1013 results about "Speedometer" patented technology

The invention discloses a wireless control method for LED illumination, a dimming device, a medium and a product, and relates to the technical field of electric illumination, and the method comprises the steps: obtaining tunnel illumination control parameters; dividing the tunnel entrance area into an entrance section, a buffer section and a basic section according to the tunnel parameters, and determining a plurality of illumination control subareas; calculating the brightness adaptation time of a vehicle driver based on the external brightness value and the vehicle passing speed, and generating an illumination gradient curve from the entrance section to the buffer section and the basic section; according to the illumination gradient curve, determining a target illumination value of each illumination control zone; converting the target illumination value into an LED driving parameter, and issuing the LED driving parameter to an LED driving circuit of each illumination control subarea; and collecting actual illumination data of each illumination control subarea, and regenerating an illumination gradient curve when the actual illumination data exceeds a preset target range or the external brightness value changes. By implementing the method, tunnel illumination can be adjusted based on illumination changes when the weather changes drastically, and driving safety is guaranteed.

The invention provides a PID (Proportion Integration Differentiation) control method for an AGV (Automatic Guided Vehicle) wheel type driving system. The method comprises the following steps: acquiring a first parameter of an AGV; filtering the first parameter, and correcting error data in the first parameter to obtain a second parameter; setting a preset speed function based on a system error model of the AGV wheel type driving system and the second parameter, enabling the AGV to operate according to the preset speed function, and combining the error model to obtain a driving gain coefficient, a friction coefficient and a speedometer gain coefficient; substituting the plurality of coefficients into the fitness function, and carrying out optimal solution solving through a preset optimization algorithm to obtain an optimal solution; verifying the optimal solution to obtain an evaluation value, and when the evaluation value is smaller than a preset threshold value, outputting a target parameter corresponding to the optimal solution; and substituting the target parameters into an AGV wheel type driving system, and controlling a chassis motor servo driving device to cooperatively complete a specified action based on the control instruction. According to the invention, the adaptive capability of the AGV to various environments is improved.

The invention relates to a task-driven unmanned aerial vehicle autonomous search method. The method comprises the following steps: acquiring an unmanned aerial vehicle speedometer by using a binocular RGB image and IMU data acquired by an unmanned aerial vehicle; obtaining three-dimensional point cloud data under a world coordinate system by using a depth map obtained by the unmanned aerial vehicle and an unmanned aerial vehicle speedometer, and establishing a probability voxel map through voxelization processing; performing target detection on the binocular RGB image by using a target detection network, and obtaining a target pose; establishing and updating a task scene map by using the target with the detection confidence exceeding the confidence upper limit and the probability voxel map; establishing a space boundary and a potential target boundary; establishing a search strategy of the unmanned aerial vehicle by using the space boundary and the potential target boundary, and determining a search viewpoint; and performing autonomous safety navigation of the unmanned aerial vehicle by using an unmanned aerial vehicle speedometer and a search viewpoint. According to the method, the problems of completely exploring a task space and simultaneously detecting a task target at high precision in a communication denial and unfamiliar and unknown scene are solved.

The invention discloses a rapid measurement method and system for geometric irregularity of a track in a turnout zone. The method comprises the steps that complete three-dimensional point cloud data of the surface of a railway turnout steel rail are obtained in real time through a multi-angle line structure laser scanner on a special detection vehicle body; accurate attitude and position data of the detected vehicle body in the measurement process are obtained in real time through an inertial navigation measurement unit and an odometer; obtaining a high-precision pose of a detected vehicle body through a robust dead reckoning method of an IMU (Inertial Measurement Unit) assisted by a speedometer dynamic lever arm value based on a variable wheel-rail contact point; constructing a turnout area three-dimensional point cloud model; extracting geometric irregularity key points of turnout steel rail point cloud from the turnout area three-dimensional point cloud model; calculating parameters of track gauge, horizontal and rail direction irregularity and unevenness; the special detection vehicle body can quickly and stably pass through a turnout area to complete continuous and accurate measurement of geometric irregularity of a track.

