336 results about "Active safety" patented technology

The invention discloses an intelligent network connection automobile active safety teaching control method based on digital twinning. The method comprises the steps that S1, multi-source sensor data are collected and preprocessed to generate a driving state data set; s2, inputting the state data into a digital twin model to drive a traffic scene and outputting a synchronous state; s3, based on Dueling-DDQN, executing strategy learning to generate an active safety control instruction; s4, the instruction response effect is simulated and verified in the virtual environment; s5, collecting driver operation behaviors, inputting the improved MHA-BiLSTM model to extract time sequence features, and outputting behavior features; and S6, comparing the driving behavior with a standard instruction item by item, calculating an operation deviation and a response difference, and generating a personalized active safety teaching task. According to the invention, efficient comparison and teaching feedback of the driving behavior and the active control strategy can be realized, and the intelligent level of driving training is improved.

The invention relates to the technical field of industrial vehicle safety control, in particular to a forklift safety online industrial monitoring management system which comprises a data fusion unit used for collecting kinematics data, position and attitude information and load distribution data of a vehicle and conducting space-time alignment processing on the collected data to generate a real-time state vector; the margin calculation unit is used for calculating a plurality of independent safety margin components and carrying out fusion processing based on the safety margin components to generate a comprehensive safety margin; the risk prediction unit is used for predicting a future safety margin value based on the time sequence of the comprehensive safety margin, and comparing and analyzing the future safety margin value with a preset safety threshold and a preset warning threshold to generate a risk level; the intervention control unit is used for generating and executing a corresponding hierarchical intervention strategy in response to the risk level; according to the invention, a complete technical link from multi-source data sensing to closed-loop control is constructed, and the conversion from passive safety to active safety is realized.

The invention relates to the technical field of automobile electronics and intelligent control, and discloses an intelligent cabin mechanical arm system which comprises a folding mechanical arm body, a tail end sensing interaction module, a driver state monitoring subsystem and a central control unit which are installed in a cabin. The central control unit controls the storage or working mode of the mechanical arm according to the comprehensive fatigue index of the driver; in the working mode, visual gazing information is used as a gating signal to activate electroencephalogram analysis, the operation intention is confirmed in combination with the visual prior probability and electroencephalogram signals, and the mechanical arm impedance parameters are adjusted in real time based on the fatigue state. According to the method, through Bayesian fusion of vision and electroencephalogram signals, the problem that single-mode control is unstable is solved; by means of variable impedance control and collision detection of the momentum observer, active safety protection based on the physiological state of the driver is achieved, and non-sensitive and high-safety intelligent auxiliary experience is provided in a limited cabin space.

The invention discloses a vehicle blind area dynamic enhancement and warning system for a low-light environment, and relates to the technical field of automobile active safety, and the system comprises a short wave infrared imaging module which is used for capturing a passive thermal feature image of a scene behind the side of a vehicle; the multi-source signal acquisition module is used for acquiring a vehicle bus signal representing a vehicle motion state and an operation intention of a driver in real time; the data processing and risk assessment module is connected with the short wave infrared imaging module and the multi-source signal acquisition module, and is used for performing fusion processing on the thermal feature image and the vehicle bus signal, identifying a blind area target and calculating a dynamic risk level of the blind area target; the grading warning and intervention module is connected with the data processing and risk assessment module; the short-wave infrared imaging technology which is sensitive to night light and high in anti-interference capacity is adopted, the imaging problem under extremely low illumination is fundamentally solved, and stable detection of vehicles and pedestrians in a long distance in a completely light-source-free environment is achieved.

