1540 results about "Automobile safety" patented technology

The invention discloses an intelligent network connection automobile safety control method and system based on active and passive safety information fusion. The system comprises an environment detection module, a risk prediction module and a cooperative control module. Wherein the environment detection module comprises a passenger state monitoring part, a vehicle system monitoring part and a traffic environment sensing part, the risk prediction module comprises a vehicle collision risk prediction part and a passenger injury risk prediction part, and the cooperative control module comprises an in-vehicle intelligent restraint system, a vehicle steering system and a control execution part of a braking system. The vehicle collision risk probability and the passenger injury probability are calculated in real time according to the established vehicle risk prediction model and the passenger injury risk prediction model by fully utilizing the early warning capability of an active safety system for potential risks. When the system encounters unavoidable dangerous working conditions, the system adjusts the state of the restraint system to enable the restraint system to reach the optimal state of current passenger protection, and extra risks, caused by non-cooperation of the active safety system and the restraint system, of passengers are avoided.

The invention provides an automatic assembling method and system for an automobile safety belt pretensioner based on machine vision, and relates to the technical field of automatic assembly.The method comprises the steps that firstly, images of standard parts of the pretensioner are collected, geometrical characteristic parameters are extracted, and the mapping relation from two-dimensional image coordinates to three-dimensional space coordinates is established; calculating coordinates of an assembly reference point and an assembly path point; acquiring a real-time image of a to-be-assembled part, extracting feature data, matching the feature data with a standard part, calculating a position deviation value and an angle deviation value, and updating an assembly path point coordinate; and controlling the robot to execute assembly, and dynamically adjusting the assembly speed and the assembly strength of the robot based on the assembly state evaluation index after data fusion of the force sensor and the displacement sensor until automatic assembly is completed.

The invention provides a new energy automobile fire dynamic risk assessment method and system based on multi-modal spatial-temporal feature fusion. The new energy automobile safety monitoring and fault early warning method comprises the steps that a multi-source data acquisition layer obtains multi-source heterogeneous data, and space-time marking is carried out; the feature fusion preprocessing layer generates a space-time consistency data stream through a space-time alignment module and missing value filling; the deep learning evaluation layer extracts multi-modal features by using a dedicated network, and outputs feature scores through time-space dependence modeling fusion; and the dynamic early warning decision-making layer generates a dynamic risk score in combination with the thermal runaway probability, the risk gradient and the aging factor, constructs a five-level risk map and executes vehicle-cloud collaborative graded early warning. According to the new energy automobile fire dynamic risk assessment method and system based on multi-modal spatial-temporal feature fusion, the limitation of traditional single data static assessment is broken through, accurate dynamic early warning is achieved, the early warning time is longer than or equal to 15 min, the false alarm rate is reduced to 4.7%, and the thermal runaway prediction accuracy rate reaches 98.3%.

The invention relates to the technical field of ship roll-on and roll-off equipment, and discloses a large automobile roll-on and roll-off transport ship movable ramp and a mounting method.The large automobile roll-on and roll-off transport ship movable ramp comprises a first hinge mount, a first ramp joint is rotatably arranged on the first hinge mount, and a second ramp joint is arranged at the end, away from the first hinge mount, of the first ramp joint; the end, away from the first ramp joint, of the second ramp joint is connected with a third ramp joint, a second hinge seat is arranged on the surface of the upper end of the hull structure and located on the inner side of the first hinge seat, a hinge shaft is arranged on the second hinge seat, and the second hinge seat is rotationally connected with the end of the third ramp joint through the hinge shaft. According to the movable ramp of the large automobile roll-on-roll-off transport ship, by arranging the supporting assembly and pulling out the positioning plug pin, when the third ramp section is lifted, the sliding block can slide along the rail base, then the positioning pin is clamped into the positioning hole, it is guaranteed that the position of the sliding block is fixed, then the supporting rod can effectively support the third ramp section, and the requirement for safe passing of automobiles is met.

