed to obtain the dynamic disposal plan for the target highway.

5. The intelligent emergency response system for highways as described in claim 1, characterized in that, When the hierarchical instruction deconstruction module performs task deconstruction on the dynamic handling scheme to obtain the hierarchical handling instructions for the target highway, it is specifically used for: The sequence of disposal nodes in the dynamic disposal plan is analyzed item by item to obtain the disposal task list of the target highway; Based on the resource node identifiers of the task list, the preset organizational responsibility list is indexed and retrieved to obtain the mapping table of the target highway. Based on the mapping relationship and the task list, the general handling content in the dynamic handling plan is translated into the action outline of the target highway to obtain the original instruction text of the target highway. The original instruction text is structured and encapsulated to obtain the graded handling instructions for the target highway.

6. The intelligent emergency response system for highways as described in claim 1, characterized in that, When the event file fusion module executes the live bitstream based on the execution of the graded handling instructions and performs event chain fusion on the abnormal event trigger signals to obtain the dynamic event file of the target highway, it is specifically used for: The system captures the live bitstream of the graded handling instructions and performs protocol parsing on the live bitstream to obtain the original live handling record of the target highway. Based on the event chain identifier of the original on-site handling record, the event chain of the abnormal event triggering signal is traced to obtain the event source file of the target highway. Using the initial alarm time in the event source file as the time reference zero point, the original on-site handling records are arranged in chronological order to obtain the event evolution sequence of the target highway; Spatially anchor the video clips of the handling process in the event evolution sequence with the event geographic coordinates of the original on-site handling record to obtain the spatiotemporal related event clips of the target highway; The spatiotemporal related event fragments are compositely encapsulated to obtain a multi-dimensional event record chain of the target highway; Add anti-tamper verification mark and file seal to the multi-dimensional event record chain and store it in the target highway event archive database to obtain the dynamic event archive of the target highway.

7. The intelligent emergency response system for highways as described in claim 6, characterized in that, When the event archive fusion module performs composite encapsulation of the spatiotemporally related event fragments to obtain the multi-dimensional event record chain of the target highway, it is specifically used for: Keyframe interpolation is performed on the video evidence units of the spatiotemporally related event segments to obtain the labeled video data of the target highway; The labeled video data is serially spliced ​​to obtain the event video sequence of the target highway; The event video sequence is encapsulated using a protocol to obtain the dynamic event recording chain of the target highway; The dynamic event record chain is hashed and digested, and an archive timestamp and file version number are added to the initially encapsulated dynamic event record chain to obtain the multi-dimensional event record chain of the target highway.

8. The intelligent emergency response system for highways as described in claim 1, characterized in that, When the scheme backtracking optimization module performs backtracking analysis on the dynamic handling scheme based on the total processing time of the dynamic event archive to obtain the optimization adjustment parameters of the target highway, it is specifically used for: The total processing time of the dynamic event archive is calibrated by time interval to obtain the full process time interval of the target highway; The entire process time interval is compared with a preset standard processing time threshold for threshold determination. When the entire process time interval exceeds the standard processing time threshold, a timeout alarm flag for the target highway is obtained. In response to the timeout alarm, the resource allocation record and execution sequence window of the dynamic handling plan are retrieved back, and the actual arrival timestamp of the handling node in the dynamic handling plan is extracted from the dynamic event archive. The deviation nodes are located by comparing the resource allocation record with the actual arrival timestamp to obtain the list of delay nodes of the target highway. By tracing the path of delay handling nodes in the delay node list, a list of road network bottlenecks of the target expressway is obtained. Based on the list of delayed nodes and the list of road network bottlenecks, the compensation parameters of the dynamic handling scheme are calibrated to obtain the optimized adjustment parameters of the target expressway.

9. The intelligent emergency response system for highways as described in claim 8, characterized in that, The calculation formula for the optimization adjustment parameters is as follows: ， ； In the formula, This refers to the resource quota correction coefficient in the optimization adjustment parameters. The path detour weight in the optimization adjustment parameters is used to... This represents the total number of delayed nodes in the list of delayed nodes. For the first The delay duration of each delayed node, For the first Bottleneck correlation factors corresponding to each delay node The preset delay attenuation coefficient, The length of the road segment affected by the incident, The preset bottleneck congestion coefficient, The total number of bottlenecks. For the first The rate of capacity loss at each bottleneck point This is the preset standard traffic capacity.

10. A smart emergency response method for highways, characterized in that, The method for using the intelligent emergency response system for highways according to claim 1: Pt.

1. Perform multi-source fusion analysis on the video stream data and traffic flow data of real-time road conditions in the target highway to obtain the abnormal event alarm information of the target highway. Pt.

2. Based on the abnormal event alarm information, perform a status query on the emergency resource database of the target highway to obtain the available resource list of the target highway; Pt.

3. Based on the event type of the abnormal event alarm information, retrieve the basic contingency plan from the contingency plan knowledge base of the target highway, and perform resource projection on the basic contingency plan based on the available resource list and the geographical coordinates in the alarm information to obtain the dynamic handling plan of the target highway. Pt.

4. Deconstruct the dynamic handling scheme to obtain the hierarchical handling instructions for the target highway; Pt.

5. Based on the real-time bitstream of the execution of the graded handling instructions, the event chain fusion of the abnormal event triggering signal is performed to obtain the dynamic event file of the target highway. Pt.

6. Based on the total processing time of the dynamic event archive, a retrospective analysis is performed on the dynamic processing scheme to obtain the optimized adjustment parameters of the target highway.

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