610 results about "Highway maintenance" patented technology

The present invention relates to the technical field of highway maintenance management, and in particular to a highway maintenance safety management system. The system includes a road condition monitoring module, a traffic load assessment module, a traffic flow redistribution module, a maintenance timing determination module, and a maintenance effect verification module, which are used to monitor multi-layer road condition data of the highway, and perform table-deep correlation detection to obtain road surface abnormal point data; quantify the road surface loss risk of the road surface abnormal point data to obtain road surface loss early warning indicators; collect vehicle images and meteorological data; analyze vehicle model loss contribution based on vehicle images; construct an environmental impact coefficient matrix based on meteorological data; construct a dynamic weight model based on vehicle model loss contribution and environmental impact coefficient matrix to obtain a road surface loss dynamic weight model. The present invention improves the efficiency, benefit and intelligence level of highway maintenance management by organically integrating highway maintenance with traffic management.

The invention relates to the technical field of road maintenance management, and particularly discloses a novel digital road maintenance management method and system based on multi-source data, and the method comprises the steps: carrying out the multi-dimensional analysis of a road crack image through employing an image processing technology based on deep learning; the method comprises the following steps of: identifying a crack type and quantifying key parameters such as width, length and area of the crack, simultaneously, capturing a time sequence change trend and a periodic rule of road traffic flow by performing time sequence analysis on historical traffic flow data of a road, and further fusing a static crack detection result with a dynamic traffic load mode through a time sequence derivation algorithm to obtain a dynamic crack detection result. The expansion trend of the crack under the action of the future traffic load is predicted, and long-term crack development prediction is formed, so that road maintenance management is performed based on the long-term prediction result of the road crack. According to the method, accurate diagnosis and active intervention of the road state can be effectively realized through multi-dimensional data collaborative analysis, so that the efficiency and effect of road maintenance are remarkably improved.

The invention discloses an intelligent asphalt pavement disease detection method based on a YOLOv5 algorithm, and relates to the technical field of intelligent expressway and road maintenance, and the method comprises the steps: obtaining video data through a vehicle-mounted or airborne pan-tilt camera, and constructing an asphalt pavement disease image data set through manual marking; a YOLOv5 target detection model is adopted, an efficient multi-scale attention mechanism is introduced, and preliminary training is carried out; detecting a real-time database on the basis of a pre-trained improved YOLOv5 target detection model, and manually checking a detection result so as to optimize the model; and performing redundant data de-duplication on continuous multi-frame image information by using a dynamic planning method, correcting the image by using a chessboard method to obtain the actual size of the target, and performing evaluation according to a disease standard. Therefore, by adopting the method, the labor cost and the calculation cost can be saved, the pressure of storage requirements can be reduced, the real-time detection effect can be realized, and the method can be widely applied to asphalt pavement disease detection.

The invention relates to the technical field of road maintenance, and discloses a road maintenance decision support system based on digital twinning, which comprises a data acquisition module, a digital twinning module, a maintenance decision module, an intelligent monitoring module and a user interface module, wherein the data acquisition module is used for acquiring various data of a road in real time, including road surface conditions, traffic flow and environmental factors; wherein the digital twin module is used for establishing a road virtual model, performing simulation analysis and providing accurate data support for maintenance decision making; wherein the maintenance decision module is used for formulating a maintenance plan and strategy by utilizing an optimization algorithm and a data analysis technology based on the output of the digital twin module. According to the road maintenance decision support system based on the digital twinning, the digital twinning model of the road is constructed, and the real-time monitoring data and the advanced algorithm are combined, so that the intelligent support of the road maintenance decision is realized.