The invention relates to the technical field of automobile safety, in particular to a human body finite element model soft tissue motion deformation non-simulation rapid calculation method. Comprising the steps of initializing a calculation structure, recognizing a skeleton-soft tissue common node NBS, and extracting a soft tissue inner surface node NSS, a near-end end face node NSP and a far-end end face node NSD. And extracting skeleton motion information, calculating node coordinate sets BS0 and BS1 based on the initial configuration B0 and the target configuration B1, and determining end face boundaries SP0 and SP1 and SD0 and SD1 by utilizing rigid body transformation. Calculating an initial displacement field D0, acting on the NSS to obtain an initial deformation inner surface SS1, and processing a penetration site to obtain SS2; and fixing the BS1, and optimizing the coordinates of the SS2 node to obtain SS3. And integrating the initial mark point sets SS0, SP0 and SD0 and the post-motion mark point sets SS3, SP1 and SD1, and calculating a final displacement field D1 through spatial interpolation. The technical scheme can quickly and accurately simulate the large deformation of the soft tissue involved in human motion.

The invention relates to the technical field of new energy automobile driving safety, in particular to a new energy automobile safety evaluation system based on big data, and the system comprises a data collection module which is used for collecting the operation data, performance data, operation environment data and loss data of a new energy automobile battery; the risk analysis module is used for analyzing the operation risk of the battery; the abnormity monitoring module is used for optimizing the analysis process of the battery operation risk; the loss analysis module is used for analyzing the loss state of the battery and analyzing the abnormal index of the battery; the aging analysis module is used for analyzing the aging state of the battery according to the battery internal resistance and the battery capacity collected in the monitoring period; and the safety evaluation module is used for evaluating the safety of the battery and adjusting the evaluation process of the safety of the battery. According to the invention, the accuracy of new energy automobile battery safety assessment is improved.

The invention relates to the technical field of driving control, in particular to a new energy automobile safe driving control method and system. The method comprises the following steps that a historical urgent danger avoiding data set and a corresponding user misoperation braking state are obtained through a new energy automobile control center, sample undersampling processing is conducted firstly, and an urgent danger avoiding balance sample is obtained; thirdly, analyzing user misoperation braking abnormity by using a balance sample, and performing disordered vector intensity calculation under a time dimension based on braking abnormity data to generate disordered vector segmentation clustering data; then, braking time sequence intervention correction sensing is carried out according to the clustering data, optimized braking intervention correction data are generated, finally, the optimized data are transmitted to a new energy automobile control terminal, and safe driving control is executed. According to the invention, the driving control technology is optimized, so that the driving control technology is more perfect.

The invention discloses a reinforcement learning automatic driving decision control method based on a Lyapunov function, and relates to the technical field of automatic driving automobile safety control. The method comprises the steps that driving state information of a self-vehicle and driving state information of surrounding environment vehicles are received, the driving state information of the self-vehicle comprises the position, the speed, the acceleration and the course angle, and the driving state information of the surrounding environment vehicles comprises the position, the speed, the course angle and lane line information of the environment vehicles relative to the self-vehicle; and a decision control model of the automatic driving task based on reinforcement learning is constructed, and the decision control model takes the driving state information of the vehicle and the surrounding environment vehicles as output and takes the optimal automatic driving strategy as output. According to the method, the reinforcement learning strategy updating process is constrained through the stability condition proved by theories, the unification of safety and decision-making efficiency is realized in dynamic scenes such as highway lane changing and emergency obstacle avoidance, and the method has a good application prospect for training the safety and strategy stability of automatic driving by adopting reinforcement learning.

