556results about How to "Realize judgment" patented technology

The invention discloses a performance prediction and fault alarm method for a photovoltaic power station. The method comprises the following steps of: a, setting the station of the power station; b, setting the operation mode of the power station; c, judging whether required real-time data or historical data exists or not; d, predicting the performance of the power station through an experience model if the state in the step a is that a new photovoltaic power station is required to be designed and the required real-time data or historical data in the step c does not exist, and predicting the performance of the power station through a data drive performance model if the required real-time data or historical data in the step c exists; e, predicting the performance of the power station through the data drive performance model or a polynomial regression model if the photovoltaic power station in the step a is operated and the required real-time data or historical data in the step c exists, and predicting the performance of the power station through the experience model if the required real-time data or historical data in the step c does not exist; f, comparing actual performance with the predicted performance, and performing fault alarm; and g, correcting the models on line by a Kalman filtering method and returning to the step c, and otherwise, directly returning to the step e. By the method, solar energy resources can be utilized to the maximum extent, and power utilization cost can be reduced; and the accuracy of performance prediction and fault diagnosis is improved.

The invention discloses an automatically calibration method based on black and white grid corner matching. The method includes adopting black and white calibrating cloth as a calibrating model, respectively detecting image corners by an improved harris corner detection calculation, building position relations between corners and forming a corner network; performing distortion correction and matching to images; calculating corner position in non-distorting images and homographic matrix of corner real position in final virtual full view bird's-eye view; and performing view changing according to virtual bird's-eye view camera position and homographic matrix, calculating corresponding relation between image points in the coordinate system and the original images, and then forming a lookup table. The automatically calibration method adopting the improved harris corner detection calculation is simple and practical, can well judge corner position relation, and forms a correct corner network; and the automatically calibration method adopting lookup table function can generate output images after the images are calibrated, is fast, and can well meet real-time need.

The invention relates to the technical field of ATM intelligent monitoring systems. A module comprises an input module, a video intelligent monitoring server, a monitoring alarm management module and an output module. A video intelligent analysis system to which the video intelligent monitoring server is related particularly refers to the behaviors of automatically detecting an object, tracking the object, and recognizing and analyzing the object. The video intelligent monitoring server relates to an anomalous event analysis system which is combined with a front camera and an upside camera to monitor anomalous and dubious behaviors of objects round an ATM, and simultaneously obtain face information of a suspect and give an alarm in time when an anomalous situation happens.

The invention discloses an intelligent drive platform for four wheels of a electric automobile, comprising four hub motors, four motor controllers, a power battery and a controller area network (CAN) communication network; further comprising an entire vehicle controller, wherein the four hub motors, the four motor controllers and the entire vehicle controller are all connected with the power battery; and the entire vehicle controller respectively controls the four motor controllers by the CAN communication network. The entire vehicle controller is located at the core of a distribution type control network, collects the information of each sub-controller and transmits the executed commands to each sub-controller for executing. The intelligent drive platform comprehensively considers the hub motor control, the entire vehicle kinetic control, the battery energy management and the instrument display based on the system and utilizes an advanced flexible control algorithm. The invention hasremarkable effects of improving the comfort performance, the maneuverability and the battery continuous driving capability of the electric automobile.

The invention discloses a method based on the topology protection of a distributing network, which comprises the following steps: (1) all distributing automation terminals respectively form a distributing network topology structure, and each distributing automation terminal is linked with adjacent nodes in a lateral communication mode; and (2) whether each switch is an adjacent node is judged based on a line failure criterion; if yes, the network topology protection corresponding to the switch is activated to trip the switch of the node; and otherwise, the network topology protection is not activated, wherein the line failure criterion is as follows: if the switch is not a transformer substation outlet switch and a line overcurrent failure is detected in one and only one of N adjacent nodes, the fact that the switch is a failed adjacent node is judged; and if the switch is a transformer substation outlet switch and a line overcurrent failure is detected in one and only one of N nodes including the transformer substation outlet switch, the fact that the transformer substation outlet switch is a failed adjacent node is judged. The method can rapidly, accurately and selectively position the failure and isolate the failure.

