480 results about "Traffic engineering" patented technology

The invention relates to the technical field of intelligent traffic engineering, and provides a road guardrail intelligent inspection and maintenance planning method based on machine learning, which breaks through the limitation of a traditional single mode in a detection link, fuses laser radar three-dimensional geometrical characteristics and visual texture information, realizes high-precision identification of defects such as microcracks and hidden corrosion, and improves the inspection efficiency. The detection problem in a complex environment is solved, and the problem that a traditional method is high in omission ratio is solved. In the aspect of dynamic planning, a multi-dimensional state space is constructed based on real-time traffic, weather and defect levels, polling path dynamic optimization and multi-vehicle collaborative operation are achieved through a reinforcement learning algorithm, and the current situations that manual planning is low in efficiency and poor in flexibility are changed. In the aspect of maintenance decision, a time sequence data analysis model is used for accurately predicting guardrail maintenance requirements, a scientific maintenance plan is made in combination with an intelligent scheduling algorithm, and efficient utilization of resources is achieved. According to the method, a complete intelligent operation and maintenance closed loop is constructed, and road guardrail operation and maintenance are promoted to be converted from passive low efficiency to active intelligence.

The invention provides an urban construction and traffic engineering investigation and design enterprise product quality management system and method. The system comprises a cross-project type quality data fusion module, a dynamic defect evolution prediction module, an intelligent layered spot check engine, a three-dimensional quality situation deduction module, a conference knowledge graph construction module, a result influence evaluation module and a self-adaptive file management system. All the modules are connected through a unified data bus to form a closed-loop management process of quality data acquisition, analysis, decision and feedback. According to the system, through the functions of multi-modal data fusion, defect prediction, intelligent spot check, situation deduction, knowledge precipitation, achievement evaluation, file management and the like, the whole-process intelligent management and control of the project quality are realized, and the management efficiency and the decision scientificity are improved.

The invention discloses a large-section long-footage mechanical blasting mixed excavation method suitable for a subway station, and relates to the technical field of underground rail transit engineering, and the method comprises the following steps: obtaining a tunnel section contour, a geologic structure and blasting parameters, building a three-dimensional blasting wave propagation inversion model, and combining geology and material heterogeneity to obtain a three-dimensional blasting wave propagation inversion model; and identifying a closed space region forming reflection interference, and predicting a space point location where blasting wave energy is abnormally accumulated. Based on the three-dimensional blasting wave propagation inversion model, the abnormal wave energy accumulation area is predicted in combination with geological heterogeneity, the high-risk blasting section is recognized, parameters are reconstructed, vibration real-time monitoring and model feedback correction are assisted, a closed-loop control system is constructed, local wave crest abnormity is effectively restrained, and the safety and controllability of large-section tunnel blasting construction are improved.

The invention provides an SDN (Software Defined Network) inter-domain traffic engineering method based on reinforcement learning, which comprises the following steps of: deploying a data traffic demand monitoring platform and a control system, and constructing a global network topological graph; calculating a short link identifier for the link in the network and distributing the short link identifier to each network device; flow judgment is carried out, upward notification is carried out according to requirements, and pre-operation of intelligent routing is cooperatively completed; deploying a reinforcement learning model in the total intelligent body, outputting an optimal cross-domain path strategy to the cooperative controller, disassembling the optimal cross-domain path strategy into flow table rules which can be executed by each domain, and issuing the flow table rules to local controllers of related domains; and each local controller pushes the flow table configuration to the domain switching equipment to complete the forwarding decision of the flow. According to the method, a complete closed-loop process of flow measurement, intelligent decision making, cross-domain control and path issuing is realized, feasible reference is provided for actual deployment of an intelligent network, and the method has good engineering popularization value and is suitable for intelligent scheduling scenes such as an operator backbone network, an industrial internet and metro edge cloud.

The invention discloses a traffic network toughness diagnosis method under flood disasters based on a space-time diagram neural network, and relates to the crossing field of traffic engineering and artificial intelligence. The method comprises the following steps: collecting traffic topology, flood monitoring and traffic flow data, and carrying out space-time alignment; a flood coupling dynamic space-time diagram is constructed, a water depth-traffic capacity response mechanism is introduced, and real-time mapping from a disaster physical state to a network topology is realized by utilizing an attenuation function meeting physical monotonicity constraint and dynamically updating an edge weight of a diagram structure according to real-time water depth; inputting the dynamic graph into a pre-trained space-time graph neural network model, extracting space-time evolution characteristics and outputting a toughness diagnosis result; model training adopts a toughness label generated based on an anti-fact baseline to carry out supervised learning, and introduces a physical constraint loss function. According to the method, the problems of decoupling of disaster features and graph structures and unavailability of toughness labels in the prior art are solved, and the physical consistency and accuracy of diagnosis are improved.