The present invention relates to a double anti-collision safety type automobile anti-collision beam structure, and relates to the technical field of automobile safety; it comprises two parallel distributed main anti-collision beams and a secondary anti-collision beam, both sides of the secondary anti-collision beam are provided with an integrated welded connecting beam, the outside of the connecting beam is provided with an energy absorption box, and the two ends of the main anti-collision beam are slidably arranged on the inner wall of the connecting beam; the ends of the two connecting beams away from the secondary anti-collision beam are integrated with the secondary side beams, and the secondary side beams and the secondary anti-collision beams are on the same arc line; the ends of the two connecting beams away from the main anti-collision beams are provided with main side beams, and the main side beams and the main anti-collision beams are on the same arc line; the present invention improves the safety performance of the automobile through the double anti-collision structure of the main anti-collision beam and the secondary anti-collision beam, and the main anti-collision beam can be buffered and expanded within a certain range, which greatly reduces the impact force when the automobile collides, and ensures the stability of the main anti-collision beam.

The invention relates to a safety air bag ignition control method and device, computer equipment, a storage medium and a computer program product. The method comprises the steps that the running state of the automobile safety air bag control system is configured through the safety control state machine; under the condition that the running state is the normal state, the ignition function of the automobile safety air bag control system is configured to be in a forbidden state through a safety control state machine; in response to the fact that the automobile safety air bag control system is powered on for the first time and / or a watchdog error is detected, the running state is switched to a watchdog error protection state from a normal state through a safety control state machine; and under the condition that the operation result of the sensor data processing unit exceeds a preset threshold value, the operation state is switched from the normal state to the safety air bag ignition enabling state through the safety control state machine, and the ignition function is switched to the starting state. By adopting the method, the low-delay and high-precision response requirements of the chip on the ignition control instruction can be met.

The invention discloses an intelligent driving fatigue evaluation method and system, and relates to the technical field of automobile safety, and the method comprises the steps: obtaining the physiological data of a driver in a driving scene; the physiological data comprises myoelectricity data, heart rate data and respiratory rate data; calculating a driving fatigue evaluation index according to the physiological data; the driving fatigue evaluation indexes comprise physical load, alertness and cognitive load; and according to the driving fatigue evaluation index, calculating a fatigue driving comprehensive evaluation index by adopting a weight method. According to the method, psychological fatigue and physiological fatigue are comprehensively considered, and from three dimensions of physical load, alertness and cognitive load, indexes such as an electromyographic signal root-mean-square value, an electromyographic signal integral value, a heart rate mean value, a root-mean-square value of a whole-course adjacent NN interval difference, a ratio of heart rate variability low-frequency power to heart rate variability high-frequency power and heart rate breathing cross consistency are synthesized; the driving fatigue evaluation is carried out by adopting a weight method, so that the accuracy and objectivity of the driving fatigue evaluation can be effectively improved.

The invention discloses a safety protection method and system based on a multi-level automobile Internet of Things, and belongs to the field of automobile safety protection, and the method specifically comprises the steps: collecting and encrypting vehicle and environment data through an encryption sensor network, and guaranteeing that the data is safely transmitted to the local through quantum encryption communication; the local processing unit processes the data by using a reinforcement learning AI decryption algorithm, and recognizes the driving risk in combination with machine learning; the risk assessment model based on multi-source information fusion systematically assesses the risk and optimizes and generates a protective measure strategy; when a risk is encountered, the Internet of Things technology instantly triggers early warning and executes protection, meanwhile, vehicle data are uploaded to the cloud in real time, a safety auditing mechanism is established, records are comprehensively monitored, and vehicle driving safety and data privacy protection are ensured.

The invention discloses an active and passive safety fusion evaluation weight coefficient determination method and system, and relates to the technical field of automobile safety evaluation, and the method comprises the steps: obtaining active safety data and passive safety data; combining the active and passive data to obtain total sample data; constructing an analytic hierarchy model and a judgment matrix of each hierarchy; calculating a total level sequence of all indexes in the scheme layer to obtain a weight value of each index; performing weighted scoring on each data sample to obtain a total score; constructing a multi-layer perceptron model; and extracting the final weight of each index. According to the method, the vehicle speed after braking of the vehicle active safety system is taken as the collision speed of human-vehicle collision simulation in the passive safety system, and an active safety index and a passive safety index are associated to carry out active and passive safety fusion evaluation; and the index weight coefficient value for fusion evaluation is extracted through an analytic hierarchy process and construction of a multi-layer perceptron model, so that the data accuracy is high, the objectivity is high, and the comprehensiveness is high.

