1343 results about "Cockpit" patented technology

An attitude display system for use in an aircraft has at least one display unit visible by a pilot within a cockpit. A symbology generator is configured for receiving input from at least one attitude sensor and generating symbology image data representative of a pear-shaped attitude indicator, distorted vertically to represent a pitch of the aircraft and rotated to represent a roll angle of the aircraft. The symbology generator may further be configured for adding a horizontal line that represents a horizon, a regular trapezoid representing a downward gravity vector at a base of the trapezoid, a pitch angle of the aircraft, split wings representing an angle of attack of the aircraft, and a stall warning in a sawtooth crack shape. A tail portion of a T-shape with the curved top edge is itself curved in a direction opposite that of an aircraft spin direction.

The invention provides a multi-screen cabin entertainment system, and relates to the technical field of embedded systems and intelligent cabins, and the multi-screen cabin entertainment system is characterized in that an application layer is deployed with a plurality of cabin entertainment applications, and when the application layer is started, content rendering requests are sent out respectively; the hardware layer is provided with a development board, is provided with a CPU core cluster and a coprocessor, and is connected with different cabin display screens through different video output interfaces. The system layer respectively distributes an independent thread and an independent frame buffer area for each content rendering request on the CPU core cluster, and establishes a mapping relation between each frame buffer area and each video output interface; and sending operation result data of each independent thread to a coprocessor for rendering, correspondingly storing a rendering result in a frame buffer area, and then sending the rendering result to a cabin display screen for display through a video output interface. The method has the advantages that on the premise that the number of hardware coprocessors is not increased, complete separation of multi-screen rendering threads and frame buffer is achieved, and multiple cockpit entertainment applications can run at the same time and do not interfere with one another.

The invention relates to the technical field of TEM models, provides a pilot dynamic evaluation method, system and device based on a TEM model and a storage medium, and solves the problems of low accuracy of flight training evaluation and poor adaptability of a training scheme. The method comprises the steps that flight control, physiological monitoring and cockpit voice data are acquired, and a multi-modal data stream is formed through time synchronization; performing threat perception, error management and non-technical skill three-level evaluation on the feature vector by using a TEM model, generating corresponding indexes, and fusing the indexes into a comprehensive feature vector; respectively processing the time sequence and cognitive features by means of a dual-channel long-short-term memory network, and extracting deep features; performing decision tracing by adopting an SHAP value so as to locate a capability defect node; finally, defect types are matched through a personalized improvement scheme recommendation mechanism, and self-adaptive training content is generated. According to the invention, the accuracy of flight training evaluation and the adaptability of the training scheme are improved.

The invention discloses a cockpit visual work efficiency evaluation method. The method comprises the following steps: establishing a cockpit geometric model according to a real cockpit; establishing a cockpit light environment model according to the cockpit light environment parameters; establishing a cockpit optical material model according to the optical material parameters of the inner and outer surfaces of the cockpit; fusing and establishing a cockpit optical model; a simulation detector is arranged on the cockpit optical model; according to the cockpit optical model and the analog detector, human eye vision optical simulation and dazzle source space tracking and positioning are carried out; according to a glare source space tracking and positioning result, a cockpit structure is optimized; and performing cockpit visual work efficiency evaluation according to a cockpit structure optimization result. According to the cockpit visual work efficiency evaluation method, reasonable evaluation of cockpit visual work efficiency readable visibility in various environments is achieved, simulation is conducted on the cockpit light environment through computer software, and adjustment can be conducted according to the working habit, the vision condition, the age and other factors of each pilot.

The invention belongs to the technical field of voice processing, and discloses an intelligent cockpit multi-mode voice interaction system and method, and the system comprises a voice triggering unit which collects the environment audio and video information in a cockpit, judges whether to enter a voice interaction mode or not through combining with the environment perception parameters in a vehicle, and sends the voice interaction mode to the vehicle; when the voice interaction triggering condition is satisfied, generating a voice interaction input signal matched with the current environment; the mouth shape analysis unit is used for carrying out acoustic feature extraction on the voice interaction input signal, synchronously analyzing the lip motion trail of the driver in the video information, establishing a corresponding relation between voice phonemes and mouth shape motion, and forming a joint analysis feature; the candidate generation unit is used for carrying out segmented alignment on the joint analysis features and constructing a continuous multi-modal fragment sequence; performing time synchronization on the multi-modal fragment sequence, and projecting the multi-modal fragment sequence to a predefined intention space to obtain a candidate intention set containing different candidate intentions; and the man-machine interaction experience of the intelligent cabin is improved.

