31 results about "Urban transit" patented technology

The invention relates to a space-ground integrated Beidou high-precision positioning method applied to urban canyons, and belongs to the technical field of navigation positioning. The method comprises the following steps: deploying a pseudo satellite base station, calibrating coordinates of the base station through carrier phase difference, and monitoring the number of Beidou visible satellites; a master pseudo-satellite is determined, timestamps and ephemeris data are broadcasted to slave pseudo-satellites through Beidou short messages, and the slave pseudo-satellites are combined with bidirectional ranging data to correct a local clock to realize high-precision synchronization; receiving Beidou and pseudo-satellite signals by a user terminal, screening effective observation values through a shielding judgment mechanism, substituting the effective observation values into a non-difference observation equation in combination with pseudo-satellite reference difference data, and resolving a fusion result through an elastic coupling mode; and finally, multi-path interference is identified by using pseudo-satellite double antennas, and historical data is called to construct an error model to correct a fusion result. The space-ground integrated positioning of Beidou and pseudo satellites in an urban canyon scene is realized, the centimeter-level positioning precision is stably output, and the high-precision positioning requirements of urban traffic, surveying and mapping and the like are met.

The invention relates to the technical field of artificial intelligence, and discloses an event prediction method and system based on multi-modal fusion, and the method comprises the steps: constructing a knowledge graph encoder, and converting domain expert knowledge into learnable vector representation; constructing a multi-granularity feature extraction network, and extracting features from different microcosmic, mesoscopic and macroscopic scales; realizing a knowledge-guided attention mechanism, and dynamically adjusting feature scale importance; constructing a prototype learning module, and establishing prototype representation of the abnormal category; a knowledge migration mechanism is constructed, and the generalization ability of the model to novel anomalies is enhanced; and multi-granularity abnormal event detection and early warning are realized, and a detection result and interpretable analysis are output. According to the method, through combination of knowledge guidance and multi-scale feature learning, efficient identification and early warning of social abnormal events under the condition of data scarcity are realized, and the method is suitable for the fields of public place safety monitoring, urban traffic safety management, large-scale activity safety guarantee and the like.

The invention relates to the technical field of artificial intelligence and automatic driving, and discloses an automatic driving digital twin agent system based on reinforcement learning training, which comprises an agent library construction module, a simulation and configuration module, a distributed simulation execution module, a scheduling and learning module, a strategy training module and a simulation migration module. The method comprises the following steps: constructing a modular digital twin agent library, combining to generate an urban traffic simulation scene, executing large-scale parallel simulation on a distributed computing cluster, implementing dynamic task scheduling and course learning according to an agent learning progress, and training a reinforcement learning strategy and a value network based on simulation data. And verifying the strategy model and implementing migration deployment from simulation to reality. According to the method, the training efficiency can be improved, the diversity of simulation environments is enriched, and the sim-to-real migration difficulty is reduced, so that the robustness of the strategy model is improved.

The invention relates to a trusted security traffic monitoring system based on an anti-quantum key management framework, and relates to the technical field of smart city traffic, and the system comprises an initialization module which is used for carrying out the initialization processing of a cloud platform, an edge gateway and a camera node; the data acquisition and transmission module is used for acquiring and encrypting monitoring data based on the initialized camera node, and transmitting the encrypted monitoring data to the cloud platform through the edge gateway in a preset data transmission mode; wherein the preset data transmission mode comprises a cross-gateway area transmission mode and a same-gateway area transmission mode; and the data detection module is used for deleting or replacing the scene of the corresponding node when the edge gateway or the camera node shows a malicious behavior or the equipment is aged. According to the method, a key system is constructed through an encryption and decryption algorithm, so that the key management framework oriented to edge computing has quantum aggression resistance, and the security of a city monitoring system in a traditional scheme is improved.

