46 results about "Transportation infrastructure" patented technology

This invention discloses a modeling method for layered soft soil subgrades reinforced with pile foundations under simulated seismic loading, belonging to the field of seismic numerical simulation in geotechnical engineering. This method constructs a multi-field coupled numerical model based on a finite element platform, defines the contact mechanisms at the pile-soil and reinforced-subgrade interfaces, and completes the construction of in-situ stress equilibrium and initial pore water pressure fields. Static results are output through fill-consolidation coupling analysis. Distributed viscoelastic artificial boundaries are automatically constructed using Python scripts, and seismic waves are converted into equivalent nodal loads using wave theory. Multi-physics field connections between static and dynamic analysis boundaries are achieved, and core response parameters such as embankment settlement and pile-soil stress are output through implicit dynamic analysis. This invention considers the seismic wave propagation effect in layered soils, reduces spurious oscillations caused by the transformation of static and dynamic boundaries, and improves simulation accuracy and efficiency. It is suitable for seismic design and analysis of transportation infrastructure in soft soil areas.

A method for setting up an electrical transportation infrastructure in a mine includes receiving mining data for different time periods of a mining interval. The data identifies expected source locations where material is extracted and destination locations where it is delivered. Using this data, a time-dependent 3D network of the mine is determined for each period, either as separate networks of paths connecting the source and destination locations or as a single network covering all periods. Based on this network, a planned placement of the electrical transportation infrastructure is numerically determined to at least approximately minimize the expected total costs of the mine over the mining interval. These costs include estimated environmental costs from transporting material between source and destination locations, subject to mining constraints. Finally, the electrical transportation infrastructure is initialized in the mine according to the planned placement.

This invention provides a method and system for intelligent observation and planning of transportation infrastructure based on multi-aircraft collaboration, relating to the field of UAV intelligent observation technology. The method includes acquiring disaster scene, target distribution, and UAV resource information; determining sensor configuration schemes; calculating target urgency and prioritizing them for allocation; constructing access maps to generate observation sequences; planning unobstructed flight paths; controlling UAVs to execute observation tasks; and generating damage assessment results. This method achieves efficient multi-aircraft collaborative observation, improving the efficiency and accuracy of post-disaster transportation infrastructure assessment.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, the operating status of the features, the identity of a vehicle operator, risk levels for operation of the vehicle by the vehicle operator, or damage to the vehicle may be determined based upon sensor or other data. According to further aspects, decisions regarding transferring control between the features and the vehicle operator may be made based upon sensor data and information regarding the vehicle operator. Additional aspects may recommend or install updates to the autonomous operation features based upon determined risk levels. Some aspects may include monitoring transportation infrastructure and communicating information about the infrastructure to vehicles.

The invention discloses an intelligent power dispatching unit and an intelligent power dispatching system thereof, and belongs to the crossing field of intelligent power grids, new energy storage and traffic infrastructures. The intelligent power dispatching unit comprises m charging piles, an energy storage system and a relay array; the relay array is arranged between the charging pile and the energy storage system and is used for power dispatching and coupling of the charging pile and the energy storage system; the energy storage system comprises n DC / DC chargers; the number of relays in the relay array is m (m + 3) / 2 + n, m is an integer greater than or equal to 2, n is an integer greater than or equal to 2, and m is an integral multiple of n. A plurality of charging piles are combined with an energy storage system and a related detection control system to form an intelligent power dispatching unit, so that the purposes of flexibly dispatching charging power, relieving peak electricity consumption pressure, charging an energy storage battery by utilizing photovoltaic or electricity price valley sections and reducing charging cost are achieved.

This application provides a method and system for assessing earthquake-induced landslide risk in transportation networks in high-intensity seismic zones, relating to the field of landslide risk assessment technology. The method includes: screening key influencing factors of earthquake-induced landslides; optimizing the construction of positive and negative sample libraries; using a spatial weighted machine learning model to evaluate landslide susceptibility and generate a susceptibility zoning map; extracting parameters of potential landslide source areas based on the high-susceptibility zone identification results; using a parallel particle discrete element method to simulate the entire landslide movement process to obtain hazard parameters; inputting the hazard parameters into a transportation engineering structure vulnerability model to quantitatively calculate the failure probability; and fusing the susceptibility probability and structural vulnerability results to generate a risk zoning map based on road network units. The final results of this application are directly applicable to the operation and maintenance management of transportation infrastructure. The provided risk zoning map can be directly used to guide the optimal allocation of risk control resources, the formulation of emergency plans, and the seismic resilience design of engineering projects, demonstrating clear application value.

