69 results about "Traffic station" patented technology

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.

A platform screen door for rail transit. By means of providing a monitoring sensor (12) and a fault early-warning device (13) for a screen door, real-time operation data of the screen door is acquired, and the real-time operation data is then input into a pre-constructed prediction model; on the basis of the prediction model, multi-round cyclic segmented prediction is performed on the real-time operation data, so as to output an operation prediction result at each time node within a target time period, wherein one piece of segmented-prediction data for the target time period is output by means of each round of prediction, and the obtained segmented-prediction data and the real-time operation data are used as model input data for the next round of prediction; and the operation prediction result is input into a pre-constructed fault monitoring model, and on the basis of the fault monitoring model, a fault type monitoring result at a corresponding time node is output. By means of the technical means, a potential fault type at a corresponding time node can be detected in a timely manner, such that accurate and efficient fault monitoring is realized, thereby improving the reliability and stability of operation of a screen door.

The invention relates to the technical field of public transport organization, in particular to an urban traffic station connection evaluation method based on multi-source data, which comprises the following steps of: performing passenger flow analysis on an upstream public transport section of a station, dividing passenger flow time periods, and acquiring multi-source connection situation data by adopting a sampling or real-time monitoring mode based on different time periods; calculating a transport capacity supply saturation index based on the station upstream public traffic section passenger flow data, calculating a dynamic transport capacity service efficiency index based on the mobile passenger-carrying end parking characteristic data, weighting to obtain a comprehensive connection bearing coefficient, estimating the real-time passenger flow arrival flow based on the arrival shift data of the traffic station and the number of resold tickets, and determining the real-time passenger flow arrival flow. And evaluating the urban traffic connection capability of each station by generating a real-time connection efficiency value. According to the method, the quantitative evaluation of the operation state of the connection system of the urban traffic station is realized, the defects of a traditional method in the aspect of multi-source data fusion are overcome, and the analysis precision of the connection capability of the urban traffic is improved.

The present invention discloses a method and system for traffic relief during the construction of a rail transit station. The method comprises: obtaining construction information of the rail transit station during the construction; setting a traffic relief speed evaluation model, and calculating a traffic relief speed index based on the construction information, for evaluating the relief speed when an emergency occurs, wherein when the traffic relief speed index is greater than a preset relief threshold, adjusting the construction area until it is less than or equal to the preset relief threshold; obtaining all paths actually selected by pedestrians, and setting a path selection evaluation model to evaluate all paths actually selected by pedestrians, finding a path with the smallest evaluation index of the paths actually selected by pedestrians as the optimal path, and setting road signs so that pedestrians can be relieved along the optimal path.

The utility model discloses a rail transit platform door isolation device, including and the mechanical isolation lock of lintel connection, and the isolation support of door leaf connection, mechanical isolation lock includes lock core, lock tongue, lock core front end connection lock tongue, and the keyhole that is equipped with for professional key access is equipped in the back, and lock core and lintel rotation is connected, forms mechanical isolation, and lock core drives lock tongue to rotate, and the clearance between door leaf is reduced, and the isolation support is prevented to cross lock tongue. Through setting lock core structure, prevent misoperation, and lock core drive lock tongue movement, prevent sliding door to slide, and sliding door can not open, on the basis of electric isolation, increase a safeguard, guarantee security.

This invention discloses a method for predicting urban rail transit passenger flow based on multimodal information fusion. First, feature vectors of urban points of interest are obtained. Then, a directed graph of rail transit stations and the positional relationship between rail transit stations and points of interest are constructed to extract feature vectors of rail transit stations. Social media text from various time periods is crawled to extract public travel interest feature vectors. Then, a multi-head cross-attention model is used to fuse the public travel interest feature vectors, rail transit station feature vectors, and historical passenger flow feature vectors. Finally, an LTSM network is used to predict the passenger flow feature vector for the next time period. This invention integrates urban point of interest features and social media text features to predict urban rail transit passenger flow, improving prediction accuracy.

The invention belongs to the technical field of urban planning, and particularly relates to a traffic station region land utilization efficiency evaluation method, which comprises the following steps of: acquiring and preprocessing point-of-interest data and a traffic station region in an analysis region; extracting land utilization layout features based on the null data set; constructing a multi-mode traffic network including walking, bicycles, buses and rail transit based on the layout features; establishing a land coupling simulation model of traffic based on the regional reachability index; causal inference and model calibration are carried out based on historical traffic intervention events of dynamic evolution; adopting a multi-objective optimization algorithm to generate traffic and land utilization configuration schemes meeting different planning objectives; according to the method, the evaluation result is subjected to visual display and decision output, unified modeling of traffic and social economic data is achieved through multi-source heterogeneous data fusion and standardization processing, and the effect of improving data space-time matching precision and calculation reliability is achieved.

