215 results about "Road traffic control" patented technology

The invention relates to the field of real-time visualization of road conditions, in particular to a data simulation visualization rendering method and system for urban traffic road conditions. The method comprises the following steps: extracting a real-time satellite streetscape image based on urban satellite remote sensing scanning, and performing scene pixel-level segmentation to obtain scene texture rendering parameters; scene illumination visual identification is carried out according to the real-time satellite streetscape image, traffic scene background modeling is carried out based on scene texture rendering parameters, and a real-time scene background model is constructed; the method comprises the following steps: acquiring urban-level multi-source traffic monitoring data flow, performing vehicle state sensing, and constructing a multi-dimensional particle feature matrix; road network topological correlation analysis and global traffic network state perception are carried out according to the real-time satellite streetscape images, and a road network state perception model is constructed. According to the invention, a real real-time traffic environment is visualized, scene effects in different traffic states are presented, the current road condition can be rapidly evaluated, and the traffic control decision efficiency is improved.

The invention discloses a traffic control and guidance system and method based on an ant colony algorithm, belongs to the technical field of road traffic control, and solves the problems that a neural network model in an existing method mainly focuses on respective route conditions of a plurality of bifurcation routes of a bifurcation on a one-way driving road, and the information fusion degree between traffic elements is low. The method comprises the following steps: identifying dynamic characteristic information of vehicles in a road network, pre-constructing a road network optimization model based on an ant colony algorithm combined with deep learning, and analyzing a pheromone spread function cluster solution; according to the invention, the road network optimization model based on the ant colony algorithm and the deep learning is pre-constructed, the collaborative optimization of traffic signal control and vehicle induction is realized, the traffic signal optimization control strategy and the vehicle optimization path strategy are output, so that the signal timing and the induction path can be matched with each other, and the control accuracy is improved. Therefore, the operation efficiency of the traffic system is improved and the accuracy and effectiveness of the guidance strategy are ensured.

The invention relates to the technical field of emergency linkage, and discloses an urban fire emergency linkage command system and method based on digital twinning, and the system comprises a multi-source heterogeneous data collection module which obtains the multi-source heterogeneous data of multiple departments in real time; the dynamic digital twinborn body construction module is used for generating a three-dimensional fire scene twinborn body with a unified space-time reference; the intelligent decision-making module is used for coupling a fire behavior diffusion prediction result of the fluid dynamic equation and a building risk prediction result of the finite element analysis model and generating a fire-fighting power dispatching instruction, a medical aid distribution instruction and a traffic control instruction; and the multi-department linkage execution module is used for sending a fire-fighting power dispatching instruction to the fire-fighting terminal, sending a medical aid distribution instruction to the medical terminal and sending a traffic control instruction to the traffic terminal so as to realize cross-department dynamic collaborative dispatching. According to the method, the emergency response speed and the decision accuracy are improved, efficient cooperation of urban fire emergency rescue is realized, and the rescue efficiency and the capability of coping with complex fire scenes are remarkably enhanced.

The invention provides an abnormal early warning method and system based on driving behaviors, and is applied to the field of data processing. According to the method, multi-level judgment of vehicle driving behaviors is realized by combining individual driving habits of drivers, road types and traffic control information, firstly, real-time driving parameters are detected based on driving identity information pre-recorded by a central controller and are compared with the individual habits, and only behaviors obviously deviating from the habits enter subsequent analysis; the driving behavior data is generated through the prediction model in combination with the road type and the traffic control information, whether the behavior is reasonable or not is further judged, the early warning pertinence is ensured, and finally the abnormal driving behavior is compared by using the group driving behavior baseline, so that the individual difference dynamic correction is realized. Therefore, on the basis of fully considering individual differences of drivers, the false alarm rate is effectively reduced, meanwhile, timely early warning of abnormal behaviors is ensured, and the driving safety and the early warning practicability are improved.