The application relates to a space-ground integrated Beidou high-precision positioning method applied to an urban canyon, and belongs to the technical field of navigation and positioning. The method comprises the following steps: deploying a pseudolite base station, calibrating the base station coordinates through carrier phase difference, and monitoring the number of visible Beidou satellites; determining a master pseudolite, broadcasting timestamp and ephemeris data to a slave pseudolite through a Beidou short message, and combining two-way ranging data to correct a local clock to realize high-precision synchronization; then a user terminal receives Beidou and pseudolite signals, screens effective observation values through a shielding discrimination mechanism, combines pseudolite reference differential data into a non-difference observation equation, and solves a fusion result through a loose-tight coupling mode; finally, the pseudolite double-antenna is used to identify multipath interference, historical data is called to construct an error model, and the fusion result is corrected. The space-ground integrated fusion positioning of Beidou and pseudolites in the urban canyon scene is realized, stable centimeter-level positioning precision is output, and the high-precision positioning demand of urban traffic and surveying and mapping is met.

This invention discloses a method for assessing the resilience of subway travel behavior during rainstorms, taking into account the impact of the built environment. It belongs to the field of urban transportation resilience assessment. The specific steps include: S1, collecting subway travel data, meteorological data, and built environment data around subway stations under rainstorm and ideal weather conditions; S2, quantifying the resilience value of subway travel behavior using the resilience triangle method; S3, constructing a spatially weighted geographic random forest model, using built environment data as features and resilience value as the objective, establishing a nonlinear mapping relationship between the two, and outputting the spatial distribution characteristics of resilience; S4, using the model to analyze the marginal contribution of each built environment factor to the resilience value, outputting the feature importance ranking, and identifying key built environment factors. This invention can quantify the disturbance and recovery capacity of subway travel behavior during rainstorms, reveal the mechanism by which the built environment affects travel behavior resilience, and provide a scientific basis for urban transportation resilience planning and rainstorm emergency management.

The invention relates to an urban underground comprehensive pipe gallery structure and a construction technology thereof, and relates to the technical field of urban underground comprehensive pipe galleries, the urban underground comprehensive pipe gallery structure comprises a foundation, a foundation pit is excavated in the surface of the foundation, a pipe gallery main body structure is arranged in the foundation pit, and the pipe gallery main body structure is used for laying and protecting urban pipelines. An auxiliary assembly is arranged in the foundation pit and used for monitoring the pipe gallery and adjusting the temperature, humidity and gas concentration, the pipe gallery body structure comprises a fence, a steel support, a bottom plate, side walls and a top plate, the fence is arranged on the periphery of the foundation pit and located above the foundation, the steel support is installed in the foundation pit, the bottom plate is arranged in the foundation pit, and the side walls are arranged on the top plate. And the side wall is poured on the side wall of the bottom plate through concrete. The construction method has the advantages that the construction efficiency is high, the structural integrity is high, interference to urban traffic and the environment is reduced, the anti-seismic performance, the anti-sedimentation performance and the like are remarkably improved, and the effect of conveniently and efficiently monitoring and ventilating the interior of the pipe gallery can be achieved.

The invention discloses a trajectory prediction method for urban vehicle tracking. The method comprises the following steps: firstly, constructing a double-layer graph attention network, and constructing a weighted directed global traffic flow graph for modeling a global flow mode of urban traffic by using urban traffic data; meanwhile, each target historical track is abstracted into a local individual track diagram, and the microscopic motion preference of the target is described. And then predicting a next-step track point of the vehicle by using a Transform model, introducing a road network topology perception loss function in a training process of the Transform model, and constraining a target prediction point and an actual road network to promote a track output by the model to better conform to road connectivity. And finally, carrying out posteriori correction on Transform output by adopting extended Kalman filtering so as to enhance the robustness of the abrupt change trajectory.

The invention discloses a public transit network optimization method and system. The method comprises the steps of 1, acquiring urban traffic network data, bus station data, station data, passenger flow OD and lines needing to be adjusted; step 2, mapping bus stops to an urban traffic road network; 3, updating the urban traffic network data; 4, adjacent bus stations are connected to form a bus traffic network; step 5, finding out a target OD which needs to be covered by the planned route; step 6, generating a candidate line pool; and 7, calculating a coverage relationship between the lines in the candidate line pool and the target OD, and then finding out a line set which can cover all the target OD and has the shortest mileage to realize public transit network optimization. According to the method, the problem of network optimization adjustment of a common asymmetric traffic network can be solved, and the applicability of the network optimization method is greatly improved. Particularly, under the condition that the current bus operation cost is high, the service level is not reduced while the operation cost is reduced.

