5653results about "Signalling/lighting devices" patented technology

A driving state monitoring and feedback method and system based on multi-modal human factors intelligent data analysis, and an edge computing terminal device. The method comprises: receiving multi-modal human factors data of a tested driver that is collected in real time (S110); pre-processing the multi-modal human factors data, wherein the pre-processing comprises denoising processing and data normalization processing (S120); sending the pre-processed multi-modal human factors data into a pre-trained first state recognition model, so as to obtain a real-time recognized driver state, wherein driver states include a normal state and abnormal states, and the types of the abnormal states include a plurality of states such as a fatigue state, a distracted state and an angry state (S130); and when it is recognized that the driver state is an abnormal state, generating, for different categories of abnormal states, driving state feedback instructions to a driving intervention system, such that the driving intervention system performs state feedback adjustments on the driver on the basis of the received driving state feedback instructions (S140). The method and system can recognize different driving states of a driver in real time and then perform processing on the basis of different driving states, thereby avoiding the occurrence of traffic accidents.

The technology disclosed teaches a system and methods for providing driver assistance alerts to a driver using an end-to-end artificially-intelligent advanced driver assistance system. The technology disclosed further includes receiving environmental data for a sequence of driving states including at least video from a camera, returns from an optical sensor, and location data from a GNSS receiver, wherein the camera, the optical sensor, and the GNSS receiver are coupled to a processor carried by a vehicle, processing the environmental data as input to an end-to-end neural network, wherein the end-to-end neural network is trained to generate prescriptive steering and speed control actions in response to a present driving state, analyzing hidden layer data and output data from the end-to-end neural network to estimate collision avoidance data, and presenting, to the driver, a user interface including driver assistance alerts based on the collision avoidance data.

Methods, systems, and devices for leveraging automotive and wearable-based data are described. For example, a system may include a wearable device, a user device associated with the wearable device, and a vehicle. The system may determine when a user is within a proximity of the vehicle based on communications between the vehicle and the wearable device, between the vehicle and the user device, or both. The system may retrieve physiological data measurement from the user via the wearable device based on determining the user is positioned in a proximity of the vehicle, such that one or more operational parameters of the vehicle may be adjusted based on the physiological data. Additionally, or alternatively, the system may receive telemetry data from one more sensors of the vehicle and may provide feedback to the user based on the telemetry data satisfying one or more trigger conditions.

The invention discloses a long downhill section truck brake pad high temperature detection and cooling method and system, and the method comprises the steps: collecting the surface temperature data of a truck brake pad in real time according to high-precision infrared temperature sensor arrays and thermal imagers disposed at the two sides of a long downhill section, and generating a time-space correlation temperature field distribution diagram; based on the temperature field distribution diagram, dynamically adjusting a temperature safety threshold curve through reinforcement learning, and outputting a dynamic early warning trigger signal; according to the dynamic early warning trigger signal, a corresponding spraying instruction is generated so as to drive a piezoelectric ceramic microvalve array of a roadside spraying device to conduct spraying cooling on the brake pad; and according to the temperature attenuation rate and infrared thermal image feedback data of the brake pad after spraying, the temperature safety threshold curve and the spraying instruction are corrected through a Bayesian optimization algorithm, and closed-loop safety regulation and control are formed. According to the embodiment of the invention, the temperature of the brake pad can be monitored in real time, accurate spraying cooling control is realized, and safe and stable braking performance of a truck is ensured.

The invention relates to the technical field of radar detection, in particular to an intelligent collision detection method and system, and the method comprises the following steps: setting an initial emission angle of a radar, monitoring a reflection signal during the movement of an object, recording the return time, calculating a reflection distance according to the light velocity and the time, adjusting the emission angle, optimizing the coverage range, and obtaining angle correction data. According to the method, the position of the object can be more accurately determined by recording the return time of the reflection signal in real time and calculating the reflection distance by using the light velocity and the time difference, and potential collision risks can be more accurately predicted and identified by iteratively optimizing the scanning path, enhancing the adaptability to the dynamic environment and updating the target trajectory information. Intelligent judgment of risk levels and adjustment of emergency response measures are carried out, the response efficiency and accuracy of an early warning system are improved, the function of a collision detection system is enhanced, traffic safety is remarkably improved, and potential accident risks are reduced.