The invention relates to the technical field of intelligent traffic, and discloses a method and device for detecting a thrown object on a road surface, and the method comprises the steps: automatically selecting the wavelength of infrared light according to the environment illumination intensity, and calculating an environment compensation coefficient; the infrared transmitting unit transmits a multi-angle light beam to the infrared receiving unit on the opposite side, and the infrared receiving unit determines the receiving state of the light beam; constructing a fan-shaped infrared beam grid, and determining an area where a suspected target is located; judging whether the suspected target is a thrown object or not, and using an area positioning model for the thrown object to obtain a central position and an effective area; implementing graded alarm; visible light image recognition is replaced by an infrared beam technology, the influence of severe weather on detection precision is effectively overcome through a self-adaptive wavelength selection mechanism, a specific lane where a thrown object is located can be accurately determined in combination with a lane recognition mechanism, and accurate guidance is provided for traffic control and cleaning operation.

The invention provides an air traffic control scene instruction recommendation method and system combined with a knowledge graph, and relates to the technical field of air traffic control. The method comprises the following steps: firstly, establishing a dynamic matching relationship between current air traffic state data (including flight real-time operation parameters, airspace use state parameters and meteorological influence parameters) and an association rule set (including air traffic control rule entries, historical instruction execution constraint conditions and airspace resource allocation criteria), and generating a preliminary instruction set; adjusting the initial instruction set in real time according to real-time air traffic state change data (including flight position change parameters, airspace flow fluctuation parameters and meteorological condition updating parameters) to obtain an adjusted instruction set; and then verifying the compatibility between the adjusted instruction set and airspace use constraint conditions (including airspace capacity limiting parameters, flight interval safety parameters and equipment operation state parameters), outputting a compatible instruction set to cooperate as a target recommendation instruction set, and assisting air traffic control personnel to make a control instruction decision.

The invention relates to the technical field of traffic control, in particular to an airspace situation prediction method and system based on a self-adaptive grid, and the method comprises the following steps: collecting the information of all aircrafts in a current airspace, including the number, speed, x coordinate, y coordinate, z coordinate, course, pitch angle and time of the aircrafts; according to the x coordinate, the y coordinate and the z coordinate of the aircraft, mapping the acquired information of the aircraft into grids of a pre-constructed airspace basic grid network, and obtaining an input feature sequence; and inputting the input feature sequence into an airspace grid situation prediction model based on 3D CNN-GCN-Transform, and outputting to obtain an airspace situation prediction result. According to the invention, accurate prediction of airspace situation change can be realized, and technical support is provided for air traffic control.

The invention relates to a multi-mode large model and light-weight small model collaborative road surface ice condensation state prediction method, and belongs to the field of road traffic safety monitoring and prediction. The method aims at solving the problem that real-time early warning and accurate prevention and control are difficult in the prior art. According to the invention, a multi-modal data coding system is constructed, road surface monitoring images, meteorological time sequence data and historical ice condensation text cases are integrated, and feature fusion is realized by adopting visual-physical feature joint coding, meteorological time sequence feature enhancement and text semantic mining; a pseudo label is generated through large model zero sample reasoning, and a lightweight small model is trained through cross-modal knowledge distillation; and finally, on the basis of a dynamic trigger type double-model reasoning framework, calling a cloud large model for fine judgment when the small model is low in confidence coefficient or high in scene complexity, and outputting the icing starting moment and thickness through confidence coefficient weighted fusion. According to the method, the prediction accuracy and real-time performance are improved, the model generalization ability is enhanced, and reliable support is provided for road traffic control in winter.

The invention provides an AGV scheduling method and related equipment integrating path planning and traffic control, the method comprises the steps of obtaining task information, vehicle dynamic factors and topological map data of an AGV vehicle, the vehicle dynamic factors comprising a cargo state, a storage location state, spinning prohibition and point location prohibition; based on the task information, the vehicle dynamic factors and the topological map data, a depth deterministic strategy gradient network is adopted to optimize the weight, and an improved A star algorithm formed by the sum of basic cost and real-time congestion cost is adopted to plan the driving path of the AGV; continuously monitoring the running state of the AGV cluster in the process that the AGV runs based on the planned path; and conflict prediction is carried out based on the operation state of the AGV cluster, and traffic control is carried out on the AGV cluster by using a preset conflict prevention mechanism and a heuristic deadlock removing strategy. According to the method, vehicle dynamic factors are considered, an A star algorithm is optimized, traffic control is configured, and the AGV scheduling efficiency is improved.