The application provides a shared bicycle demand prediction method, system, device and medium, and belongs to the field of computer application, and comprises the following steps: acquiring order data of shared bicycles at a traffic station in a target area; using sparrow search algorithm to optimize hyperparameters of a model based on long short-term memory neural network and random forest; combining long short-term memory neural network and random forest model by using least square weight combination to obtain a demand prediction model; inputting order data of shared bicycles in a region to be predicted into the demand prediction model to obtain demand prediction data of shared bicycles in a set time period. The model performs well on a data set with large demand and obvious change over time, is suitable for shared bicycle demand prediction at a subway station, and provides theoretical support for planning shared bicycle distribution and scheduling, and is complementary to subway service.

The utility model discloses a platform door rail side anti-pinch lock, which relates to the technical field of rail traffic platform doors, and comprises a sliding door, the sliding door comprises sliding door frames on two sides, lock holes are arranged on the sliding door frames, the sliding door further comprises a pressing assembly, and the pressing assembly comprises a bottom shell. The two ends of the bottom shell are connected with sliding door frames on the two sides of the sliding door through a plurality of fixing screws respectively, the bottom shell is connected with an unlocking assembly, the structure is simple, rigid connection is adopted, jamming is not prone to occurring, installation is convenient, the requirement for assembly precision is low, practicability is high, later maintenance and repair are convenient, the product cost is low, and the practicability is high. Furthermore, passengers and station service can unlock the sliding door through the body part during use, so that the personal safety is guaranteed, and the safety is improved.

This invention provides a method, system, computer equipment, and storage medium for predicting passenger flow at rail transit stations. The method extracts directed origin-destination (OD) pairs from the entry and exit records of an automated fare collection system using a fully directed network; determines the travel time for non-transfer and single-transfer journeys; determines the real-time location of passengers based on the OD pairs and travel time; determines the passenger flow at each station within a target time period based on the passengers' real-time locations; acquires and processes weather factors; constructs a CNN-BiLSTM-Attention passenger flow prediction model; and uses the passenger flow at each station within the target time period and weather factors as input variables to predict the passenger flow at each station using the CNN-BiLSTM-Attention passenger flow prediction model. This invention considers the influence of weather factors, time dependence, and spatial characteristics, enhancing the focus on key features and improving the accuracy of station passenger flow prediction.

The invention belongs to the technical field of urban rail transit safety management, and particularly discloses an urban rail transit station crowd stability identification and early warning method, which comprises the following steps: acquiring personnel action data under various crowd flow movement scenes, quantifying conflict events among personnel based on a Worronoi diagram and a speed obstacle model, and obtaining quantitative characteristics; abstracting personnel as nodes, abstracting conflict events as directed edges, and constructing a time-varying conflict network; setting a percolation threshold value, and continuously analyzing a communication state and a conflict index set of the conflict network in a threshold value increasing process; generating a stability criterion according to the change trend of the connected subgraph along with the threshold value, judging the stability of the target scene in combination with the conflict index set, and outputting an early warning signal; the method has the following advantages that individual microscopic behaviors and system macroscopic steady-state characteristics can be described at the same time, multi-scene stability criteria are unified, steady-state real-time recognition and instability early warning of people in the rail transit station are achieved, and the in-station passenger flow safety management level can be improved.

The invention discloses a rail transit station ventilation system fault monitoring and early warning method and device, and relates to the technical field of intelligent monitoring. According to the technical scheme, the method comprises the steps that real-time environment parameters and real-time passenger flow volume parameters of all key areas of a rail transit station and real-time operation parameters of all key equipment in a ventilation system are obtained; performing time sequence alignment and preprocessing on the real-time environment parameters and the real-time operation parameters to obtain real-time multi-source fusion data; inputting the real-time multi-source fusion data into a preset fault recognition model to obtain a fault recognition result corresponding to the real-time multi-source fusion data; determining a target early warning probability threshold value corresponding to the at least one fault type according to the real-time passenger flow volume parameter, and judging whether the ventilation system meets an early warning condition or not according to a comparison result of the fault occurrence probability and the target early warning probability threshold value; and if yes, generating early warning prompt information corresponding to the ventilation system. The accuracy and timeliness of fault monitoring and early warning of the ventilation system are improved.