The invention provides a multi-path main road signal cooperative control method considering speed fluctuation, and the method comprises the steps: firstly collecting traffic data, including road network geometric data, traffic flow data and signal control data, and determining a plurality of main paths according to the traffic flow data; then, based on the running speed of each vehicle on each main path, the vehicle running average speed and the speed fluctuation quantity on each main path are calculated; and finally, constructing a signal control optimization model: constructing a target function by taking weighted green wave bandwidth maximization of all paths as a target, adding a loop integer constraint, an interference constraint, a speed fluctuation space-time constraint, a highest speed fluctuation constraint and a lowest speed fluctuation constraint, solving the signal control optimization model, and obtaining an optimized signal period and green wave bandwidth. And outputting the optimized signal timing strategy. The signal timing generated by the method has a good prospect in the aspect of reducing travel delay and parking times, and a better multi-path collaborative effect can be realized.

The invention discloses a LiDAR-IMU coupling speedometer method and system, electronic equipment and a vehicle, and belongs to the technical field of high-precision positioning and high-reliability positioning, IMU sampling data and LiDAR sampling data are acquired, IMU predicted pose data are generated, fuzzy processing is performed on the predicted pose data through a fuzzy information processing means, and the positioning precision of the vehicle is improved. And taking the pose transformation data as an initial pose estimation value of LiDAR point cloud registration, obtaining a state observation value at the moment n through LiDAR point cloud registration iterative calculation, and fusing the pose transformation data and the state observation value to form the LiDAR-IMU coupling odometer. According to the method, the pose change ratio and the pose estimation variance are generated in combination with the fuzzy processor, the LIO odometer is formed based on the LiDAR point cloud registration technology of the feature points and the EKF fusion technology, and compared with the prior art, the accuracy and the real-time performance of the LIO odometer are remarkably improved.

The invention provides a quad-rotor unmanned aerial vehicle trajectory tracking control method and device, equipment and a storage medium, and belongs to the technical field of unmanned aerial vehicle control, and the method comprises the steps: determining a translation system state variable and an attitude system state variable of an unmanned aerial vehicle based on the real-time trajectory data of the quad-rotor unmanned aerial vehicle; calculating a translation disturbance estimated value based on the translation system state variable, the disturbance observer constant and the expected speed; thrust data is determined based on the translation system state variable, the translation disturbance estimated value, the expected speed, the expected position and outer ring controller parameters of the unmanned aerial vehicle; determining a desired attitude angle based on the thrust data and the desired yaw angle; calculating a control moment based on the expected attitude angle, the attitude system state variable and an inner ring controller parameter of the unmanned aerial vehicle; and based on the thrust data, the control torque and the physical parameters of the unmanned aerial vehicle, calculating to obtain a rotor expected rotating speed, and controlling the unmanned aerial vehicle based on the rotor expected rotating speed. The accuracy of flight control of the unmanned aerial vehicle can be improved.

The invention discloses a multi-signal fusion yaw velocity credibility calculation method and electronic equipment. The method includes calculating a first yaw velocity based on a vehicle model; calculating a second yaw velocity based on the lateral acceleration; calculating a third yaw velocity based on the geometric constraint of the wheel speed difference; determining whether a credibility updating condition is satisfied; and if yes, determining the credibility of the actually measured yaw velocity of the sensor according to the first yaw velocity, the second yaw velocity, the third yaw velocity and the actually measured yaw velocity of the sensor. Multi-dimensional signals such as the wheel speed, the steering angle and the acceleration are fused, and fault tolerance is improved. And through threshold screening and weighted fusion, noise and sudden change interference are suppressed. And front wheel calculation can be switched when a rear wheel breaks down, so that the system continuity is guaranteed.

System and method for monitoring vehicular traffic on a bridge, including receiving digital data representing the response of the bridge to a traffic event, where the digital data has been collected during the traffic event, from displacement sensors and accelerometers mounted on the superstructure of the bridge, wherein the digital data from the displacement sensors embody bending responses of the bridge, the digital data from the accelerometers embody acceleration responses of the bridge, and the digital data from the sensor are synchronised in the same time space, providing a parametric model which uses modal parameters to simulate generalized boundary conditions and two-dimensional behaviour of the bridge; using the parametric model to process the digital data to solve for deformation of the bridge and characteristics of the vehicle traffic, and generating an output that describes the deformation of the bridge and characteristics of the vehicle traffic.