The invention discloses a highway inspection unmanned aerial vehicle task planning monitoring system based on a knowledge graph, particularly relates to the technical field of unmanned aerial vehicle intelligent inspection, and is used for solving the problem that an existing system cannot generate a feasible decision scheme when an airspace control rule conflicts with an emergency timeliness requirement. The method comprises the following steps: constructing a knowledge graph integrating geographic no-fly zone space coordinates, an aging constraint time threshold and a traffic flow thermodynamic map layer, triggering a rule conflict state when detecting that an overlapping region exists between an aging constraint target position and a no-fly zone, and further fusing a real-time traffic control instruction and unmanned aerial vehicle maneuvering characteristic parameters to generate an elastic space domain; and after verification of a high-flow area overlapping rate threshold value or approval of a forced passing instruction, creating a temporary channel entity which covers the overlapping area coordinates and is associated with a time threshold value, and finally generating an inspection route which penetrates through a conflict area and meets a passing time limit based on the entity, thereby realizing coordination of dynamic rule conflict resolution and safety emergency inspection.

The invention provides a voice instruction intelligent analysis method and system applied to an air traffic control scene, relates to the technical field of air traffic control, and aims at the characteristics of voice instruction interaction between a controller and a flight crew in the air traffic control scene to construct an instruction interaction expectation model. The instruction interaction expectation model comprises an instruction sequence association rule and a semantic constraint condition set which are generated based on historical controlled call data, and an interaction feature set of speaker identity features, instruction component time sequence features, voice intonation fluctuation features and the like in a real-time capture voice interaction process; inputting an instruction interaction expectation model for dynamic matching and deviation identification, generating an interaction deviation analysis result, triggering an intention clarification and instruction confirmation process based on the analysis result, obtaining a complete instruction component set, generating an instruction analysis result meeting an air traffic control data exchange standard after structured conversion processing, and pushing the instruction analysis result to an air traffic control automation system. The accuracy and efficiency of air traffic control voice instruction analysis are effectively improved.

The invention relates to a multi-model AGV (Automatic Guided Vehicle) mixed traffic control method based on edge calculation, which comprises the following steps of: S1, arranging a visual camera and an edge calculation platform above a traffic control area, acquiring image information of the traffic control area, and delimiting a plurality of virtual boundary lines in a video image so as to define a monitored area boundary; determining coordinates of a traffic management area, calculating a coordinate function, and establishing a mapping relation from an image to an actual environment; s2, collecting a feature data set of a target object needing traffic control in advance and storing the feature data set into a scheduling system; s3, presetting a traffic rule: if the target object is identified and the target object and the newly-added AGV are about to enter the traffic control area at the same time, the scheduling system sends a traffic control signal to the newly-added AGV to pass through, and the newly-added AGV can pass through after the target object completely passes through the control area; according to the invention, the traffic control problem of newly added AGVs and original AGVs during production line technical transformation is fundamentally solved, and smooth implementation of new projects is facilitated.

The invention discloses an aircraft recovery scheduling method and device based on a self-adaptive Lagrange multiplier, and relates to the technical field of aviation traffic control automation, and the method comprises the steps: building a constrained Markov decision process model of an aircraft recovery scheduling problem; introducing and initializing a Lagrangian multiplier by using a Lagrangian relaxation technology, and converting the constrained Markov decision process model into an unconstrained optimization problem to obtain a Lagrangian function; and performing main dual collaborative iterative optimization based on a Carlo demander-Kuhn-Tucker condition, and adaptively adjusting the Lagrange multiplier until the Lagrange multiplier converges to obtain an optimal strategy. According to the method, the constraint weight is dynamically adjusted in the main dual collaborative iteration mechanism, so that the rationality and accuracy of large-scale cluster recovery scheduling are improved.