The present application provides an asphalt pavement apparent disease evolution deduction method, system, device and medium, which belongs to the field of road engineering, transportation infrastructure operation and maintenance and intelligent detection technology, and comprises the following steps: constructing a unified space-time reference system, aligning and normalizing multi-source data in space-time; forming section-level disease quantification characteristics based on the recognition results of the inspection images and the structural indexes; event coding the maintenance measures of the road surface and pre-processing the section-level disease quantification characteristics corresponding to the time of the maintenance measures; constructing the correlation, time lag effect and spatial consistency between the disease types, disease characteristics and structural indexes to generate the collaborative evolution characteristics of the coupling relationship between diseases; constructing a deep time series prediction model to obtain the disease development trend at a specified time scale in the future, and forming the section-level disease evolution prediction result. The present application can depict the disease development law at different road sections and different time scales, and predict the future disease expansion.

The present application relates to a bridge degradation identification and maintenance decision support method and system based on a knowledge graph, belonging to the technical field of intelligent operation and maintenance of transportation infrastructure and engineering information processing, and solving the defects of weak data fusion capability, opaque causal modeling and non-traceable decision support of the prior art. The method comprises: acquiring and preprocessing multi-source heterogeneous data to generate a standardized data set; performing semantic alignment to extract candidate entities and relationships; constructing a knowledge graph ontology and loading it as a knowledge graph; using an adaptive quantile threshold to binarize the factor intensity and disease severity sequence, and fusing a one-point smoothing mutual information and a Spearman correlation coefficient to learn the causal weight; completing the bridge factor influence relationship and calculating the weight through graph reasoning; and finally calculating the bridge degradation risk score and outputting the high-confidence influence path based on the shortest path algorithm. The present application realizes multi-source data fusion and explicit modeling of the degradation causal chain, and provides a scientific basis for bridge maintenance decision-making.

The invention provides a conical track supporting framework, which relates to the field of traffic transportation infrastructure, and comprises a conical main framework formed by splicing a plurality of modularized three-dimensional truss units and an auxiliary inner framework arranged in the main framework, and the auxiliary inner framework is transmitted to node balls through a track mounting support. The node balls distribute loads to the rod pieces through the connecting bases on the surfaces of the node balls, the elastic damping assemblies in the connecting bases absorb impact energy in the process, then the loads are transmitted through a dual-framework system composed of the modular three-dimensional truss units and the inner framework, and the dual-framework system and the modular three-dimensional truss units form a space grid structure through the shared node balls. When the structure vibrates, the tuned mass damper is started to work, the mass block of the tuned mass damper reciprocates in the protective shell, vibration energy is consumed through the spring element and the viscous fluid damper, and effective transmission of loads and active control of vibration are achieved through cooperative work of all the parts of the whole system.

The invention discloses a pavement structure interlayer bonding state field test method based on vibration spectrum analysis, and relates to the technical field of traffic infrastructure detection, and the method comprises the following steps: at the beginning stage of pavement structure interlayer bonding state field test, carrying out energy gradual rise control on excitation input of an excitation device, and continuously changing the excitation intensity along the time direction and forming an excitation energy evolution track. According to the method, an excitation energy evolution track is established through energy gradual increase control, overall resonance caused by sudden energy increase is avoided, interlayer slippage spectrum features are extracted, and accurate recognition of the local bonding state is achieved; and through phase transfer analysis and breathing type excitation adjustment, interlayer micro-motion can be continuously distinguished, a stable judgment base line is constructed, and dynamic identification and high-sensitivity tracking of the critical viscosity loss state are achieved.

This invention discloses a method, device, and medium for intelligent prediction of roadbed defects based on time-series augmented data, relating to the field of intelligent operation and maintenance of transportation infrastructure. The method first preprocesses the raw monitoring data to obtain a standardized multi-dimensional time-series dataset. Addressing the scarcity of defect samples, a time-series generative model is used to learn the temporal evolution patterns of defects and generate synthetic samples, constructing a class-balanced augmented dataset. Subsequently, a collaborative optimization framework is used to simultaneously search for the globally optimal feature subset and the globally optimal hyperparameter combination, and this is used to train a target prediction model. Finally, the target prediction model is used to analyze real-time data and output the defect prediction results. This invention effectively solves the problem of early identification and prediction of roadbed defects with small sample sizes through time-series data augmentation and feature-hyperparameter collaborative optimization, improving prediction accuracy and timeliness.