The invention provides a train attitude precision keeping method and system based on inertial quaternion modeling, and belongs to the technical field of train operation positioning. Through a quaternion modeling train attitude feedback compensation model, auxiliary calibration of a gyroscope is realized by using an accelerometer, and calculation of an inertial attitude is realized; converting the acquired wheel speed sensor information into three-dimensional speed under a navigation coordinate system through attitude information resolved by a quaternion modeling train attitude feedback compensation model, and further integrating to obtain a position; and fusing the speed and position information of the wheel speed sensor after attitude conversion with the speed and position information obtained by inertial navigation dead reckoning to realize error correction of the inertial navigation system. According to the method, the problem that the train state sensing precision is degraded due to the fact that a satellite navigation / inertial navigation system positioning model is difficult to overcome inertial device error accumulation when a satellite fails is solved, the train attitude precision is kept, and then error divergence of a combined positioning system during satellite signal denial is effectively restrained.

A system (1) for efficiently determining a driving behaviour of a driver driving a vehicle. The system includes a 3-axis accelerometer (2) generating accelerometer data (3), a direction sensor (4) generating direction data (5) and orientation sensor (6) generating orientation and angular velocity data (7), all placed inside the vehicle. The system (1) also includes a processing unit (8) which processes the accelerometer data (3), the direction data (5) and the orientation data (7), and calibrates the accelerometer data (3) to generate a calibrated accelerometer data (9). The calibrated accelerometer data (9) is used in determining the driving behaviour of the driver of the vehicle and generate Driving Deficiency Alerts, including but not limited to Over-speeding. Hard acceleration. Sudden Braking, Fast Cornering, Quick Lane Changing, Distracted Driving, Dangerous Driving over bumps and Crash Detection.

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 road condition early warning method and system based on an automobile data recorder, and relates to the technical field of road condition early warning, and the method comprises the steps: starting a vehicle, recording the driving road condition through the automobile data recorder, collecting the driving speed of the vehicle, and detecting the recorded video data to recognize road condition obstacles; the actual distance and speed of an obstacle are calculated based on the recognized road condition obstacle, the movement track of the obstacle is predicted, and the dynamic TTC is calculated through the predicted movement track of the obstacle in combination with the vehicle running speed. According to the method, the motion state vector of the obstacle is constructed, and the attention mechanism and the LSTM model are combined to predict the trajectory and calculate the dynamic TTC value, so that the future position and relative trend of the obstacle can be accurately judged, the potential collision risk can be recognized in advance and graded early warning can be realized, and the accuracy of road condition early warning can be effectively improved.

The invention provides an omni-directional all-drive robot trajectory tracking method based on constraint simplification, and belongs to the technical field of ground wheel type mobile robot trajectory tracking. According to the method, a robot kinematic model is established on the basis of rigid body dynamics, the transformation relation between each set of wheel speed vectors and robot speed information in a world coordinate system is represented, and multiple sets of hard constraint problems caused by motor physical characteristics are converted into soft constraint or unconstrained problems in a target function. And the program running speed and the solving success rate are improved. In addition, tracking errors caused by mechanical friction and noise interference are compensated for on the control outermost ring based on high-frequency speedometer information, and it is ensured that the robot accurately executes according to a control instruction. Through experimental verification, the solving speed of each frame of the method is within 50ms, and the tracking error evaluation of a reference trajectory is controlled within 5cm.

The invention relates to a non-inductive FOC open-loop to closed-loop switching method and device for an electronic water pump and a vehicle. The method comprises the steps that a rotor is pre-positioned; starting an open loop I-F; switching condition judgment; estimating the rotor speed based on an observer, calculating a normalization factor, and obtaining a mixed scale factor through cubic polynomial operation; acquiring an open-loop current instruction of a q axis and a closed-loop current instruction output by a closed-loop speed PI regulator; performing weighted synthesis on the two paths of current instructions according to the mixing scale factor to obtain a temporary target current instruction, and applying a change rate limit to obtain a final current instruction output in the current period; the original angle error of the observer estimation angle and the open-loop slope angle is calculated and normalized, the allowable adjustment step length and direction of the round are dynamically determined, and the angle correction amount of the round is generated and superposed to the open-loop slope angle to update the rotor angle reference value; and closed-loop switching is completed. According to the invention, the problems of electromagnetic torque impact and rotating speed fluctuation caused by instruction step change are solved.