The invention relates to a network message monitoring and fault recording integrated device for an intelligent transformer substation. The device comprises a signal access unit, a signal processing and analyzing unit and an information output unit, wherein the signal access unit is used for receiving comprehensive signals, which contain a primary system signal and a secondary system signal of the intelligent transformer substation and transmitting the comprehensive signals to the signal processing and analyzing unit; the signal processing and analyzing unit is used for analyzing the comprehensive signals of the intelligent transformer substation; and the information output unit is used for outputting the alarm signal-containing comprehensive signal analyzing result after the analysis of the comprehensive signals. The device comprehensively analyzes the comprehensive signals, which contain the primary system signal and the secondary system signal, brings great convenience to operation, maintenance, modulation and breakdown maintenance, shortens the troubleshooting time, improves the power supply quality of the intelligent transformer substation, saves the space occupied by the traditional equipment and saves investment.

The invention relates to a computer-aided reference system and a computer-aided reference method for fusing multimodal mammograms. The method comprises steps: image preprocessing is performed on breast ultrasounography and molybdenum target images of a same patient; the region of interest of ultrasound image and the region of interest of molybdenum target image of breast are obtained by using thepreprocessed ultrasound and molybdenum target images as inputs; the texture and depth features of ROI in breast ultrasound images and mammography are extracted; the extracted GLCM, LBP, HIS texture features and CNN depth features are fused in series to construct texture; a deep fusion feature model is constructed; the texture-Deep fusion feature model is used as input, and a regularization limit learning machine is used to classify the breast masses into benign and malignant ones. The invention uses the regularization limit learning machine to classify the benign and malignant breast masses, realizes the judgment of the nature of the breast masses from the clinical requirements, and provides an objective reference basis for the doctor to diagnose the breast masses.

Provided is an online monitoring method for lubricating oil of a wind-power transmission. The online monitoring method for the lubricating oil of the wind-power transmission comprises the following steps that performance analysis is carried out on a tribology system of a gear case of the wind-power transmission, and a comprehensive information monitoring method which is based on three aspects, namely an abrasion, a lubricating oil physical and chemical performance and pollution is proposed; an integral information monitoring system is established through testable analysis, and viscosity, water and an abrasive grain are adopted to be used as testable characteristics corresponding to the three classes of information of the abrasion, the lubricating oil physical and chemical performance and the pollution; by utilizing the embedded type integral sensor technology, real-time obtaining of the information is achieved; by adopting a TCP / IP network communication protocol, remote monitoring is achieved; a relation model of the abrasion, a lubrication oil product and the pollution are established, and inducements of the abrasion or lubricating malfunctions are speculated. Online perfect information obtaining is achieved, the analysis on origins of malfunctions is provided, the effective monitoring method for a running state of the gear case of the wind-power transmission is achieved, and according to positioning of an abrasive malfunction, an oil replacing suggestion and other maintaining suggestions, the important engineering significance for lowering the triology malfunction and prolonging the complete machine service life is achieved.

The invention provides an alarm system for detecting the abnormal operation of a wind driven generator. A sound acquisition module is disposed on the wind driven generator. The alarm system includes the sound acquisition module, an acoustic signal processing module, a fault diagnosis module, and an early warning module which are successively connected. The early warning module is configured to detect the working state of the wind driven generator. If discovering that the wind driven generator operates abnormally, the early warning module gives an early warning message to remind a maintenance worker to perform maintenance. The alarm system provides a simple, high-efficiency and low-cost noncontact in-position fault diagnosis method for anomaly detection of the wind driven generator, and gives guidelines for the normal operation and maintenance of the wind driven generator.

The invention relates to a testing method for working performance of concrete and an apparatus implementing the same. The testing apparatus comprises a concrete slump tester, a cement mortar fluidity testing jumping table and a circular extending table. In similar testing of the slump of concrete disposed on a large table-board, the jumping table vibrates preset times according to certain frequency and certain vibration amplitude after a slump cylinder is hoisted, which enables the slump and flowing of the concrete to be improved and the concrete to form a circular truncated cone shape with a larger area; the slump H after vibration, the mobile extended diameter D of the concrete, center thickness h1 and edge thickness h2 after vibration are measured, the inclination angle theta of a frustum after slump of the concrete is calculated through conversion, bleeding and the segregation degree of the concrete are observed, and thus, working performance of the concrete can be comprehensively estimated. Compared with the prior art, the invention has the following advantages: working performance of fresh concrete can be conveniently and quickly tested and distinguished, and the method and the apparatus are applicable to a wide variety of concrete.