The invention discloses a duplex-screen intelligent cabin interaction method and system, and relates to the technical field of intelligent cabin interaction, and the method comprises the steps: collecting user operation behavior data, vehicle state data and environment perception data in real time through a vehicle-mounted sensor group, a man-machine interaction interface and a vehicle bus; establishing a multi-dimensional user data model containing an interaction feature vector, a driving mode matrix and a preference configuration tree; the method comprises the following steps: analyzing user historical interaction data based on an adaptive weighting algorithm, and calculating use frequency weight coefficients of different functional modules; according to the duplex-screen intelligent cockpit interaction method and system provided by the invention, the precision of a user portrait is remarkably improved by constructing a multi-dimensional user data model, personalized interaction experience is realized, and the interface layout and interaction logic can be dynamically adjusted according to a real-time driving scene by adopting a self-adaptive weighting algorithm and a random forest classifier, so that the user experience is improved. The real-time performance and the adaptability of the system are enhanced, and the interaction experience is optimized.

The invention discloses a real-time emotion perception and voice interaction system for an intelligent cabin. The system comprises a multi-modal data acquisition module used for synchronously acquiring a facial image, a voice signal and text input of a driver; the visual feature enhancement unit is used for carrying out restoration and emotion distribution extraction on the low-quality image; the audio noise reduction and feature extraction unit is used for extracting voice emotion features; the text emotion coding unit is used for fusing relative position coding and context semantic information; the cross-modal fusion module is used for outputting an emotion classification result by integrating visual, audio and text features; the personalized emotion database is used for storing historical emotion data of the user and performing emotion trend prediction and early warning judgment; the large language model feedback module is used for generating structured cue words according to the emotion recognition result and the driving situation and generating natural language feedback; the voice synthesis and output module is used for adjusting voice parameters and performing feedback output through a vehicle-mounted multi-channel; according to the invention, the emotion expression of human-vehicle interaction is enhanced.

The invention relates to the technical field of vehicles, in particular to an intelligent cabin man-machine cooperative control method and device, a vehicle, a medium and a product. Performing fusion processing on the voice signal data, the visual signal data and the tactile signal data of the current driver by using a preset dynamic weight distribution model to obtain a multi-modal fusion control instruction; and under the condition that the multi-mode fusion control instruction meets a preset sight-voice dual-mode condition, synchronously issuing the multi-mode fusion control instruction to a plurality of target execution devices in the intelligent cabin so as to drive each target execution device to perform cooperative control. Therefore, by constructing a cooperative control mechanism of multi-mode sensing and dynamic weight distribution, the problems that the false wake-up rate is high, the voice and graphical interface cooperative efficiency is low and the interaction mode cannot adapt to a complex driving environment due to a single or separated interaction mode in the related technology are effectively solved.

The invention discloses a predictive vehicle control system and method for multi-modal consciousness recognition and electronic equipment, and relates to the field of remote monitoring, and the system comprises a multi-modal sensing module, an intention prediction module, a cross-domain pre-control module and a false trigger suppression module. The multi-mode sensing module is used for collecting three-mode data of sight, gestures and voice and dynamically distributing weights based on environmental parameters; the intention prediction module is used for performing time-space synchronization verification on the three-mode data and calculating comprehensive confidence in a grading manner; the cross-domain pre-control module outputs pre-control instructions to a cabin domain, a vehicle body domain and a power domain based on the effective intention; the false triggering suppression module is used for dynamically adjusting a confidence coefficient threshold value based on a driving scene and has a failure backspacing learning function; wherein each module performs data interaction based on a vehicle-mounted Ethernet / CAN bus.