The invention provides a speedometer sideslip online compensation integrated navigation method based on FPGA (Field Programmable Gate Array) hardware acceleration. Relates to the technical field of train navigation positioning. According to the SINS / DR integrated navigation system, an IMU inertial measurement unit is integrated in an SINS inertial navigation module and specifically comprises a three-axis gyroscope and a three-axis accelerometer, in SINS / DR integrated navigation, mapping from sensor data of the gyroscope, the accelerometer, an odometer and the like to a slip mode is achieved by adopting a Sheng differential equation model, and the SINS / DR integrated navigation system is obtained. Two speedometers are installed on non-steering wheels on the two sides respectively, a speedometer speed error model is established to compensate and correct the actual speed, and acceleration of a Kalman filtering algorithm is achieved through an FPGA.

The invention relates to the field of automatic driving, in particular to a laser radar and IMU fusion-based unmanned mine car pose calculation method, which comprises the following steps of: calculating an estimated pose of an unmanned mine car based on point cloud data; acquiring sensor data of an IMU and a speedometer; generating map information based on the point cloud data and the sensor data; calculating the zero deviation of the gyroscope according to the zero deviation estimation target function of the gyroscope, and correcting the data of the sensor; based on a sliding window, solving a predefined cost function, and optimizing the estimated pose and the corrected sensor data to obtain an optimized state vector; carrying out closed-loop detection; and when a closed loop appears, correcting all the optimized state vectors by solving a preset error function according to the optimized state vectors to obtain the real pose of the unmanned mine car. According to the invention, the limitation of single laser radar positioning in a feature-deficient or repetitive environment can be overcome, and the positioning accuracy is improved.

The invention discloses a speedometer design method, system and equipment based on fusion of a wheel speed meter and an IMU (Inertial Measurement Unit). The method comprises the following steps: acquiring a plurality of data measured by an inertial measurement unit, and acquiring an attitude rotation matrix obtained by sequentially rotating a coordinate system b in the inertial measurement unit according to the directions of a Z axis, an X axis and a Y axis; determining a state space model of the odometer; constructing a speed observation model of the wheel speed meter based on the state space model; calculating a first error state of the speed observation model, and determining an observation matrix of the wheel speed meter according to the first error state; inputting a plurality of data measured by the inertial measurement unit into the state space model to obtain a predicted value output by the state space model; and calculating a second error state of the state space model, and determining the state of the odometer based on the state space model, the second error state, the predicted value and the observation matrix of the wheel speed meter. According to the invention, the accuracy and stability of track plotting can be improved.

A hydrogen gas filling device includes a reception circuit, a difference calculation circuit, a filling speed calculation circuit, an accumulator, and a filing machine. The reception circuit is configured to receive, from a vehicle equipped with a tank to be filled with hydrogen gas and powered by the hydrogen gas, a value of a parameter of the vehicle. The difference calculation circuit is configured to calculate a difference between a predetermined value and the value of the parameter received from the vehicle. The filling speed calculation circuit is configured to calculate a filling speed of the hydrogen gas depending on the difference. The accumulator is configured to accumulate hydrogen gas. The filling machine is configured to fill the tank with the hydrogen gas from the accumulator at the calculated filling speed. A hydrogen gas filling method includes the operations noted above.

The invention provides a lane lighting method based on vehicle visual perception, a storage medium and a system. The method comprises the following steps: analyzing a road image collected by a vehicle front-view camera; when the lane type in front of the vehicle is identified as a curve, determining the position of a center line of a curve entrance; an initial illumination angle is calculated according to the road curvature and the current illumination angle of the headlamp, and the transverse offset of the vehicle in the lane is calculated according to the position of the center line and the real-time position of the vehicle; and calculating an angle adjustment coefficient of the headlamp according to the transverse offset and the vehicle speed, adjusting the initial illumination angle according to the angle adjustment coefficient to obtain a target illumination angle, and controlling the headlamp to illuminate according to the target illumination angle. According to the method, the illumination angle of the headlamp in the curve scene is accurately adjusted, so that a driver can clearly see the curve boundary at night, the driver is assisted in judging the distance between the vehicle and the curve boundary, and the driving safety is improved.