The invention relates to an automobile windshield shelter removing method and system and an automobile, and belongs to the technical field of automobile active safety. The method comprises the steps that the surface of the windshield is monitored through a vehicle-mounted camera; when a shielding object is identified, calculating a view shielding coefficient based on the area, the position, the light transmittance and the type of the shielding object, and determining an initial influence level according to the view shielding coefficient; corresponding cleaning strategies are executed according to the influence levels, windscreen wiper cleaning is started at the low level, pneumatic suction generated by vehicle intersection is used for cleaning at the middle level, and negative-pressure airflow cleaning is induced through dynamic opening of a skylight at the high level; if the shielding is not removed, the influence level is increased step by step, and circulation execution is carried out until the shielding is removed or automatic parking is triggered. According to the method, grading, closed-loop and non-contact intelligent removal of different types of sheltering objects is achieved, and invalid or even harmful operation of a traditional windscreen wiper in a dry sheltering scene is effectively avoided.

The invention relates to the technical field of vehicle intelligent driving and active safety control, and discloses an active obstacle avoidance method and system considering multi-source uncertainty and fault positioning, and the method comprises the following steps: S1, predicting the tracks of a normal vehicle and a sideslip vehicle, and obtaining the predicted position and covariance of the normal vehicle and the sideslip vehicle; s2, constructing an extended state equation containing a positioning fault, and estimating and compensating a positioning deviation; s3, establishing a linear error tracking model, unifying various uncertainties into equivalent disturbance, and solving a disturbance invariant set; s4, generating a candidate obstacle avoidance track based on the compensated state; s5, track comfort is evaluated, hard constraints are checked, and infeasible tracks are removed; s6, transversely expanding the contour of the vehicle by using a disturbance invariant set, and carrying out longitudinal and transverse separation expansion on the contour of the target vehicle based on the predicted covariance; s7, performing robust collision detection by using the disconnect axis theorem; and S8, carrying out robust tracking control by adopting Tube-MPC. According to the invention, safe and stable obstacle avoidance control can be realized under complex disturbance and fault positioning conditions.

The invention discloses a multi-source data fusion vehicle anti-collision system based on a 4D millimeter-wave radar, which is applied to the technical field of vehicle active safety, and comprises a 4D millimeter-wave radar detection module used for collecting 4D information of targets around a vehicle and distinguishing a pavement target from an air interference target; the vehicle state detection module is used for synchronously acquiring running parameters of the vehicle at the same acquisition rate as that of the radar detection module; the data fusion processing module is used for carrying out fusion and noise reduction processing on the 4D information and the running parameters of the vehicle on the basis of a fusion algorithm of Kalman filtering and a DS evidence theory; the collision risk estimation module is used for calculating the collision time and the collision probability based on the fusion data and constructing a two-parameter risk level judgment model based on the collision time and the collision probability; and the anti-collision execution module is used for executing a corresponding anti-collision intervention action according to the risk level. The accuracy, the stability and the adaptability of the vehicle anti-collision system are effectively improved.

The invention discloses a fault diagnosis and fault-tolerant control method for in-situ steering of a distributed driving vehicle on a wet and slippery road surface, and aims to solve the problem of instability of the vehicle when a driving unit has faults such as driving failure, mechanical locking or excessive slipping. According to the method, the vehicle state is obtained in real time, the initial torque instruction is calculated, and online diagnosis and accurate recognition of the fault mode are achieved. Aiming at hardware faults such as driving failure, the system breaks and isolates a fault wheel; and aiming at excessive slipping, the torque is preferentially and actively reduced to recover the adhesive force, and temporary isolation is carried out after recovery failure. Once the fault unit is confirmed to be isolated, the system immediately starts a torque reconstruction module based on quadratic programming (QP), and the driving task is optimally redistributed to the remaining healthy wheels in real time so as to maintain the expected yaw moment of the whole vehicle. According to the strategy adopted by the invention, faults with different properties can be effectively distinguished and processed in a differentiated manner, and the control stability and active safety of the vehicle under the conditions of severe work and partial failure are remarkably improved.

