621 results about "Active safety" patented technology

The invention relates to the technical field of vehicle lateral stability control, and discloses a multi-source sensing fusion vehicle lateral stability coordination control system which comprises a multi-source sensing module, a fusion decision module, a control execution module, a state evaluation module and a coordination optimization module. The multi-source sensing module is provided with multiple types of sensors, and vehicle transverse motion parameters, tire attachment parameters and the like are collected and preprocessed. The fusion decision module constructs a data fusion model and a control rule, and dynamically simulates control parameters; the control execution module transmits the rule to a steering mechanism, a braking mechanism and the like, adjusts the output power and returns feedback data; the state evaluation module performs data standardization processing, calculates a first evaluation index, compares the first evaluation index with a reference threshold value, and preliminarily evaluates the stability; and the coordination optimization module calculates a second evaluation index in combination with the road environment parameters when being unstable, and performs secondary evaluation and adjusts the control instruction. The system is suitable for the field of active safety control of various vehicles.

The invention discloses a driver state sensing system based on physiological indexes and external behavior analysis, which relates to the technical field of vehicle active safety control, and comprises a sensor group integrated in a driver contact or close area and a vehicle control part and used for collecting physiological signals and behavior characteristic signals of a driver in real time, the physiological signals at least comprise heart rate and skin electric signals, and the behavior characteristic signals at least comprise eyelid movement, head posture and steering wheel operation signals. According to the driver state sensing system, the comprehensiveness and accuracy of driver state sensing are remarkably improved by integrating physiological indexes and external behavior analysis, the limitation of single signal judgment is effectively overcome through a multi-source signal fusion mechanism, the reliability of state evaluation is ensured, and the advanced signal preprocessing technology adopted by the system is high in reliability. The data anti-interference capability is enhanced, the feature extraction precision is improved, and the robustness of the model is enhanced.

The invention discloses a dangerous driving critical state identification method, and relates to the technical field of intelligent driving safety. According to the method, multi-mode signals of eye movement, electrocardio, skin electricity, vehicle operation and the like are collected and converted into a unified phase field, and the synchronous coherence of the unified phase field is analyzed; the individual phase dynamics manifold of the driver is learned on line by using a Shenchang differential equation, and a system instability precursor is identified by detecting the behavior that a state point escapes from a steady state attractor; further, multi-dimensional indexes such as synchronous collapse and topological fracture are fused, collapse time is estimated in combination with a Lyapunov index, and an advanced early warning instruction is generated; and finally, based on the model predictive control and the personalized phase response curve, generating and executing targeted multi-mode phase reset intervention, and forming a sensing-early warning-intervention active safety closed loop. According to the invention, normal form transformation from post-event alarm to beforehand regulation and control is realized, and early warning advancement and intervention accuracy are improved.

The invention relates to the technical field of automobile active safety, in particular to an intelligent brake pad abrasion measuring method and system based on multi-sensor fusion, and the method comprises the steps that S1, multi-source sensing signals are synchronously collected, and wheel speed pulse signals and brake pressure signals from a vehicle CAN bus are received; s2, multi-modal signal feature extraction: carrying out time domain filtering processing on the original thickness signal to form a thickness change feature vector, carrying out space partition calculation on the temperature distribution signal to form a temperature gradient feature matrix, and carrying out wavelet packet decomposition on the braking vibration signal to form a frequency domain energy feature set; s3, dynamically fusing decisions, outputting a joint feature vector, and generating a wear loss estimated value and a confidence index; and S4, performing Kalman filtering correction on the wear loss estimated value according to the confidence index to form final wear thickness data. According to the brake pad wear intelligent measurement method and system based on multi-sensor fusion, the problem that brake pad wear cannot be accurately monitored and intelligently diagnosed online in real time can be solved.