The invention discloses a wheel falling-off early warning system, relates to the technical field of automobile safety, and solves the technical problem that the wheel falling-off early warning efficiency is low due to the fact that abnormal judgment is carried out by calculating a state coefficient of a wheel and comparing the state coefficient with a fixed threshold in the prior art to cause a false alarm condition in abnormal recognition of wheel falling-off. The method comprises the steps of obtaining wheel data, vehicle data and road surface data; calculating a wheel wear coefficient according to the historical wheel data and the historical vehicle data; calculating a comprehensive abnormal coefficient of the wheel after calculating an external abnormal coefficient according to the wheel data; generating an alarm signal according to the comprehensive abnormal coefficient; according to the technical scheme, a prompt is made according to the alarm signal, factors in the aspects of wheel abrasion, wheel vibration and the like are considered in factors affecting wheel falling, related threshold values are dynamically adjusted according to the running states of the wheels on different roads, the false alarm situation during running on bumpy roads can be reduced, and meanwhile the wheel falling early warning efficiency is improved.

An OTA security update method and system for intelligent connected vehicles are provided. The method includes: the downloaded software update packet from a CDN to UC-master is decrypted, and verified for the first time through signature verification; for the secondary verification, decomposing a current software update packet into a plurality of sub-packets; calculating HASH values of the sub-packets in sequence; thereafter, constructing a Merkle tree according to these HASH values; calculating a root HASH value of the Merkle tree; after the sub-packets are transferred from a UC-master to ECU-UAs through a gateway or a domain controller, recalculating the HASH values of the sub-packets; reconstructing the Merkle tree according to these HASH values; recalculating the root HASH value of the Merkle tree; comparing the two HASH values; if they are equal, starting a normal update procedure; otherwise, terminating this OTA update by the UC-master immediately.

The utility model discloses a side punching die for an exhaust hood of an automobile safety air bag. The side punching die comprises an upper die and a lower die, an exhaust hood is arranged between the upper die and the lower die, and the upper die and the lower die form a side punching hole in the exhaust hood; the upper die comprises an upper supporting part; the upper mold core is connected to the upper supporting part; the elastic upper die wedge is connected to the upper supporting part; the lower die comprises a lower supporting part; the unloading plate is connected with the lower supporting part, and the top of the unloading plate is in contact with a flange on the exhaust hood; the lower die wedge is connected with the lower supporting part; the lower die core is arranged in the lower supporting part, is connected with the lower die wedge and is connected with the unloading plate; one end of the side punch is in sliding connection with the lower die core, and the other end of the side punch makes contact with the lower die wedge and is used for forming a side punched hole; the elastic side sliding block is connected in the lower supporting part in a sliding manner, is linked by the elastic upper die wedge and is used for pressing the outer wall of the cover cylinder; therefore, the technical problems that the machining difficulty is relatively large, and chippings and burrs are clamped in the mold, so that the mold is damaged are solved.

The invention relates to automatic assembling and riveting equipment for a steel wire rope and a support of an automobile safety belt, a steel wire rope bending device comprises a bending track, a bending driver, a bending seat, a bending clamping jaw, a bending table and a closing piece, and the bending driver is arranged at one end of the bending track and drives the bending seat to slide along the bending track; the bending clamping jaw is arranged on the bending seat and used for clamping a steel wire rope, the bending table is arranged at the other end, opposite to the bending driver, of the bending rail, a U-shaped block is arranged on the bending table, rolling wheels are arranged at the ends of the U-shaped block respectively, and rolling grooves opposite to the steel wire rope are formed in the rolling wheels. The folding pieces are arranged on the two sides of the bending rail correspondingly and fold and bend the steel wire rope.