The invention discloses an urban rail transit station site selection multi-objective optimization method and a related device, and belongs to the crossing field of urban planning and traffic engineering, and the method comprises the following steps: according to preprocessed urban road network data, screening crossing points of urban three-level roads and roads above the three-level roads as candidate stations; the coordinates of the candidate sites are coded; based on the preprocessed crowd travel origin and destination data, POI data, building data and land utilization data, quantifying the service people flow, facility accessibility and land development intensity of each candidate site, and forming a feature matrix of each candidate site; and constructing a multi-target traffic station site selection model, screening candidate stations meeting distance constraints through a greedy search algorithm according to the feature matrix, inputting the candidate stations to NSGA-II, and solving a multi-target optimization function of the multi-target traffic station site selection model to obtain an optimal planning result. The method can solve the problems that in the prior art, the target is single during site selection, and the inter-site distance constraint is not considered.

The invention discloses a high-speed rail seamless track displacement real-time detection system based on Beidou navigation, and relates to the technical field of traffic engineering, a target locking module is used for receiving Beidou observation data by using a Beidou GNSS receiver, locking GNSS lock losing signals at various monitoring moments based on the Beidou observation data, and transmitting the locked GNSS lock losing signals to the target locking module; the GNSS lock losing signal comprises a GNSS interruption starting point, a signal lock losing time period and a corresponding track space position; the interruption compensation module is used for initializing a mapping vector according to a track state before a signal lock losing time period to form a track estimation sequence, and judging whether IMU drift tends to systematic deviation or not after modal residual verification; the reconstruction module is used for performing error compensation on track position points at all moments in a signal lock losing time period if the deviation tends to systematic deviation; and the identification module is used for carrying out feature extraction in a signal lock losing time period based on the reconstruction module, and delimiting a dominant source of the current displacement in a form of a spatial domain angle.

The invention discloses a ballastless track concrete bonding interface mechanical state testing method, belongs to the technical field of track traffic engineering, and realizes a multi-field coupling loading test on a ballastless track interlayer test piece by constructing an interlayer mechanical testing device comprising a servo loading mechanism, a DIC technology and finite element mechanical analysis. A high-speed camera is adopted to synchronously record the whole process of interlayer interface damage, an interface stress distribution cloud picture is obtained in combination with a distributed strain patch, and a load-displacement curve and interlayer slippage data are synchronously collected. A refined finite element model containing a cohesion unit is established based on measured data, and iterative fitting of a simulation result and test data is achieved by dynamically adjusting interface damage parameters. According to the method, the limitation of a traditional single-point stress test is broken through, space-time multi-scale analysis of interlayer mechanical behaviors is achieved, the technical problems that an interlayer interface failure mechanism is not clear and simulation model parameters are difficult to calibrate are solved, and a novel test is provided for durability evaluation of a ballastless track structure.

The invention belongs to the crossing field of traffic engineering and information technology, and discloses a highway continuous longitudinal slope section traffic safety knowledge graph construction method. According to the method, road section features, traffic flow, historical accidents and environmental data are integrated, and a multi-source data set is constructed through cleaning and standardization processing; defining a road section, an accident, an environment and a vehicle entity, and constructing a multi-level knowledge graph comprising a static topology layer, a dynamic attribute layer and a probabilistic reasoning layer; knowledge triples are extracted by using a natural language processing technology, and real-time risk assessment and early warning are realized by dynamically fusing association logic of gradient, environment and accident data in combination with a rule engine; a graph database is adopted to store the graph, and semantic query and dynamic updating are supported. The method breaks through the limitation of traditional single data source analysis, solves the problem of coupling risk assessment of dynamic environmental factors and static features under complex terrains through multi-source fusion and probabilistic reasoning mechanisms, and remarkably improves the traffic safety risk prediction precision.