An arrangement for connecting transportation infrastructure peripheral devices, such as elevator and escalator peripheral devices, to a transportation infrastructure devices, such as elevator, using a building network is disclosed. In the arrangement a virtually dedicated channel for communication between elevator and escalator peripheral devices is created. The channel is used for transmitting signals, such as elevator calls, so that there is no need to use a dedicated and separated network elevator and escalator peripheral devices.

This invention relates to the interdisciplinary field of next-generation information technology and intelligent transportation infrastructure safety monitoring, and discloses a bridge fire risk status assessment method and system based on a large model. The key technical points are: system initialization and physical device-twin base mapping construction; collaborative perception of multimodal physical quantities and spatial visual features; transient thermal resistance network deduction and global synchronization deviation quantification; dimension-aligned graph network feature fusion; large model state reasoning with embedded physical knowledge constraints; safety margin quantification and three-dimensional coordinate-level hardware linkage. It employs digital twin thermal resistance network deduction, graph topology feature fusion, and large model physical knowledge constraint collaboration technology. By transforming the underlying objective thermodynamic mechanism into a dynamic penalty term and injecting it into the large model reasoning layer for decision correction, it eliminates the problem of insufficient physical consistency in purely data-driven models and constructs a hardware-level control closed loop for the entire system from multimodal perception to three-dimensional spatial targeted electromechanical linkage.

A data control device (1) successively executes logic based on action logic that describes action of an object. When the fact that the object has moved to a predetermined position is notified from a traffic simulator (3A) in accordance with execution of specific logic, the data control device (1) determines to which of a first shop simulator (3B) and a second shop simulator (3B) data of the object is to be transmitted using an attribute of the object stored in advance. The data control device (1) transmits the data of the object to the shop simulator (3B) to which the data of the object is determined to be transmitted. Such processing of the data control device (1) can be applied to social simulations used in a local government or a transportation infrastructure, for example.

The application discloses a kind of material performance and carbon emission collaborative prediction method for guardrail design, belong to the field of transportation infrastructure construction.It includes the following steps: collecting relevant data, converting category type features in data into model embedding vectors, and combining physical heuristic combined features and numerical features, obtaining an enhanced feature matrix after adaptive multi-kernel transformation;The enhanced feature matrix obtains the hidden layer representation matrix through the shared feature extraction layer;The hidden layer representation matrix is input into the material performance preliminary prediction branch and the carbon emission preliminary prediction branch to obtain the preliminary prediction result;The collaborative fusion layer uses trainable collaborative matrix and bias vector to collaboratively adjust the preliminary prediction of the two branches to obtain the collaborative prediction result;According to the collaborative prediction result, it is determined whether the scheme is feasible.The application can fully exploit the nonlinear relationship between data, significantly improve the generalization ability and prediction accuracy of the model.

The application belongs to the technical field of high-speed railway engineering and new generation information technology, and specifically relates to a railway subgrade disease evaluation method based on multi-model integration. Existing subgrade disease data is acquired, disease influence factors are screened, a sample set is constructed, and key influence factors are screened through Pearson correlation analysis. Based on the key factors, six machine learning algorithms are used to construct prediction sub-models of four disease types, and the prediction results of the multi-models are fused through an adaptive weight distribution method based on model performance evaluation. The integrated model is used to evaluate the disease proneness of the region to be analyzed, key factors are selected based on a multi-model feature importance voting mechanism, and a structural equation model is used for causal relationship analysis to explain the prediction results of the integrated model. The application provides technical support for intelligent transportation infrastructure management, and significantly improves the accuracy, stability and scientificity of subgrade disease evaluation.