The invention relates to the field of automatic driving vehicle control, in particular to a sightseeing vehicle anti-collision control method and system based on a multi-mode radar. Comprising the following steps: acquiring a multi-modal radar original signal, and performing timestamp alignment and noise reduction processing to generate standardized fusion data; performing multi-target classification based on a convolutional neural network, and outputting a target recognition result in combination with Doppler frequency shift compensation and distance calculation; generating a hierarchical response strategy through dual-threshold comparison and environment interference dynamic weight adjustment; the strategy is converted into a PWM control signal, and a control instruction is generated through relay driving adaptation and hardware compatibility detection; a relay is driven in real time, motor response is collected, and execution effect evaluation and time sequence marking are completed; and brake release and system parameter synchronization are realized through PID closed-loop control. The problems of insufficient multi-target identification precision, poor environmental interference adaptability and response delay are solved, and the active safety performance of the sightseeing vehicle is remarkably improved.

The invention relates to the technical field of risk assessment, in particular to a safe driving assessment method and system based on Beidou navigation. The method comprises the following steps: acquiring corresponding real-time position, speed and driving track data in a vehicle driving process through a Beidou navigation module, and acquiring vehicle state data and environment sensing data to obtain a vehicle multi-dimensional driving state data set; performing vehicle space-time and driving operation feature analysis and driving road matching analysis on the vehicle multi-dimensional driving state data set to obtain vehicle driving road attribute matching data; and carrying out vehicle driving risk estimation and vehicle safety over-rate evaluation based on the vehicle driving road attribute matching data, carrying out safety comparison verification evaluation, generating vehicle personalized driving improvement suggestions, and pushing the vehicle personalized driving improvement suggestions to the vehicle-mounted terminal to execute corresponding vehicle safe driving behavior improvement operation. According to the invention, real-time monitoring, accurate evaluation and active safety intervention of vehicle driving behaviors can be realized.

The invention relates to the field of vehicle intelligent control, in particular to a dynamic target prompting method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining a dynamic target and motion data thereof in a vehicle driving environment; then, the driving direction of the vehicle is detected, the motion data is analyzed, a traversing dynamic target with a crossing trend is identified, and potential dangers are locked in advance. And then, detecting whether a collision risk target object exists between the transverse moving target and the transverse moving target based on the reverse driving direction, and if the collision risk target object exists, executing a safety prompt operation on the transverse moving target. Therefore, a set of complete active safety warning mechanism is constructed, other vehicles and pedestrians can timely perceive the danger, compared with the prior art, the system is not in the state of passively waiting for the danger, the safety of the vehicles and the pedestrians in the road environment is greatly improved, and the occurrence probability of traffic accidents is reduced.

The method is mainly applied to the technical field of automobile engineering. The invention discloses a driving turning anti-collision control method and device, a vehicle and a medium, and the method comprises the steps: responding to a steering instruction of the vehicle, and generating a local coordinate system taking the current position of the vehicle as an original point; determining predicted position coordinates of the vehicle in the local coordinate system based on the steering angle and the driving speed of the vehicle; when the obstacle is detected, determining the obstacle coordinate of the obstacle in the local coordinate system; determining a collision risk value of the vehicle and the obstacle based on the predicted position coordinate and the obstacle coordinate; and when the collision risk value is larger than a preset safety threshold value, a braking instruction is sent to the vehicle so as to control the vehicle to brake. According to the method, the static or low-speed moving obstacle can be effectively identified in a complex turning scene, and a braking measure is taken in time, so that the active safety of the vehicle in the turning process is improved, and the collision risk is reduced.

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 belongs to the technical field of industrial vehicle active safety control, and particularly discloses an industrial vehicle safety anti-collision early warning method and device, and the method comprises the steps: building a unified space-time perception reference through fusing ultrasonic wave, inertial navigation, laser radar and camera data; extended Kalman filtering is fused with inertial navigation prediction and laser radar poses, and high-precision positioning in the tunnel is achieved. Constructing a high-dimensional time sequence feature vector, and predicting a future collision risk in combination with a Bi-LSTM model; the early warning threshold value is dynamically adjusted according to the load, the gradient and the sensor state; the method has the following advantages that the early warning accuracy and response speed under the complex working condition are remarkably improved, and the operation safety of the industrial vehicle is guaranteed.