The invention specifically relates to a tunnel group road section traffic capacity assessment method based on intelligent network connection, which relates to the technical field of traffic engineering, and comprises the steps of constructing an AI-driven dynamic assessment model based on fusion data and a digital twinborn model in combination with tunnel engineering constraints, and calculating the traffic capacity, congestion risk and bottleneck position of each road section of a tunnel group in real time. In the invention, a multi-source data acquisition system is combined with an edge and cloud two-stage fusion architecture to construct an LSTM-XGBoost double-model architecture; the LSTM model can calculate and predict the traffic capacity of four time nodes in the future 10 minutes in real time, the XGBoost model accurately locates the bottleneck position and quantifies the contribution degree of four types of causes, meanwhile, the precision is ensured through multi-dimensional verification, the tunnel group whole domain can be covered, instantaneous traffic changes can be captured, and a panoramic decision basis of real-time data, prediction trend and bottleneck causes is provided for traffic management.

The invention discloses a data processing method and system for intelligent road detection and related equipment, and relates to the technical field of traffic engineering and artificial intelligence crossing. In the road detection process, multi-sensor fusion equipment with dynamic adjustment is adopted to collect multi-source data; the real-time environment perception model based on deep reinforcement learning dynamically optimizes the parameters of the multi-modal sensor, and improves the data acquisition quality in severe weather and environment. Millimeter-level alignment of multi-source data is realized by adopting a spatio-temporal model, and a generative adversarial network is introduced to enhance the multi-source data after spatio-temporal alignment so as to supplement missing data details and improve data quality. Disease intelligent identification is carried out on multi-source data through a sample learning model and a meta-learning algorithm, the sample learning model solves the problem of insufficient labeling samples of micro-disease data, the meta-learning algorithm is quickly generalized on the basis of a small amount of labeling data, micro-diseases such as early cracks and hidden road structure layer defects are identified, and the accuracy of identification is improved. And the accuracy of road disease identification is improved.

The invention provides a quasi-zero-stiffness base and an adjustable quasi-zero-stiffness local resonance super-structure vibration isolation device, belongs to the field of environmental vibration reduction and isolation in traffic engineering and civil engineering, and aims at solving the problems that in the prior art, a spring quasi-zero-stiffness structure is complex in installation structure and poor in structural stability. The device comprises a bottom plate, a plurality of first beams with a positive stiffness effect, a plurality of second beams with a negative stiffness effect and a plurality of regular triangular prisms, the first beam, the second beam, the regular triangular prism and the bottom plate are integrally formed, on one hand, it is ensured that all connecting pieces are in rigid connection, the situation that connecting points affect the stability of the structure is avoided, on the other hand, the assembling process can be simpler, and the assembling efficiency is improved.

The invention relates to the field of traffic engineering, and discloses an urban road network toughness management platform and evaluation method based on dynamic cascade failure, and the platform comprises a disturbance scene simulation and random capacity degradation module, a dynamic cascade failure process simulation module, and a multi-dimensional toughness index calculation and uncertainty evaluation module. A toughness three-dimensional vector is formed by integrating system robustness, restorability and performance accumulated loss, and a time-varying dynamic traffic distribution model considering road network structure change is used for depicting a cascade failure dynamic process; a random variable is introduced into a damaged road section capacity index, and a new evaluation method is provided for solving the defect that the existing toughness evaluation method is difficult to comprehensively quantify the robustness and the restorability of a road network. A failure diffusion mechanism in an abnormal scene is truly restored, and an effective method is provided for overcoming the double defects that a traditional model is insufficient in quantification of travel behavior dynamics and a system recovery process.

A system manages network traffic in a distributed system comprising a plurality of network devices. The network devices are divided into a plurality of network slices, each of the network slices including a subset of the network devices such that there is no overlap of network devices between the network slices. Individual network slices are associated with individual slice controllers, and an individual slice controller is configured to manage network routing of an individual network slice. Each of the individual slice controllers route the network traffic within each respective individual network slice. The network traffic is independently routed based on expected network conditions for each respective individual network slice, and data defining routing decisions is contained within each network slice to limit fault effects between the network slices.

The invention discloses an optimization system and method for SDN traffic engineering, and the method specifically comprises the following steps: S1, obtaining a traffic matrix in a network, and representing the network topology as a graph structure; s2, inputting the traffic matrix and the graph structure into a constructed feature extraction model, and outputting a feature vector; s3, inputting the feature vector into a deep reinforcement learning model for iterative optimization, and outputting an initial flow distribution proportion strategy; and S4, performing constraint optimization on the initial flow distribution proportion strategy, and outputting a final flow distribution strategy.