The embodiment of the invention provides a vehicle intelligent agent control method and device, electronic equipment, a vehicle and a medium, and the method comprises the steps that a central intelligent agent receives task analysis information sent by a cabin intelligent agent, and the task analysis information is obtained by carrying out semantic analysis on an intelligent agent cooperative control task after the cabin intelligent agent receives the intelligent agent cooperative control task; splitting the agent cooperative control task into a plurality of sub-tasks according to the task analysis information, allocating an execution agent to each sub-task, and generating a task execution plan; the execution intelligent agent comprises an intelligent driving intelligent agent and a cabin intelligent agent; and sending a task execution request corresponding to each sub-task to each execution agent according to the task execution plan, so that each execution agent executes the corresponding sub-task according to the task execution request. According to the invention, the cabin intelligent agent, the intelligent driving intelligent agent and the central intelligent agent cooperatively control the user intention of the task around the intelligent agents and cooperatively execute the task, so that the task execution efficiency and effect are improved.

The invention discloses an intelligent cabin healthy light environment adjusting system and method based on biological feedback, and belongs to the technical field of intelligent cabin and vehicle control. The method comprises the following steps: collecting a multi-modal physiological signal of a passenger; physiological signals are processed in parallel through two paths; determining a feed-forward control weight based on the dynamic change degree between the current steady-state emotional state and the future emotional state trajectory; according to the feed-forward control weight, performing weighted fusion on the current steady-state emotional state and the future emotional state track to generate a comprehensive light environment adjustment instruction; according to the comprehensive light environment adjusting instruction, a dynamic light and shadow relieving strategy is generated and executed, and the strategy at least comprises at least one of the color temperature, the brightness or the dynamic rhythm of the cabin light environment. By introducing the feedforward control mechanism, the emotional fluctuation of the passenger can be predicted and intervened in advance, the response delay of the system is reduced, the conversion from passive response to active prediction is realized, and the timeliness and accuracy of emotional relief are improved.

The invention discloses a multi-mode voice interaction system and method for an intelligent cabin. Firstly, various vehicle working condition parameters in a CAN bus are read in real time, a wavelet domain Wiener filtering and judgment statistic enhancement strategy is dynamically adjusted, and self-adaptive voice purification based on vehicle state prior is achieved. Secondly, a bidirectional long-short-term memory network is adopted as a semantic understanding core, semantic feature vectors are extracted from enhanced signals through segmented maximum pooling operation, and the problem of semantic confusion caused by manifold collapse in a traditional method is effectively solved. And the feature vector and a safety state signal are synchronously input into an improved LLM-CoT engine and a dynamic arbiter, so that context accurate understanding and safety-up priority response are realized. According to the method, vehicle working condition perception and biLSTM depth time sequence modeling are deeply adapted to a vehicle-mounted complex acoustic scene, the error rate of semantic understanding is remarkably reduced in actual measurement under multi-person dialect dialogue, and the accuracy, robustness and safety of intelligent cabin interaction are systematically improved.

Embodiments of this application provide a control method and apparatus, and a transportation means. The method may be applied to the field of intelligent cockpits. The method includes: obtaining sensor data when an input from a user in a cockpit for indicating to generate an image is detected, where the sensor data includes a first image acquired by a camera of the transportation means or a speech signal acquired by a microphone of the transportation means; and controlling, based on the sensor data, a display area in the transportation means to display a second image. Embodiments of this application may be applied to an intelligent vehicle or an electric vehicle, to help improve a degree of personalization of content displayed in the cockpit, so as to help improve use experience of the user.

The invention belongs to the technical field of flight test, and discloses a cockpit vision field evaluation test flight method suitable for a troposphere manned airship, which comprises the following steps: selecting an airship test condition; the airship climbs to a preset field height and keeps level flight; a preset flight test action is completed; and commenting by a flight tester, and filling in a cockpit vision field commenting card. According to the method, the blank of the flight test method for evaluating the visual field of the cockpit of the troposphere manned airship with the vector propulsion system is filled, and the flight test efficiency and the flight test quality of the manned airship are improved.