The invention relates to a parking management platform parking space recommendation method and device based on a traffic station yard, computer equipment, a storage medium and a computer program product. The method comprises the following steps: determining a predicted parking space utilization rate corresponding to each parking lot subarea in a parking lot; according to the predicted parking space utilization rate and the destination information of the to-be-analyzed vehicle, the predicted priority of each parking lot subarea is obtained, and then a target parking lot subarea corresponding to the to-be-analyzed vehicle is determined; determining candidate idle parking spaces matched with the vehicle type of the to-be-analyzed vehicle in the target parking lot subarea, and obtaining historical idle time periods corresponding to the candidate idle parking spaces; the vehicle types comprise public transport vehicles and social vehicles; and candidate idle parking spaces of which the historical idle time periods meet the predicted parking time period of the to-be-analyzed vehicle are screened out to serve as target idle parking spaces matched with the to-be-analyzed vehicle, and corresponding parking space recommendation information is generated and sent to a target terminal. By adopting the method, the parking efficiency can be improved.

Stations are monitored that join and leave a multicast group associated with one or more switches over a wired channel and one or more access points over a wireless channel. At least one of latency or packet loss over a threshold are detected for a specific VLAN group. Multicast traffic is segregated in response to the detection, at the one or more switches, by reassigning stations that are not associated with multicast traffic to a new VLAN group, and by at the one or more access points, reassigning stations that are associated with multicast traffic with the low bandwidth frequency and reassigning stations that are not associated with multicast traffic with the high bandwidth frequency.

The invention relates to a roadside parking system, in particular to a logistics system based on a public transport system. The roadside display system and the three-dimensional parking garage are combined, and automatic parking and automatic vehicle taking are achieved through the intelligent vehicle transporter. Moreover, the outdoor display devices which are uniformly and dispersedly deployed and generally have a certain volume are used as the deployment basis of the three-dimensional parking garage, so that the advantages of centralized parking and distributed parking can be combined, the parking function that the outdoor display devices are uniformly and dispersedly deployed along the lane and have the accommodating capacity that the unit area is several times higher than that of the parking spaces on the road is realized, and the space utilization rate is increased. According to the invention, vehicle parking and taking are carried out based on automatic parking and automatic vehicle taking, fee evasion and arrearage can be effectively avoided, a large number of managers are not needed, the number of bad debts and labor cost can be effectively reduced, and road resource occupation is reduced. According to the logistics system based on the public transport system, the underground space of the traffic station or the roadside parking system is used as the cargo storage space of the traffic station.

The invention discloses a traffic resource dynamic allocation method based on a confidence map convolutional network. The traffic resource dynamic allocation method comprises the following steps: modeling a current actual traffic network and traffic stations; performing feature extraction on traffic network graph data generated by modeling through a graph embedding method to determine a feature extraction vector; processing the feature extraction vector based on a deep belief network, and spreading and updating through a graph convolutional neural network, thereby updating the feature representation of the node and changing the label type, used for representing the tension degree of traffic resources, of each node to generate a target topological structure; and automatically allocating traffic resources to the corresponding traffic stations according to the target topological structure so as to realize one-time automatic allocation of the traffic resources, and performing automatic allocation of the traffic resources again based on the updated actual traffic network data. According to the invention, the resource allocation problem of the traffic station can be timely responded, so that the traffic resources can be better and dynamically allocated.

The application provides a travel service recommendation method and device, an electronic device and a storage medium. The method comprises the following steps: performing regional clustering based on station position information of a traffic station to obtain a plurality of candidate travel region pairs, and constructing a candidate travel chain; obtaining first historical travel data in a preset historical period, and extracting corresponding second historical travel data for a preset operation time interval; for each candidate travel region pair, determining a maximum number of transfers, and obtaining a target historical passenger flow in a continuous historical time interval; combining a preset screening condition to screen a target travel region pair; extracting third historical travel data, generating a travel inappropriateness evaluation index of each operation time interval based on the first and third historical travel data for each target travel region pair, and recommending a travel service to a travel object according to the travel inappropriateness evaluation index. The application can provide personalized traffic services for travel objects with the same travel demand and provide a good travel experience.