This invention discloses a novel power hybrid simulation system and method that considers urban transportation integration, addressing the problem that simulation applications involving electric vehicles (EVs) in grid coordination cannot reflect the impact on the transportation system. The transient simulation collaborative management unit sends dispatch instructions from the dispatch master station unit to the EV-charging pile control unit and the EV-transportation collaborative simulation unit. The EV-charging pile control unit generates dispatch control instructions based on the dispatch instructions and sends them to the multi-dimensional hybrid simulation unit. The EV-transportation collaborative simulation unit performs long-term, grid-related collaborative simulations based on the dispatch instructions, generating time-series simulation data, which is then sent to the multi-dimensional hybrid simulation unit via the transient simulation collaborative management unit. The multi-dimensional hybrid simulation unit performs grid transient simulations based on the dispatch control instructions and time-series simulation data, generating grid transient simulation data, which is then sent to the EV-transportation collaborative simulation unit via the transient simulation collaborative management unit.

The application discloses a kind of city traffic wisdom street lamp based on Internet of Things, it is related to outdoor street lamp technical field, including fixed frame, the fixed frame bottom end is equipped with fixed rod, the fixed frame top is equipped with frame cover, climate monitoring mechanism, the climate monitoring mechanism includes movable plate, collection notch and movable pass, the movable pass is set in the middle part of frame cover, movable plate is movably installed in the inside of movable pass, the movable plate middle part is equipped with collection notch.The application is used in cooperation with climate monitoring mechanism and illumination monitoring mechanism, in the use process of outdoor street lamp, by monitoring different climate, the result generated by monitoring is used to adjust the working position of photosensitive sensor, ensure the stability of photosensitive sensor during operation, and the accuracy of sensing monitoring, avoid the change of outdoor climate, the light becomes dark and the position of photosensitive sensor is in the shadow, resulting in the error of the result when photosensitive sensor judges.

This invention discloses a method, device, system, and storage medium for extracting urban traffic scenes, belonging to the field of intelligent interpretation technology. The method comprises: obtaining 3D point cloud data and image data of an urban traffic scene; extracting static elements of the urban traffic scene using a trained KPConv network based on the 3D point cloud data, obtaining the static elements of the urban traffic scene, and parameterizing the static elements of the urban traffic scene; extracting dynamic objects in the urban traffic scene using a trained YOLOv7-W6 network based on the image data, obtaining the dynamic objects in the urban traffic scene, and mapping the dynamic objects in the urban traffic scene to the coordinate system of the 3D point cloud data, thereby completing the urban traffic scene extraction. This method can effectively extract static elements and dynamic objects in urban traffic scenes.

This invention discloses a small target detection method and system based on improved YOLOv11 and fused attention, applicable to small target detection in unmanned aerial vehicles (UAVs). The method includes the following steps: constructing a backbone network using a custom module SFBCR; constructing a neck network using a custom module MFBCR to obtain a custom model; and designing a fused attention mechanism based on the SimAM attention module and PartialConv partial convolutional modules. The model parameters are determined by training on the public UAV small target dataset VisDrone. Compared with existing neural networks, the proposed detection method achieves an average accuracy improvement of 2.03% in UAV small target detection applications while maintaining detection speed. It can be used in smart city construction to improve urban traffic management.