The invention discloses a camera apparatus. The camera apparatus comprises a camera, a control chip, an infrared optical filter and a communication module. The infrared optical filter is movably arranged at the incident side of the camera, the control chip, when receiving a visible light shooting instruction, controls the infrared optical filter to deviate from an incident port at the incident side of the camera, the camera acquires a visible light image, and the control chip is used for determining whether a monitoring area is at a preset fire risk state; when the monitoring area is at the preset fire risk state, the infrared optical filter shields the incident port at the incident side of the camera; and the control chip, according to a received infrared light image, determines whether the monitoring area is at a preset fire state, and when the monitoring area is at the preset fire state, sends second fire alarm information to a preset monitoring server. The invention also discloses a fire detection alarm system and method. According to the invention, visible light image acquisition and infrared light image acquisition are integrated together, and the cost of the camera apparatus and the cost for arranging the fire detection alarm system based on the camera apparatus are reduced.

The embodiment of the invention discloses a lightweight method and device for a convolutional neural network. The method comprises the steps of obtaining a weight coefficient matrix of each convolution kernel in each convolution layer in the convolution neural network model; setting the weight coefficient value of which the absolute value in the weight coefficient matrix is smaller than a preset threshold value to be zero for any one weight coefficient matrix to obtain a first matrix and a second matrix, wherein the first matrix comprises all non-zero weight coefficients in the weight coefficient matrix, and the second matrix comprises the subscript values of all non-zero weight coefficients of the weight coefficient matrix in the weight coefficient matrix; taking the first matrix and thesecond matrix as the compressed weight coefficient matrixes; and carrying out traffic jam identification on the input image according to the weight coefficient matrix after each convolution kernel ineach convolution layer in the convolution neural network model is compressed.

The invention discloses an identification method for a webpage information related region. The identification method for the webpage information related region includes: 1) establishing a regional information body; 2) extracting metadata information and text of crawled webpage information and dividing the extracted information title and text into words; 3) analyzing geographical name pronouns which express places in the words, judging whether there are reference relationships between the geographical name pronouns and the previous geographical terms, if so, replacing the geographical name pronouns with the corresponding geographical terms; 4) analyzing non-standard geographical name words in the words, and replacing the non-standard words with standard words; 5) analyzing the regional information of the relative position based on the regional information body to acquire an accurate geographical name word; 6) judging the analyzed webpage information based on the regional information body, and classifying the webpage information into a successfully matched region. The identification method for the webpage information related region greatly improves the identification accuracy for the webpage information related region.

The invention relates to a method for determining a gesture moving direction based on a hidden Markov model. The method comprises the following steps of: a, recognizing a human face; b, acquiring a gesture area gray-scale map through multi-threaded fusion; c, updating a gesture moving history map and acquiring a moving energy map according to the gesture area gray-scale map; d, dividing vector horizontal angles; e, acquiring a starting moment and an ending moment of gesture movement through the moving energy map, and splitting the gesture movement; and f, training hidden Markov model parameters, and presuming the gesture moving direction by the forward algorithm and the backward algorithm of the hidden Markov model. By the method for determining the gesture moving direction based on the hidden Markov model, the gesture moving direction of the hidden Markov model is determined by using a plurality of determining conditions, so that the determination accuracy of the gesture movement can be improved, and the interference of various factors in a determination result can be obviously reduced.

The invention discloses an overhead wire icing on-line monitoring device based on machine vision, which is composed of hardware and software, wherein the hardware is divided into a lower computer and an upper computer; the lower computer hardware comprises a controlling and processing unit based on DSP, an image acquisition unit, a data acquisition unit, a data storage unit, a GPRS wireless communication unit and a solar energy photovoltaic light source unit; the upper computer hardware is composed of a monitoring center server unit and a GPRS wireless communication unit; and the upper computer hardware and the lower computer hardware realize wireless communication via a GPRS wireless network. The software is also divided into an upper computer and a lower computer, wherein, the lower computer software is in charge of driving the lower computer hardware to collect images and data, and the lower computer software calculates and judges icing thickness and type according to the collected image; then the GPRS wireless communication unit is driven to send compressed image and monitoring results to the upper computer; the upper computer software is in charge of driving upper computer hardware to finish GRPS wireless communication and realizes human-computer interaction interface and monitoring information management. The invention can monitor icing disasters on all sides.