1. Name of this design product: Urban Intelligent Bus Stop Sign. 2. Purpose of this design: This design is used to display relevant traffic stop information. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The invention relates to the technical field of rail transit facilities, in particular to a safety protection door for a rail transit platform, which comprises a fixed door frame mounted on the platform and two movable door units slidably arranged in the fixed door frame. The movable door unit comprises a door body frame and sliding block mechanisms arranged at the top and the bottom of the door body frame. Through the arrangement of the door body frame and the driving mechanism, the sliding block mechanism slides on the surface of the door body frame and moves to different positions to form four working modes of closing, transverse opening, double opening and three opening, and the four working states of train operation, normal passenger flow, large passenger flow and ultra-large passenger flow are coped with correspondingly; when it is monitored that passenger flow starts to gather in a certain vehicle door or platform area, the door or several adjacent doors can be immediately switched to a three-opening mode to form a fast-passing channel to quickly digest the passenger flow, the door opening strategy of the whole platform does not need to be changed, and the smooth transition capacity enables operation scheduling to be more leisurely and scientific.

This application relates to the field of data communication technology and discloses a method and system for implementing a station-level intelligent agent in rail transit. The method includes: constructing a specialized agent base using an ARM processor, designing a LiteIP secure communication bus based on an FPGA, building a multi-core CPU cluster to construct the intelligent agent's central hub, establishing a real-time and entity database to form a data foundation, integrating federated learning and neural network-based decision generation, and executing edge computing to achieve station-level autonomous control. This application achieves millisecond-level data exchange and intelligent collaborative control within the station-level system, significantly improving the system's response speed and processing efficiency in emergency situations.

This invention relates to the field of equipment operation and maintenance, and particularly to a predictive maintenance method, system, equipment, and medium for rail transit platform screen doors. The method includes: acquiring multimodal sensing data and time-varying operating condition characteristics of the station area; inputting the sensing data into a multimodal fusion model, and extracting physical loss, time-series load, and operation and maintenance semantic feature vectors through heterogeneous parallel branches; performing self-learning alignment and fusion of features based on a cross-attention mechanism, and outputting an operating status score and associated text; inputting the associated text into a large language model, using a fault causal logic chain to back-verify and correct candidate root causes; analyzing the fault root causes and multimodal sensing data to obtain an initial maintenance strategy, and performing dynamic optimization to generate a maintenance plan. Therefore, this invention, through deep fusion of multimodal data and causal logic reasoning, realizes fault early warning, root cause localization, and operation and maintenance resource scheduling for rail transit platform screen doors, improving the intelligence level of operation and maintenance management and the equipment operation guarantee capability.

The present invention provides a rail transit station management method and device, the method comprising: receiving, by an LBS signal receiver, positioning uplink information sent by terminal devices in each target area isolated by an electronic fence; determining the residence time of the operation and maintenance personnel corresponding to each terminal device in each target area based on the positioning uplink information sent by each terminal device and the time when the positioning uplink information sent by each terminal device in each target area is received; and determining the prompt information to be sent to each operation and maintenance personnel based on the residence time and operation and maintenance tasks of each operation and maintenance personnel in each target area. The rail transit station management method of the present invention can determine the time and trajectory of each operation and maintenance personnel's activities in different target areas by performing positioning analysis on the terminal devices, thereby facilitating intelligent prompting of the operation and maintenance personnel according to the operation and maintenance tasks of each operation and maintenance personnel, thereby realizing intelligent management of the location status of the operation and maintenance personnel.

Embodiments of the present application provide a method and device for determining the geographic coding of a traffic station of a target trip. The method comprises: obtaining origin station data, arrival station data and trip information of the target trip; querying at least two groups of candidate arrival station data according to the arrival station data; obtaining at least two groups of multi-dimensional feature vectors according to the origin station data, the trip information and each group of candidate arrival station data; determining the geographic coding of the traffic station of the target trip according to the two groups of multi-dimensional feature vectors; and outputting the geographic coding of the traffic station of the target trip. Embodiments of the present application can accurately distinguish between stations with the same name but different locations, effectively reduce the error rate of zoning identification, and ensure the accuracy of core businesses such as fare setting and financial subsidy allocation.

The utility model relates to the field of traffic platforms, and provides a rail traffic platform which is characterized in that a guardrail assembly for forming a queuing channel is arranged in a platform ceiling, and when the passenger flow volume of the platform below the platform ceiling is large and tourists need to be classified and queued in order, a positive and negative motor can be started to drive a rotating shaft to rotate; under the cooperation of a synchronous wheel and a synchronous belt, the two sets of two-way screw rods synchronously rotate in the same direction, at the moment, sliding seats in threaded connection to opposite threads on the two sides of the two-way screw rods synchronously, oppositely and horizontally move and drive a fluted disc to rotate through a tooth groove set, and at the moment, all rotating arms and telescopic rod pieces synchronously rotate along with the fluted disc to be vertically downward; at the moment, the elastic ropes between the two sets of rotating balls on the two sides form a guardrail channel for passengers to queue up and get on, and compared with a comparison file, the problem that the guardrail assembly is treaded by the passengers, so that dirt is attached to the guardrail assembly, and even the guardrail assembly is damaged is effectively solved.