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 provides a vehicle stability control method, device and system and electronic equipment, relates to the technical field of vehicle active safety control, and aims to construct a control framework based on a two-degree-of-freedom dynamical model and realize accurate control of the yaw velocity and the side slip angle of a vehicle. By introducing the road adhesion coefficient and combining the vertical load of each wheel for independent torque distribution, the tire adhesion utilization rate and the environmental adaptability and safety of the vehicle under different road conditions (such as ice and snow, wet and slippery conditions and dry conditions) are improved. According to the scheme, calculation is easy and convenient, response is rapid, good engineering practicability is achieved, and the robustness and adaptability of the system under the complex working condition are enhanced while the vehicle stability and the path tracking capacity are improved.

The invention relates to the technical field of active safety of forklifts, and discloses a driving assistance method for stability adjustment of a forklift, which comprises the following steps: acquiring input parameters of the forklift for driving assistance; acquiring a fuzzy set corresponding to the input parameter; establishing a fuzzy rule base for logical reasoning based on the fuzzy set of the input parameters; constructing a decision function through a weighted average method to calculate a driving mode control value, and optimizing a weight through minimizing a decision error based on supervised learning; outputting a corresponding driving mode according to the driving mode control value; the invention further discloses a driving assistance system for forklift stability adjustment. The driving assistance system comprises a road surface recognition module, a forklift state acquisition module, a parameter fuzzification module, a fuzzy rule base storage module, a driving mode decision module and a driving mode execution module. By monitoring a plurality of input parameters, the overall performance and the adaptive capacity of the forklift system are improved, and efficient operation and safe operation of the forklift system in a dynamic complex environment are ensured.

The invention relates to a safety protection method based on dynamic monitoring of circulating flow of heat source equipment. The method comprises the following steps: collecting pipeline pressure data, circulating water flow data and circulating water temperature data in a circulating pipeline of heat source equipment through a multi-source sensor; inputting the circulation pipeline data into a preset heat source equipment state model to perform working condition evaluation so as to generate an equipment working condition report; performing fault feature extraction on the equipment working condition report, and identifying an abnormal operation mode according to the extracted fault features; in response to the identified abnormal operation mode, determining a fault type matched with the abnormal operation mode according to a preset fault type library; and based on the determined fault type, generating a corresponding control instruction by using a preset risk-instruction mapping rule. According to the invention, real-time monitoring of the operation state of the heat source equipment, automatic identification of abnormal modes and active safety protection control are realized.

The invention belongs to the technical field of flight simulation training equipment control, and particularly relates to a full-motion flight simulator teacher seat adaptive control method, system and equipment. The problem that in the prior art, passive safety protection exists, high-frequency vibration interference exists, and dynamic working condition self-adaptive capacity is lacked, so that the posture imbalance risk of a teacher is caused is solved. The method comprises the steps that platform motion data, teacher skeleton key points and pressure distribution data are collected in real time, the current flight working condition is recognized after multi-source fusion processing, and the weight proportion of all data sources in deviation calculation is dynamically determined; by calculating the deviation between the weighted current posture of the instructor and the standard posture, a multi-direction self-adaptive adjustment instruction is generated to drive the seat to conduct displacement and angle adjustment, closed-loop adjustment is conducted on the basis of the residual deviation till the precision requirement is met, and active safety protection and intelligent self-adaptive adjustment of the seat are achieved.

The invention relates to a vehicle active safety control method and system, a storage medium and a vehicle, and belongs to the field of intelligent driving control. The vehicle active safety control method comprises the steps that driving state information is obtained in real time; calculating a longitudinal risk avoidance determination threshold based on the driving state information, and setting a first trigger condition based on the longitudinal risk avoidance determination threshold; if the longitudinal distance between the vehicle and the target vehicle meets the first triggering condition, an automatic emergency braking system is activated, and a first deceleration used for controlling longitudinal braking of the vehicle is generated; after the automatic emergency braking system is activated, a transverse risk avoiding judgment threshold value is calculated on the basis of the driving state information updated in real time, and a second triggering condition is set on the basis of the transverse risk avoiding judgment threshold value; if the longitudinal distance between the vehicle and the target vehicle meets a second triggering condition, an automatic emergency steering system is activated, and a second control instruction is generated; wherein the second control instruction is used for controlling the automatic emergency steering system to execute the cooperative steering angle and controlling the automatic emergency braking system to execute third deceleration cooperating with the cooperative steering angle.