The invention discloses a method and a device for biometric authentication, and a biometric authentication system. According to the detailed description of the invention, the method comprises the steps of receiving at least two types of biological characteristic signals; respectively extracting the same physiological characteristic out of the at least two types of biological characteristic signals; and processing the physiological characteristic to judge whether the at least two types of biological characteristic signals stem from the same real organism or not. According to the detailed description of the invention, the authenticity of a to-be-authenticated or a to-be-identified organism can be judged. Therefore, the security of an identity authentication system is improved.

The invention discloses a dynamic path planning method for AUV (Autonomous Underwater Vehicle) submarine topography matching, and belongs to the technical field of AUV navigation. The dynamic path planning method comprises environment modeling, offline path planning and online path re-planning. An environment model is constructed by topography information and topography source confidence, whereina topography characteristic is represented with a topography standard deviation. Offline path planning is based on a rapid search random tree algorithm, improves a new node and father node selection algorithm, and processes the topography information by roulette and a mahalanobis distance so as to avoid a low topography information region. When an AUV navigates along an offline path and detects changes of the topography information, online re-planning implements judgment on the topography changes by methods of judging the topography changes, searching a local navigation optimal node, re-optimizing a global path and the like, and ensures navigation accuracy. The dynamic path planning method is applicable to long-voyage high-accuracy AUV path planning, and particularly when the topography information is changed, by modifying the path in real time, navigation accuracy and a path distance are ensured.

The invention discloses a malicious code detecting system and method based on dynamic instrumentation. The method comprises the steps that a software to be detected is uploaded on a system simulator of a mobile terminal; a framework of the software to be detected of the system simulator is ordered again by an instrumentation manger of a server, an instrumentation strategy file is implanted into the system simulator, and one or more probe functions monitor an API function of the framework according to the instrumentation strategy file; a sound monitor of the server communicates with the mobile terminal and receives the operation behaviors and content of the software to be detected which are conducted to the API function and obtained by the probe functions; the detected content is compared with a malicious API sequence feature library, if the detected content exists in the malicious API sequence feature library, the software is marked to have malicious behavior operation, and if the detected extent does not exist in the malicious API sequence feature library, the software is marked to be safe, so that the safety of the software to be detected is determined. By means of the system and method, it is achieved that the software to be detected is installed and operated in the system simulator of the mobile terminal, and malicious codes are detected through instrumentation, so that it is avoided that safety hazards or hidden dangers are caused to the mobile terminal.

The invention relates to the technical field of artificial intelligence, and discloses a cough disease identification method and device based on deep learning, which comprises extracting sound characteristics of the cough audio from a plurality of cough audio frame sequences; obtaining the sound characteristics of the cough audio from several cough audio frame sequences; classifying and predictingthe sound characteristics of the cough audio through a cough disease recognition model to obtain a cough disease label corresponding to the cough audio; outputting a cough disease identification result corresponding to the cough audio according to the cough disease label. Cough disease identification method and device based on deep learning has the advantage of convenience and rapidness that cough disease identification method and device based on deep learning automatically recognize cough diseases according to cough audio frequency by the adoption of in-depth learning method and cough disease recognition model and don't need to recognize cough diseases according to human experience.

The invention discloses an intelligent traffic violation information collecting device and collecting method. The device is installed at the center of an intersection and comprises a hardware device and software architecture. The hardware device comprises a central processing chip, a camera, a signal lamp signal extraction module, a memory module, a power source module and a network interface. The software architecture comprises a remote control module, a communication module, an automatic learning module, a digital video acquisition module, a vehicle target identifying and tracking module, a vehicle violation detection module and a violation information transmission management module. By using the vehicle violation information collecting device of IOT technology design, through video image analysis, violation and violation type can be judged, vehicle violation information is uploaded to a traffic command center through a network, the application of one device with multiple functions is realized, the intelligent traffic violation information collecting device has the advantages of a simple structure, intelligence, simplicity and convenience in use, and a wide application prospect.