The invention discloses a FanERC ship filling active safety disengaging device which comprises a left valve body, a right valve body and an air inlet connector, the left valve body and the right valve body are fixedly connected through a breaking bolt, a sealing cavity is formed in the connecting position after the left valve body and the right valve body are connected, and the air inlet connector is fixedly arranged on the left valve body and communicates with the sealing cavity. The gas inlet connector is connected with a nitrogen releasing device, after the nitrogen releasing device receives a releasing signal sent by the main control system, the nitrogen releasing device releases high-pressure nitrogen, the high-pressure nitrogen enters the sealing cavity through the gas inlet connector, the breaking bolt is thrusted and broken through high pressure, the left valve body and the right valve body are separated, and the left valve body and the right valve body automatically achieve self-sealing. The active separation mode does not need to depend on too large tension borne by the pipeline to break the bolt, impact and damage of the tension to the LNG conveying pipeline, the filling hose and other equipment can be reduced to the maximum extent, the LNG leakage risk caused by pipeline damage is reduced from the source, and the service life and safety of filling operation related equipment are guaranteed.

The invention discloses an unmanned aerial vehicle nest full life cycle management and control method, system, product and device, and relates to the field of unmanned aerial vehicle nests, and the method comprises the steps: employing a bidirectional access mechanism to carry out the bidirectional validity verification of an unmanned aerial vehicle and a nest, and generating an access safety certificate; integrating multi-dimensional data through edge computing nodes, and constructing a visual relation model and a dynamic behavior monitoring model; carrying out real-time risk identification and early warning by adopting a multi-dimensional feature fusion anomaly detection algorithm; the digital twinning technology is utilized to fuse aircraft nest operation data, and predictive maintenance is achieved through a life prediction model; and safely erasing the sensitive data of the equipment and cancelling the voucher to form a management closed loop. Through a bidirectional access mechanism, multi-dimensional anomaly detection, predictive maintenance and safe decommissioning processing, full-link active safety protection from access, operation, maintenance to decommissioning is realized, the safety and reliability of a machine nest system are improved, and the system can be applied to complex scenes with strict safety requirements such as electric power inspection.

The invention relates to a dynamic positioning switching control method for an automatic driving mine vehicle, and the method comprises the following steps: carrying out the control of the dynamic positioning switching of the automatic driving mine vehicle based on the dust concentration change rate data and the visibility change rate data of a historical set time period, and the first dust concentration change rate data and the first visibility change rate data of a current region; predicting second dust concentration change rate data and second visibility change rate data in a future set time period; and determining a risk level of the current area and a trigger condition corresponding to the risk level based on a preset area threshold table, and comparing the second dust concentration change rate data and the second visibility change rate data with the trigger condition. According to the method, the pre-switching process can be triggered before the sudden change of the dust concentration occurs, precious buffer time is gained for a system, mode conversion from traditional passive response to active pre-judgment and adjustment is achieved, the positioning interruption and out-of-control risks of a vehicle in the scene of the sudden change of the dust are reduced, and the active safety capacity of driving operation is improved.

The invention provides a forward collision risk processing method and device, equipment and a medium, and relates to the technical field of auxiliary driving, and the method comprises the steps: forming a forward target sequence through synchronously obtaining the speeds, accelerations and vehicle distances of a vehicle and a plurality of front vehicles, and constructing a relative speed, relative distance and longitudinal acceleration time sequence according to a time dimension; calculating nominal collision time and a time margin based on the motion relation between the two vehicles, and introducing a motorcade compression index and a deceleration wave intensity index to correct the nominal collision time so as to obtain effective collision time; collision hazards are quantified according to a collision relative speed, a compression index and a deceleration wave intensity index, a controllability score is constructed in combination with effective collision time and a time margin, then a severity score and the controllability score are mapped into discrete risk levels, and differential active safety measures such as transverse avoidance are triggered according to different risk levels. The method can simultaneously consider the longitudinal compression trend of the motorcade and the deceleration wave cumulative effect to trigger the evasion strategy.

