964 results about "Speed measurement" patented technology

The invention discloses an indoor water tank sediment starting speed measurement system and method, and aims to solve the technical problem that data accuracy is affected due to the fact that a sensor disturbs a flow field in an existing measurement method. The core of the technical scheme is that the non-contact measurement characteristic of the PIV technology is applied to the whole process from flow field construction to data acquisition. The device is mainly composed of an imaging unit, a laser lighting unit, a movable sliding frame, a water flow adjusting unit and a buffer plate. Optical measurement is carried out through the imaging unit and the laser illumination unit, a physical sensor does not need to be arranged in a flow field, and interference of a measuring instrument on a water flow structure and a sediment starting process is fundamentally avoided. The movable sliding frame which is integrally designed integrates the functions of sediment laying, particle throwing and measuring, so that a test area can be quickly positioned; and the buffer plate and the water inlet and drainage adjusting unit are combined, so that a gradually-changed flow field from weak to strong can be accurately and stably simulated.

The invention belongs to the technical field of intelligent traffic, and discloses a road vehicle speed and distance detection method, system and device based on unmanned aerial vehicle vision. The method comprises the steps of tracking a vehicle in a to-be-processed video aerially photographed by an unmanned aerial vehicle in real time through an improved YOLOv11 network and a BotSort algorithm to obtain a vehicle trajectory, and converting a vehicle pixel coordinate detected by each frame into a world coordinate in combination with a conversion matrix H of the pixel coordinate and the world coordinate to form a trajectory sequence of the vehicle in the world coordinate system; and for a certain vehicle i, according to the pixel coordinates at the t-th moment and the (t + t)-th moment in several continuous video frames, corresponding world coordinates are obtained through the conversion matrix H, the displacement between two points is calculated according to an Euclidean distance formula, and the average speed of the vehicle in the time period is calculated. According to the invention, efficient, stable and reliable vehicle speed measurement and vehicle distance calculation can be realized.

The invention relates to the field of meteorological detection and analysis, and discloses a low-altitude complex wind field detection and inversion method based on a vehicle-mounted laser radar, and the method comprises the steps: determining a scanning point location based on the terrain, building distribution and simulation data; optimizing the driving path of the vehicle-mounted radar to cover the high-risk area; acquiring three-dimensional wind field data by adopting an RHI and PPI multi-mode scanning strategy; the influence of vehicle-mounted movement on speed measurement is corrected; calculating turbulence intensity and vortex nucleus position by using spectral width characteristics; and identifying the wind shear position and strength through a slope algorithm. According to the invention, low-cost and high-precision wind field detection is realized through maneuvering deployment and multi-mode cooperation, and reliable technical support is provided for safe flight of the unmanned aerial vehicle, low-altitude traffic management and meteorological early warning.

The invention relates to the technical field of video water flow velocity detection, and discloses a river video velocity measurement method and device based on a multi-feature fusion PSA-ResNet network, and a medium. The method comprises the following steps: constructing an STIA data set; extracting low-level textural features of the space-time image by using a CLBP multi-feature extraction algorithm, performing channel-level fusion on a feature map and an original RGB image to form a six-channel CLBP-STIA feature map, and constructing a CLBP-STIA data set according to the six-channel CLBP-STIA feature map; fusing a pyramid segmentation attention module PSA in a residual block of the residual network ResNet to construct an angle classification model, and training the model by using a CLBP-STIA data set; generating enhanced feature representation of the to-be-detected space-time image by referring to the above mode, then inputting the enhanced feature representation to the trained classification model, and outputting a corresponding texture principal direction angle; and acquiring the actual length of the velocity measurement line in the video image, and calculating the actual flow velocity of the surface flow feature on the velocity measurement line in combination with the texture main direction angle. The texture main direction is accurately estimated, so that the speed measurement precision and efficiency are improved.

The invention discloses a method for calculating a vehicle speed based on a moving unmanned aerial vehicle video, and belongs to the technical field of vehicle speed calculation methods through videos, and the method comprises the steps: extracting global feature points of a video frame through employing an SIFT operator, calculating a homography matrix H through combining with an RANSAC algorithm, projecting a previous frame image to a current frame, and carrying out the calculation of the current frame image; the method effectively eliminates the interference of the motion (such as flight attitude change and displacement) of the unmanned aerial vehicle on the vehicle speed calculation, solves the problem of speed measurement failure caused by the deviation of the motion directions of the unmanned aerial vehicle and the vehicle in the traditional method, enables the algorithm to be suitable for complex scenes such as curves and multi-angle flight of the unmanned aerial vehicle, improves the adaptability of the system in a dynamic environment, and improves the reliability of the system. According to the method, the YOLOv5-1 model is combined with the DeepSORT algorithm, high-precision detection and stable tracking of the vehicle are achieved, even under the complex conditions that the vehicle is partially shielded, illumination changes and the like, continuous detection frame association can still be kept, and reliable time sequence data support is provided for vehicle displacement calculation.