The invention discloses a filtering anti-blocking structure of a drainage pipe for road maintenance, and relates to the technical field of sewage discharge. The filtering anti-blocking structure of the drainage pipe for road maintenance comprises a first pipeline, and the top of the first pipeline is fixedly connected with a first filtering mechanism. According to the filtering anti-blocking structure of the drainage pipe for road maintenance, sewage is preliminarily filtered by arranging the conical filtering cylinder, and the sewage is secondarily filtered by arranging the first filtering disc and the second filtering disc in a matched manner, so that the situation that a single filtering net is easily and instantly blocked by large-particle impurities is avoided, the pressure of post-stage filtering is reduced, and the filtering efficiency is improved. A limiting rotating ring block is arranged, a first driving motor is started, the limiting rotating ring block is finally driven to rotate through gear meshing, at the moment, a rotating ball continuously slides on the surface of the limiting rotating ring block, and a first spring is matched, so that a second fixing block periodically reciprocates; finally, the banister brush is promoted to clean the through holes of the conical filter cartridge, and the through holes are prevented from being blocked.

The invention belongs to the field of road maintenance detection, and discloses an asphalt pavement crack detection method and system based on image analysis, electronic equipment and a storage medium, and the method comprises the following steps: collecting an image of an asphalt pavement, and preprocessing the collected image to obtain a first image; segmenting the preprocessed image by using a full convolutional neural network, and performing morphological processing on the segmented image to obtain a second image; calculating a gray level co-occurrence matrix of the second image and extracting texture features, detecting edge information of the second image by using an edge detection algorithm, and combining the texture features with the edge information to obtain a crack candidate area; constructing a convolutional neural network model, and training the convolutional neural network model through the historical crack image and the historical non-crack image to obtain a crack recognition model; and inputting the crack candidate region into a crack identification model for crack identification to obtain a crack identification result.

The invention relates to the field of intelligent transportation systems, discloses an intelligent highway maintenance system and method, and aims to solve the fundamental defects that in the prior art, the data acquisition dimension is single, the maintenance decision depends on artificial experience, and prospective prediction is lacked. The method comprises the following steps: acquiring multi-modal dynamic sensing data covering a whole road domain; constructing and updating a four-dimensional space-time digital twinborn model in real time; driving the causal graph neural network model to perform structure health state prediction and diagnosis; generating an active maintenance instruction through a multi-objective optimization engine; and the autonomous maintenance execution unit is dispatched to complete unmanned closed-loop operation. According to the method and the system, fundamental transformation of road maintenance from passive response to active prevention, from artificial experience to intelligent decision making and from discrete operation to closed-loop automation is realized, and the maintenance efficiency, the safety and the health level of the whole life cycle of the road are remarkably improved.

The invention provides a road maintenance unit intelligent division management system based on BIM-GIS, and belongs to the technical field of traffic operation and maintenance. The system comprises a BIM module used for establishing a BIM model of a target road; the GIS module is used for carrying out maintenance unit division on the target road based on a unit division rule to obtain a plurality of maintenance units; the BIM-GIS fusion module is used for carrying out position matching on the BIM model and a plurality of maintenance units; and the interaction module is used for displaying the maintenance information of each maintenance unit and executing maintenance operation in response to the maintenance instruction. The road maintenance unit intelligent division management system based on the BIM-GIS provided by the invention can improve the refinement degree of road maintenance and significantly improve the accuracy and efficiency of maintenance management.

The invention belongs to the technical field of road maintenance, and particularly relates to a pretreated waste mixture high-content ultrathin overlay and a preparation method thereof, and the pretreated waste mixture ultrathin overlay comprises the following raw materials: a pretreated waste mixture, a new aggregate, special recycled asphalt and mineral powder. The purpose of the invention is achieved by performing pretreatment modification on the waste milling material to improve the strength and interface cohesiveness of the waste milling material, activating the activity of the original aged asphalt by using the special recycled asphalt, reducing the mixing temperature and the like. The ultra-thin overlay with the pretreated waste milling material mixture and the doping amount larger than 80% can make full use of the advantages of a regeneration technology and an ultra-thin overlay technology, and has the advantages of being environmentally friendly, high in interface cohesiveness and regeneration utilization rate, capable of saving energy and reducing cost, capable of improving pavement performance and the like.