The present disclosure is directed to composite components of a structure, comprising: 1) a polymeric resin having a surface in a planar or three-dimensional shape, comprising a recycled polymer present in the polymeric resin at 1 to 100 percent by weight; and 2) a surfacing agent comprising a microporous sheet adhered to the polymeric resin. The microporous sheet comprises a polyolefin polymeric matrix; particulate, inorganic filler distributed throughout the matrix; and a network of interconnecting pores communicating throughout the microporous sheet. The structure comprises a vehicle, building, bridge, transportation infrastructure, oil rig, oil platform, water tower, power line tower, support structure, wind turbine blade, wall, or shipping container. Also provided are methods of making a molded composite component for a structure, methods of recycling a polymer, and methods of mitigating detrimental effects on a surface of a molded composite vehicle component caused by contaminants present in a recycled polymer.

This application provides a method and system for dynamic prediction and decision-making regarding the transportation costs of power materials, belonging to the field of power Internet of Things and intelligent supply chain management technology. The method involves: constructing and dynamically updating a Regional Logistics Capability Index (LCI) covering several administrative units based on multi-source data collected from transportation infrastructure data sources, freight platforms, historical waybill databases, and environmental early warning platforms; collecting shipment information, material characteristics, and route information for the target power material transportation task, and inputting this information, along with the corresponding LCI, into a pre-trained transportation cost prediction model to calculate the predicted transportation cost and confidence interval for the target transportation task; and applying the predicted transportation cost and confidence interval to at least one supply chain decision in intelligent supplier selection, risk control for changes in shipping location, and / or the generation of differentiated inventory strategies. This application improves the accuracy of transportation cost prediction, optimizes supply chain decision-making, enhances resilience, and reduces costs.

This invention relates to a passive network anomaly monitoring and automated UAV inspection method and system, belonging to the field of intelligent operation and maintenance technology for transportation infrastructure. The method includes steps S1, anomaly perception and identification; step S2, UAV path generation; step S3, UAV inspection and target data acquisition; step S4, damage assessment report generation; and step S5, condition-based maintenance decision-making. This invention achieves high-precision passive network identification with extremely low power consumption, solving the problem of insufficient capture of anomaly features in flexible structures by existing SHM (Survey-Synchronous Mapping) technology. Based on digital twin and reinforcement learning technologies, it enables UAVs to complete path planning and autonomous takeoff within seconds of an event occurring, overcoming the shortcomings of existing UAVs' periodic rather than event-triggered inspections and low recognition rates, thus improving the processing efficiency of passive network anomaly events.

The invention discloses an accurate control construction method and limiting device for a bridge pier column steel bar protective layer. The limiting device comprises a limiting component used for positioning the distance between a steel bar cage and a formwork, and the limiting component comprises a fixing nut, a limiting bolt body and a locking adjusting assembly; according to the method, the construction of the protective layer of the bridge pier stud is promoted to be transformed and upgraded from a manual experience type to a standardized precise regulation type, a standardized construction method capable of being copied and popularized is formed, and a mature technical solution is provided for similar projects. By improving the construction quality and durability of the bridge structure, the service life of the bridge is prolonged, the operation and maintenance cost of the whole life cycle is reduced, safe and reliable operation of public transport infrastructures is guaranteed, and remarkable industry demonstration value and social benefits are achieved.

The invention discloses roadbed filler based on calcium carbonate industrial solid waste and red clay synergistic improvement and a construction method of the roadbed filler, and belongs to the technical field of roadbed filler. The roadbed filler based on calcium carbonate industrial solid waste and red clay synergistic improvement is prepared from the following raw materials in parts by mass: 40 to 65 parts of calcium carbonate industrial solid waste, 30 to 55 parts of red clay, 0.2 to 0.6 part of citric acid, 2 to 5 parts of alkali modified bagasse, 0.5 to 1 part of sodium bentonite and 1 to 2 parts of silica fume. According to the invention, outsourced sandstone is replaced by calcium carbonate industrial solid waste, so that the solid waste can be efficiently consumed, and carbon emission is reduced. Citric acid and medium-temperature roasting treatment have a synergistic effect, Ca < 2 + > dissociation of the calcium carbonate industrial solid waste is further promoted, and the sodium bentonite is cooperated to further reduce the shrinkage and expansion rate and the liquid limit of the red clay. The alkali-modified bagasse is added, so that the interface can be strengthened, and the long-term pavement performance is improved. The construction method is simple, environmental protection, performance and economical efficiency are taken into consideration, the requirements of traffic infrastructure are met, and the good application value is achieved.