The embodiment of the invention discloses a network configuration method and device, a data forwarding method and device, equipment and a storage medium, and the network configuration method comprises the steps: obtaining slice configuration information between source end equipment and sink end equipment, and the slice configuration information comprises a network slice ID, bandwidth information, a segment routing traffic engineering strategy and a target service identifier; generating a routing path between the source end device and the sink end device according to the bandwidth information and the segment routing traffic engineering strategy; generating a slice configuration command according to the slice configuration information and the routing path, and issuing the slice configuration command to each device in the routing path, the slice configuration command is used for instructing each device to transmit target service data corresponding to the target service identifier according to a network slice channel corresponding to the network slice ID. According to the embodiment of the invention, the data transmission efficiency can be improved, and the waste of bandwidth resources is reduced.

The invention discloses a road traffic engineering test detection data acquisition and evaluation system, which relates to the technical field of traffic detection and comprises a data acquisition module, a data processing and analysis module, an evaluation index matching module, a data evaluation module and a result output module. According to the invention, automatic identification and accurate evaluation can be carried out according to characteristics of different types of roads, acceptance of newly built roads and reconstruction of old roads are ensured to reach the standard, and the limitation of traditional unified standards is overcome; multi-dimensional data acquisition is comprehensive and highly targeted, and evaluation deviation is avoided; indexes are comprehensive and can be dynamically adjusted, the reality of new and old roads is met, and evaluation effectiveness is improved; and single and comprehensive evaluation optimization is realized, multiple factors are considered, and a comprehensive and objective basis is provided for road acceptance and reconstruction.

The invention relates to the technical field of traffic engineering management, and particularly discloses a traffic engineering quality safety dynamic supervision and management system and method, and the method comprises the steps: constructing a multi-dimensional sensing network which comprises an entity, an environment and a behavior sensing layer, and collecting data; a three-dimensional model is built based on the BIM technology, and standardized data and model millisecond mapping are fused and visualized; an LSTM and random forest hybrid algorithm is adopted to establish a three-level early warning model, and risks are identified and pushed in a graded manner; matching the disposal flow according to the early warning level, tracking the progress by the mobile terminal, and checking the closed loop in a grading manner; and key node data are stored through a multi-level block structure, an alliance chain permission, a consensus mechanism and an intelligent contract, so that reverse tracing is realized. According to the invention, real-time acquisition, dynamic modeling, intelligent early warning, co-processing and credible tracing of quality safety data in the traffic engineering construction process are realized, the quality safety risk is reduced, and the management efficiency and supervision transparency are improved.

The invention belongs to the field of underground traffic engineering, and relates to a construction method and structure for constructing a transfer node through an underground excavation underneath pass operation station. The newly-built station and the existing operation station are in T-shaped node transfer, when the existing operation station is constructed in the early stage, transfer nodes are implemented in different periods, and a plurality of supporting piles and supporting beams are reserved below a bottom plate in the range of the transfer nodes, so that the safety of the existing operation station is protected when the transfer nodes are subjected to underground excavation construction in the later stage. When a newly-built station adjoins an operation station, open excavation and sequential construction are carried out to complete a main body structure, fender posts within the height range of the operation station are broken, new and old structures are connected, fender posts within the negative three-layer range of a transfer node are broken, and underground excavation construction is carried out in a joint control mode of excavation face zoning and longitudinal step-by-step excavation to penetrate through the existing operation station. And the reserved pile foundation is broken according to needs, stable stress conversion is achieved, and the safety of an operation station above is ensured. According to the method, the construction risk can be effectively controlled, the safety of underground excavation and underneath crossing of the existing operation station is achieved, then the transfer function is achieved, and good economic benefits are obtained.

The invention provides a public transport supply and demand matching method and a related device, and belongs to the technical field of traffic engineering and urban planning. According to the invention, the matching degree of a supply network and a demand network is calculated through a supply-demand matching evaluation algorithm, and a public transport supply-demand matching index of a spatial analysis unit is obtained; and obtaining a public traffic supply and demand matching result based on the public traffic supply and demand matching index. According to the invention, the problem of low accuracy of public transport supply and demand matching is solved.