The invention discloses a highway maintenance knowledge question and answer method and system based on multi-modal information, and belongs to the technical field of knowledge question and answer. Comprising the steps of obtaining user question data and converting the user question data into a plurality of modal feature vectors; processing the plurality of modal feature vectors through a preset multi-modal decoupling network to obtain complementarity features and consistency semantic features; on the basis of the complementarity features and the consistency semantic features, independent retrieval of all modes is carried out in a preset multi-mode knowledge base with the consistency semantic features as guidance, cross-mode association retrieval is carried out through the association degree between different modes of knowledge, and candidate knowledge of all modes is obtained; and according to the consistent semantic features, processing each modal candidate knowledge through an answer generation network to obtain a multi-modal answer. The accuracy and flexibility of answering the expressway maintenance knowledge can be improved, and the problem that the processing accuracy of the existing question and answer task containing the multi-modal expressway maintenance knowledge is not high is solved.

The invention relates to a remote visual remote-control automatic inspection device for highway maintenance operation, and relates to the technical field of intelligent monitoring of traffic safety facilities, and the remote visual remote-control automatic inspection device comprises a rack which is used for being hung on a guardrail of a high highway, the rack is provided with a camera shooting system and a sensor system which are used for data acquisition and transmission, and further comprises a data processing and analyzing system and an alarm and notification system which are connected to the camera shooting system; the anti-falling walking mechanism is arranged on the rack and comprises a walking assembly and a strong wind prevention assembly, the anti-falling walking mechanism has a walking inspection mode and a strong wind prevention mode, and when the anti-falling walking mechanism is in the walking inspection mode, the walking assembly is started; and when the anti-falling walking mechanism is in the strong wind prevention mode, the strong wind prevention assembly is started. The method has the effects of carrying out comprehensive coverage monitoring in a certain span region and improving the inspection efficiency and the inspection quality of road inspection.

The invention relates to the field of road maintenance engineering, in particular to anti-crack mortar for repairing road cracks and a preparation method of the anti-crack mortar. The anti-crack mortar for repairing the road cracks is prepared from the following raw materials in parts by mass: 90 to 130 parts of a gel material, 10 to 20 parts of a composite reinforcing agent, 120 to 180 parts of aggregate, 5 to 15 parts of a polymer auxiliary agent, 2 to 10 parts of propylene glycol, 0.3 to 0.8 part of a water reducing agent, 0.3 to 0.6 part of a retarder, 1.5 to 5 parts of a combined auxiliary agent, 20 to 40 parts of water and the like. The finally prepared anti-crack mortar not only has more excellent anti-crack performance, but also can keep good cohesiveness, has excellent adaptability and weather resistance in high and low temperature environments, is excellent in salt corrosion resistance and long in service life, reduces the maintenance frequency, and is suitable for large-scale popularization and application. The comprehensive performance requirements of the existing road maintenance engineering field on the anti-crack mortar for repairing are met.

The invention relates to the technical field of detection devices, in particular to a road maintenance ground permeability detection device which comprises a detection support, an inner enclosure, an outer enclosure and a check ring. The inner enclosure is arranged in the vertical direction and located at the lower end of the detection support, and a detection space is defined among the inner enclosure, the detection support and the ground. The outer enclosure is rotationally installed at the lower end of the check ring, and a smearing space is defined by the detection support, the inner enclosure, the outer enclosure and the check ring. According to the ground permeability detection device for road maintenance, the detection support, the inner enclosure, the outer enclosure and the check ring are arranged and matched, when a sealing material is smeared, an automatic smearing mode is adopted to replace manual smearing, the smearing area is large, the efficiency is high, and in the whole smearing process, the smearing efficiency is high; the detection space and the smearing space are separated from each other through the inner enclosure, so that the sealing material in the smearing space can be prevented from entering the detection space, and the accuracy of subsequent detection is improved.