The invention provides an automobile emergency response message processing method based on a Beidou short message, and relates to the technical field of intelligent automobile safety, and the method comprises the steps: S1, monitoring whether an automobile fault or accident index is generated or not in real time; s2, automatically triggering or manually triggering the generation of a short message used by communication in a vehicle fault state; s3, compressing the generated short message into a data packet, and uploading the data packet to a Beidou satellite; s4, sending the information to a preset rescue platform through a Beidou satellite communication module; the vehicle state acquisition module, the Beidou short message communication module, the trigger control unit and the message generation engine are applied to the automobile emergency response message processing method. According to the technical key points, an optimal satellite combination is automatically selected to carry out positioning calculation through a Beidou / GPS dual-mode positioning mode, the reliability of position data can be improved, the coverage range is wide, the dependence of manual operation is reduced through an automatic triggering mechanism, and the probability of personnel survival is improved.

The utility model discloses an automobile safety belt toughness performance detection device, which relates to the technical field of automobile part detection devices and comprises a workbench, auxiliary grooves are formed in the front side and the rear side of the surface of the workbench, and a guide groove is formed in the middle of the upper portion of the surface of the workbench. Supporting plates are fixedly arranged at the positions, located at the two ends of the guide groove, above the surface of the workbench, and fixing mechanisms are arranged above the opposite sides of the surfaces of the supporting plates. Compared with an existing common automobile safety belt toughness performance detection device, the automobile safety belt toughness performance detection device can conveniently and effectively fix a safety belt, the safety belt is tensioned and stretched along with toughness detection, the safety belt can rotate towards one side of the middle through the clamping teeth, and the safety belt cannot rotate due to limiting of the rear end of the pressing plate and the bottom plate; therefore, even in the tensioning and stretching detection process of the safety belt, the fixing firmness is kept, the safety belt is prevented from loosening, and the stability of the safety belt in the testing process is greatly improved.

The invention discloses a method for placing a dummy in a large-inclination-angle lying posture. The method comprises the steps that S1, a backrest angle coordinate, a cushion angle coordinate and an H-point coordinate mean value of a test seat at a target position are obtained; s2, keeping the included angle between the backrest and the cushion unchanged, rotating the test seat around the first mark point until the cushion angle of the test seat reaches a preset angle, and defining the posture as a cushion angle standard position posture; s3, acquiring a backrest angle and a second mark point coordinate under a cushion angle standard position posture, and calculating a cushion angle standard position posture reference pelvic angle; s4, calculating a corner difference of a cushion angle standard position posture and a target position reference pelvic angle; s5, keeping the included angle between the backrest and the cushion unchanged, and rotating the test seat around the first mark point until the second mark point, the backrest angle and the cushion angle return to the target position; s6, calculating a dummy target pelvic angle; and S7, placing the dummy on the test seat. The problems that errors exist in automobile safety evaluation data of the dummies in the large-dip-angle lying posture, and evaluation is not accurate are solved.

The invention discloses a vehicle blind area monitoring system and a truck, and relates to the technical field of automobile safety. The system comprises an electronic control device, a camera device, a projection device and a sensor. After a truck provided with the system is started, the camera device obtains a real-time video picture of a driving blind area of the truck; the sensor emits a detection signal outwards, receives a reflection signal after the detection signal is reflected by an obstacle, and generates an electric signal based on the reflection signal; the electronic control device processes the electric signal and determines the distance between the obstacle and the truck; when the distance is smaller than or equal to a preset distance threshold value, a driving signal is sent to the projection device; and after the projection device receives the driving signal, a real-time video picture of the driving blind area is displayed on a windshield of the truck. Therefore, the obstacle appearing in the driving blind area can be efficiently detected, the distance between the obstacle and the truck is smaller than or equal to the preset distance threshold value, and the obtained real-time picture with the obstacle is presented on the windshield of the truck.