The invention discloses a cascading filtering positioning method and device in a complex and severe environment of a well mine and a medium, and achieves a high-precision positioning function of a well mine unmanned vehicle based on a cascading filtering method. According to the method, the IMU, the wheel speed and the wheel rotation angle are subjected to data fusion through adaptive Kalman filtering, the influence of non-Gaussian noise on wheel speed measurement is reduced through non-Gaussian noise feature extraction, and robust prior positioning information is obtained. According to the method, a regular term representing feature degradation is constructed, a laser radar observation model based on a prior map and laser radar data is constructed, and finally, a result of the laser radar observation model and prior positioning information are fused according to the regular term under a regularization Kalman filtering framework to obtain posterior positioning information. The precision and robustness of the method meet the positioning requirements of the mine unmanned vehicle.

The invention relates to a train dormancy awakening method and system based on TACS fusion control, and the method comprises the following steps: before a train is dormant, an AOM stores the position information of the train; in the train dormancy process, the speed measurement positioning board card keeps power supply, the speed measurement positioning module continuously collects speed pulse signals, train position information is calculated, and the train position information obtained through calculation is sent to the AOM; before the train is awakened, the AOM compares the position information obtained from the speed measurement positioning module in real time with the position information stored before dormancy, and whether the train is allowed to be awakened or not is judged based on the comparison result. According to the method, power supply is kept for the speed measurement positioning module during the train sleep period, real-time monitoring of the train position during the sleep period is achieved, meanwhile, through position comparison before wakeup, the wakeup efficiency of the train is improved, and wrong wakeup operation caused by abnormal movement of the train is prevented.

The invention relates to a long-gap discharge leader development speed measurement method based on radiated electromagnetic wave detection. The method comprises a set of high-frequency antennas and a high-speed oscilloscope and a long-gap discharge leader development speed calculating method. The method adopts a certain antenna arrangement form; long-gap discharge radiated electromagnetic wave pulse time is detected simultaneously through the plurality of antennas; leader head position is positioned according to time difference of a signal arriving at different antennas; and furthermore, the long-gap discharge leader development speed can be calculated. The method can effectively improve the measurement precision of the discharge leader development speed, and resolution reaches the level of 0.1 ns.

The embodiment of the invention discloses a real-time tennis ball speed calculation method and system based on a sliding window, and the method comprises the steps: carrying out the data buffering through employing a 35-frame first-in first-out buffer region based on a three-dimensional track point, screening effective points, calculating the instantaneous speed according to a Euclidean distance formula and an inter-frame time interval, and obtaining the real-time tennis ball speed. And through a three-frame sliding window average smooth speed curve, abnormal values are filtered by using a 10-220km / h threshold value, and ball speed calculation is realized. Through three-dimensional track points, ball speed calculation is realized through the steps of data buffering, effective point screening, instantaneous speed calculation, sliding window averaging, threshold filtering and the like. Compared with traditional single-point speed measurement, the precision is improved by about 20% by means of three-frame sliding window and three-dimensional coordinate calculation, and single-frame errors are reduced; the robustness in a complex scene is enhanced through data screening, window averaging and threshold filtering; the process is simple, the calculated amount is small, and the real-time requirement of occupational competitions is met; a fixed 35-frame buffer area optimizes resources, and memory redundancy is avoided.

The invention discloses a flow velocity measurement system adopting bubble tracing, and the system comprises a circulation loop which is internally provided with a medium storage tank and a pump body; the air supply branch is connected into the circulation loop and provided with an air storage tank, and the air storage tank is used for supplying air to the circulation loop so that bubbles can be generated in the circulation loop; and the flow velocity measuring device is used for monitoring bubbles in the circulation loop. In conclusion, the flow velocity measurement device obtains the bubble motion information from the outside of the circulation loop, and a speed measurement device such as a sensor does not need to be inserted into the circulation loop, so that disturbance to a medium flow field in the circulation loop is avoided, the measurement is more real and reliable, and the accuracy is higher.