Solutions are disclosed that enable capacity-aware local repair of tunnels in packet switched wide area networks (WANs). Traffic engineering agents on the routers are programmed to create the tunnels and include sets of primary and alternate tunnels sharing the same source and destination. A tunnel source router is provided a traffic split for allocating incoming traffic to its primary and alternate tunnels for when the primary tunnel is operating at or near full capacity operation, and another traffic split that shifts at least some traffic from the primary tunnel to the alternate tunnel, when the primary tunnel's capacity drops below a threshold. A tunnel may lose capacity for commonly-occurring reasons, such as a disturbance to cabling and faults in optical transceivers. Traffic engineering agents along the tunnel report capacity to the tunnel source router, permitting the network to respond to capacity changes more rapidly than waiting for network tunnel reconfiguration.

The invention discloses a plane alignment element segmentation and node identification method and system based on curvature characteristics, and the method comprises the steps: carrying out the smoothing of the curvature of point cloud data of a road center line through a local weighted regression algorithm, and obtaining a smooth curvature; traversing the smoothed curvature by adopting a sliding window, calculating a variable coefficient of the curvature in each window, judging the consistency of the curvature and the linear element type according to the size of the variable coefficient to obtain a preliminary candidate node, respectively extracting the curvatures of the left side and the right side of the candidate node by taking the node as a center, and carrying out least square method linear fitting to obtain a final candidate node; and obtaining an intersection point of the fitting straight lines, and determining a final node position. The method can effectively solve the problems of large curvature fluctuation of the road center line and high node identification difficulty, has the advantages of high node positioning accuracy, strong adaptability and high calculation efficiency, and can be widely applied to the fields of road digital modeling, traffic engineering design and maintenance and the like.

The utility model provides a vibration monitoring device for a subway upper cover building, which relates to the field of underground traffic engineering, and comprises a device body and a plurality of groups of vibration measuring instruments, the device body comprises a vibration measuring main part and a monitoring host arranged on the surface of the vibration measuring main part, and the vibration monitoring device is provided with the plurality of groups of vibration measuring instruments through the vibration measuring main part. Due to the fact that the vibration meter is detachably connected with the installation groove, a worker can install the vibration meter in different directions of the vibration measurement main part according to requirements, multi-point monitoring operation is achieved, operation is flexible, the workload can be greatly relieved, and the monitoring efficiency is improved; a worker can flexibly separate individual vibration meters from the vibration measurement main part for use according to requirements, and at the moment, the vibration meters are fixed on the upper cover building through the adhesive structures, so that the monitoring range can be enlarged, the overall practicability is high, and the popularization value is high.

Systems and methods are provided for effectuating a filtering technique that can enable available bandwidth (e.g., on a network path) to be estimated in the presence of moderate losses caused by certain queue management techniques. When packet losses exist on a network path due to certain types of packet queue transmission mechanisms, methods, or models, a bump detection algorithm (BDA) can be used to perform bandwidth estimation. When a pattern of packet loss is identified (from its signature) as being one with which BDA can be performed to accurately estimate available bandwidth on a network path, the BDA-based bandwidth estimate may be used to place / route and load balance network traffic, or otherwise used to engage in network traffic engineering, take other network-related action(s), or reported out. Otherwise, the bandwidth estimation is suppressed and not used.

The invention relates to the technical field of traffic engineering facility monitoring, and particularly discloses a traffic engineering facility safety state monitoring system and method based on the Internet of Things, and the method comprises the steps: deploying distributed intelligent sensing nodes comprising multiple types of sensors and edge calculation units at key monitoring points of facilities; nodes collect data by adopting a dynamic self-adaptive sampling mechanism, and an edge computing unit preprocesses the data and performs preliminary abnormity early warning; the data is transmitted to a cloud platform through a hierarchical communication network; the cloud platform performs deep analysis by using a federated learning safety evaluation model, and calculates a safety index to generate an evaluation report; and when the monitoring value exceeds the threshold value, four-stage early warning is triggered corresponding to different inspection or disposal processes. According to the invention, through the whole process optimization of dynamic sampling-layered transmission-federated learning evaluation-multi-stage early warning, efficient, accurate and low-consumption monitoring of the traffic engineering facility safety state is realized, and the contradiction between data privacy protection and evaluation precision is solved at the same time.

