2637 results about "Emergency brake" patented technology

The invention provides a railway line monitoring alarm method and system, and relates to the technical field of computers, and the method comprises the steps: continuously collecting a dynamic monitoring data set comprising a track structure vibration waveform sequence, a track surface optical image sequence and an environment meteorological parameter sequence through a plurality of sensor nodes of a target railway line; carrying out multi-modal feature fusion processing on the dynamic monitoring data set, generating a comprehensive state evaluation matrix containing a vibration energy distribution vector and the like, carrying out risk alarm grade classification on the comprehensive state evaluation matrix by utilizing a preset track safety evaluation model, and outputting an abnormal event type code and an abnormal region position code; then, a multi-stage linkage control instruction set containing a train emergency braking triggering instruction and the like is generated based on the multi-stage linkage control instruction set, the multi-stage linkage control instruction set is synchronously transmitted to a central dispatching system, the central dispatching system is driven to execute rail blocking, train speed regulation and control and equipment maintenance operation according to instruction priorities, and comprehensive and intelligent monitoring and efficient alarm response to railway lines are achieved.

The invention discloses a container wharf hazardous chemical transport vehicle intelligent tracking and positioning system comprising a data acquisition module used for acquiring vehicle positioning, driving behaviors and environment state data; the data fusion and time synchronization module is used for performing time alignment on the multi-source data; the behavior modeling and trajectory prediction module is used for extracting driving behavior characteristics and predicting a driving trajectory; the risk assessment and anomaly detection module is used for calculating an anomaly score and predicting a driving risk; the security strategy optimization module is used for constructing a zero-sum game security control model and optimizing speed limit, path and early warning strategies; the remote control and intelligent intervention module is used for executing remote speed regulation, emergency braking, path optimization and alarm pushing in the intelligent dispatching system; and the cloud monitoring and data analysis module is used for storing a track, an environment, a driving score and a safety strategy and predicting a long-term risk trend. According to the invention, based on intelligent game and multi-modal fusion, accurate tracking and safety management and control of the hazardous chemical substance transport vehicle are realized.

The invention relates to the technical field of vehicle safety, and discloses a braking method and system based on vehicle automatic emergency early warning and braking and a storage medium. The method comprises the following steps: fusing multi-modal sensor data to generate a dynamic environment perception graph and calibrating the dynamic environment perception graph; generating a real-time risk distribution map and a potential collision probability prediction matrix based on the dynamic risk assessment model; carrying out matrix multi-stage decision optimization to generate emergency braking trigger conditions, and dividing early warning levels and scheduling according to the conditions and a risk map; and the braking system control parameters are adapted according to the early warning instruction set, and a final execution scheme is generated after verification. The system comprises a sensing module, an evaluation module, a decision module, an early warning module and an execution module. Electronic equipment and a computer readable storage medium can execute the method. Through multi-modal fusion, dynamic risk assessment, graded early warning and redundancy check, the safety performance of the vehicle in a complex environment is improved, accurate early warning and reliable braking are achieved, and the method is suitable for the technical field of vehicle safety.

The invention discloses an intelligent automobile longitudinal driving assistance system based on driving characteristics. The intelligent automobile longitudinal driving assistance system comprises a driver state and environment sensing module, a driver characteristic real-time identification module, an intelligent decision-making and mode switching module and a style self-adaption longitudinal control module. The driver state and environment perception module analyzes environment information and driving behavior characteristics by constructing an extended intelligent driver model, and defines acceleration deviation to perform driving style clustering. And the driver feature real-time identification module deploys the BP neural network model in an online system to realize real-time identification of the driving style. The intelligent decision-making and mode switching module intelligently assesses risks in combination with driving styles and environment information, and dynamically switches four modes of cruise control, car following, early warning and emergency braking. And the style self-adaptive longitudinal control module adaptively adjusts a control strategy according to the driving style and the expected acceleration, and converts the expected acceleration into driving torque or braking pressure through a dynamic weight mechanism, so that personalized longitudinal control is realized.