The invention relates to the technical field of resource scheduling, in particular to a road maintenance allocation system and method based on data analysis, and the system comprises a material aging evaluation module, a road wear evaluation module, a traffic load influence analysis module, a budget allocation module and a maintenance adjustment module. According to the method, by collecting and analyzing the initial components of the highway pavement material and monitoring changes in different time periods, the attenuation rate and the mass loss of the material can be accurately calculated, the recognition precision of the highway maintenance requirement is improved through data driving, it is ensured that resources can be more effectively distributed to the area where maintenance is most needed, and the maintenance efficiency is improved. Not only can the actual loss degree be responded, but also the future wear trend and damage expansion can be predicted, the utilization and budget distribution of maintenance resources can be optimized, the specific influence on the pavement wear can be analyzed in combination with traffic flow and vehicle load distribution data, and the fund and maintenance plan can be further accurately adjusted. And the maintenance work is more prospective and targeted.

The invention belongs to the technical field of road maintenance, and discloses a road concrete pavement layer self-adaptive crushing method based on microwave-assisted resonance, and the specific technical scheme is as follows: a microwave heating device is used for pretreating a cut and divided crushing area, and a concrete layer is weakened through a heating effect of microwave radiation to realize separation of a pavement layer; when it is judged that the temperature of the concrete in the heating area reaches the needed temperature through the thermal infrared imager, the inherent frequency of the concrete is calculated, a calculation result is fed back to the resonance crushing device, and the resonance crushing device enables the pavement layer to generate forced vibration to be crushed by generating excitation frequency; the novel method for crushing the concrete pavement layer based on microwave-resonance energy coupling has the characteristics of being accurate, controllable, efficient, applicable to multiple scenes and the like, and can be matched with an acoustic emission system to realize closed-loop control of concrete crushing, so that the working environment of the concrete pavement layer is greatly improved, and the service life of the concrete pavement layer is prolonged. And the maintenance frequency of the equipment is greatly reduced while the crushing efficiency is improved.

The invention relates to the technical field of application computer science and artificial intelligence, and discloses a highway pavement disease rapid identification and diagnosis system based on deep learning, and the system comprises a data collection and preprocessing module which is used for obtaining and processing multi-source time series data; the unified state vector characterization module is used for constructing a unified vector for characterizing the comprehensive state of the pavement; the spatio-temporal evolution and inference module is used for simulating the spatio-temporal evolution process of the pavement state; the model training and optimizing module is used for carrying out optimization training on the evolution model; and the diagnosis and prediction application module is used for generating a final diagnosis report and maintenance decision. According to the method, the development trend of the pavement diseases and the effects under different maintenance scenes are deduced and simulated through the spatio-temporal depth model jointly constrained and optimized by physical and causal knowledge, a complete closed loop of the pavement diseases from static recognition to dynamic diagnosis and decision making is realized, and the scientificity and the intelligent level of road maintenance management are improved.

The utility model belongs to the technical field of rainwater collection and utilization, and particularly relates to an automatic road rainwater collection and storage device which comprises a water storage pool body, a water collection assembly is installed on one side of the water storage pool body, and a reinforcing supporting plate is connected to the inner wall of the water storage pool body in a welded mode. A liquid level display assembly is installed on the other side of the water storage tank body, a sealing cover protection assembly is installed on the top of the water storage tank body, the bottom end of the water storage tank body communicates with a water outlet pipeline, and the water collection assembly comprises a water collection channel; a plurality of water collecting and catchment pipelines can be designed and built according to specific terrains, rainwater on the road can be conveniently collected, the water storage pool is arranged to store the rainwater, the road can be maintained or nearby green belts can be irrigated by utilizing terrain difference or pumping water in the pool through a water pump when the rainwater is needed, and the rainwater collecting and catchment functions are achieved. The utilization rate of rainwater is conveniently increased, and water resources are saved.