This invention provides an integrated load-bearing device for foundation construction in transportation engineering, relating to the field of lifting and hoisting machinery. It includes a support beam and a main load-bearing plate. Auxiliary load-bearing longitudinal beams are installed on both sides of the main load-bearing plate. A drive electromagnetic motor is mounted on the longitudinal alignment adjustment wheel. A superconducting magnetic levitation auxiliary lateral movement suspension frame is installed above the main load-bearing plate. A magnetic levitation lateral movement track is fixed inside the superconducting magnetic levitation auxiliary lateral movement frame. Combined with superconducting magnetic levitation lateral movement, it achieves contactless, high-precision lateral displacement. With the addition of a magnetorheological fluid controllable damping lock sleeve and a stepped variable load clamp locking beam, it achieves stable lifting of large loads, dynamic anti-sway, and adaptability to various component specifications. The device achieves positioning through longitudinal alignment adjustment wheels, magnetic levitation lateral movement, and hook fine-tuning, and also functions as a maintenance platform to ensure operational safety. This device can meet the efficient hoisting requirements of heavy components such as precast piles and box girder segments, significantly improving the safety and construction efficiency of transportation infrastructure construction.

This invention discloses a method and management system for constructing a real-world database of carbon footprint for transportation infrastructure, relating to the field of carbon emission technology. The method includes: acquiring full lifecycle data of transportation infrastructure; performing data preprocessing and binding geospatial information to generate a multimodal real-world raw data pool; converting spatial coordinates in the real-world raw data pool into linear station coordinates; mapping data records to corresponding spatiotemporal grid units to form a linear engineering gridded carbon flow inventory dataset; extracting carbon emission data from the spatiotemporal grid units and, combined with a spatially constrained causal discovery algorithm, mining the causal relationship between carbon emissions and the geographical environment and engineering geology; constructing carbon digital twins for different types of transportation infrastructure equipment; and establishing standardized data service interfaces. This invention solves the problems of data fragmentation and spatiotemporal inaccuracy in traditional carbon footprint management by constructing a real-world data foundation covering the entire lifecycle of transportation infrastructure products.

This invention discloses a roadbed filler material based on the synergistic improvement of calcium carbonate industrial solid waste and red clay, and its construction method, belonging to the technical field of roadbed filler materials. The raw materials of the roadbed filler material based on the synergistic improvement of calcium carbonate industrial solid waste and red clay, by weight, include: 40-65 parts calcium carbonate industrial solid waste, 30-55 parts red clay, 0.2-0.6 parts citric acid, 2-5 parts alkali-modified sugarcane bagasse, 0.5-1 parts sodium-based bentonite, and 1-2 parts silica fume. This invention, by replacing purchased sand and gravel with calcium carbonate industrial solid waste, can efficiently dispose of solid waste and reduce carbon emissions. The synergistic effect of citric acid and medium-temperature roasting further promotes the CaO reduction of calcium carbonate industrial solid waste. 2+ The dissociation process, combined with sodium-based bentonite, further reduces the shrinkage rate and liquid limit of red clay. The addition of alkali-modified bagasse strengthens the interface and improves long-term road performance. The construction method of this invention is simple, balances environmental protection, performance, and economy, and is suitable for transportation infrastructure needs, demonstrating significant application value.

The invention discloses a hydrogen concentration field space-time reconstruction and prediction method and system based on sparse sensor data, and relates to the technical field of hydrogen energy safety utilization. The method comprises the following steps: simulating various hydrogen leakage working conditions through numerical simulation, and generating sparse sensor time sequence data and complete two-dimensional concentration field data; preprocessing and standardizing the data, and dividing the processed data into a training set, a verification set and a test set; training a neural network prediction model by using the training set and the verification set to obtain a trained neural network prediction model; and inputting sparse sensor time sequence data collected in real time into the trained neural network prediction model, and outputting a current time concentration field reconstruction result and a future time concentration field prediction sequence through anti-standardization processing. The method can provide full-time-space and prospective situation awareness for the hydrogen leakage risk of the closed space, and has important application value for guaranteeing safe operation of hydrogen energy conveying infrastructures.