The invention relates to the related technical field of application performance monitoring, in particular to a low-Token consumption time sequence analysis method based on time sequence data visualization and a multi-modal large model, which comprises the following steps: step S1, cleaning, normalizing and feature extraction are performed on original time sequence data, and features comprise trend features, periodic features and abnormal features; s2, a customized time sequence trend chart is generated according to the features extracted in the step S1, the trend chart comprises a customized coordinate axis, a multivariable visual distinguishing identifier, a feature highlight identifier and a long time sequence segmentation identifier, and the method relates to a long time sequence data efficient analysis technology under the scenes of industrial equipment operation and maintenance, financial risk control, urban traffic scheduling and the like. By customizing the time sequence visual coding compression data Token amount and combining with the time sequence enhancement fine tuning optimization multi-modal model, low-cost and high-precision analysis of long time sequence data is realized, and technical support is provided for time sequence abnormity early warning, trend prediction and correlation diagnosis.

The invention discloses a coordination control phase difference transition decision-making and distribution method, which comprises the following steps of: correlation adjustment amount calculation: taking any specified time point as a unified clock reference point, and calculating an extended transition adjustment amount required by a period switching moment and a shortened transition adjustment amount corresponding to the extended transition adjustment amount; according to the transition decision model establishment, through association adjustment amount and period phase boundary constraint, through accurate phase difference transition control, differentiated green time ratio distribution, real-time dynamic feedback and multi-field applicability, the defects in dynamic adaptability, multi-objective optimization and engineering economy in the prior art are systematically overcome, and the method has the advantages of high efficiency, high reliability and the like. And a core technical support is provided for intelligent upgrading of urban traffic.

The invention provides an optimization method based on an Infomap algorithm and a genetic algorithm, aiming at solving the problem of inaccurate functional area division caused by neglect of node attributes in the existing urban activity area identification method. The method comprises the following steps: (1) carrying out gridding processing on mobile phone signaling data, and constructing a space interaction network fusing node attributes; (2) realizing high-modularity community detection considering node attributes based on an enhanced Infomap algorithm; and (3) modeling and quantitatively analyzing the boundary effect of the active area, and proposing optimization suggestions. The space interaction network is constructed based on the mobile phone signaling data, and an enhanced Infomap algorithm considering node attributes is provided to complete community detection, so that quantitative analysis of the importance of each activity area and the boundary effect of the activity area is implemented, and reference is provided for constructing a more efficient and sustainable urban traffic network.

The application provides an intersection signal optimization timing method based on queue length and delay, comprising the following steps: S1, road end equipment collects traffic situation data; S2, historical data aggregation and algorithm data preparation; S3, timing optimization model based on queue length and signal control delay; relying on the traffic data collected by the urban traffic flow monitoring equipment and the phase control data of the signal machine, the fine timing result of the urban intersection signal control scheme is calculated more quickly and conveniently, a set of reasonable timing optimization model for the continuous and real traffic passing demand of the intersection is provided, the more accurate data in different time periods is accurately controlled and optimized, the same set of timing scheme method is used, and the space-time data resources of the intersection equipment and the signal machine are fully utilized.

The invention discloses an urban traffic intelligent street lamp based on the Internet of Things, and relates to the technical field of outdoor street lamps, the urban traffic intelligent street lamp comprises a fixing frame, a fixing rod is installed at the bottom end of the fixing frame, a frame cover and a climate monitoring mechanism are installed at the top end of the fixing frame, and the climate monitoring mechanism comprises a movable plate, a collection notch and a movable through opening. A movable through opening is formed in the middle of the frame cover, a movable plate is movably installed in the movable through opening, and a collecting notch is formed in the middle of the movable plate. Through cooperative use of the climate monitoring mechanism and the illumination monitoring mechanism, in the use process of the outdoor street lamp, the working position of the photosensitive sensor is adjusted by monitoring different climates and through results generated during monitoring, the working stability of the photosensitive sensor and the accuracy during sensing monitoring are guaranteed, and the working efficiency of the outdoor street lamp is improved. And the condition that the judgment result of the photosensitive sensor has an error due to the fact that outdoor climate changes, light darkens and the position of the photosensitive sensor is located at a shadow position is avoided.