The invention discloses an expressway material supply early warning method based on meteorological data, and relates to the technical field of traffic engineering. Comprising the steps that a multi-source sensing module collects multi-dimensional information sources regularly, a data fusion center fuses the multi-dimensional information sources, a central processing unit establishes a congelation risk prediction model, a risk early warning module conducts congelation risk grading early warning, and an intelligent decision module conducts material supply scheduling optimization. According to the invention, the response time efficiency is greatly improved, the supply and demand matching precision is obviously improved, the purchasing efficiency and reliability are improved, the decision scientificity and cost are optimized, and the accident rate and economic loss are reduced; the problems of incomplete data, inaccurate prediction, one-sided evaluation, unbalanced scheduling and fuzzy response of the traditional highway anticoagulation and communication preservation material supply are solved, and the anticoagulation and communication preservation targets of accurate early warning, on-demand scheduling, controllable cost, safety and high efficiency are achieved.

The invention discloses an evaluation index system construction method for a construction time sequence of an urban composite channel, relates to the technical field of traffic engineering and urban planning, and solves the problems of facility layout conflict, traffic operation disturbance, low efficiency of resource allocation and the like caused by the lack of scientific time sequence overall planning of the construction time sequence of an existing urban rail-road composite channel. The construction method comprises the following steps: S11, dividing a city composite channel construction process into a plurality of evaluation stages of construction time sequence influence; s12, determining an evaluation dimension in each evaluation stage; s13, extracting an evaluation criterion based on each evaluation dimension; s14, refining a plurality of secondary evaluation indexes according to each evaluation criterion, and constructing an evaluation index system according to the secondary evaluation indexes; and S15, determining the meaning, the calculation method and the numerical value acquisition mode of each secondary evaluation index. The invention further discloses an evaluation method for the construction time sequence of the urban composite channel. According to the invention, the scientificity of traffic planning decision and the efficiency and benefit of engineering implementation can be improved.

The invention relates to the technical field of traffic engineering, in particular to a self-repairing type warm-mixing flame-retardant microcapsule and an asphalt mixture, and the microcapsule comprises a core material and a shell material; the composite material is characterized in that the core material comprises a self-repairing component and a warm mixing functional component, the self-repairing component is at least one of sulfur, epoxy resin or recycled asphalt, the warm mixing functional component is an organic wax-montmorillonite composite component, and montmorillonite is modified by a silane coupling agent; the shell material is at least one of ammonium polyphosphate, melamine formaldehyde resin or nano aluminum hydroxide, and nano silicon dioxide particles of which the surfaces are grafted with azobenzene groups are loaded on the surface of the shell material; through cooperation of multiple components, a light, mild and stress triple triggering mechanism is constructed, core material release is accurately regulated, warm mixing, self-repairing and flame-retardant components are mutually promoted, the repairing efficiency and flame-retardant durability are improved, efficient function coupling is achieved, and the pavement performance is optimized.

The present invention relates to the technical field of transportation engineering and municipal engineering construction, specifically to an isolation structure and method for over-station construction. An isolation structure for over-station construction, comprising a transversely arranged horizontal steel beam and a longitudinally arranged main steel beam, characterized in that: an isolation membrane structure is provided on the transverse steel beam and the main steel beam, the lower end of the isolation membrane structure is connected to a dense-mesh safety green net, the lower end of the dense-mesh safety green net is connected to a vertical hard isolation structure, and the vertical hard isolation structure is located on the inner side of the platform. Compared with the existing technology, it can be constructed during the operation of the train, and after it is erected, it has high-demand isolation and safety protection, and is fully isolated from the track area, so that the construction in the station and the train operation do not affect each other, thereby improving work efficiency and construction safety.

The invention discloses a method for merging road network data subjected to multi-user asynchronous modification, and relates to the technical field of traffic and transportation engineering, geographic information systems and traffic network data processing. According to the method, basic components of the road network data are abstracted, a basic data set is created, difference analysis is carried out on new data and the basic data, and then the road network data are merged; and detecting and marking data conflicts. And selecting a proper merging strategy according to a conflict detection result, and carrying out updating operation on the basic data, including newly added element integration, conflict element processing and deleted element processing. According to the invention, the efficiency and accuracy of data merging are improved, the quality and availability of road network data are ensured, and the method is suitable for multi-user cooperative road network data maintenance scenes in the fields of urban planning, traffic management and the like.