The invention discloses an expressway maintenance construction area vehicle operation carbon emission metering method based on multi-agent simulation, a storage medium and equipment. In the method, a simulation model based on a multi-agent system is constructed, and the method comprises a vehicle agent for realizing generation and position updating of a vehicle in a road network; the road section intelligent agent is used for updating road section flow and traffic capacity; and the construction intelligent agent realizes adjustment of the construction scheme of the construction road section. And according to the division of the vehicle types and the vehicle energy types, carbon emission generated by vehicle operation during construction is measured and calculated, and carbon emission generated by construction activities in the construction process is measured and calculated. According to the method, through quantitative analysis, the influence of different construction schemes on the average speed, the vehicle delay time and the carbon emission of the highway section can be evaluated. The rule that the traffic carbon emission changes along with the length of a construction area of a construction road section, the speed limit value and the lane closing form can be revealed and can be used as a reference basis for construction engineering design and implementation.

The invention discloses a pavement maintenance system and detection method based on an unmanned aerial vehicle, and belongs to the technical field of highway maintenance, and the method comprises the following steps: obtaining a pavement image and three-dimensional point cloud data of a target road section based on a main survey machine; screening a road surface suspicious region set in the target road section based on the road surface image and the three-dimensional point cloud data acquired by the main surveying machine; planning a re-exploration path based on the road surface suspicious region set; the method comprises the following steps: acquiring an optical image, a thermal infrared image and three-dimensional point cloud data of a road surface suspicious region set from a surveying machine; and performing defect verification on the road surface suspicious region set based on the optical image, the thermal infrared image and the three-dimensional point cloud data acquired from the surveying machine. The technical problems that a traditional road surface detection mode is low in detection efficiency, needs to close a lane and hinders traffic are solved, and the technical effect of low-cost, high-precision and rapid road surface detection is achieved.

The invention provides a highway maintenance safety operation cooperative prevention and control system integrated with a four-prevention and one-hiding technology. According to the system, the safety of road maintenance operation is improved. The early warning control module is connected with the remote sound-light-electricity early warning unit, the upstream guardrail early warning unit, the forward anti-mistaken-running unit and the lateral anti-mistaken-running unit through the Internet of Things and the single-chip microcomputer control technology, an operation area is monitored in real time, social vehicles are prevented from mistakenly running into the operation area, and the operator safety monitoring module is connected with the early warning module in real time through intelligent wearable equipment. An early warning signal is sent to an operator to remind the operator to avoid risks in time, and the cooperative control module fuses real-time data of all the modules, carries out global target optimization decision, adjusts the working state and ensures cooperative and efficient operation of all the modules. Through the combination of four-prevention and one-hiding technologies, the safety of road maintenance operation is effectively improved, the risk of accidents is reduced, and the operation efficiency is improved.

The invention discloses a pavement crack segmentation and quantification method based on pyramid region attention, and relates to the technical field of computer vision. The road maintenance mileage is increased year by year, the capital and human input required for maintaining the road network is quite huge, and the efficient, accurate and robust pavement crack segmentation and quantification method has important significance in monitoring the pavement damage condition and reducing the road maintenance expenditure. According to the method, the long-distance dependency relationship can be effectively captured while the low calculation cost is kept, the segmentation precision of the pavement crack is improved, the crack damage rate is calculated according to the segmentation result, a basis is provided for evaluation of the road damage condition, the pavement maintenance decision-making efficiency is improved, and the maintenance expenditure is reduced.