The invention belongs to the technical field of flight simulation training equipment, particularly relates to an intelligent temperature control system for a flight simulator cabin, and solves the problem that the requirements of flight simulator temperature control on multi-dimensional physiological perception fusion, multi-target collaborative optimization and rapid personalized adaptation and active safety protection of new pilots cannot be met in the prior art. According to the method, a multi-modal sensing layer processes multi-channel skin physiological data, physical environment data and pilot electrocardiosignals, a human body heat balance equation for blood flow correction is constructed, and physiological feature vectors including predicted core body temperature, predicted average votes and predicted dissatisfaction percentage are generated; the decision-making layer generates a temperature control instruction and a confidence evaluation value through a meta-learning model, a reward function is in a four-dimensional dynamic weighting form, and the weight is adjusted through an IF-THEN rule according to the state; and the dynamic execution layer adopts a PID closed loop to adjust the partition temperature and triggers response in a grading manner. Accurate and personalized temperature control is achieved, and the training quality and safety are guaranteed.

The invention discloses an intelligent cabin interaction priority dynamic allocation system and method and electronic equipment, and relates to the field of cabin interaction, and the system comprises a multi-mode signal input layer which is used for continuously receiving original interaction instruction signals of a voice recognition module, a gesture recognition module, an eye movement tracking module and a touch screen module; the context sensing layer is used for collecting vehicle state data, driver state data and environment state data in parallel; the dynamic priority arrangement engine comprises a multi-factor fusion and weight calculation module and an arbitration and scheduling module; the multi-factor fusion and weight calculation module is used for normalizing the context data into a weight influence factor and calculating a real-time dynamic priority score of each interaction mode; the arbitration and scheduling module is used for comparing priority scores and selecting an optimal execution mode, and sending suppression signals to other modes at the same time; and the instruction execution layer is used for receiving the final instruction of the arbitration and scheduling module and issuing the final instruction to a vehicle-mounted application for execution.

The invention belongs to the technical field of amphibious aircraft flight control, and discloses an amphibious aircraft fly-by-wire flight control system and a working method, a cockpit control device is connected with and controls a normal instruction sensor and a backup instruction sensor, the normal instruction sensor transmits a signal to an actuator control electron, and the backup instruction sensor transmits a signal to the actuator control electron; the actuator control electronics and the flight control computer transmit signals mutually, the actuator control electronics and the actuator control module transmit signals mutually, and the actuator control electronics further receive signals of the external signal sensor, the direct angular rate sensor, the flap position sensor and the flight control mode switch; the backup command sensor transmits the signal to the backup flight control computer, and the backup flight control computer transmits the signal to the actuator control module; the actuator control module is connected with and controls the actuator, and the angular displacement sensor is arranged on the actuator and transmits collected signals to the actuator control module. The problem that a current fly-by-wire flight control system is not matched with amphibious aircraft cross-medium application is solved.

The invention relates to the technical field of fatigue behavior detection, and provides a GFFY-YOLO-based yawning detection model: on the basis of YOLOv11, an efficient neck global feature fusion network A-GFPN is designed, and a WIoU mechanism is introduced into a loss function part, so that the error of a positioning regression frame is reduced, and the operation speed of the model is improved while high precision is ensured. The method is reasonable and feasible, the key frame reflecting the fatigue state change of the driver can be efficiently and accurately extracted, the detection precision of fatigue behaviors such as yawning and the system response speed are effectively improved, and the calculation burden is greatly reduced while the real-time requirement is met. The method simplifies the video preprocessing process, has good adaptability and expansibility, can flexibly cope with processing challenges brought by different scenes and parameter changes, is suitable for various vehicle-mounted application scenes such as an intelligent cockpit and an ADAS system, has remarkable supplementing and improving effects on an existing fatigue detection technology, and has good application prospects. Wide market prospects and application values are realized.

The invention discloses a cabin area controller upgrading test device and method. The device comprises a cabin area controller, an initialization unit, a control unit, a switch switching unit and a power supply unit. The first input end of the switch switching unit is connected with the initialization unit, the second input end of the switch switching unit is connected with the control unit, and the output end of the switch switching unit is connected with the cabin domain controller; the switch switching unit is used for controlling the on-off between the initialization unit and the cabin domain controller; the control unit is used for sending a test signal to the cabin domain controller and switching the cabin domain controller from an initial setting state to a test setting state; the first end of the power supply unit is connected with the cabin area controller, the second end of the power supply unit is connected with the control unit, the power supply unit is used for supplying power to the cabin area controller based on the first control signal sent by the control unit, the structure is compact, the cost is low, the stability and the reliability are higher, and the system is suitable for a laboratory environment where a large number of OTA tests need to be repeatedly carried out.