The application provides a passenger flow congestion delay prediction method and system, belongs to the technical field of commuting delay prediction, selects delay data of adjacent, same time of past several days and same time of past several weeks of a to-be-measured time period in a historical delay data set, constructs an explicit and implicit traffic relationship graph between traffic sites according to the data, makes input data of passenger flow congestion delay prediction fully consider time characteristics of the historical time dimension of the traffic sites and spatial characteristics of adjacent or highly-correlated traffic sites in the spatial dimension, and further involves characteristics of external influence factors in passenger flow congestion delay prediction, so that the historical data of the sites, the space-time correlation between the traffic sites and various external influence factors are fully considered, and the accuracy and applicability of the passenger flow congestion delay prediction model are improved.

1. Name of the product of this design: Security Shield Door (DZT‑PBM‑601). 2. Application of this design product: Used in various transportation platforms and pedestrian walkways to ensure passenger safety. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: Stereoscopic drawing 1.

The invention relates to the technical field of anti-pinch detection, and discloses a rail transit platform shielding door anti-pinch detection device, which comprises a base, the top of the base is fixedly connected with a supporting rod, one side of the supporting rod is provided with a frame, and toughened glass is installed in an inner cavity of the frame; according to the device, the efficient anti-pinch detection function is achieved through the sensing mechanism. The rubber strip on one side of the movable frame can provide preliminary buffering when the door body is closed, so that the risk of clamping injury is reduced; and the sensor on one side of the supporting block can monitor the surrounding environment of the door body in real time, once an object or a person is detected to be in a closed path, a signal is sent in time to control the driving motor to stop or rotate reversely, and the clamping injury condition is avoided. Compared with a traditional mechanical anti-pinch device, the design is faster in response and higher in intelligent degree, potential safety hazards can be effectively reduced especially in the passenger flow dense period, and more reliable protection is provided for passengers and articles.

The application discloses a model establishment method and device for track traffic flood prevention, a server and a medium. The method comprises the following steps: acquiring digital twin data of a track traffic station, determining the number of flood prevention key points and corresponding flood prevention attribute categories according to the digital twin data; when the total number of flood prevention input control key points, flood prevention transitivity key points, flood prevention decisive key points and flood prevention control key points is greater than a first threshold value, a dimensionality reduction improved feedforward neural network is established; and when the number of one fourth of the flood prevention input control key points, the number of the flood prevention transitivity key points, the number of the flood prevention decisive key points and the number of the flood prevention control key points is less than the first threshold value, a GNN model is established. The complexity of the current station can be determined, and a suitable model can be selected according to the complexity. By using the suitable model, the calculation amount can be reduced, and the overfitting phenomenon caused by the excessive complexity of the model can be avoided.

The invention discloses a traffic flow prediction method based on a space-time diagram neural network and related equipment, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining a traffic network diagram; wherein nodes of the traffic network diagram represent traffic stations, and edges between the nodes represent roads between the corresponding traffic stations; dynamically acquiring time sequence data of each traffic station and carrying out normalization preprocessing on the time sequence data; wherein the time sequence data comprises the traffic flow and the vehicle speed of the corresponding traffic station; dynamically updating the traffic network map by using the time sequence data after the normalization preprocessing to obtain a dynamic update map; extracting spatial features of the dynamically updated graph by using a graph attention network; extracting time features of corresponding scales from the spatial features by using three long and short time memory networks with different time scales; and predicting the traffic flow of the next time step according to the time characteristics of the three scales. The traffic flow can be predicted more accurately.

The application discloses a positioning method, device, equipment, storage medium and product, and belongs to the computer technical field.The method comprises the following steps: acquiring station fingerprint information corresponding to at least one traffic station; acquiring target base station information corresponding to a target positioning point; matching the target base station information with the station fingerprint information, generating matching data corresponding to the target base station information and the at least one traffic station; and determining a target traffic station matched by the target positioning point based on the matching data.The technical scheme provided by the embodiment of the application can be applied to the field of maps, the base station information corresponding to the positioning point is matched with the station fingerprint capable of representing the characteristics of the base station, the station positioning is realized, the problem of inaccurate station positioning caused by factors such as weak satellite navigation positioning signals or few station wireless local area network distributions can be avoided, and the accuracy, timeliness and flexibility of the station positioning are improved.