The invention relates to an expressway maintenance management method and system, and relates to the field of road maintenance, and the method comprises the steps: obtaining humidity change diagrams corresponding to a plurality of positions in a tunnel and vibration change diagrams corresponding to the plurality of positions, the humidity change diagrams and the vibration change diagrams are humidity change diagrams and vibration change diagrams from the last maintenance time to the current time, determining an abnormal risk value of each position based on the humidity change diagrams and the vibration change diagrams, and obtaining historical monitoring videos in the tunnel; the historical monitoring video is a monitoring video from the last maintenance time to the current time, determining the severity of an accident occurring in the tunnel and the position of the accident based on the historical monitoring video, judging whether a road section needing to be maintained exists or not based on the abnormal risk value and the severity of the accident, and if the road section needing to be maintained exists, stopping maintenance. And if yes, outputting the road section to be maintained. The method and the device have the effect of finding the position where the tunnel is about to be damaged or damaged in time.

The present invention belongs to the technical field of construction carbon emission, and specifically discloses a method and system for calculating carbon emission and carbon reduction during highway maintenance and repair construction, by calculating the carbon emission of construction machinery, carbon emission of material transportation, carbon emission factor per unit shift, carbon emission factor per unit turnover of transportation equipment, construction material usage, carbon dioxide emission factor of construction materials, the number of recycled materials in the project content, carbon emission factor of recycled material production process, fossil fuel consumption and carbon emission factor of fossil fuel, and then obtaining the total direct carbon emission during highway construction. The present invention solves the problem that the prior art does not calculate the carbon emission and carbon reduction generated by the entire highway during the construction process to obtain the exact carbon emission.

The invention provides a road maintenance project carbon emission prediction method based on a fuzzy polynomial neural network, and the method comprises the steps: collecting and calculating the carbon emission data of a plurality of completed road maintenance projects, calculating the carbon emission through employing a method combining a quota method and an emission coefficient method, and constructing a basic data set; based on the basic data set, identifying an emission heat source, matching engineering quantity parameters, and primarily screening and selecting key indexes to construct input data of a prediction model; performing nonlinear modeling and generalization ability mining through a fuzzy polynomial neural network model, and constructing and training a prediction model based on the input data; and predicting the carbon emission of the road maintenance project through the prediction model. According to the highway maintenance engineering carbon emission prediction method based on the fuzzy polynomial neural network, rapid and accurate prediction of carbon emission can be realized only based on a small amount of key information in the early stage of the highway maintenance engineering.

The invention relates to the field of road detection management, in particular to a road maintenance polling analysis early warning method and system, and the method comprises the steps: determining all abnormal driving intervals of a global line of a road based on dynamic detection data of a ground polling process of the road; determining all form abnormal intervals of the global line of the highway based on visual detection data of the aerial inspection process of the highway; based on the driving abnormal interval and the form abnormal interval, estimating structural degradation interval distribution information, and generating a disease early warning map of the road in combination with external environment characteristics of the area where the road is located; and in combination with the driving state characteristics of the road, the prejudgment information of the master generation of the road is estimated, so that the change operation of the electronic map terminal is carried out. According to the method, global disease occurrence distribution early warning can be performed by combining the influence data of the highway pavement on driving and the highway pavement structure state data, structural accidents possibly occurring on the highway can be predicted, driving guide information can be changed in time, and the reliability of highway maintenance inspection is improved.

The invention is suitable for the technical field of intelligent traffic and digital construction, and provides a highway maintenance construction traffic influence simulation method based on an unreal engine V5, which comprises the following steps: acquiring a target area satellite image, a digital elevation model and road network vector data, completing coordinate unification and layer registration in a QGIS, generating a geographic base map, importing the geographic base map into CityEngine, and constructing a highway maintenance construction model. A model matched with a real road network structure is generated by utilizing a CGA rule, an unreal engine V5 is imported through a Datasmith plug-in to establish a digital twinborn simulation environment, a vehicle entity is generated through blueprint logic in a simulation scene and runs along a spline path, speed regulation and avoidance are dynamically performed based on the vehicle distance, the passing time of a construction area is recorded and compared with a non-construction standard, and the real road network model is established. Calculating traffic efficiency, collecting vehicle density, speed and path occupancy rate, and generating a thermodynamic diagram to realize traffic state visualization. Therefore, the static, low-efficiency and non-interactive characteristics of traditional construction influence evaluation are broken through, and the scientificity, accuracy and engineering implementability of construction organization optimization and traffic flow pre-judgment are remarkably improved.