This utility model relates to the field of directional sign technology, specifically an urban traffic directional sign. The utility model includes a mounting frame fixed to the ground by expansion bolts. A sign body is mounted on the front of the mounting frame, and the sign body is fixed to the mounting frame by clamps and screws. A lifting assembly is provided on the front of the mounting frame. The lifting assembly includes a lifting U-shaped block disposed on the arc surface of the mounting frame. A positioning rod is fixedly connected to the side of the lifting U-shaped block near the mounting frame. The positioning rod is inserted into the mounting frame. By setting up the lifting assembly, when the sign body is installed on the mounting frame, the lifting U-shaped block is dragged, causing the positioning rod to insert into the mounting frame. Then, the sign body is placed on the lifting U-shaped block, followed by fixing the sign body using a fixing mechanism. Finally, clamps and screws are used to fix the sign body and the mounting frame, thereby achieving the effect of lifting and pre-fixing the sign body as much as possible.

The invention discloses an urban land vacancy condition identification method based on multi-source data, and relates to the technical field of urban planning, tourism planning, natural language processing and urban traffic, and the method comprises the steps: firstly, extracting residential land in vector building contour data through a remote sensing image interpretation method; secondly, extracting a height value of the vector building contour data; then, the building area value of each land plot and the number of residents of each land plot are calculated; and finally, calculating the number of people in the unit building area of each land parcel, and carrying out urban land vacancy condition identification through the number of people in the unit building area or a machine learning algorithm. According to the method, the urban land vacancy state can be efficiently and automatically identified.

The invention relates to the technical field of urban traffic noise elimination construction, in particular to a sound barrier anti-collision wall positioning and trepanning device which comprises a connecting frame, and the side walls of the two ends of the connecting frame are slidably connected with a first clamping frame and a second clamping frame correspondingly. The two ends of the side walls, close to each other, of the first clamping frame and the second clamping frame are rotationally connected with second rolling wheels. Rolling wheels I are rotationally connected to the middle areas of the left and right ends of the bottom of the connecting frame; the rolling wheel I and the rolling wheel II on the connecting frame, the clamping frame I and the clamping frame II are respectively in sliding contact with the side walls and the top of the left end and the right end of the anti-collision wall, so that the trepanning equipment slides at the upper end of the anti-collision wall. A walking mechanism is composed of the connecting frame, the first clamping frame, the second clamping frame, the first rolling wheel and the second rolling wheel, a drilling machine fixing device is composed of a vertical sliding block, a parallel sliding rail, a parallel sliding block, a sliding rod and an electric drill mounting plate, the time for carrying drilling equipment and manually holding a drilling machine in the construction process is greatly shortened, accurate positioning of the drilling position can be achieved, and the drilling efficiency is improved. And the punching efficiency can be effectively improved.

The present disclosure belongs to the technical field of charging station planning, and specifically relates to a site selection planning method and system for urban charging stations, comprising: constructing a city network model based on the structure of the urban transportation network; evaluating the importance of charging demand points based on the constructed network model and urban charging station address evaluation indicators; performing a preliminary selection of charging station addresses based on the evaluated importance of the charging demand points; and planning the preliminarily selected charging station addresses using an improved grey wolf algorithm with the goal of minimizing total investment, thereby obtaining a site selection planning scheme for urban charging stations.

The invention discloses a preparation method of engineering building thermal insulation and noise reduction technical glass and technical glass, and belongs to the technical field of glass manufacturing, the preparation method comprises the following steps: outer layer glass and inner layer glass are obtained through cutting, and the outer layer glass and the inner layer glass are used for forming an outer layer structure and an inner layer structure. The porous aerogel layers are arranged in the outer glass layer and the inner glass layer, the porous aerogel layers are of a level pore channel structure, the thermal insulation performance is good, transmission of high-frequency sound can be effectively blocked, sensors are installed on the porous aerogel layers, action array modules are embedded in the porous aerogel layers, and the thermal insulation performance of the sensor is improved. The active noise reduction model receives the noise electric signal and performs noise correction processing so as to generate an optimal control signal, and the control signal controls the action array module to generate reverse sound waves and perform active noise reduction on low and medium frequency urban traffic noise, so that the noise reduction performance of the glass adopting the thermal insulation and noise reduction technology is remarkably improved, and the use effect is good.