The present invention discloses a dynamic capability-graded traffic management method for heterogeneous robots, including: S1 establishing a unified dispatching platform to receive capability registration information from heterogeneous robots; S2 defining the capability type of the robot, which is determined by a combination of a basic capability feature set and a non-empty subset of an extended capability feature set; S3 the unified dispatching platform dynamically generates a decision plan based on the robot's registered capability type and path conflicts; S4 monitoring queues and issuing queue positions to non-read-only robots, which then queue up in turn at a certain distance and speed; S5 detecting and identifying faulty robots, demarcating fault isolation zones, and executing avoidance based on capability type; S6 monitoring deadlocks and executing deadlock resolution strategies based on capability type; S7 fusing robot sensor data, with the platform and local terminals collaboratively executing avoidance. Through dynamic capability grading and targeted dispatching strategies, the operational efficiency and safety of heterogeneous robots and the overall system performance are effectively improved.

The invention discloses a method for generating a signal lamp signal according to a phase name, and relates to the technical field of road traffic control, and the method specifically comprises the steps: obtaining a direction keyword array and a turning keyword array according to a set phase name, reading an array of a half-crossing pedestrian lamp in each direction of an artificially set intersection, and determining whether the intersection is a half-crossing pedestrian lamp or not; the method comprises the following steps of: calculating a vehicle driving lamp state, assigning a value to the lamp color array, obtaining a driving lamp array, calculating a pedestrian lamp state according to the driving lamp array, obtaining a pedestrian lamp array, and controlling the driving lamp and the pedestrian lamp according to the driving lamp array and the pedestrian lamp array. According to the invention, the standard signal lamp color comparison table is automatically generated according to the phase name, the complicated calculation of manual setting is reduced, and the error probability is reduced.

A computer-implemented method comprising the following steps: obtaining (600) an image timestamp indicating the time of acquisition, by a traffic control radar, of an image showing a vehicle's license plate, the image timestamp having been provided by a clock on the traffic control radar; obtaining (602) time synchronization data, said time synchronization data having been received by the traffic control radar during a predefined time interval including the image timestamp to temporally synchronize the clock of the traffic control radar with a time server; and consistency testing (604) of the image timestamp with the time synchronization data, the consistency test producing a test result indicating whether the image timestamp is valid or invalid. Figure for the abstract: Fig. 4

The invention discloses a road passage control method and system based on visual detection, and relates to the technical field of road passage control methods, and the method comprises the steps: determining a release lane passage road according to a multi-phase passage road, and determining the congestion condition of each driving road, according to the congestion condition of each driving road, the plurality of traffic routes and the real-time image of the multi-phase passing road, the traffic guidance of the traffic signal to each driving road is determined, and the accuracy of the traffic guidance of the traffic signal to each driving road is improved. Determining an overall congestion combination according to the abnormal congestion event, the daily congestion event and the traffic plan project of each driving road; according to the traffic combination content of each overall congestion combination, the sub-traffic route of each driving road and the corresponding road peak driving flow, the driving load level corresponding to each driving road is determined, the accuracy of the driving load level corresponding to each driving road is improved, and intelligent traffic regulation and control of each driving road are triggered.

This invention discloses a global optimization method for differentiated traffic control measures that does not violate travel demand, relating to the field of intelligent traffic management technology, and includes the following steps: Step 1: Construct a global optimization framework for differentiated traffic control measures; Step 2: Define the urban traffic network and demand flow parameters; Step 3: Establish a mixed-integer linear programming model for optimizing road network flow distribution; Step 4: Consider factors such as flow demand, flow balance, and travel impedance, approximate the impedance function and objective function with secant lines, and construct constraints for the mixed-integer linear programming model; Step 5: Solve the model to obtain the optimal flow distribution result; Step 6: Obtain differentiated traffic control measures from the model based on the flow distribution result. This invention's method can construct a mixed-integer linear programming model that balances individual interests and overall efficiency based on the complex and diverse travel demands in large-scale urban road networks, design hierarchical control measures, and achieve synergistic optimization of control and path guidance, thereby improving the overall traffic efficiency of the road network.