The invention discloses an unmanned vehicle intelligent obstacle avoidance method and system based on a multi-modal sensor, and relates to the field of automatic driving and intelligent traffic. According to the technical key points of the invention, data of a laser radar and a depth camera are aligned through a space-time registration module; the laser radar point cloud is preprocessed, obstacle point cloud is segmented, fusion clustering is carried out in combination with three-dimensional semantic seed points output by a depth camera, and an obstacle cluster with a semantic tag is generated; and calculating a three-dimensional directed bounding box (OBB) of an obstacle, dynamically adjusting a safety distance according to the speed of the vehicle, expanding the OBB of the vehicle, and carrying out collision detection by adopting a separation axis theorem. When a collision risk is detected, the system sequentially triggers a first-level early warning instruction and a second-level emergency braking instruction, and safe and efficient unmanned vehicle dynamic obstacle avoidance is achieved. According to the method, the advantages of multiple sensors are fully utilized, the obstacle detection precision and the response speed are effectively improved, and reliable technical support is provided for application of the unmanned driving technology in a complex road environment.

The invention belongs to the field of data processing, and discloses a test method for pedestrian trajectory prediction and emergency braking in an automatic driving platform. Comprising the steps of segmenting a real road environment in advance, obtaining grades of small road segments according to calculation of segmentation coefficients, carrying out resource allocation on the small segments according to the grades, and collecting multi-source heterogeneous data; importance optimization is introduced into a Transform model, possible prediction trajectories of individuals are generated, graph data are constructed by using the possible prediction trajectories, an Autoencoder anomaly detection mechanism is introduced, high-risk trajectories are screened out, and high-risk scenes are output; combining the road geometric model with the high-risk scene to form a scene library, loading the scene in a simulation platform, carrying out automatic driving test, carrying out virtual-real data cross validation in combination with real vehicle test data, and obtaining performance evaluation of an algorithm; pedestrian track prediction and emergency braking in the automatic driving process are achieved.

The invention discloses a collision early warning method and device based on a fusion sensor and a medium, and relates to the technical field of data processing.The method comprises the steps that radar point cloud information in front of a vehicle is collected through a millimeter-wave radar, and image information in front of the vehicle is collected through a camera device; the radar point cloud information in front of the vehicle and the image information in front of the vehicle are fused through a three-dimensional environment analysis model to obtain a three-dimensional environment in front of the vehicle, and the three-dimensional environment in front of the vehicle comprises obstacle distribution coordinates; traversing the obstacle distribution coordinates to perform collision risk assessment to obtain a collision risk level; when the collision risk level is larger than or equal to a first risk level threshold value, emergency braking is executed; and when the collision risk level is greater than a second risk level threshold, generating a collision early warning signal for early warning, thereby achieving the technical effects of initially identifying a target contour through the image, executing analysis modeling of part of point cloud data in a targeted manner through the radar point cloud, reducing the calculation amount and further improving the early warning timeliness.

The invention discloses a semitrailer automatic emergency braking control system and method based on vehicle-road cooperation. The system comprises an information acquisition module and a multi-stage AEB early warning module. The invention provides a semi-trailer braking control system, a multi-stage AEB braking module, an inverse braking module and a PID control module, and provides a braking control method using the control system, and accurate multi-stage early warning and multi-stage braking control are output for a semi-trailer under different road situations based on the vehicle-road cooperation technology. The brake deceleration output by the control strategy is converted into brake master cylinder pressure by constructing an inverse brake module; and based on a PID control module, the error between the ideal expected braking deceleration planned by the control strategy and the actual braking deceleration of the semi-trailer actually running under each working condition is reduced. The semitrailer can accurately judge and output accurate control braking deceleration according to different road scenes such as various road attachment conditions, and the requirement for automatic emergency braking control of the semitrailer under the complex road working conditions such as a low attachment road surface, a curve and a ramp is met.