The invention discloses an agent travel scheme generation and dynamic updating method based on a large language model, and the method comprises the steps: organically integrating five modules: environment perception, social coordination, scheme generation, dynamic updating and experience learning, and achieving the humanization travel decision of an agent in urban traffic simulation for the first time. The system innovatively combines the reasoning ability of a large language model with the real-time requirement of traffic simulation, and breaks through the technical bottlenecks of a traditional rule-based simulation system in the aspects of intelligence, dynamics and individuation through a multi-level reflection mechanism and a continuous learning framework. According to the method, discrete decision algorithms are integrated into a coherent decision process; expanding a static planning method into a dynamic adaptive system; the independent decision of the individual is upgraded to the collaborative decision of the group; and single decision output is evolved into continuous learning optimization.

The utility model discloses a large landscape gallery frame for an urban traffic square, which comprises a support beam structure, and the edges of two opposite end parts of the support beam structure are gradually narrowed and converged to one point to form a shape with a tip; the side edge of the supporting beam structure is connected with a plurality of supporting columns, and the supporting columns incline in the direction away from the adjacent tip ends of the supporting columns. According to the technical scheme, the corridor frame has the function of guiding the direction of people flow, and the traffic efficiency of a square is improved; the occupied area is reduced, and people flow obstruction is reduced.

The invention relates to the technical field of video processing and live-action fusion, and discloses a real-time video stream distortion correction and splicing method for live-action fusion. According to the method, multi-source data are synchronously collected through a camera array ad hoc network integrating multiple sensing units, effective spatial anchor points are generated and screened through five-mode fusion, video elements are decomposed, association with the anchor points is established, distortion correction and spatial calibration are synchronously completed based on an adaptive element calibration matrix, and the distortion correction and spatial calibration precision is improved. And finally, dynamic seamless fusion of multiple paths of videos is realized through virtual space adaptive grid splicing. According to the method, a traditional linear processing flow is thoroughly overturned, the core problems of high splicing delay, poor dynamic scene adaptability and insufficient multi-element cooperative calibration precision in the prior art are solved, the method is suitable for various live-action fusion scenes such as urban traffic monitoring and large-scale venue security and protection, and the real-time performance and the seamless performance of video splicing are remarkably improved.

This invention discloses a method, system, device, and storage medium for identifying commuting behavior. The method includes: acquiring mobile phone signaling data and school AOI data, and preprocessing the mobile phone signaling data and school AOI data; determining, based on the mobile phone signaling data and school AOI data, fixed-station objects based on the school and the corresponding types of fixed-station objects; the type being the type corresponding to the geographical grid visited or resided in by the object; and, based on the type and the object's basic information, determining the object's population category, the start point, and the end point of commuting behavior based on a preset classification strategy. This application combines large-scale mobile phone signaling data and school AOI data to determine the object's stationing type; further, it allows for fine-grained segmentation of population categories and commuting behavior, which helps improve the precision of population identification. This method can be widely applied in the field of urban transportation planning technology.

The utility model provides a tunnel signal lamp control system, and relates to the technical field of traffic signal equipment, the tunnel signal lamp comprises a communication control unit, an LED light emitting unit, and a 24V switch power supply, the communication control unit comprises a first one-chip microcomputer, an MOS switch, an input serial port, a first output serial port, and a first voltage stabilizing power supply; the tunnel signal lamp control device comprises a second single-chip microcomputer, a network communication unit, a second output serial port, a second voltage-stabilized power supply and a 5V switching power supply. The tunnel lamp control device has the beneficial effects that the tunnel lamp control device realizes automatic control of the tunnel signal lamp through a cascade mode that the output serial port is connected with the signal lamp input serial port, improves the operation efficiency and accuracy of the tunnel signal lamp, further guides a vehicle to run at a limited speed, reduces congestion caused by too low running speed of the vehicle, and improves the urban traffic efficiency.