The present invention relates to a warning system and in particular to a warning system that is movable to a monitoring zone. The invention has been developed primarily for use for early notification of danger by approaching vehicles to a monitored zone such as an emergency in an emergency lane of a roadway. The warning system of the invention comprises at least two forms of detectors for detecting and tracking vehicles and obtaining characteristics of the tracked vehicle relative to the monitored zone a determinator for receiving the characteristics of the tracked vehicle relative to the monitored zone and assessing the expected relative impact of the vehicle on the monitored zone and an alarm system for providing an alarm action according to a predetermined danger of the assessed expected relative impact of the vehicle to the monitored zone.

The present disclosure relates to methods and system for acquiring and analyzing biosignals or physiological signals of a person sitting in a vehicle and predicting (in real-time) time-varying attention, engagement level or alertness level using the biosignals. The biosignals may be acquired using one or more clusters of electrodes together with a wearable user device or from a sensing device that is embedded in the seat of the vehicle. In some embodiments, the biosignals may be utilized to predict restedness level of the subject, to monitor or predict physiological state of the subject, to detect a distress situation and to adapt a vehicle control accordingly. In some other embodiments, the biosignals can be transformed into communication, for example, speech signals or instructions for the vehicle. One or more actions may be triggered based on the analysis of the biosignals including engaging the person, generating alerts, or adapting the vehicle control.

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 relates to a vehicle-mounted geological disaster early warning system and method based on environmental perception, and relates to the technical field of vehicle early warning. The system comprises an information acquisition module used for acquiring geological disaster information, vehicle information and external environment information in real time; the judgment and analysis module predicts a vehicle driving path through a driving path prediction unit; inputting the geological disaster information into a pre-trained geological disaster early warning model through a geological disaster prediction unit, and predicting a geological disaster occurrence probability value of each monitoring point or region; evaluating the risk level of the influence of the geological disaster on the vehicle through a risk evaluation unit; and the early warning execution module is used for matching safety suggestions according to the risk levels and carrying out early warning prompt. According to the method, the information is comprehensively acquired, the geological disaster prediction model is used for evaluating the risk in real time, early warning and safety suggestions are provided in time, and the driving safety can be effectively improved.

The present invention discloses a multi-module coordinated fault detection and early warning method for hydrogen-electric electric vehicles, which relates to the technical field related to electric vehicle fault detection. The method includes: determining multiple functional modules of hydrogen-electric electric vehicles; collecting multiple functional modules through an on-board sensor network to obtain multiple sensor data sets; performing pattern recognition on multiple sensor data sets based on a pattern classification algorithm, and outputting a real-time matching working mode; constructing a module coordination relationship database; calling the module coordination relationship database to identify the module coordination relationship diagram corresponding to the real-time matching working mode; performing coordinated fault detection on multiple sensor data sets according to the module coordination relationship diagram, and outputting a fault early warning signal corresponding to the real-time matching working mode. The method solves the technical problem that the comprehensive fault detection means lacking the coordinated relationship of multiple functional modules in the prior art, which leads to untimely and incomplete fault identification of electric vehicles, and achieves the technical effect of improving the comprehensiveness and accuracy of fault identification.

A vehicle periphery monitoring device is configured to: specify positions of detection points of an obstacle with respect to a vehicle based on detection results of multiple periphery monitoring sensors equipped to the vehicle; update the positions of the detected detection points corresponding to a position change of the vehicle; storing the updated positions of the detection points in a memory that maintains stored information during a parked state of the vehicle; and estimate, at a start time of the vehicle from the parked state, a position of a detection point, which is located in a blind spot and is not detected by all of the multiple periphery monitoring sensors at the start time of the vehicle, using the positions of the detection points stored in the memory.