The present application provides a vehicle cruise control method and system, a medium, an electronic device, and in-vehicle infotainment. The vehicle cruise control method comprises: calculating a speed deviation on the basis of a preset speed of a vehicle and an ego-vehicle speed; on the basis of a speed deviation range where the speed deviation is located, selecting variable control parameters, and performing segmented control on a requested acceleration, wherein the speed deviation range is a range obtained by division on the basis of the magnitude of speed deviation, and includes a negative large deviation zone, a negative small deviation zone, a positive small deviation zone, and a positive large deviation zone; and calculating a PID control quantity of vehicle cruise control on the basis of the variable control parameters and the speed deviation. The present application can improve the control precision of cruise control, and reduce the speed fluctuation generated in the control process.

The embodiment of the invention provides a traffic signal-based vehicle path planning method and related equipment, and belongs to the technical field of automatic driving. The method comprises the following steps: acquiring traffic light data of each intersection of a target driving path; according to the green light time interval of the traffic light data, time constraint calculation of multi-intersection continuous passing is carried out, and a time constraint of continuous green wave passing is obtained; performing speed calculation on each road section according to the time constraint to obtain a speed interval of each road section; performing quadratic programming on the speed interval by taking the energy consumption and the driving time as optimization objectives to obtain a global speed sequence; and performing multi-dimensional constraint and multi-target optimization on a speed controller of the vehicle according to the global speed sequence so as to control the vehicle to run on the target running path. According to the embodiment of the invention, the vehicle can be guided to realize continuous green light passing, and the driving efficiency and the driving comfort are improved while the driving energy consumption of the vehicle is reduced.

The invention discloses an automatic driving vehicle control method and device and an automatic driving vehicle, and belongs to the field of automatic driving. The control method comprises the following steps: after acquiring vehicle information and a non-driving track of a target vehicle and acquiring road information and system delay time, firstly determining a target obstacle based on the size of the vehicle and the non-driving track, and calculating a relative distance based on motion information of the target obstacle; the minimum braking distance of the target vehicle is calculated based on the road information, the system delay time and the vehicle speed, when the relative distance is smaller than or equal to the minimum braking distance, it is indicated that the collision risk exists, and therefore the target vehicle needs to be controlled according to a preset control strategy. According to the scheme, the minimum braking distance is calculated from multiple dimensions, when to conduct braking control can be accurately judged in combination with the relative distance, and driving safety of the automatic driving vehicle in complex environments such as mines can be ensured.

The present disclosure provides a camera calibration method based on vehicle localization, mainly considering that a vehicle is not of an ideal rigid structure, and shaking of a vehicle body during operation, uneven road surfaces, or different loads will cause variations in extrinsic parameters of a camera system, resulting in perceptual information errors. Therefore, through perceptual information from a fused image, an inertial measurement unit, a speedometer, and the like, combined with the road and marking information provided by a high-definition map, the relative motion between the vehicle body and a vehicle chassis is simultaneously described with a mass-spring-damper model, so as to complete the determination of six-degree-of-freedom positions of the vehicle body and the vehicle chassis, and finally the extrinsic parameters of cameras are immediately calibrated with the vehicle chassis as reference coordinates.

The invention provides a monorail crane rail deformation monitoring method based on an inertia measurement technology, and belongs to the technical field of coal mine underground rail monitoring. According to the technical scheme, the method comprises the following steps: S1, deploying a plurality of IMU modules at equal intervals in the extension direction of a monorail crane track; s2, collecting initial IMU data of each IMU module and a monorail crane operation speed signal; s3, resolving initial spatial position data of the track, and generating an undeformed monorail crane track reference value; s4, in the coal mine transportation process, current IMU data and speedometer speed signals of all IMU modules are collected regularly in real time; s5, calculating the current spatial position data of the track; s6, calculating a displacement difference value and an attitude angle deviation of each measuring point; and S7, determining that the region is a monorail crane track deformation point. The system has the beneficial effects that high-resolution real-time monitoring is realized through high-frequency data acquisition and multi-sensor fusion, the external interference resistance is high, and a deformation area can be accurately positioned without interrupting operation.