The invention relates to a multi-modal active safety margin evaluation and checking method and device and a storage medium, which are applied to the technical field of electric power spot market, and the method comprises the steps: constructing a state judgment-index self-adaption evaluation framework, and when a system is in a risk state, calculating an interval overlapping index to quantify the risk exposure degree; when the system is in a safe state, a safe distance index is calculated to quantify safe redundancy, the multi-modal index system overcomes the defect that information is unilaterally evaluated by a traditional single index, refined and differentiated evaluation on the degree of risk and the degree of safe redundancy is achieved, and more comprehensive information support is provided for scheduling decision making; by comparing the calculated index with the preset threshold value, an active checking signal which can be directly fed back to a market clearing model is generated, or a clear suggestion is provided for a dispatcher, so that the problem of disjunction between evaluation and decision in the prior art is solved, and integrated intelligent cooperation from state perception, quantitative evaluation to closed-loop correction is realized.

The invention discloses an anti-fatigue driving signal lamp and atmosphere lamp control method and a vehicle, and relates to the technical field of vehicle intelligent auxiliary driving and active safety, and the method comprises the steps: collecting a cab video stream, and positioning face key points after image preprocessing; calculating an eye PERCLOS index and a mouth yawning frequency, and dynamically adjusting a weight based on a face angle so as to fuse and calculate a comprehensive fatigue index; carrying out grading judgment on the index by utilizing a hysteresis interval containing a starting threshold value and a reset threshold value, and reducing a judgment threshold value in real time by utilizing a linear model according to the vehicle speed; and driving an indoor atmosphere lamp to execute a breathing or stroboscopic mode according to the judged sober, mild or severe fatigue grade, controlling an outdoor signal lamp and a road surface projection assembly to execute corresponding warning actions, and performing reverse pre-distortion processing on a projected image. According to the invention, through multi-source feature fusion, hysteresis threshold determination and vehicle speed correction mechanisms, the stability of fatigue monitoring and the accuracy of warning are improved.

The application provides a kind of active safety control method and device of vehicle.When dangerous target appears in front of the vehicle, the active safety control method includes: according to whether brake system and AEB module have fault, AEB fault condition is set to allow triggering or prohibit triggering;According to whether steering system and AES module have fault, AES fault condition is set to allow triggering or prohibit triggering;According to the vehicle speed of the vehicle, AEB speed condition is set to allow triggering or prohibit triggering, and AES speed condition is set to allow triggering or prohibit triggering;According to TTB_limit, TTB_trigger, TTT_limit, TTT_trigger and collision time, AEB collision time condition is set to allow triggering or prohibit triggering, and AES collision time condition is set to allow triggering or prohibit triggering;When multiple AEB conditions are all allowed to trigger, the AEB module can be triggered to execute AEB function;When multiple AES conditions are all allowed to trigger, the AES module can be triggered to execute AES function.In this way, the triggering of active safety function is accurate and safe, and the connection between functions is smooth.

The invention provides a method and device for safely driving a vehicle, a storage medium and a computer program, and relates to the technical field of automobile active safety. The method comprises the steps of collecting an image of a foot area of a driver; identifying a shoe type, a shoelace state and a foot pad state of the driver based on the image; when the shoe type of the driver does not conform to any one or more of the preset shoe type, the shoelace state does not meet the first preset state and the foot pad state does not meet the second preset state, it is determined that the vehicle is in the non-safe driving state; generating first reminding information, wherein the first reminding information is used for reminding a driver that the vehicle is in the non-safe driving state. According to the method, whether the shoe type of the foot area of the driver is compliant or not and whether the shoelace state and the foot pad state meet the preset requirements or not can be detected, the driver is reminded in time when potential safety hazards exist, and sudden risks such as pedal control interference and braking delay caused by the potential safety hazards of the foot area are effectively avoided; and the life and property safety of drivers and passengers and road participants is ensured.