Device for dehumidifying a closed casing.The device for dehumidifying comprises a box comprising an inlet communicating with the interior of the closed casing and an outlet, a heating module able to be controlled to generate heat, a desiccant configured to adsorb moisture when it is not heated by the heating module and to return adsorbed moisture by desorption when it is heated by the heating module, a mobile plug able to be moved to alternately open and close the inlet and the outlet, a bias spring configured to move the mobile plug when the heating module does not heat the desiccant and a shape memory alloy spring configured to move the mobile plug when the heating module heats the desiccant, said shape memory alloy spring being able to be heated by the heating module at the same time as the desiccant. The device for dehumidifying is suited for dehumidifying any type of closed casing, it is cost efficient both in design and in power consumption, and it is easy to implement thanks to its small size and its simple design.

The invention relates to a control method of an oxygen supply system, the oxygen supply system, a vehicle and a storage medium, and relates to the technical field of automobiles. The method comprises the following steps: acquiring an external oxygen content value outside a vehicle and a blood oxygen value of a user inside the vehicle; under the condition that the outside-vehicle oxygen content value and / or the blood oxygen value meet the oxygen supply condition, prompt information is output, and the oxygen supply condition comprises at least one of the following items: the outside-vehicle oxygen content value is lower than a preset oxygen content value, and the blood oxygen value is continuously lower than a first preset blood oxygen value within a first preset duration; the prompt information is used for prompting a user to start an oxygen supply mode; and in response to the instruction of starting the oxygen supply mode, controlling the oxygen generator to start working to supply oxygen to the interior of the vehicle. Therefore, oxygen can be supplied to the interior of the vehicle, and the health state of a user in the vehicle is prevented from being affected by insufficient oxygen in the vehicle.

The invention provides a multifunctional controller for a new energy automobile and the new energy automobile, and relates to the technical field of new energy automobile control. The multifunctional controller for the new energy automobile comprises a data collection module, a data processing module, a prediction module, a storage system, a communication system, a user interface, a software system, a battery management system, an auxiliary driving system, a safety system, an emotion recognition module, a power supply system and a continuous learning system. Through the prediction model and time sequence analysis, the charging and discharging strategy of the battery is optimized, the service life of the battery is prolonged, the energy efficiency is improved, a power system is optimized according to real-time data and a prediction result, the performance and efficiency of the vehicle are improved, and thermal management of the vehicle is optimized according to weather forecast and real-time traffic information. The optimal performance can be kept under different weather conditions, and the system can automatically adjust the internal environment, such as temperature and music playing, of the vehicle by analyzing the emotional state of the driver so as to adapt to the emotion of the driver.

This disclosure relates to a system and method for real-time monitoring of driver in a vehicle. The method includes capturing at least one of a head movement, steering direction, and a direction of gaze of the driver. The method further includes determining a Plane of Vision (POV) for the driver based on end point of each side view mirrors, a rear-view mirror and bottom of a windshield of the vehicle. The method further includes determining a Region of Interest (ROI) for the driver based on one of a bounding box regression model and a direction of movement of the vehicle. The method further includes determining a Line of Gaze (LOG) for the driver based on the direction of gaze. The method further includes identifying a distraction level of the driver while driving the vehicle based on determining at least one of the POV, the ROI, and the LOG.

The present disclosure relates to safety devices and systems for light mobility vehicles. In one example, a safety device for a light mobility vehicle includes a circuit board, one or more connectivity modules coupled to the circuit board, and an antenna coupled to the circuit board. The circuit board may be positioned within or coupled to a light mobility vehicle part. The antenna is configured to mitigate interference of one or more components of the light mobility vehicle part with the one or more connectivity modules.

The invention provides a new energy automobile power battery abnormity diagnosis method and device and a storage medium. The method comprises the following steps: respectively inputting preprocessed historical state data into a voltage prediction model and an equivalent circuit model to obtain a first voltage prediction value and a second voltage prediction value; comparing the voltage predicted value with an actually measured voltage value to obtain a first comparison result; determining a voltage abnormity level according to the first comparison result and a fault forecasting strategy, determining a battery unit with abnormal voltage, and generating voltage abnormity information; inputting the target feature data into a deep belief network model to obtain a temperature prediction value, and comparing the temperature prediction value with an actually measured temperature value to obtain a second comparison result; and identifying the battery unit with abnormal temperature according to the second comparison result, judging the type of temperature abnormality, and generating temperature abnormality information. The accuracy of the battery abnormal state result is high, the battery abnormal diagnosis efficiency is improved, and the battery abnormal state result is more comprehensive.