The invention relates to the technical field of air traffic control, in particular to a multi-mode fusion real-time intelligent monitoring system for air traffic control command. According to the method, a three-dimensional intelligent analysis system of interface situation analysis-voice instruction recognition and understanding-air traffic control information fusion is constructed, and a safety monitoring closed loop of an air traffic control command whole process is realized on the premise that an existing system architecture is not changed; and real-time deduction and risk early warning of the airspace security situation are realized. The generated early warning information is synchronously pushed to a radar controller, an assistant controller and a main controller in a standardized visual and audio coding form through a newly-added safety information prompting module, a three-in-one cooperative cognitive space is constructed, the problem of information asymmetry among multiple seats and multiple on-duty roles in a traditional mode is effectively solved, and the safety of the system is improved. And important technical guarantee is provided for safe operation of civil and aviation pipes.

The invention relates to the technical field of data processing and logistics management, and discloses a cross-border e-commerce logistics order analysis and management system based on big data, and the system comprises a data obtaining module which is used for calculating and forming real-time state data; the potential energy calculation module is used for quantifying the state data into a regional logistics potential energy value; the risk identification module is used for monitoring the potential energy value change to identify a potential risk area; the risk matching module is used for comparing the current risk feature with a preset historical interrupt event feature fingerprint; and the strategy generation module is used for generating a self-adaptive intervention strategy accordingly. According to the method, the potential energy field model and the fingerprint database are constructed, so that the logistics risk is pre-judged in advance and accurately determined, invalid distribution caused by traffic control can be effectively avoided, the decision-making efficiency is improved, the customer recognition degree is guaranteed by generating an intervention strategy, and the analysis and management level of cross-border e-commerce logistics is systematically improved.

1. The name of the design product: traffic signal. 2. The use of the design product: used for municipal road traffic control, maintaining traffic order and improving traffic efficiency. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

An artificially intelligent air traffic control system is provided. The system can include an artificially intelligent (AI) sensor configured to detect and remotely communicate with one or more flying vehicles and an AI local server communicatively coupled to the AI sensor. The artificially intelligent local server can send control instructions including authorization for the one or more flying vehicles to fly in an airspace and a flight path to fly through the airspace. The system can also include an AI cloud server communicatively coupled to the AI local server. The AI cloud server can receive data from the AI local server and the AI sensor associated with the one or more flying vehicles. The AI local server can send the authorization and the flight path to the one or more flying vehicles via the AI sensor based on the received data stored on the AI cloud server.

The present disclosure relates to systems, methods, and apparatus for improving aircraft traffic control. An example apparatus includes: a network interface for obtaining air route traffic (ART) data associated with aircraft flying in an airspace segment during a first time period; a database controller for generating a first database entry by mapping an extracted portion of the ART data to a first database entry field of the first database entry; and an ART segment service for executing a machine learning (ML) model using the database entry to generate a first aircraft traffic count for the airspace segment during the first time period, executing the first ML model to generate a second aircraft traffic count for a second time period in response to selecting a first ML model from the ML models based on the first aircraft traffic count, and sending the second aircraft traffic count to a computing device to enable aircraft flight plan adjustments.

An artificially intelligent air traffic control system is provided. The system can include an artificially intelligent (AI) sensor configured to detect and remotely communicate with one or more flying vehicles and an AI local server communicatively coupled to the AI sensor. The artificially intelligent local server can send control instructions including authorization for the one or more flying vehicles to fly in an airspace and a flight path to fly through the airspace. The system can also include an AI cloud server communicatively coupled to the AI local server. The AI cloud server can receive data from the AI local server and the AI sensor associated with the one or more flying vehicles. The AI local server can send the authorization and the flight path to the one or more flying vehicles via the AI sensor based on the received data stored on the AI cloud server.

Methods, devices, and systems for false target detection for airport traffic control are described herein. One device includes a user interface, a memory, and a processor configured to execute executable instructions stored in the memory to receive one or more sensor reports from one or more sensors, aggregate data that corresponds to a particular target from the one or more sensor reports, determine the particular target is a false target responsive to only one of the sensor reports including data that corresponds to the particular target, and display the particular target as a false target on the user interface responsive to determining the particular target is a false target.