The air quality intelligent monitoring system based on sensing data feedback comprises a sensing array module, a preprocessing module, a risk assessment module, an energy consumption decision module, a mode switching module, a data fusion module and a linkage module. The sensing array module generates an environment parameter signal; the preprocessing module generates a standardized characteristic signal; the risk assessment module receives the standardized characteristic signal and forms an early warning instruction signal; the energy consumption decision module analyzes the change gradient of the standardized feature vector and generates an activation instruction according to the vector stability; the mode switching module generates a state configuration signal and feeds back the state configuration signal to the sensing array module; fusing the data to generate a diffusion prediction signal; the linkage module generates an emergency braking instruction and transmits the emergency braking instruction back to the data fusion module. The intelligent air quality monitoring system based on sensing data feedback can solve the problem that intelligent linkage of multi-source pollution monitoring, dynamic energy saving and real-time early warning of industrial places is poor.

The invention provides a vehicle driving control method and device for a backlight scene, equipment and a medium. The method comprises the steps that multi-source information of a target vehicle is acquired in real time; performing fusion calculation on the multi-source information to obtain a current backlight risk index of the target vehicle; determining a driving assistance strategy or an automatic emergency braking strategy based on the backlight risk index; and controlling the target vehicle according to the driving assistance strategy or the automatic emergency braking strategy. According to the vehicle driving control scheme for the backlight scene, the backlight risk index is generated by fusing the multi-source information, the backlight scene is accurately judged, the corresponding driving assistance or automatic emergency braking strategy is formulated, the driving safety and reliability of the vehicle in the complex backlight environment are improved, and the driving safety of the vehicle in the complex backlight environment is improved. The problems that in the prior art, due to dependence on a single sensor in a backlight scene, the target recognition precision is low, a dynamic adaptation mechanism is lacked, and a braking strategy is difficult to pre-judge and adjust in advance are solved.

The invention belongs to the technical field of control valve adjustment, and particularly relates to a military and civilian dual-purpose ship electric control valve actuator which comprises a target analysis module, a dynamic compensation module, a parameter transmission module, a closed loop calibration module and an emergency braking module. Valve displacement increments and initial motor rotating speed parameters are distributed for all the sub-windows, the comprehensive influence of gear return difference, thermal deformation, friction and vibration interference on valve displacement is effectively considered in the execution process of the sub-windows, a mechanism coupling compensation factor with a dynamic learning optimization mechanism is generated, displacement errors are combined to be superposed to the rotating speed parameters of the next window, and a dynamic learning optimization mechanism is generated. According to a double-layer correction framework of child window dynamic compensation and tail end closed-loop calibration, technical closed-loop from local interference suppression to global precision guarantee is achieved, an emergency braking module is additionally arranged to avoid the risk of out-of-control displacement caused by sudden load impact, and efficient and safe operation of a ship is effectively guaranteed.

The invention relates to an automatic emergency braking control method and device, computer equipment and a vehicle. The method comprises the following steps: acquiring own vehicle state information, and determining whether an own vehicle meets a preset effective condition or not according to the own vehicle state information; under the condition that the own vehicle state information meets a preset effective condition, target vehicle state information is obtained, and the longitudinal collision time between the own vehicle and the target vehicle is calculated according to the target vehicle state information and the own vehicle state information; under the condition that the longitudinal collision time meets a preset collision condition, determining that the target vehicle is a short-distance early warning target, and giving an alarm; and detecting the definition of the current lane line, and controlling the vehicle to brake and decelerate according to the current road curvature under the condition that the current lane line is not clear and the vehicle is in a stable straight moving state. The method can adapt to vehicle requirements, reduces the false triggering probability, avoids vehicle instability, and improves the vehicle driving safety and reliability.