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.

A redundant parking brake apparatus is provided for a vehicle having components of a parking brake system. The redundant parking brake apparatus comprises a first parking brake controller arranged to (i) monitor a first signal indicative of a request to apply parking brakes of the vehicle, and (ii) provide one or more control signals to be applied to components of the parking brake system to apply the parking brakes in response to receiving the first signal. The redundant parking brake apparatus also comprises a second parking brake controller arranged to (i) initiate a timer counter in response to receiving the first signal, and (ii) provide one or more control signals to be applied to components of the parking brake system to apply the parking brakes when the timer counter has reached a predetermined count.

The invention relates to a vehicle dynamic adjustment method for a side collision accident, and the method comprises the following steps: S1, collecting vehicle body multi-dimensional information data information, vehicle environment information data information and vehicle passenger information data information, and building a real-time updated data model through data fusion; training a neural network according to virtual collision data generated by the vehicle collision simulation software to obtain a collision risk prediction model; s2, inputting data in the model into a collision risk prediction model to obtain the injury degree of a passenger and collision prediction position point information, dividing the state between a vehicle and a potential collision object into different risk levels, and generating a risk map; and S3, the vehicle adjusting system adjusts the height, the speed and the seat posture of a vehicle suspension system and a vehicle safety belt according to the different risk levels, risk prompting is carried out on vehicle passengers so as to reduce the risk levels, and the risk map is updated in real time. According to the invention, the safety of passengers in a side collision accident can be improved.

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

The disclosure relates to the system and methods for generating a guidance path for automated navigation of large agricultural equipment. Vehicle path data from leading vehicles can be recorded, stored or inputted into the system for generation of guidance paths offset from the swaths traversed by the leading vehicle. Combines, planters sprayers and other vehicles utilizing guidance system can be used to record leading vehicle data for use by the following vehicle in real time or in subsequent cycles. Enterprise systems can manage multiple grain carts and / or combines or other vehicles to maximize efficiency.

Embodiments herein comprise monitoring factors related to braking of an autonomous vehicle. In response to determining, based upon data from one or more sensors, whether a failure state from a set of one or more failure states has occurred, a failure log is updated to record the occurrence of the detected failure state. In one or more embodiments, the failure states have associated severity levels, and the updated log and associated severities are used to determine a braking safety or failure metric for the vehicle. In one or more embodiments, if the vehicle has a metric corresponding to a rule that correlates the braking safety metric value to a set of one or more actions, the corresponding action(s) may then be implemented. For example, if the braking safety metric has a value corresponding to a rule that indicates the vehicle is unsafe, the vehicle is parked.

An impairment analysis (“IA”) computer system for detecting an impairment is provided. The IA computer system is associated with a host vehicle, and includes at least one processor in communication with at least one memory device. The at least one processor is programmed to: (i) interrogate or otherwise scan a target vehicle by using a plurality of sensors included on a host vehicle to scan the target vehicle and a target driver; (ii) receive sensor data including target driver data and target vehicle condition data; (iii) analyze the sensor data by applying a baseline model to the sensor data; (iv) detect an impairment of the target driver or target vehicle based upon the analysis; and / or (v) output an alert signal to a host vehicle controller, or direct collision preventing actions (such as automatically engage vehicle safety systems), based upon the determination that the target driver or target vehicle is impaired.

A wear detection system can be configured to receive a video stream including a plurality of images of a bucket of the work machine from a camera associated with the work machine. The bucket has one or more ground engaging tools (GET). The wear detection system can also be configured to identify a plurality of tool images from the video stream over a period of time. The plurality of tool images depict the GET at a plurality of instances over a period of time. The wear detection system can also be configured to determine a plurality of tool pixel counts from the plurality of tool image and determine a wear level for the GET based on the plurality of tool pixel counts.