The invention discloses a track non-contact intelligent detection system and method based on multi-source data fusion, relates to the technical field of track detection, and aims at efficiently completing track detection with low cost. The system comprises a frame body, a plurality of line structured light 3D cameras, a synchronous controller, a processing computer and a speedometer; the linear structured light 3D cameras are arranged on the two sides of the frame body, and the optical axes of the linear structured light 3D cameras are arranged to be perpendicular to the axis direction of the steel rail to be measured; the synchronous controller, the processing computer and the speedometer are integrated at the bottom of the frame body, and the synchronous controller and the speedometer are respectively connected with the structured light 3D camera through cables.

The invention provides a semi-active suspension control method and device, a storage medium and an electronic device.The method comprises the steps that the road surface feature elevation of a road surface abnormal object of a vehicle in the driving direction is recognized, and the driving speed of the vehicle in the driving direction is detected; calculating a front wheel shock-absorbing opportunity of the vehicle for the road surface abnormal object according to the driving speed, and calculating a shock-absorbing damping coefficient of the vehicle for the road surface abnormal object according to the driving speed and the road surface feature elevation; determining that the front wheels of the vehicle enter a shock absorption control state when the front wheel shock absorption time arrives, and controlling a shock absorber of a front axle suspension of the vehicle based on the shock absorption damping coefficient; judging whether the front wheel is switched from the damping control state to the aftershock control state or not; if the front wheels are switched to the aftershock control state, the aftershock elimination damping coefficient of the vehicle for the road surface abnormal object is calculated according to the running speed, and a shock absorber of a front axle suspension of the vehicle is controlled based on the aftershock elimination damping coefficient; and the driving safety and stability of the vehicle are improved.

The invention discloses an ultrathin electronic glass roller way speed measurement support and a speed measurement method, and the support comprises a support which is connected to a mounting disc for fixing a supporting roller through a bolt, the support is fixedly provided with an encoder, a detection shaft of the encoder is connected with a connecting disc through a coupler, the connecting disc is clamped at the end part of the supporting roller, and a signal of the coupler is connected with a speedometer. And a driving control system and an alarm of the supporting roller are connected through a linear speed meter. The effect of improving the roller way rotating speed detection precision and frequency is achieved.

A visual front alert system attached to an inside surface of a vehicle windshield for instructing observers as to movement of the vehicle. A strip shaped body incorporates a plurality of illuminating elements communicating with a PCBA. An accelerometer is connected to the PCBA, with a power supply operating the accelerometer and PCBA. In response to a determined acceleration of the structure, the accelerometer inputs a signal to the PCBA, representative of the vehicle movement, with the PCB in turn providing an output signal causing the illuminating elements to generate a visual output corresponding to said input signal. The visual output further includes a first output representative of a steady or accelerating motion of the vehicle and a second output further representative of a decelerating or braking condition of the vehicle. An ambient light sensor associated with the processor component manages an intensity of the illuminating elements based upon ambient lighting conditions

The invention relates to a collision early warning method and system adaptive to dynamic collision time, a vehicle and a medium, and the method comprises the steps: S1, obtaining the position and state information of the vehicle, transmitting the position and state information of the vehicle to other surrounding vehicles, and receiving the position and state information of other vehicles transmitted by other surrounding vehicles or roadside equipment; s2, according to the position and state information of the vehicle and the position and state information of other surrounding vehicles, the position relation of all the vehicles is obtained; s3, calculating a current collision time threshold value of the vehicle and other surrounding vehicles according to the speed of the current vehicle; and S4, according to the position and state information of each vehicle and the corresponding current collision time threshold, judging whether the two vehicles have a collision risk or not, if the collision risk exists, sending out early warning information, and if the collision risk does not exist, not sending out the early warning information. According to the method, the actual distance can be controlled more accurately during early warning, and early warning is given to the vehicle in advance when the collision risk is predicted.