The invention relates to the technical field of engineering machinery, and discloses an engineering machinery active safety control method and device based on multi-parameter analysis, and the method comprises the steps: collecting the multi-modal data of an environment where the engineering machinery is located based on a multi-modal data collection device, and constructing a dynamic model of the engineering machinery and the environment according to the multi-modal data, analyzing the multi-modal data through a dynamic model to obtain an environment data analysis result and an equipment data analysis result, determining an operation risk level of the engineering machinery according to the environment data analysis result and the equipment data analysis result, and determining an optimal working path of the engineering machinery according to the multi-modal data. And generating a safety control strategy according to the operation risk level and the optimal working path. Therefore, by implementing the method, the evaluation accuracy of the operation risk can be improved, the probability of misoperation of operators is reduced, the operation accuracy and reliability of the engineering machinery are enhanced, and the operation efficiency, the operation stability and the operation safety of the engineering machinery are further improved.

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 discloses a distributed driving electric vehicle path tracking and stability control method and system, and belongs to the technical field of electric vehicle active safety control. The method comprises the following steps: constructing a state-space equation based on a driver path tracking model and a vehicle three-degree-of-freedom motion model; establishing a dynamic envelope region based on a phase plane method, inputting the current parameters of the vehicle into the dynamic stable envelope region, and outputting a weight; constructing a controller based on the state-space equation, and taking the weight output by the dynamic stable envelope region as the control weight of the controller; inputting the vehicle state variables and the vehicle parameters into a controller, and outputting a longitudinal driving torque, an additional yaw torque, an additional front wheel turning angle and a driver intention turning angle required by driving; the additional front wheel turning angle and the driver intention turning angle are superposed to serve as input of a steering motor; a torque distributor is designed to distribute a longitudinal driving torque and an additional yaw torque, and the distributed torques are used as given values of the four hub motors.

The invention discloses a rollover risk pre-judgment and speed closed-loop control system and method integrating an IMU and an encoder, and relates to the technical field of vehicle active safety control. The system comprises an inertial measurement unit, an encoder, a controller, an execution mechanism and an alarm, the inertial measurement unit provides vehicle attitude data, and the encoder provides vehicle speed information. And the controller fuses the data in real time to calculate a vehicle rollover risk index, and sets a double-threshold criterion: when the risk is close to a threshold, an early warning is given, and when the risk exceeds the threshold, a deceleration control instruction is sent to the execution mechanism. The executing mechanism adjusts vehicle power output or braking accordingly, and automatic speed reduction is achieved. The controller forms a closed-loop control loop through feedback of the encoder, the speed reduction force is dynamically adjusted, and the speed of the vehicle is stably reduced to a safe range. Through the method, the rollover risk of the vehicle can be sensed in advance and actively intervened, rollover accidents are avoided, and the rollover-resistant safety of the vehicle is remarkably improved.

The invention discloses a driving and braking suspension cooperative control method, device and equipment, a medium and a product, and relates to the field of vehicle active safety control. The method comprises the steps that a driving demand analysis and decision module determines driver demand torque, a control mode and a neutral steering target according to the vehicle state, the steering angle of a steering wheel of a driver and input information of a driving / braking pedal; the hybrid coordination control module determines front and rear motor torques according to the torque required by a driver and the vehicle state under the conventional working condition, and determines four-wheel cylinder brake pressure by using sliding mode control according to the vehicle state; the torque vector optimization distribution control and Smith predictor control method is adopted to determine the torque of a front motor, the torque of a rear motor and the brake pressure of a four-wheel cylinder according to the torque required by a driver, the vehicle state and a neutral steering target under the limiting working condition, and the weighted pseudo-inverse distribution vehicle body posture coordination control is adopted to determine the damping force of the semi-active suspension. The method can achieve the precise tracking of the expected neutral steering target, and gives full play to the lateral movement limit of the vehicle.