The invention relates to the technical field of automobile collision safety, and discloses a passenger posture prediction method and system based on active safety early warning, and the method comprises the steps: synchronously collecting vehicle dynamics data, passenger target muscle group surface electromyogram signals and kinematics states under a simulated or real AEB working condition; after preprocessing the data, constructing a myoelectricity-attitude prediction model by using a CNN and LSTM hybrid model; training the model by using a large amount of data to learn the internal relationship between the characteristics and the passenger kinematics state change, and predicting the kinematics state of each section of the passenger body at the collision moment; acquiring a vehicle deceleration curve, inputting characteristics to predict the posture of a passenger, converting into a simulation software instruction to complete initialization of a virtual dummy, and running collision simulation; the problem that the initial position of a traditional collision simulation model cannot reflect the actual posture of a passenger under the emergency braking working condition, and consequently data difference is large is solved.

The invention discloses a telescopic discharging platform and a using method thereof, and relates to the field of building construction.The telescopic discharging platform comprises a mounting frame unit, a movable frame, a supporting rod unit, an H-shaped steel frame and a supporting unit, the modular H-shaped steel frame and reinforced angle steel cross beam combined design is adopted, dynamic supporting compensation is achieved in cooperation with a damper and a telescopic air cylinder, and dynamic load impact is effectively absorbed; and structural deformation is avoided. The platform adopts a folding movable frame, a plug-in type supporting unit and standardized bolts for connection, field assembly is convenient and fast, various monitoring devices such as a platform pressure sensor, a horizontal sensor and a supporting pressure sensor are integrated, data such as load, inclination angle and supporting state are collected in real time, dynamic safety evaluation is achieved, the system automatically judges the load state, and the safety of the system is guaranteed. Graded early warning is triggered, a locking air cylinder is controlled in a linkage mode, a power source is cut off, and active safety protection is achieved.

The present application relates to a kind of road fog dangerous working condition identification processing method based on multi-sensor fusion, the method includes: step 1, camera, millimeter wave radar and laser radar specificity degradation features under fog environment are extracted in parallel;Step 2, based on the feature real-time evaluation sensor confidence and dynamic weighted fusion, obtain comprehensive visibility estimation V final =η*[W cam *V vis +W rad *φ(C rv )+W lid *ψ(1 / λ)], And dangerous working condition level;Step 3, according to dangerous working condition level, establish the accurate mapping lookup table of grade and vehicle control instruction, according to accurate mapping lookup table, execute the vehicle active safety control strategy corresponding to dangerous working condition level;Step 4, comprehensive visibility estimation and dangerous working condition level are packaged as standard car-road cooperation message, broadcast through vehicle-mounted communication unit, realize the vehicle-vehicle, vehicle-road early warning of over-the-horizon.This technical scheme solves the technical problems such as the present technology fusion level is shallow, information utilization rate is low, output result is rough, lack of adaptive ability etc.

The invention provides a traffic participant road condition early warning method and system based on a smart phone, and relates to the technical field of active safety. The method comprises the following steps: acquiring a video stream through a smart phone camera, and synchronously acquiring data of a gyroscope, an accelerometer, an ambient light sensor and a GPS; identifying a user motion state and an environment scene based on the sensor data; carrying out target detection, semantic segmentation and distance estimation on the video frame by adopting a lightweight neural network; performing risk assessment according to the target type, the distance and the movement speed of the user, and generating an early warning instruction; a multi-mode warning is sent to a user in a voice, vibration, vision or interface switching mode; and dynamically adjusting the analysis frequency and the power consumption mode according to the environmental complexity. Existing hardware of the smart phone is fully utilized, extra equipment is not needed, low-cost and high-universality real-time environment perception and active early warning are achieved, and the travel safety of traffic participants such as walking and riding is remarkably improved.