The utility model discloses a device used for detecting parameters of a mowing robot, comprising a workbench and a mowing robot, the workbench is provided with a test platform, the mowing robot is installed on the test platform, the device also comprises three-axis electrical parameter modules, the two sides of the test platform are both provided with the three-axis electrical parameter modules, and the three-axis electrical parameter modules are connected with the test platform. The three-axis electrical parameter module is used for detecting information of a wheel set and a cutter head of the mowing robot. The wheel set information of the mowing robot can be collected through the self-resetting wheel speed measurement module, the cutter information of the mowing robot can be collected through the photoelectric sensor, and the information can be collected through the PCB main control board.

The invention provides an intelligent traffic cone barrel anti-collision early warning method based on binocular vision, and aims to improve the safety of a road construction operation area. And accurate data are provided for subsequent detection and analysis through a binocular camera high-precision calibration technology based on circle detection. In combination with a data acquisition and enhancement technology, high-quality training data is provided for an improved RT-DETR algorithm, and the accuracy and efficiency of vehicle identification are significantly improved. A binocular vision depth perception and StrongSORT multi-target tracking algorithm is utilized to realize real-time speed measurement and distance measurement of a vehicle, and accurate input is provided for track prediction. Based on a GAN multi-modal trajectory prediction technology, a plurality of future trajectories are generated, and a multi-level early warning decision is realized through a comprehensive collision risk index (CRI). According to the method, the limitation of an existing prediction method in a complex road scene is effectively solved, the vehicle behavior intention is predicted and analyzed through the multi-modal trajectory, and reliable early warning information can be provided under various complex road conditions.

The invention discloses a hidden danger pre-diagnosis method of an elevator traction system, relates to the technical field of elevator safety monitoring, and is used for solving the technical problems of poor real-time performance, low accuracy and difficulty in defect positioning of hidden danger diagnosis of the elevator traction system in the prior art. The hidden danger pre-diagnosis method for the elevator traction system comprises the steps that multi-source data are synchronously collected, specifically, a current transformer is deployed in a power supply loop at the input end of an elevator traction motor to collect a three-phase current instantaneous value, a speed measurement encoder is used for measuring the speed, the elevator running state, the speed, the floor position and the time-variable load weight are synchronously obtained, and a time-space correlation data set is constructed; signal self-adaptive preprocessing: performing layered noise reduction, working condition alignment and dynamic normalization processing on the acquired current signals; multi-scale feature fusion extraction: current signal features are extracted from a basic feature layer, a time domain feature layer, a frequency domain and a time-frequency domain feature layer; and feature optimization and decision making: after feature screening and dimension reduction fusion, inputting a pre-training classification model to output hidden danger types, positions and risk levels.

The invention discloses a control method for controlling the follow-up speed change of a drip irrigation disc of a seeder based on Beidou speed measurement. The control method comprises the following steps: S1, collecting and preprocessing position information and speed information of a tractor; s2, inputting the preprocessed data into a fusion calculation unit, and executing space-time weight calibration; s3, inputting the fusion speed sequence into a speed prediction network, extracting multi-scale features, and generating a speed guide feature map; s4, generating a target rotating speed instruction according to the mapping function and operation parameter modulation; s5, inputting a target rotating speed instruction to a motor control unit, and generating a current signal through dual-channel torque regulation and control; s6, a motor is driven to rotate the drip irrigation disc, the actual rotating speed is collected, and an error sequence is constructed; and S7, inputting the error sequence into a calibration module, generating a correction parameter to update a current signal, and realizing synchronous control. According to the invention, high-precision synchronous control of the drip irrigation disc on the speed of the tractor is realized, and the drip irrigation consistency, the response speed and the operation stability are improved.

The invention discloses an automobile long-distance speed recognition and tracking method based on target detection, and the method comprises the steps: collecting a vehicle driving video in real time through a fixed camera position and angle, and carrying out the recognition of a vehicle in each frame of image of the video through a pre-trained YOLOv12 target detection model; performing preliminary speed estimation on the automobile by adopting an inter-frame difference method, further constraining a speed change rate, and performing time sequence correction on the speed change rate by adopting Kalman filtering to obtain a corrected speed estimation value; calculating the displacement and the motion deflection angle of the adjacent frames in the transverse and longitudinal directions, and integrating the displacement and the motion deflection angle with the corrected speed estimation value to form a time sequence input feature; and carrying out modeling on a historical track through the trained time sequence deep learning model to realize dynamic speed correction. According to the method, the dependence on physical space calibration is obviously weakened, the perception capability of the model on the motion trend is improved, and the method is suitable for vehicle tracking and speed measurement tasks in long-distance and low-resolution scenes.