The invention relates to the field of multi-robot cooperative scheduling, and discloses a multi-robot cooperative scheduling unmanned underground mechanical garage system and method, and the system comprises a hardware subsystem which comprises a transfer robot, a parking space frame, a vertical elevator, and an entrance and exit junction area; the control system is deployed in the central control server, and the control system comprises a multi-layer dynamic data grid generation module which is used for constructing a discretized data grid corresponding to a garage physical space; and the central data calculation module is used for continuously updating the data of each data layer in the multi-layer dynamic data grid according to the real-time state of the garage. In the regional congestion degree and traffic control layer, the congestion index is calculated according to the density, the speed variance and the dispersion in the movement direction of the transfer robot, and the task gravitation modulation coefficient is generated, so that the tendency of the robot to enter the crowded region is reduced, the adaptive dispersion of the traffic flow is promoted, and the continuity of garage operation is maintained.

A collision avoidance system (CAS) airborne unit onboard an aerial platform of a first priority level includes a navigational module to determine current position of the aerial platform; a communication module to intermittently transmit a localization transmission, and to receive intermittently transmitted localization transmissions from another CAS airborne unit on-board another lower priority level aerial platform; and a processor to calculate, based on the received intermittently transmitted localization transmissions and on a current location, speed and heading of the CAS airborne unit, a collision risk between the aerial platform and the other aerial platform, and to generate one or a plurality of steering commands and cause a transmission of one or a plurality of a steering commands to be performed by the other aerial platform and to cause the steering commands to be transmitted by the communication module to the other CAS airborne unit.

A system for displaying a taxi clearance including a display is configured to display the position of an aircraft during airport taxiing with a first sensor for detecting the location of the aircraft during airport taxiing. The display indicates the position of hold stops and taxi paths at the airport. An input provides taxi instructions into the system. The input may be manually by the pilot or via a transmission from the air traffic control. The taxi instructions are represented on the display as a taxi path on the taxiways with a first hold stop identified on the route. The display indicates the aircraft's proximity to said hold stop.

The utility model discloses a mobile monitoring camera device, which comprises a quadrilateral conical cylinder and a monitoring camera, the monitoring camera is arranged at the top of the quadrilateral conical cylinder, a photovoltaic panel assembly is arranged on the outer wall of the bottom of the quadrilateral conical cylinder, a base is fixedly arranged on the outer wall of the bottom of the quadrilateral conical cylinder, and a camera is arranged on the base. A storage battery is installed in the base, and the photovoltaic panel assembly is connected with the storage battery through an inverter. The quadrilateral conical cylinder serves as a warning mark carrier and a camera supporting platform, cable laying is omitted, the limitation that traditional monitoring equipment depends on a fixed power source and a foundation is broken through, the device can be rapidly deployed to complex temporary road conditions, and the device is particularly suitable for traffic control, emergency disaster relief and other scenes needing rapid response. Visual deterrent force is formed through cooperation of the quadrilateral conical barrel and the camera, and passing vehicles or pedestrians are effectively reminded to go out safely in combination with the high-definition video recording and infrared night vision functions of the camera.

The utility model relates to traffic control's hydraulic lift column technical field, concretely relates to a traffic control's hydraulic lift column, through traffic control's hydraulic lift column still include the counterweight of lifting assembly, and the square hole is established on the upper surface of counterweight, square hole inner wall four corners all swing and connect with the connecting column side surface, the lifting hydraulic column output is fixedly connected with the connecting plate upper surface center, the lifting hydraulic column end fixedly connected with the top plate, the connecting column bottom fixedly connected with the mounting panel, the mounting panel lower surface fixedly connected with the universal wheel, obtain traffic control's hydraulic lift column when the hydraulic column telescopic, through the connecting plate drive connecting column and bottom mounting panel lift, realize the retraction of universal wheel, avoid the structure of lock piece possibly because outdoor environment leads to lockout malfunction, make the device fast switching between the moving state and the working state, realized the effect of the beneficial effect of obviously improving the response speed of traffic control and the deployment flexibility and the service life of mobile component.