The invention provides a multi-sensor fusion mountainous area multi-machine lifting power failure early warning method and system, and relates to the technical field of data fusion, and the method comprises the steps: 1, carrying out the coordinate transformation of fused three-dimensional environment perception data, obtaining the environment configuration data under global coordinates, carrying out the kinematics parameter extraction of the environment configuration data, and obtaining the kinematics parameters of the environment configuration data; constructing a dynamic monitoring plane; and 2, in the dynamic monitoring plane, taking the top end of a lifting hook of a corresponding crane, a middle section joint of a lifting arm and the center of a rotary platform as three space positioning calibration points, solving equation parameters of a space circle passing through the three space positioning calibration points, and establishing a space circle geometric structure by taking the circle center of the corresponding space circle as a reference center. Through multi-sensor fusion sensing and dynamic data processing, accurate control over the multi-machine lifting environment and the crane state in the mountainous area is achieved, a reliable basis is provided for collision risk judgment, and active safety of the multi-machine lifting operation in the mountainous area is effectively guaranteed.

The invention discloses a petroleum transportation safety supervision method and device based on artificial intelligence, and relates to the technical field of petroleum transportation, and the method comprises the following steps: S1, carrying out the quantification of a transportation chain safety factor and the construction of an intrinsic risk index; s2, obtaining a dynamic dangerous field index; s3, constructing a safety control priority index; s4, constructing a risk coupling propagation model; s5, the response intensity is quantified, and a multi-strategy response coefficient is output; s6, automatically deducing a final intervention instruction; and the security supervision device is constructed based on the steps. According to the invention, the system can identify essential risks, transient risks and cross-node linkage risks in a transportation chain in real time, can automatically screen proper regulation and control strategies according to risk propagation intensity, and finally generates an intervention instruction which can be directly executed. The upgrading of safety supervision from point-level monitoring to networked, predictive and active safety control is realized, and the overall safety level and operation reliability of a petroleum transportation system are greatly improved.

The invention relates to a tread pattern depth estimation method based on a physical information fusion network, and belongs to the technical field of intelligent traffic systems and vehicle active safety. The method comprises the following steps: firstly, acquiring three-axis acceleration data under different working conditions through a tire built-in sensor; zero phase shift filtering, phase alignment and resampling preprocessing are carried out on the signals to form standard waveform data; then constructing a spatial-temporal feature extraction network, extracting time sequence features through a convolutional layer and a circulating layer, and fusing normalized load and speed working condition information; a physical constraint module based on a tire rigidity mechanism is introduced, the pattern depth and the vertical deformation amount are predicted by using learnable parameters, and a theoretical load is reversely deduced to establish a mechanical equilibrium constraint; and finally, network parameters and physical parameters are synchronously optimized by adopting a mixed loss function, and wear state grades and confidence coefficients are output through a probability statistical method. According to the method, the estimation precision and the physical interpretability of the model under the complex variable load working condition are effectively improved.

The invention relates to the field of road construction detection, and discloses a municipal engineering road base material thickness laser detection device which comprises a shell, a first protection assembly is arranged at the lower end of the interior of the shell, a second protection assembly is arranged on the periphery of the first protection assembly, and the second protection assembly is arranged at the lower end of the interior of the shell. A mounting frame is arranged at the upper end of the interior of the shell, a laser sensor is arranged at the lower end of the mounting frame, a support assembly is arranged at the upper end of the shell, and balancing mechanisms are rotationally arranged at the positions, located at the lower end of the support assembly, of the periphery of the shell. The road base material thickness laser detection device for municipal engineering provided by the invention has the functions of integrated active safety, modular drop resistance, self-cleaning and anti-interference stability, laser is blocked through a gravity sensing deflection physical layer, modular parts absorb energy and can be replaced at low cost during dropping, and pulse blowing and magnetic attraction locking are adopted, so that the detection efficiency is improved. And safety, precision and durability are ensured.