The utility model discloses an auxiliary speed measuring device for a main shaft of a steel cord stranding machine, which relates to the technical field of steel cord production equipment and comprises a transmission case and a mounting frame mounted on the transmission case, an encoder is mounted on the mounting frame, and the transmission case is further provided with an adjusting mechanism for adjusting the mounting position of the encoder. The adjusting mechanism comprises a side plate, a screw rod and a guide groove plate, the side plate is transversely fixed on one side of the top of the transmission case, the guide groove plate is longitudinally fixed on the other side of the top of the transmission case, one end of the guide groove plate is fixedly connected with the side plate, and the screw rod is longitudinally arranged in the guide groove plate. According to the utility model, the speed measurement transmission belt can be conveniently and rapidly installed, the tension degree of the test transmission belt can be adjusted during installation, good contact between the transmission belt and a belt wheel is ensured, and slipping is prevented, so that the transmission efficiency and the stability of a system are maintained, the speed measurement accuracy is ensured, and measurement errors caused by improper tension degree are avoided.

Disclosed are embodiments for determining the position and speed of a projectile in three-dimensional world coordinates using a single camera and radar. In some embodiments, a method comprises: determining a zero radial speed time of the projectile based on radar measurements of the projectile; determining a radial speed of the projectile at a particular time based on the radar measurements; determining a radial speed slope at the particular time based on the radial speed measurements; determining a two-dimensional image point of the projectile at the particular time; determining a depth scale coefficient at the particular time based on the zero radial speed time, the radial speed, the radial speed slope, the image point, and a homographic transformation; and determining a position of the projectile in space at the particular time based on a three-dimensional position of the camera, the depth scale coefficient, the image point and the homographic transformation.

The invention relates to the technical field of vehicle speed measurement, and particularly discloses a vehicle speed measurement method during unmanned aerial vehicle highway inspection based on an unmanned aerial vehicle nest, and the method comprises the steps: enabling the unmanned aerial vehicle nest to receive a task instruction, carrying out the highway inspection based on an inspection path after the unmanned aerial vehicle takes off, carrying out the multi-mode road surface intelligent segmentation, and outputting a binary road surface mask, time-space cooperative vehicle tracking is carried out, a vehicle trajectory data set with a unique ID is obtained, unmanned aerial vehicle RTK positioning data and ground marker coordinates are obtained, a pixel-physical space mapping table is output, millimeter wave radar altimeter data is collected for vehicle speed measurement, and a vehicle speed vector with a timestamp is output. The problems of vehicle missing detection and speed measurement blind areas caused by a traditional speed measurement method are solved, and the problem that efficient and accurate data support cannot be provided for highway management is solved.

The invention relates to a coal flow detection system and a control method thereof, and the system is characterized in that the system specifically comprises the following modules: a weighing detection module, a speed detection module, a temperature compensation module, a data processing module, a communication module, an alarm module, a power management module and a display module; the weighing detection module is connected with a differential input interface of the data processing module through a full-bridge strain circuit; the speed detection module is connected with a timer capture unit of the data processing module through an orthogonal encoder interface; the temperature compensation module is connected with a sensor interface of the data processing module through a digital bus; the data processing module communicates with the communication module and the display module through a high-speed serial interface; the alarm module is connected with the data processing module through an isolated digital output interface. The problem that an existing detection method only depends on single weighing or speed measurement, the actual situation of the coal flow cannot be comprehensively and accurately reflected, and consequently the measurement result error is large is solved.

Disclosed are an internal magnetic control device, a flywheel assembly and a fitness equipment, wherein the flywheel assembly comprises a flywheel, an internal magnetic control device and a speed measuring device, wherein the internal magnetic control device comprises a housing unit, a driving unit, two swing arms and two sets of magnetic elements, wherein the driving unit is arranged at the housing unit; a pivoting end of each of the swing arms is rotatably mounted at the housing unit; a driven end of each of the swing arms is rotatably connected to the driving unit; the two sets of the magnetic elements are respectively arranged at each of the swing arms; wherein the flywheel is rotatably arranged around the internal magnetic control device, wherein the speed measuring device comprises a sensing element and an acting member.