The invention discloses an injection molding machine fault emergency safety protection control system, which belongs to the technical field of fault emergency processing, and comprises a sensor system, an intelligent data analysis module, a self-adaptive emergency control unit, an alarm and display module and a safety protection module. The sensor system collects operation data of key components of the injection molding machine in real time; the intelligent data analysis module performs data analysis and fault diagnosis by using machine learning; the self-adaptive emergency control unit automatically adjusts parameters according to a diagnosis result, and emergently stops or recovers equipment operation; the alarm and display module sends an alarm signal in time and displays related information; the safety protection module guarantees the safety of equipment and personnel through an emergency braking sub-module, a protective fence sub-module, a fire alarm sub-module, a fire extinguishing sub-module and the like. All the modules work cooperatively, faults are effectively monitored and diagnosed, safe and stable operation of the injection molding machine is ensured, the production efficiency is improved, and the occurrence probability of safety accidents is reduced.

In various examples, a line of sight (LOS) filter may be used to determine whether or not a detected object represents a potential collision risk, filter out detected objects that are deemed not to be a collision risk, and provide a representation of the remaining detected objects for evaluation by one or more downstream automatic emergency braking (AEB), collision mitigation braking systems (CMBS), and / or other modules of an ego-machine. For example, the LOS filter may use an estimated position of a detected object to derive a corresponding LOS angle between the heading of the ego-machine and the detected object, and apply one or more thresholds based on the LOS angle to identify detected objects that are non-collision risks. As such, the LOS filter may remove non-collision risks from consideration by the downstream AEB, CMBS, and / or other module(s).

The invention discloses an intelligent safety control method for an exhibition, and the method comprises the steps: multi-sensor data fusion, real-time modeling and prediction, intelligent obstacle avoidance and planning, emergency braking and safety protection, cooperative control and communication, risk assessment and early warning, learning and self-adaption, and monitoring and manual intervention. The motion states of actors and stage equipment can be monitored and predicted in real time, and collision accidents are effectively avoided. And meanwhile, through the arrangement of an emergency braking system and protective equipment, the safety in the exhibition process is further improved. Besides, the control system has learning ability and adaptive ability, can automatically adjust safety control parameters according to different performance contents and stage arrangements, and improves the flexibility and practicability of the system.

The invention provides an intelligent vehicle lane changing trajectory planning method based on model predictive control, which comprises the following steps: firstly, sensing environment information in real time, calculating an emergency braking distance and an expected safety distance, and deciding behaviors of an intelligent vehicle; secondly, on the basis that a vehicle point quality model serves as a prediction model, an improved artificial potential field method and a model are combined to predict, control and plan a lane changing track, and the current optimal lane changing reference track selected from the sine lane changing reference track cluster is included; and finally, tracking the trajectory by adopting a trajectory tracking controller based on model predictive control. The improved artificial potential field method is adopted to fully adapt to the position, speed and acceleration changes of surrounding obstacle vehicles, the dynamic obstacle avoidance effect is remarkable, and the lane changing safety of the intelligent vehicle is guaranteed; the situations of following the front vehicle, canceling lane change and the like are also considered, and the adaptive scene is wider.

The invention provides a vehicle control method and device, a vehicle and a storage medium, the method is applied to the field of vehicles, and the method comprises the steps that under the condition that the vehicle is in a direct drive mode, whether the vehicle is in an emergency braking working condition or not is judged; if the vehicle is in the emergency braking working condition, it is determined that the vehicle needs to be controlled to exit from the direct drive mode, and a target torque reduction gradient in the process that the vehicle exits from the direct drive mode is determined; and according to the target torque reduction gradient, torque reduction of the engine is controlled, and under the condition that the output torque of the engine is reduced to the target torque, a clutch of the vehicle is controlled to be in an open state, so that the vehicle is controlled to exit the direct drive mode. According to the method, the vehicle can be controlled to exit the direct-drive mode in advance, the problem of clutch opening delay is solved, the situation that an engine is reversely dragged is avoided, and the safety of the vehicle is improved.