The invention belongs to the field of rail transit tool safety detection, and provides a railway vehicle fault vehicle-mounted acoustic detection system and a detection method. According to the technical scheme of the invention, the system and the method solve the problems in the prior art that the existing manual detection is difficult in operation and low in accuracy and a dynamic detection system installed on the ground is poor in detection real-time performance. A sound obtaining unit is used for obtaining an original sound signal. A signal processing unit is used for carrying out the filtering treatment and the data separation treatment on the original sound signal. A feature extraction unit is used for carrying out the feature extraction on the processed sound signal. A comparison unit is used for performing the time-domain and frequency-domain analysis on the extracted feature to obtain a characteristic value matrix of the sound signal. The characteristic value matrix is compared with a sound characteristic database without a fault standard. During the comparison process, based on the domain and frequency domain combination method, whether a fault exists or not, and the existence degree of the fault are judged in the time domain firstly. Secondly, the comparison is further performed in the frequency domain to obtain a corresponding fault diagnosis result. Therefore, the system and the method are used for the fault detection of various rail vehicles.

The invention discloses a method, a system and a device for establishing a label switch path (LSP) for realizing the judgment of an LSP boundary so as to automatically trigger the creation of a lower-level LSP. The method for establishing a label switch path (LSP) comprises the following steps: label switch router (LSR) nodes acquire LSP path computation results obtained by inquiring a path computing element (PCE), wherein the path computation result includes interface switching capability information of each LSR node of the LSP; and the LSR nodes execute a process of establishing the LSP, wherein the interface switching capability information of each LSR node of the LSP is carried by a Path message of a path for establishing the resource reservation protocol (RSVP) signaling of the LSP.

The invention discloses a defective condition detection method based on curved and dotted singularity characteristics of an insulator of an overhead contact system of a high-speed rail. The method comprises the steps as follows: the overhead contact system is shot at night, so that an image of a to-be-detected insulator is obtained; the image of the to-be-detected insulator is subjected to contrast ratio enhancement and Gaussian filter and noise reduction processing; an approximate direction of the insulator in the image is determined through Radon transformation; then the insulator is determined and an angle is finely adjusted by using the curved singularity characteristics of the second generation curvelet transform; and finally a defective condition of the insulator is judged by the curved singularity characteristics of the second generation curvelet transform and the dotted singularity characteristics of the wavelet transform. The method can distinguish the insulator rapidly and correctly, and the state whether the insulator is damaged, a defective foreign matter blended state, and a type of the defective state are judged effectively. The actual input quantity is the image to-be-detected, the actual output quantity is a picture of the insulator which is positioned and result data of the defective state detection, the distinguishing effect is good, and the judgment result is accurate and reliable.

The invention discloses an unmanned aerial vehicle inspection ground measurement and control station and a transportation safeguard system used for a power transmission line. The unmanned aerial vehicle inspection ground measurement and control station and the transportation safeguard system comprise an unmanned aerial vehicle platform, a ground data real-time processing system, a ground data processing center and a data link system, wherein the unmanned aerial vehicle platform is the main platform for data collection and acquisition; the unmanned aerial vehicle platform transmits the data to the ground data real-time processing system through the data link system; and the ground data real-time processing system performs data processing, and then stores the data in the ground data processing center. The advanced and mature Z5 unmanned helicopter system in China is adopted for platform improvement; multiple kinds of high-definition sensor technologies are adopted for data collection; accurate positioning, control by the ground, intelligent recognition on lines and other obstacles, automatic collision avoidance, comprehensive analysis on multiple kinds of data, and artificial intelligence processing are carried out to obtain the work-area three-dimensional visual information; and therefore, the recognition and determination of potential safety harzards and abnormal conditions of the power transmission line, and rapid fault point positioning for the power transmission line are realized.

The invention discloses a method for judging the correctness of the position relation of strokes of a handwritten Chinese character based on template matching. The method comprises the specific steps of building a whole character feature set and a part feature set of a standard Chinese character; recording handwriting of the Chinese character handwritten by a user to obtain stroke features of the Chinese character; carrying out matching comparison on whole character features of the user Chinese character and whole character features of the standard Chinese character, building the one-to-one correspondence relation between the strokes of the user Chinese character and strokes of the standard Chinese character, confirming the attribute of each stroke of the user Chinese character, and distributing the strokes of the user Chinese character into parts to which the strokes belong; carrying out matching comparison on part features of the user Chinese character and part features of the standard Chinese character, judging whether the relative azimuth relation and the distance relation between the strokes in the parts of the user Chinese character are correct, and judging whether the relative azimuth relation and the distance relation between the parts of the user Chinese character are correct. The method can be used for judging whether the position relation between the strokes of the Chinese character handwritten by the user is correct and whether the position relation between the parts of the Chinese character handwritten by the user is correct and has important value in applications of judging the writing quality of the handwritten Chinese character and the like.