Systems, methods, and non-transitory computer readable media for identifying a cockpit alert context during an aircraft mission are provided. The system includes a controller configured to: store message content in a clearance look-up table for one or more clearance messages received from air traffic control (ATC) during the aircraft mission that contain cockpit data about which an avionic system in an aircraft may later sense and generate a cockpit system alert for display on a cockpit display device; monitor a plurality of avionic systems in the aircraft for a cockpit system alert; retrieve an ATC clearance message from the clearance look-up table that corresponds to a detected cockpit system alert when a cockpit system alert is detected; and signal an aircraft display device to display the ATC clearance message in a visually distinguishable manner that indicates that the displayed ATC clearance message relates to a detected cockpit system alert.

The invention relates to the technical field of driver state monitoring, in particular to a driver on-duty state early warning system based on deep learning, which comprises a data acquisition module for acquiring videos in a driver cab; the data processing module is used for determining a key region of the video based on a target detection model to obtain a feature vector; the characteristic analysis module is used for determining whether the behavior coherence of the driver in the cockpit is qualified or not based on the behavior coherence characterization parameters and adjusting the time sequence sliding step length of the target detection model according to the ratio; the action monitoring module is used for determining whether the gesture action of the driver reaches the standard or not based on the action standard degree and adjusting the key point confidence coefficient of the target detection model according to the difference value; and the state analysis module is used for determining whether the driver on-duty state is abnormal or not based on the on-duty state similarity and adjusting the classification confidence threshold of the target detection model according to the relative difference. According to the invention, the accuracy of driver on-duty state early warning is improved.

A craft is provided with a lever that can control the power / speed of the craft and semi-automatically transition the craft in various modes of operation. This makes control of the craft somewhat similar to control of a boat, thereby bringing a maritime flight control experience to a wing-in-ground effect vehicles, hydrofoiling vessels, seagliders, and seaplanes. Further, various audio, visual, and / or haptic devices in the cockpit can provide alerts / feedback to the operator on the use of the lever and mode transitions.

The invention relates to the technical field of automobile testing, and discloses a method and system for evaluating and testing visual field glare of a driver in a cabin, and the method comprises the following steps: starting from the position of the eyes of the driver, capturing a brightness distribution image of the whole visual field, and dividing the image into a plurality of sub light source regions around a glare source; dividing the visual field into a main sight area and a residual light sight area according to the attention distribution of the driver, and endowing sub light source areas falling into different areas with different weight values; calculating a unified glare index according to the weighted sum of the glare intensity of each sub light source area and the background brightness in the cabin; and finally, comparing the index with a preset threshold value, and outputting an evaluation result. According to the method, the large-area light source is divided into the sub-light sources, weighted calculation is carried out in combination with the attention of the driver, the problem that a traditional glare evaluation model is not suitable for a close-range non-point light source scene of the automobile cabin is solved, a scientific evaluation system matched with the automobile cabin is established, and the glare evaluation result is more accurate.

A method for the automatic adjustment of a cockpit inside a road vehicle comprising the steps of determining anthropometric data of a driver; processing an ergonomic position of a model of the driver sitting on board the road vehicle; processing an optimal configuration of the cockpit; operating a plurality of actuator systems so as to cause the cockpit to reach the optimal configuration; wherein the ergonomic position of the model is processed in association with a minimum ground visibility; a minimum visibility of a control panel; and at least one first comfort angle of a body joint of the driver.

The invention relates to the technical field of vehicle bodies, in particular to a collision force transmission inclined strut structure. The hinge column inner plates are arranged at the two ends of the front-end large casting, one end of the inclined strut structure body is installed on the front-end large casting, the other end of the inclined strut structure body is installed on the hinge column inner plates, and the inclined strut structure body, the front-end large casting and the hinge column inner plates form a triangular stable structure. The section of the inclined strut structure body is of an M-shaped structure. The inclined strut structure has the beneficial effects that according to the technical scheme, the inclined strut structure body with the special structure is designed, one end of the inclined strut structure body is installed on the front-end large casting, and the other end of the inclined strut structure body is installed on the hinge column inner plate, so that the inclined strut structure body, the front-end large casting and the hinge column inner plate form a triangular stable structure; the inclined strut structure can effectively reduce the impact force of head-on collision on a passenger compartment, so that the safety performance of the cockpit is improved.