The invention discloses a vehicle RM I anti-rolling regulation and control method fusing load and tire pressure estimation, and belongs to the field of vehicle safety, and the method comprises the following steps: S1, obtaining vehicle chassis pressure data, suspension displacement data and tire pressure data in real time; s2, estimating and optimizing load distribution based on the acquired data; s3, realizing adaptive adjustment of an RM I trigger threshold based on an optimized load distribution estimation result and a driving condition; and S4, judging whether a trigger threshold value is reached or not under the current driving working condition, if so, executing a preset anti-rolling control strategy, and otherwise, returning to the step S1 for continuous monitoring. According to the vehicle RM I anti-rolling regulation and control method fusing the load and the tire pressure estimation, the load distribution is accurately estimated through multi-source data fusion, high-precision and intelligent regulation and control of vehicle rolling prevention are achieved in combination with self-adaptive threshold adjustment and a multi-system cooperative control strategy, and the safety and stability of driving under complex working conditions are remarkably improved.

The invention discloses a high-integration intelligent ignition head device and an automobile safety communication power supply system thereof. The device comprises an input unit, a power management module, a communication module, a communication judgment module, an MCU, a voltage sensing module, a current sensing module, an ignition control module, an ignition element and a substrate, and an environment self-adaption unit, a dual-mode wireless energy supply unit and an optical fiber diagnosis channel can be additionally arranged. The system adopts the device, communicates with a central control unit through a redundant optical fiber bus and a double-wire bus, and further comprises the central control unit, a dynamic topology reconstruction unit and a pre-ignition energy distribution unit. Through digital signal control, multi-dimensional sensing module integration and a double-wire bus topological structure, ignition threshold multi-stage protection, state real-time monitoring and feedback, multi-ignition-head parallel independent control and miniaturized function integration are achieved, and the reliability, the intelligent degree and the driving efficiency of an automobile safety system are improved.

The invention discloses an ABS real-time self-adaptive control method and system based on hub sensing signal fusion, and relates to the field of automobile safety control. The method comprises the steps that S1, multi-source hub sensing signals of all wheels are synchronously collected; s2, calculating a hub response coupling factor based on the multi-source hub sensing signal; s3, calculating an instantaneous slip rate based on the coupling factor and the wheel speed in combination with vehicle dynamic parameters; s4, on the basis of the wheel speed, the braking torque and the tangential acceleration, the coupling factor and the instantaneous slip rate are combined, and the normal load is calculated; s5, calculating an adhesion coefficient according to the instantaneous slip rate, the normal load and the wheel speed; s6, according to the slip rate deviation, a fusion weight is generated in combination with the coupling factor, and the adhesion capacity of the whole vehicle is calculated; and S7, according to the adhesion coefficient, the normal load, the slip rate and the adhesion capacity of the whole vehicle, the target braking force is calculated, and the wheel braking strength is adjusted. By monitoring the state of the wheels in real time, the slip rate is accurately controlled, braking force distribution is optimized, and the response precision and stability of the ABS are improved.

The invention discloses a motor controller circuit system and a motor controller, and is applied to driving fault detection of the motor controller, the circuit system comprises a driving detection circuit, the driving detection circuit is respectively connected with a main controller and a driving circuit, and through the driving detection circuit, a first PWM signal sent by the main controller is firstly read; a second PWM signal output by the driving circuit is read back; secondly, comparing the first PWM signal with the second PWM signal and outputting a fault diagnosis result; and then, according to a fault diagnosis result, a driving circuit fault indication signal is output to the main controller, so that a safety state is output through the main controller. According to the technical scheme, on one hand, the fault of the driving chip can be diagnosed, and on the other hand, fault conditions such as failure of the driving circuit can be diagnosed, so that the coverage rate of fault diagnosis of the driving circuit is improved, and the safety integrity level of the automobile ASILD is further improved.

The invention discloses a car door collision reminding system and method based on fisheye camera image distortion correction, and relates to the technical field of car safety reminding. According to the system, scene images on the two sides of a car in the parking state are collected in real time through a fisheye camera, image calibration and distortion correction are carried out through an improved Harris corner detection algorithm, and the car door collision reminding system is obtained. In combination with a multi-task learning model of a convolutional neural network, the potential collision risk in the vehicle door opening process is analyzed in real time, the distance and height between an obstacle and a vehicle door are calculated through a signal processing module, a reminding module generates reminding signals of different grades, and the reminding signals are fed back to a driver in time through a vehicle display screen and a sound system. And the image display module marks the dangerous area and the dangerous level on the display equipment in real time. The system has wider visual angle coverage, higher detection precision and stronger environmental adaptability, effectively avoids the occurrence of vehicle door collision accidents, and is particularly suitable for narrow parking spaces, complex urban environments and high-density people flow areas.