The invention discloses a typical natural driving scene recognition and extraction method for intelligent driving system testing. The method is realized based on a system comprising a data extractionand calculation module and a typical scene type recognition module. The data extraction and calculation module obtains driving scene key parameters from a vehicle driving database through screening, matching and calculation; and the typical scene type recognition module identifies typical scenes according to the provided driving scene key parameters and the driving characteristics of the main vehicle and the relative state of the main vehicle and the target object, and the typical scenes comprise a dangerous scene, a main vehicle lane changing scene, a vehicle following driving scene, an adjacent vehicle switching-in scene, a front vehicle switching-out scene and a line patrol driving scene. According to the method, the typical natural driving scene is comprehensively extracted, offline application to the typical natural driving scene is achieved, the structure is complete, and the applicability is high.

The invention discloses a traffic signal lamp image processing method and a traffic signal lamp image processing device. The color and shape of an abnormal traffic signal lamp are recovered, and falsedetection of a red lamp and a yellow lamp are avoided. The accuracy of traffic signal lamp image processing is improved. The traffic signal lamp image processing method provided by the invention comprises the steps that the status of a current traffic signal lamp is determined, wherein the status of the traffic signal lamp comprises a red lamp status, a green lamp status and a yellow lamp status;the long exposure frame image and the short exposure frame image of the status of the current traffic signal lamp are collected; according to the long exposure frame image and the short exposure frame image of the status of the current traffic signal lamp, the shape of the current traffic signal lamp is recovered to acquire the shape recovery image of the traffic signal lamp; and color recoveringis carried out on the shape recovery image of the traffic signal lamp.

The invention discloses an automobile ignition judgment method which comprises the following steps: at first preset time intervals, reading current real-time voltage values of an automobile; judging whether a voltage difference between a real-time voltage value read at present and a historical voltage value read at a second current preset time interval is greater than a preset threshold; and if the voltage difference is greater than the threshold, confirming that the automobile has ignition operation at present. The invention further discloses an ignition judgment device and vehicle-mounted equipment. By adopting the automobile ignition judgment method, accurate judgment on an automobile ignition state is conveniently and efficiently achieved.

The invention provides a method used for online monitoring of low-frequency oscillation of an electric power system and based on combination of change-point detection and a Prony method. The method comprises steps as follows: on the basis of a WAMS (wide area measurement system), converting power angle data of all observation units in the system into relative power angle values based on reference units; monitoring abrupt change of relative power angles of the observation units; in response to the abrupt change, constructing a time sequence by the aid of real-time data of relative power angle values; performing change-point detection, and detecting types causing dynamic response of the system; executing set processing in response to different types causing the dynamic response of the system: performing Prony algorithm based system mode analysis, or returning to the former steps for continuously monitoring the abrupt change of relative power angles of the observation units and processing a change-point detection result. With the adoption of the method, the defects of a conventional low-frequency oscillation online monitoring system can be overcome, the low-frequency oscillation state of the system is accurately judged, meanwhile, the influence caused by non-stationary performance of an oscillation starting early signal can be avoided, and the precision and the reliability of system mode information acquired with the Prony method are improved.

The invention discloses a traffic adjusting system and method capable of recognizing a road condition and automatically moving a road isolation strip. The traffic adjusting system comprises an isolation strip moving device and a road condition recognition control system. The isolation strip moving device comprises isolation guardrails arranged on a road and sliding guide grooves arranged perpendicular to the direction of lanes on the road. Two rows of idler wheels are arranged at the bottom of each isolation guardrail, two idler wheels are arranged in each row, each row of idler wheels can freely slide on the ground, one idler wheel is driven through a motor, guide rods extending into the sliding guide grooves are arranged at the bottom of each isolation guardrail, and the multiple isolation guardrails are connected end to end to form the movable road isolation strip. The road condition recognition control system is used for recognizing the traffic road condition on the road and movingthe road isolation strip for one or more lanes to the side with less vehicles through motor drive according to road condition judgment. The isolation strip is controlled to move, a single-side congestion condition in on-off-duty rush hours is relieved, and a guarantee is provided for private car smooth passage in the rush hours.