The invention discloses an online safety management and early warning method for a power battery of an electric vehicle, which comprises the following steps of: acquiring multi-dimensional operation data of the power battery and preprocessing the multi-dimensional operation data to obtain a standardized data set; obtaining a dynamic working condition and a time sequence feature based on the standardized data set, generating a battery state feature set and judging whether the battery state feature set meets a preset condition, and if not, optimizing the battery state feature set to obtain an optimized feature set; constructing a risk assessment model, and combining the optimized feature set to obtain a battery safety risk probability and judge a risk level; if the risk level exceeds a threshold value, obtaining a personalized management strategy generated by the cloud based on the optimized feature set and issuing the personalized management strategy to a vehicle end controller; and fusing vehicle end real-time data and battery aging data through an online learning algorithm, dynamically adjusting risk assessment model parameters, generating an adaptive model, and outputting a graded early warning signal. According to the method, the safety risk of the power battery under the complex working condition is effectively evaluated, and a real-time early warning and personalized management strategy is provided.

The invention discloses an intelligent parking guarding method and system based on a multi-modal large model, and the method comprises the steps: S1, collecting the multi-modal sensing data inside and outside a vehicle, and carrying out the time-space alignment and coordinate mapping of the multi-modal sensing data; s2, performing feature extraction and semantic enhancement processing on the multi-modal perception data to generate visual features, radar features and audio features; s3, inputting the visual features, the radar features and the audio features into a multi-modal large model to output cross-modal joint features; s4, performing target identification detection and behavior intention prediction, and outputting a threat judgment result; and S5, dynamically generating a hierarchical response strategy according to the threat judgment result, and issuing a real-time early warning prevention and control instruction to a vehicle execution mechanism. According to the method, the problem of sensing limitation of a vehicle parking method in the prior art can be solved, and the intelligence and the safety of vehicle parking are improved by integrating multi-source data and by means of the powerful analysis capability of a multi-mode large model and giving an alarm for abnormal behaviors and potential safety threats in time.

The invention provides a vehicle blind area monitoring device and method based on a rear camera. According to at least one implementation mode, the invention provides a vehicle blind area monitoring device based on a rear camera, and the device comprises an image acquisition unit, a control unit and a display unit. The image acquisition unit is configured to acquire a rear image from a rear camera mounted on a vehicle. The control unit is configured to set a region of interest in the rear image based on a steering signal or a lane departure signal of the vehicle, determine whether there is a risk of approaching an object in the region of interest to the vehicle, and generate a blind spot image based on whether there is a risk of approaching. The display unit is configured to display a blind spot image.

The invention discloses a vehicle door and window state monitoring and early warning method and system, and belongs to the technical field of vehicle monitoring. The method comprises the steps that when doors and windows are not closed and a vehicle locking signal is received, the parking environment of a vehicle is graded, and an environment risk index is determined; historical behavior data of a vehicle owner is obtained, behavior modeling is carried out, a parking duration level is determined, screening is carried out in a preset parking duration level table, and a duration risk index is determined; acquiring weather information, and determining a weather risk index based on a screening result of the weather information in a preset weather condition grading table; determining a comprehensive risk value according to the environment risk index, the duration risk index and the weather risk index; and according to the comprehensive risk value, determining an early warning level and pushing early warning information to the user side in a corresponding early warning form. More flexible, accurate and humanized prompts can be provided according to different scenes, user responses and personalized requirements; the problem of low interaction efficiency in the prior art is solved.

Provided are a driving state monitoring and feedback method and system based on multi-modal human-factor intelligent data analysis, and an edge computing terminal device. The method includes: receiving multi-modal human-factor data collected in real time from a tested driver; preprocessing the multi-modal human-factor data; inputting the preprocessed multi-modal human-factor data to a pre-trained first state identification model to obtain a driver state identified in real-time, the driver state including a normal state and a plurality of abnormal states; and generating, in response to the driver state being identified as an abnormal state, a driving state feedback instruction for the category of the abnormal state and sending the driving state feedback instruction to a driving intervention system, to cause the driving intervention system to perform state feedback adjustment on the driver based on the received driving state feedback instruction.