The invention relates to the technical field of progress management, in particular to a road maintenance construction progress management method and system, and the method comprises the following steps: obtaining road maintenance construction data, calculating the driving time of construction equipment, the passing matching performance and the equipment scheduling sequence, screening a path with blocked passing, and building an equipment passing priority sequence. According to the method, pavement wear monitoring data is utilized, equipment operation intensity is matched according to wear conditions, material laying and mechanical frequency are optimized, pavement non-uniform wear is reduced, construction procedure time data are combined, a procedure connection sequence is optimized, construction continuity is improved, equipment sharing conflicts are reduced, and actual execution data of task nodes are analyzed; according to error accumulation, accurate correction, dynamic adjustment of a construction plan and matching of construction site requirements are carried out, the construction scheduling flexibility is improved, the plan execution precision is enhanced, construction interruption is effectively reduced, and the overall efficiency of road maintenance construction is improved.

The invention provides an expressway digital maintenance management method and system, and belongs to the field of pavement maintenance, and the method comprises the construction of a multi-mode sensing network, and achieves the accurate monitoring of a vehicle impact event and a pavement foreign matter through the pre-burying of a LoRaWAN vibration sensor and a millimeter wave radar array. A road surface point cloud model is generated by using a laser radar and an integrated navigation system, and three-dimensional space-time disease modeling is realized by combining infrared thermal imaging data. And during work order generation, maintenance decision is performed through a semi-Markov decision process, a maintenance strategy is optimized by adopting deep reinforcement learning, and an AR work order is generated for visualization and conflict detection. And meanwhile, a multi-relation graph is constructed to predict a pavement performance attenuation trend, and knowledge migration and generalization of a cross-section maintenance strategy are realized by using federal migration learning, so that the maintenance working efficiency and quality are improved, and digitization and automation of highway maintenance management are realized.

The invention discloses an intrusion early warning system for a road maintenance period, which relates to the technical field of traffic, and comprises a recording unit arranged in an event monitoring area and used for recording data of an intruded vehicle and uploading the data to an Internet of Things cloud platform to perform classification and risk assessment on an intruding event; a driving-in speed function and a driving-out speed function are constructed in a speed monitoring area, a dynamic overspeed reference value is calculated after integration and serves as an overspeed judgment basis of a current time window, and a dynamic display unit is arranged in a buffer area to receive and display the dynamic overspeed reference value in real time and update the dynamic overspeed reference value according to the sequence of the time window. According to the system, full-chain type monitoring is formed from the buffer area, the speed monitoring area to the event monitoring area, through collection and analysis of vehicle information, driving speed and track data and connection with the Internet of Things cloud platform, not only can overspeed behaviors be judged in real time, but also intrusion events can be classified and subjected to risk assessment, and the safety of the system is improved. And reliable data support is provided for subsequent optimization of a traffic management strategy.

The invention discloses a road maintenance construction equipment operation safety evaluation method and system, and relates to the technical field of equipment safety evaluation, and the method comprises the steps: collecting equipment multi-source operation state data, and carrying out the normalization processing, and forming a standardized working condition vector sequence; by taking each time sequence vector in the working condition vector sequence as a graph node, constructing a weighted adjacency matrix to generate a working condition evolution state graph; constructing a task feature vector according to the demand of a to-be-executed task, matching atlas nodes, calculating a path comprehensive score, and screening an optimal evolution path; all nodes in the optimal evolution path are mapped to a construction area, and the comprehensive score of the path is corrected by fusing environmental factors; and grading and classifying the corrected score and outputting a safety level and a control strategy. According to the invention, through dynamic risk correction and evolution path pre-judgment, closed-loop intelligent decision-making of construction safety is realized, and early warning timeliness and environmental adaptability are improved.