The invention relates to the technical field of intelligent traffic and vehicle active safety, and discloses a sampling vehicle active safety early warning method fusing multi-source data. The method comprises the following steps: acquiring a historical flight state, real-time environment sensing data and task planning information of a sampling vehicle; performing space-time alignment to form a fusion data set; constructing a vehicle dynamics constraint model and an obstacle motion prediction model; coupling the two to generate a vehicle reachable area and obstacle intrusion probability distribution in a future time window; and if the weighted collision risk index exceeds a threshold value, the graded early warning is triggered. The system integrates a GNSS, an IMU, an atmospheric sensor, a laser radar and a task planning interface, and supports generation of an avoidance track after early warning. Through multi-source data deep fusion and physical constraint modeling, the false alarm rate is significantly reduced, and the autonomous safe flight capability of the sampling vehicle in a complex airspace is improved.

The utility model discloses a road roller contact type anti-collision system which comprises two mounting bases, a mounting bracket is fixedly mounted at the upper ends of the two mounting bases, a travel switch is fixedly mounted on the inner wall of each mounting bracket, and the travel switches are fixedly mounted on the mounting brackets. A tensioning device is fixedly installed on the back face of each of the two installation supports, a safety protection plate is fixedly installed on the outer surfaces of the two tensioning devices through a connecting rod, and a travel switch is connected with an emergency stop switch through a signal line. And the safety is poor. According to the technical scheme, the contact type anti-collision system of the road roller is provided. The anti-collision device, namely the safety protection plate, is arranged in front of the road roller, so that emergency braking and automatic flameout operation of the road roller are finally achieved, collision accidents are effectively avoided, and the active safety of the road roller in a complex construction environment is greatly improved.

The application discloses a mountain road automatic driving car rear vehicle safety detection method and system, and belongs to the technical field of vehicle active safety detection. The application collects the position, speed and acceleration of a driver following an automatic driving car at each moment in a no-lane-changing overtaking scene, and then extracts eight features including maximum speed, minimum speed, speed average, speed standard deviation, acceleration, deceleration, distance and headway. The driver is divided into three types of aggressive, conservative and intermediate by using principal component analysis and K-means clustering algorithm. A following safety threshold model is constructed for each type of driving style. The following data of the rear vehicle is collected in real time, the features are extracted and the driving style is matched, the safety threshold of the corresponding style is called to complete safety detection, and a warning is given if the threshold is exceeded. The application can effectively avoid the collision risk of the automatic driving car rear vehicle at the mountain curve, and provides technical support for the driving safety of the mountain road automatic driving scene.

The application discloses a traffic sign recognition method and system for active safety of commercial vehicles, and specific steps of the recognition method are as follows: S1, capturing road panoramic image information through a vehicle-mounted camera device, and performing pretreatment operation on the road panoramic image information, and setting a threshold value through color transformation space to extract an image of a region of interest; S2, matching the image of the region of interest with a traffic sign template library picture, and positioning a sign image in the road panoramic image according to a matching result; S3, designing and building a neural network model, training the neural network model on a sampling traffic sign data set, and obtaining an optimal traffic sign recognition model; S4, merging a multi-branch structure in the optimal traffic sign recognition model, and obtaining a remodeling model; S5, performing classification recognition on the sign image in step S2, inputting the sign image into the remodeling model in step S4 after normalizing the sign image, and judging a traffic sign type according to an output result.

A method, device, vehicle, and storage medium for tire blowout control of a vehicle are disclosed, relating to the field of active safety technology for automobiles. The method includes: acquiring the vehicle's current state information and tire blowout information; adjusting the current state information based on the tire blowout information to obtain tire blowout state information after the blowout, wherein the tire blowout state information includes the actual yaw rate and actual sideslip angle of the vehicle after the blowout; if the vehicle is in an unstable state, acquiring the vehicle's desired yaw rate and desired sideslip angle, and determining a sliding surface control function based on the desired yaw rate, desired sideslip angle, actual yaw rate, and actual sideslip angle; determining a balancing yaw moment based on the sliding surface control function, and controlling the non-blowout wheels based on the balancing yaw moment and the tire blowout information. This application controls the vehicle based on the corrected state information, improving the accuracy of tire blowout control.