The invention belongs to the technical field of intelligent automobiles, and discloses a collision early warning method, device and equipment for an electric unmanned vehicle. The method comprises the following steps: acquiring environmental information data around a vehicle in real time through a sensor; preprocessing the acquired environment information data to obtain effective data which can be used for subsequent analysis; calculating a predicted track of the vehicle and a motion track of the target object according to the obtained effective data; calculating the probability of collision by using a collision probability model according to a calculation result; when the calculated collision probability exceeds a preset threshold value, an early warning signal is sent to a vehicle control system; and after the early warning signal is received, the vehicle control system takes corresponding emergency braking measures to avoid collision. According to the invention, by using the sensor and the collision probability model, comprehensive monitoring of the surrounding environment of the electric unmanned vehicle is realized, the potential collision risk is predicted in advance, and the safety of vehicle driving is improved.

The invention discloses an aggregate loading size identification and detection control system based on radar identification, and particularly relates to the field of constructional engineering, which comprises a multi-source sensing module, a feature extraction module, an index calculation module, a threshold judgment module, a logic decision module and a control execution module. Characteristic parameters such as phase difference and coordinate deviation are extracted through multi-modal processing, four kinds of comprehensive indexes such as volume uniformity and overload risk are generated, risk grading early warning is achieved through a three-level threshold system, a control instruction is generated in combination with a state machine model and a logic gate strategy, and the system is provided with an electro-hydraulic proportional valve and a redundant braking mechanism. The system supports multi-stage response from rate adjustment to emergency braking, has the characteristics of multi-dimensional dynamic monitoring, intelligent decision making and environment self-adaption, effectively improves the safety and automation level of bulk cargo loading operation, and is suitable for continuous operation requirements of complex industrial scenes.

Provided are a method and system for auxiliary emergency braking after a braking failure, and an electronic device, a computer-readable storage medium, a computer program product and a computer program. The method comprises: obtaining a braking system failure factor parameter numerical value on the basis of a braking system health state observer or a fault diagnosis module of a current vehicle; constructing a braking risk decision function on the basis of a braking system failure factor and related data of the current vehicle to calculate a current braking risk value, and obtaining a desired lateral displacement of the current vehicle on the basis of the current braking risk value and steering system data; constructing an integral heuristic barrier Lyapunov function on the basis of the desired lateral displacement of the vehicle and vehicle state information after decision making, and obtaining a desired vehicle traveling yaw angle on the basis of a calculation result of the function; and converting the desired vehicle traveling yaw angle into an input front wheel steering angle value of the current vehicle, and converting the input front wheel steering angle value of the current vehicle into steering-assist electric motor output data, so that a steering system intervenes in and controls safe braking after a braking process fails.

The invention relates to the technical field of intelligent traffic, and discloses a traffic processing method and system, a terminal and a storage medium, and the method comprises the steps: dynamically adjusting traffic lights and public traffic scheduling information based on multi-dimensional traffic data and a first algorithm model; wherein the multi-dimensional traffic data comprises traffic prediction data, environment state data and vehicle running state data; and acquiring navigation path planning information and emergency braking information of each vehicle based on the multi-dimensional traffic data, the traffic light adjustment condition, the public traffic scheduling information and the vehicle operation information. By means of the method, safe and efficient traffic signal adjustment, public traffic scheduling and path planning work can be achieved.