As automotive security concerns are rising, the Controller Area Network (CAN)—the de facto standard of in-vehicle communication protocol—has come under scrutiny due to its lack of encryption and authentication. Several vulnerabilities, such as eavesdropping, spoofing, and replay attacks, have shown that the current implementation needs to be extended. Both academic and commercial solutions for a secure CAN have been proposed, but OEMs have not yet integrated them into their products. The main reasons for this lack of adoption are their heavy use of limited computational resources in the vehicle, increased latency that can lead to missed deadlines for safety-critical messages, as well as insufficient space available in a CAN frame to include a Message Authentication Code (MAC). By making a trade-off between security and performance, this disclosure overcomes the aforementioned problems of a secure CAN.

The invention relates to the technical field of biomechanical detection and automobile safety evaluation, and discloses an automobile collision dummy abdomen safety test device and method. The testing device comprises a human body feature modeling module which is used for establishing a target population abdomen parameterized model based on statistical analysis, determining a key size design domain covering target population percentile and constructing a target population metrology database; the abdominal mechanical property simulation module is used for obtaining a human tissue relative density distribution function based on the hyperelastic constitutive model, taking the density distribution function as an input parameter for manufacturing a gradient honeycomb structure and simulating human abdominal mechanical properties through relative density gradient distribution in the thickness direction; the multi-mode sensor integration module adopts a distributed intelligent sensing network architecture and is composed of a sensing layer, a transmission layer and a processing layer. By integrating pressure, deformation, acceleration and tissue stress sensors and combining a real-time feedback algorithm, collision parameters are dynamically optimized, and the test precision and the biological fidelity are improved.

The utility model discloses a window breaking hammer for double-layer laminated glass, which relates to the field of automobile safety instruments, and comprises a grab handle and a hammer head, the hammer head is provided with a tapered wedge-shaped part, the end part of the hammer head is provided with a conical tip, one side facing the grab handle is provided with a cutting structure for cutting a glue film, the glass is broken and punctured through the conical tip, so that the front section of the hammer head enters, and the glass is broken through the cutting structure. And then, the grab handle is rotated by taking the non-penetrating part of the hammer head as a fulcrum, and the tough middle adhesive film is efficiently cut by the cutting structure according to the slope lever principle, so that the escape hole is quickly formed. In addition, an auxiliary sharp corner structure can be arranged at the tail part of the hammer head to cooperatively destroy the adhesive film; and a safety belt cutting device and an anti-falling flange are integrated on the grab handle or the hammer head, so that the multifunctionality and the operation safety are enhanced. The window breaking device solves the key problem that a traditional window breaking device cannot effectively process a laminated glass middle film, and is particularly suitable for automobile emergency window breaking escape.

The invention discloses an SRL-based intelligent networked automobile function degradation decision-making method and system. The method comprises the following steps: step 1, acquiring environment information and monitoring a trigger event; 2, grading the system risk assessment indexes of the trigger event monitored in the step 1, determining a corresponding automobile safety integrity grade according to an actual driving mode, and obtaining the system risk of the automobile; 3, according to the environment information collected in the step 1, integrating the risk fields of the static obstacles, the dynamic obstacles and the road boundaries, and utilizing a driving risk field model to obtain the driving risk of the vehicle; 4, describing the function degradation decision-making process of the intelligent networked automobile through a CMDP model to obtain an optimal function degradation strategy; wherein the state space S and the cost function of the CMDP model both comprise the system risk in the step 2 and the driving risk in the step 3. According to the method, efficient, safe and stable function degradation decision making of the intelligent network connection automobile in a complex and changeable scene can be achieved.