This invention discloses a method for evaluating the cleaning effect of highway lighting fixtures based on multi-source data fusion, belonging to the field of intelligent transportation infrastructure maintenance technology. This method aims to solve the problems of existing evaluation methods, such as single-dimensionality evaluation, static weight models failing to adapt to the differentiated needs of different road sections, and fixed maintenance cycles being unscientific. Key technical points include: collecting illuminance, surface image, and power consumption data of the lighting fixtures and calculating multiple evaluation indicators; constructing an evaluation matrix based on these indicators and fusing subjective and objective weights to obtain a static comprehensive weight; dynamically adjusting the weights according to different road section types such as tunnel sections or straight sections and calculating a comprehensive evaluation score; constructing and training a long short-term memory network prediction model; and finally using this model to predict future dirt coverage and determine the optimal cleaning cycle. This method is mainly used for the intelligent operation and maintenance of highway and urban expressway lighting systems to improve maintenance efficiency and optimize energy consumption.

The invention relates to the technical field of tunnel construction, and particularly discloses a lightweight curtain grouting material and a preparation method thereof.The lightweight curtain grouting material comprises a component A, a component B and a component C. The component A comprises 30-50 parts of a geopolymer-based cementing material, 5-30 parts of lightweight aggregate, 0.5-2 parts of a water reducing agent, 0.1-1 part of a stabilizer and 8-10 parts of water; the component B comprises 10-25 parts of an alkaline activator solution; the component C comprises 1-5 parts of intelligent microcapsule suspension; the component A, the component B and the component C are mixed near a grouting opening through a grouting system and then are poured. The lightweight curtain grouting material can be used for seepage prevention, reinforcement and repair operation in the fields of tunnels, underground engineering, hydro-junctions, traffic infrastructures and the like, and has the advantages of being lightweight, high in strength and good in durability.

The application discloses a kind of mountainous area highway electromechanical equipment's whole life cycle management method, it is related to intelligent transportation infrastructure management technical field, including, standardization equipment operation data set is input into bayesian network evaluation architecture, through multilevel fault propagation path analysis each node posterior probability under environmental parameter dynamic constraint, generates equipment health assessment report;Device control execution state record is fused with historical electromechanical equipment operation data, and equipment whole life cycle degradation curve is constructed by spatiotemporal correlation analysis, and trend feature extraction and signal separation processing are carried out, and equipment whole life cycle analysis report is generated.The application improves the pertinence and timeliness of maintenance decision, realizes the fine monitoring and prediction of equipment whole cycle operation performance, so as to provide reliable basis for scientifically formulating maintenance plan, reducing whole life cycle cost and prolonging equipment service life.

This useful solution refers to a concrete production process using fly ash to partially replace river sand and blast furnace slag to partially replace cement, resulting in high-strength concrete suitable for various construction projects such as civil engineering, transportation infrastructure (bridges, roads), and hydraulic engineering. These concretes have very low chloride ion permeability and superior corrosion resistance to reinforcing steel due to chloride ion penetration, making them highly suitable for constructing bridges, roads, ports, etc., in marine environments. The process includes the following steps: Step 1 involves preparing the materials for the cement-concrete mixture, including crushed stone (D), river sand (C), PCB30 cement (X), superplasticizer (SD), fly ash (TB), and finely ground blast furnace slag (XL); Step 2 involves mixing the cement-concrete mixtures to obtain cement-concrete mixtures with a slump SN of 4-6 cm.

The patent provides a set of innovative'signal lamp fault automatic alarm 'solution, and aims to thoroughly change the traditional passive operation and maintenance mode depending on manpower. The core innovation of the method lies in that a cloud-side-end collaborative intelligent system is constructed, comprehensive state sensing is realized by deploying a multi-source sensor, and a diagnosis engine of triple comparison of a control instruction, an actual state and a safety rule is initiatively adopted. The engine not only can accurately identify hardware faults such as lamp bead damage, but also can automatically detect hidden logic faults such as time sequence chaos and signal conflicts, and effectively solves long-term pain points in the industry. The system has intelligent grading alarm and predictive maintenance capabilities. According to the influence degree of a fault on traffic safety, differential response from emergency field alarm to platform early warning is automatically triggered, so that alarm information is structured and accurate, and the maintenance efficiency is greatly improved. Meanwhile, potential faults can be warned in advance by analyzing the performance degradation trend, and transformation from post-maintenance to pre-maintenance is achieved. According to the invention, Internet of Things perception, edge intelligence and traffic rules are deeply fused, a real-time, accurate and active closed-loop management system is formed, the intersection safety level and the operation and maintenance management intelligence degree are significantly improved, and key technical support is provided for intelligent traffic infrastructure construction.