The invention discloses a vehicle driving early warning and braking control method and system based on visible light and infrared light, and belongs to the field of image processing and vehicle control. The method comprises the following steps: acquiring bimodal data, namely visible light data and infrared data, by using a visible light camera and an infrared thermal imager, and preprocessing the bimodal data; feature fusion is carried out on the preprocessed bimodal data, and a YOLOV5 model is input for training, so that a Yolo-DMFF-object model is obtained; a Yolo-DMFF-object model is used for detecting a target object and measuring the distance; according to the detected target object and distance, the emergency braking module is controlled to give out voice early warning and emergency braking; according to the method, object identification and vehicle early warning braking functions are fused through fusion of identification and distance measurement technologies, function connection from target detection to vehicle control is realized, an efficient and reliable solution is provided for intelligent driving in a complex traffic environment, and driving safety, response speed and driving convenience are improved.

The invention relates to a resetting method and system for a zero-pressure seat of a vehicle, and the method comprises the steps: judging whether a passenger is on the zero-pressure seat or not and whether the zero-pressure seat is in a zero-gravity state or not through a seat controller, and obtaining a judgment result; when the judgment result is that the passenger is on the zero-pressure seat and is in the zero-gravity state, the seat controller sends the judgment result to an automatic emergency braking system, so that the automatic emergency braking system sends a pre-collision signal to the seat controller after the vehicle has a collision risk and triggers emergency braking; the seat controller receives the pre-collision signal; and the seat controller generates a reset signal according to the pre-collision signal and sends the reset signal to the driving mechanism, so that the driving mechanism drives the backrest to rotate by a preset angle, and the zero-pressure seat is reset to the safe state from the zero-pressure state before the vehicle collides. According to the resetting method and system for the zero-pressure seat of the vehicle, before the vehicle collides, the zero-pressure seat is quickly reset from the zero-gravity state to the safe state, and therefore passengers can receive the collision in a relatively safe posture.

The invention discloses an automatic emergency braking control method and device based on a black spot technology and a vehicle. When the vehicle enters a black spot area, the vehicle obtains an optimal active braking parameter to correct the active braking parameter of the vehicle, and automatic emergency braking is executed based on the corrected active braking parameter; the method for obtaining the optimal active braking parameters comprises the following steps: dynamically delimiting a black spot area according to multi-dimensional data when emergency braking of each vehicle is triggered; obtaining the multi-dimensional data in the black spot area; and obtaining the optimal active braking parameters based on the vehicle speed, deceleration fluctuation, braking distance, vehicle weight and environment information during emergency braking. And the optimal active braking parameter when emergency braking is triggered in the black spot area is obtained. According to the method, the black spot technology is combined, the black spot area is established, ADAS program upgrading is conducted on the vehicle entering the black spot area, the vehicle can better adapt to the vehicle condition and the road condition in the area, the active braking curve is optimized, the comfort degree is improved, the situation that braking is not stopped after the automatic emergency braking function is triggered is reduced, and safety is improved.

The invention provides a train operation control method and device under severe weather, and the method comprises the steps: obtaining train idling slip information sent by a train automatic protection subsystem or a train control and management system, and determining a rail slippery state according to the train idling slip information; determining a severe weather mode instruction of the target train based on the rail slippery state and the weather state; and sending a severe weather mode instruction to the train automatic protection subsystem or the train control and management system, wherein the severe weather mode instruction is used for indicating a target train in the target operation area to enter a severe weather mode. According to the train operation control method and device in the severe weather, the severe weather mode instruction of the target interval is determined according to the wet and slippery state of the rail and the weather state, safety protection can be carried out on the guaranteed emergency braking rate in the severe weather, and the situation that due to the fact that the train braking adhesion coefficient is reduced to break through the existing design boundary, the train operation efficiency is improved is avoided. Therefore, the safety of train operation is improved.

An electrified vehicle includes a human-machine interface to enable a towed vehicle mode to enable electric pumps to lubricate and / or cool vehicle components and to disable driver assistance features while the electrified vehicle is being towed by another vehicle. The electrified vehicle includes a drivetrain having an electric machine configured to provide propulsive torque to vehicle wheels, a high-voltage traction battery selectively connected to the electric machine, a battery powered fluid pump configured to pump fluid to the drivetrain, and a controller programmed to, after receiving a signal enabling towed vehicle operation of the electrified vehicle, control operation of the battery powered fluid pump while the electrified vehicle is being towed. The controller may disable one or more driver assistance features and alerts such as automatic emergency braking, automatic shifting of the drivetrain, automatic parking brake operation, automatic headlights, automatic steering, cruise control, parking assistance, and external object distance detection.