The invention discloses an intelligent detection system and method for the loading state of a railway wagon. The system comprises a frame, a 3D acquisition module, a vehicle number identification module, a speed measurement module, a control center and a data processing module. The frame is erected across two sides of the track; the 3D acquisition module comprises a laser scanning turntable; the laser scanning turntable is arranged on the frame and comprises a base disc, a laser scanning unit and a rotating shaft; the plurality of laser scanning units are mounted on the base disc, are uniformly distributed on the circumference taking the rotating shaft as the center, and are used for acquiring contour information of the surface of the railway wagon body; and the data processing module reconstructs vehicle body surface three-dimensional information according to the contour information, and identifies and obtains the loading state of the railway freight car. The base disc drives the laser scanning unit to rotate around the axis of the rotating shaft, the rotating direction is the same as the advancing direction of the railway wagon, and meanwhile the posture is adjusted in real time, so that the problems of motion blurring, data dislocation, three-dimensional point cloud data oscillation and the like existing when 3D image information of the railway wagon passing at a high speed is scanned and collected are solved.

The invention relates to a manual driving vehicle overspeed behavior identification and intervention method based on a detection carrier, and the method comprises the steps: building a detection carrier system, collecting adjacent HV point cloud data through a laser radar, carrying out the median average filtering, K-Means and DBSCAN combined clustering preprocessing, and achieving the multi-target dynamic tracking through a Point Pill + DeepSORT model; and calculating the real average speed of the HV by using a 1-3s self-adaptive speed measurement window, and comparing the road speed limit to complete the overspeed identification. And when overspeed is judged, dynamically triggering a corresponding high-speed camera to capture, extracting license plate information, fusing speed and GPS data to generate illegal evidence. The method comprises the following steps: quantifying the influence of a detection carrier on an HV individual overspeed behavior, training an HV swarm agent based on VAE-WGAN data enhancement and a double-branch deep Q network, simulating multiple traffic scenes in SUMO, and determining an optimal deployment scheme of the detection carrier by using a dynamic Gaussian mixture Bayesian network and a double-layer double-target optimization model. The method breaks through the limitation of traditional speed measurement, improves the recognition precision and deterrence effect, and balances the traffic safety and efficiency.

The invention provides a speed-measurement-free unmanned ship tracking control method and system based on absolute position sensing. Aiming at the problem that a following boat cannot acquire speed information due to failure of a pilot boat speed sensor or communication failure, a distributed finite time state observer is designed, and the speed of a pilot boat is estimated in real time by combining an absolute position and positioning information. And designing an auxiliary controller by adopting a backstepping method based on the observation speed, and constructing a stability constraint. And a model prediction control framework based on a distributed Lyapunov function is further proposed, so that the multi-unmanned ship system can realize expected formation trajectory tracking and attitude consistency only depending on self-sensing and positioning information, and meanwhile, the formation stability is ensured. According to the method, under the condition that the speed of the pilot ship cannot be obtained, the speed can still be accurately estimated, and the control strategy can be optimized online, so that the intelligent sensing, positioning precision, control performance and robustness of the unmanned ship formation system are remarkably improved.

The invention discloses a high-pressure CO2 oil displacement micro-fluidic chip device which comprises an upper polar plate, a middle partition plate, a lower polar plate, a speed measurement module, a porous medium radial flow module and a liquid outlet module, the speed measurement module is arranged on the upper surface of the middle partition plate; the porous medium radial flow module and the liquid outlet module are arranged on the upper surface of the lower polar plate; the upper polar plate, the middle partition plate and the lower polar plate are sequentially stacked from top to bottom; the speed measurement module is connected with the porous medium radial flow module; and the porous medium radial flow module is connected with the liquid outlet module. According to the device disclosed by the invention, a pore throat structure in rock is simulated by constructing a micron-sized or even smaller complex flow channel, and the CO2 flooding crude oil flow characteristic and the CO2 distribution rule are simulated; a transparent visualization device structure is designed, and visualization of the action mechanism of the CO2 oil displacement system and the reservoir fluid distribution characteristics is guaranteed.

The embodiment of the invention discloses a carrier integrated navigation method, device and equipment and a medium, and relates to the technical field of intelligent driving navigation, the method comprises the following steps: acquiring wheel speed data of a current epoch output by a wheel speed measurement unit, and acquiring inertia measurement data of the current epoch output by an inertia measurement unit; inputting a non-integrity constraint prediction model to obtain a non-integrity constraint component of the current epoch; and constructing a three-dimensional motion constraint observation value based on the non-integrity constraint component and the wheel speed data, performing measurement updating on a kinematics observation equation of the Kalman filter, obtaining a state estimation result obtained by updating, and outputting a positioning result in the current epoch. According to the method, the lateral and vertical velocity components are dynamically predicted through the non-integrity constraint prediction model, the three-dimensional motion constraint observation value is constructed, and the state estimation of the Kalman filter is optimized, so that the problem of carrier motion constraint performance degradation under a complex motion condition can be effectively relieved, and the integrated navigation precision can be further improved.