The invention relates to the technical field of automobile cabin environment control, and discloses an intelligent cabin environment adaptive adjustment system based on an AI large model, which comprises a sensing module, an AI large model decision module, an execution module and a feedback module. According to the intelligent cabin environment self-adaptive adjustment technology based on the AI large model, a mixed decision sub-model of an AI large model decision-making module adopts an MPC-TD3 fusion algorithm, and a user behavior learning sub-model of the AI large model decision-making module learns user physiological parameters and operation records collected by a sensing module; the multi-physics field prediction sub-model predicts a cabin environment and a power battery state, and corrects a decision result in combination with comfort parameters fed back by a PMV-PPD evaluation model and an SET evaluation model of the feedback module in real time, so that the problems that a single MPC model is insufficient in robustness under complex working conditions and a single reinforcement learning model is difficult to quantify the comfort feeling of a user are solved, and the user experience is improved. And the dynamic response speed and the adjustment precision are considered.

The invention discloses an airport fire fighting truck simulator, which has the technical structure that the simulator comprises a cockpit body, an instructor control system, a computer simulation system, a visual system and a sound system, adopts a modular design, and integrates 1: 1 real truck original components; real-time synchronization and real-time data interaction of signals of multiple subsystems are achieved through the CAN bus controller and the master controller. Control signals of the driving control system and the fire-fighting equipment operating platform are accessed to the visual host through data lines to drive the vehicle dynamics model, the airport environment simulation and the aircraft fire and fire extinguishing interaction system in real time to generate dynamic three-dimensional visual and sound effect feedback; the teacher console can monitor operation of students in real time, dynamically adjust training scenes and synchronously display the fire extinguishing effect through the visual host, double-person cooperative training, multi-mode switching and complex scene simulation are supported, and the system has excellent application and popularization prospects in special fire extinguishing scenes of airports.

The invention discloses an automatic loading system. The automatic loading system comprises the steps of initializing loading parameters and rules based on an order; the forklift conveys the material trays to an unstacking station; a laser radar scans a vehicle and generates point cloud data on site, and vehicle body and loading position coordinates are obtained through an AI model and an algorithm; the stand column type robot is guided to unstack through 3D vision; the telescopic belt line conveys the box body; scanning and removing abnormal box bodies during conveying; and the loading mechanism is guided by the 3D vision to complete loading according to rules. The system further comprises a task board, a step crossing module and other auxiliary modules, a cockpit and other auxiliary modules, loading automation and intelligence are achieved, and efficiency and quality are improved.

The invention provides a communication interconnection multi-seat cabin system which comprises seats with a partition seat position detection function and at least one mobile terminal independent of seat cabins, the seats are in wireless communication connection with the mobile terminals, and body position sensing assemblies used for detecting the body states of passengers are arranged on the seats; the multi-seat cockpit system further comprises a game console with a wireless communication interconnection function and a display screen, the seats, the game console, the mobile terminal and the display screen form a multimedia cockpit interaction system, and a passenger sends a posture operation instruction on the seats through the body position sensing assembly to relieve fatigue. According to the invention, not only can a passenger on one automobile seat operate the game, but also passengers on a plurality of automobile seats can interact with each other, so that the communication among a plurality of passengers is facilitated. The posture of a user can be adjusted through the body position sensing assembly, and muscles can be stretched and physical fatigue can be relieved by adjusting the body posture while communication interaction is carried out.

A system includes a first camera located within a cockpit of an aircraft to track the eye movement of at least one pilot, and a second camera to track an ambient light source. The system includes an electrochromic panel having an array of dimmable cells. The system further includes a controller, equipped with one or more processors responsible for modifying the array of dimmable cells. The controller receives eye tracking data from the first camera associated with a gaze target of the pilot, and light tracking data from the second camera, which includes parameters associated with the ambient light source. Based on the eye tracking and light tracking data, the controller determines a glare location on a surface of the electrochromic panel where the gaze target intersects. The controller may then selectively modify a tint level of specific dimmable cells in the panel to address the determined glare location.