The invention relates to a method (16) and an assistance system (11) for supporting at least partially automated longitudinal control (23) of a motor vehicle (4). The invention further relates to a correspondingly equipped motor vehicle (4). In the method (16), objects that appear relevant for the longitudinal control (23) of the motor vehicle (4) are identified independently of one another based on sensor data (19, 20) from various environmental sensors (7, 8). It is then also determined separately whether the respective relevant objects make it necessary to exceed a predetermined maximum permissible standard braking acceleration outside of emergency braking maneuvers in order to avoid a collision. Only if this is the case in both instances is the exceeding of this otherwise maximum permissible standard braking acceleration enabled for an automated longitudinal control system (9) of the motor vehicle (4) by a corresponding control signal (27).

The invention relates to an electric drive semitrailer grading AEB control decision-making method considering road surface factors, and the method comprises the following steps: S1, enabling a vehicle to obtain front vehicle information and road surface information through a sensor, a high-precision map and other ways, calculating a correction adhesion coefficient through combining with the state of the vehicle, and determining the maximum gradient limit; s2, outputting a maximum braking deceleration correction factor through fuzzy control by taking the correction adhesion coefficient and the gradient as input; s3, according to the advantages and disadvantages of the road surface working conditions and the maximum braking deceleration correction factor, the maximum braking deceleration is calculated according to the working conditions; s4, calculating a safe braking distance and collision time according to the current state of the vehicle and the speed and distance of the front vehicle; and S5, the collision time is used for early warning decision making, the safety braking distance is used for emergency braking decision making, the corrected maximum braking deceleration serves as a full-force braking target value, and graded AEB control is achieved. According to the method, road surface factors are fully considered, vehicle safety can be guaranteed under different attachment conditions and slope road surfaces, and the braking stability is remarkably improved.

The invention discloses a method for reducing the loss of an automatic driving vehicle collision test device, and the method comprises the following steps: obtaining preset test vehicle parameters which comprise the maximum deceleration amax of an automatic emergency braking system, the test vehicle speed vtest and the communication system delay time t delay; when an emergency braking system of the test vehicle is triggered, emergency avoidance triggering time t triggering is calculated through a formula t triggering = v test / amax + t delay; after position data of the test vehicle and the background target object are collected in real time, the real-time relative distance D is calculated, and the collision time t collision is calculated through a formula t collision = D / v test; and when t collision is less than or equal to t trigger, driving the background target object to move away from the collision direction through the mechanical execution mechanism. Before collision, the target object is actively driven to be away from the collision direction, and structural damage caused by direct collision can be avoided.

The invention relates to the technical field of photovoltaic module manufacturing, in particular to a lamination process parameter self-adaptive regulation and control system and method. Comprising a multi-source sensing module, an edge calculation module and a dynamic execution module, and temperature, pressure and thickness data of a lamination process are collected in real time through an infrared thermal imaging unit, a distributed pressure sensing unit and an ultrasonic thickness monitoring unit; the edge calculation module adopts a CNN-LSTM hybrid model to perform spatial-temporal feature fusion analysis on the multi-source data, predicts a defect risk level and generates a regulation and control instruction; the dynamic execution module achieves dynamic parameter adjustment through the partition temperature control unit, the hydraulic servo unit and the emergency braking unit, the problems of parameter stiffness, defect detection lag and the like of a traditional lamination process are solved, the AOI spot check defect rate is reduced to 0.6% from 1.3%, the lamination period is shortened by 3 minutes, and the production efficiency and the product quality are remarkably improved.