According to the novel transponder device and the method and device for achieving multiple functions through power line carrier communication, multiple functions such as train positioning and speed measurement, station track occupation recognition, train occupation and integrity check and train-ground communication are achieved through the novel transponder device and the power line carrier communication, and wireless communication technologies such as the power line carrier communication are integrated; the method can be applied to train operation control, train-ground coordination action, locomotive vehicle information management, unmanned stations and train state monitoring in various scenes, can simplify the types of equipment, reduces the construction cost and the maintenance workload, and improves the transportation efficiency and safety at the same time.

The invention provides a speed measurement method based on dynamic zooming of an unmanned aerial vehicle and an inspection system. The method comprises the following steps: acquiring a video stream acquired by the unmanned aerial vehicle in real time through a camera for dynamically adjusting focal length parameters; inputting the video stream into the detection model frame by frame; outputting a target detection frame set of the corresponding current frame; performing cross-frame association on the detection frames of the adjacent frames through a ByteTrack algorithm, and distributing a unique instance identifier for the same target; acquiring real-time parameters of the unmanned aerial vehicle, establishing a real pavement coordinate system and a pixel imaging coordinate system, and performing coordinate system projection mapping; and calculating the real speed of the target. The method has the beneficial effects that the coordinate mapping error is greatly reduced through dynamic parameter fusion and unmanned aerial vehicle displacement compensation, and particularly, the improvement is obvious in a pitch angle or zoom scene; through introduction of central point position transformation, image center offset caused by digital zooming is dynamically calibrated, and pixel-physical coordinate mapping distortion caused by pure image cutting or interpolation amplification is effectively eliminated.

The invention discloses a single-sensing double-blade tip timing vibration speed measurement method, system, medium and equipment, and the method comprises the steps: only installing a blade tip timing sensor in the circumferential direction of a rotor blade case, and obtaining a blade arrival time sequence generated when rotor blades sequentially pass through the blade tip timing sensor; calculating the instantaneous rotating speed of the rotor based on the arrival time intervals of all adjacent rotor blades; the blade tip linear velocity between the two rotor blades is extracted by combining the circumferential included angle and the measuring point radius of any two rotor blades in the blade disc; removing a trend term related to the rotating speed from the blade tip linear velocity to obtain a velocity quantity reflecting the real vibration characteristics of any two rotor blades; a two-degree-of-freedom dynamic model is constructed by combining prior information of a blade Campbell diagram, and double-blade vibration parameter identification is realized by adopting a nonlinear least square fitting method.

The present invention relates to the technical field of rail transit. Disclosed are a railway crossing control system, method and apparatus, and a storage medium. The system comprises: a speed measurement and distance measurement device, which is used for acquiring the real-time speed of a train and the real-time distance from the train to a crossing on the basis of the real-time signal strength and the real-time signal strength change rate of a detection signal; and a central device, which is used for determining a target crossing closure notification position by means of a pre-trained train operation state prediction model on the basis of the real-time speed of the train and the real-time distance from the train to the crossing, generating crossing closure information and sending the crossing closure information to a crossing device, and generating a train movement permission and sending the train movement permission to an onboard device. In the technical solution of the present embodiment, a crossing closure notification position is determined on the basis of the real-time speed of a train and the real-time distance from the train to a crossing, such that a crossing closure occasion can be automatically determined on the basis of the real-time running speed of the train, the distance from the crossing closure notification position to the crossing can be shortened, the crossing closure occasion is delayed, and the transportation efficiency on a railway side and a road side can be improved.

The invention provides a slip rate determination method, a vehicle and a computer readable storage medium, and relates to the technical field of vehicle control, and the method comprises the steps: calculating the wheel speed deviation rate of each wheel, and carrying out the dynamic correction of the measured wheel speed of each wheel based on the wheel speed deviation rate, and calculating the slip rate of each wheel on the basis of the corrected measured wheel speed of each wheel. According to the method, high-precision and independent calculation of the slip rate of each wheel is realized, and the problem of inaccurate slip rate calculation caused by wheel speed measurement errors caused by factors such as inconsistent tire pressure, different wear degrees, mixed use of new and old tires, tire size difference and the like is effectively solved.