The invention belongs to the technical field of automobile seats, and provides a zero-gravity seat protection method and system based on collision risk prejudgment and application, and the method comprises the steps: monitoring collision risk information and vehicle state information in real time, carrying out the fusion processing of the collision risk information and the vehicle state information, carrying out the collision risk prejudgment, and generating an early warning signal when a judgment result meets any preset collision triggering condition; multiple zero-gravity seat active safety protection actions are executed in a millisecond level in parallel or under condition triggering, so that a seat backrest is reset to a safety protection posture from a zero-gravity posture through a synergistic effect, cooperative fixing of the posture of a passenger is synchronously completed, and the zero-gravity seat active safety protection actions are completed within 200 milliseconds; and when it is detected that the angle of the seat backrest reaches the target angle, the dual self-locking function is triggered, and locking of the seat backrest is completed. According to the invention, millisecond man-machine cooperation zero-gravity seat active safety protection can be carried out based on prospective collision risk pre-judgment, and the method has the advantages of low cost, high reliability and low false triggering rate.

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 distributed driving vehicle fault-tolerant driving control method considering motor torque time lag, and belongs to the technical field of vehicle system active safety control. According to the method, firstly, an FIR filter with a linear phase characteristic is utilized to characterize a wheel torque time lag tau; estimating the time lag of each wheel torque in real time by adopting a gradient descent method to obtain a time lag estimated value # imgabs0 # obtained in real time, and designing a fault-tolerant driving control strategy according to the estimated value of the wheel torque time lag; and designing a Smith predictor according to different driving modes in the designed fault-tolerant driving control strategy to realize compensation of time delay. The method is based on the FIR filter, can be efficiently realized in hardware, and is good in stability and strong in noise suppression capability.

The invention discloses an assembly type riding safety helmet which comprises a main helmet body, the main helmet body comprises an outer shell and an inner shell, and the outer shell is installed outside the inner shell in a sleeving mode; the front lamps are fixedly mounted at the positions, close to the two opposite sides, of the front side of the outer shell; a penetrating type tail lamp is fixed to the rear side of the outer shell; the front speed measuring radar is embedded and fixed in the center of the front side of the outer shell, a first control chip is arranged in the front speed measuring radar, and the first control chip is electrically connected with the front speed measuring radar and the front lamp; and the rear speed measuring radar is embedded and fixed in the center of the rear side of the outer shell, a second control chip is arranged in the rear speed measuring radar, and the second control chip is electrically connected with the rear speed measuring radar and the tail lamp. According to the invention, through the arrangement of the front speed measuring radar and the rear speed measuring radar, the speed of moving objects in the front and at the rear is conveniently measured, and once the speed is greater than a set threshold value for measurement and control, the corresponding control chip controls the tail lamp or the front lamp to flash for warning, so that active warning is realized, and active safety protection is realized to a greater extent.

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 provides an emergency call system, method and device based on AI vision and a storage medium, and relates to the technical field of active safety of intelligent network connection automobiles. The system comprises a camera module, a DMS module, an OMS module, an AI vision algorithm module, an AI vision application module and an eCall application module which work cooperatively. Aiming at the three defects that a traditional emergency call system depends on collision triggering, data dimensions are deficient and active protection is absent, DMS and OMS are innovatively and deeply integrated with the emergency call system, a multi-modal fusion decision mechanism is realized in combination with a layered AI visual architecture, and through deep cooperation of camera shooting, DMS, OMS, AI visual algorithm, AI visual application and an eCall application module, the multi-modal fusion decision mechanism of the emergency call system is realized. A full-link intelligent safety closed loop of sensing, decision making, control and rescue is constructed, early recognition, active intervention and accurate rescue of sudden diseases of drivers, serious fatigue disability and emergency physiological events of passengers are achieved, and meanwhile the rescue quality of collision accidents is improved.

The invention relates to the field of safe driving, in particular to a vehicle tire burst control method, electronic equipment, a storage medium and a vehicle. The vehicle tire burst control method comprises the steps that if it is determined that a first tire of a vehicle bursts, unbalance parameters of the vehicle at the current moment are obtained; the second tire is controlled to rotate towards the first tire side according to the steering angle, the second tire is a rear wheel non-burst tire, and the steering angle is determined according to the unbalance parameter. According to the invention, real-time and effective active safety control can be carried out on the vehicle, so that the safety of the vehicle is improved.