348 results about "User driven" patented technology

A framework for machine learning modeling of structured data that includes one or more artificial intelligence-based agents. These artificial intelligence-based agents are configured to create and execute chains of repeatable actions to perform user-driven and user-defined workflows with a given problem set and identified outcomes. Structured data that has been processed is fed by the artificial intelligence-based agents to language models to formulate actions operate as tools for analyzing a problem set that can be chained together to address a given workflow, in one or more prompts for constructing and delivering the identified outcomes. Chains of repeatable actions for saved and utilized for additional workflows having similar problem sets, and executed based on pre-identified triggers.

The invention discloses an unmanned aerial vehicle cooperative inspection monitoring system based on BIM construction. The system comprises a data acquisition module which acquires an original visible light image, infrared thermal imaging and point cloud data of a construction area through unmanned aerial vehicle carrying equipment; the data processing module carries out denoising, enhancement, noise reduction, temperature calibration or downsampling processing on the three types of data; the BIM module performs spatial pairing on the processed three types of data, constructs a basic three-dimensional model of a construction area based on point cloud data, maps image and thermal imaging information, and adds a construction progress and a project amount plan to form a 4D BIM model; the construction inspection module obtains time and engineering quantity deviation from the 4D BIM model, generates a construction inspection report, and calculates a monitoring priority value of each building area according to the construction inspection report; and the user interaction module generates an inspection target according to the monitoring priority value, and a user drives the unmanned aerial vehicle to obtain new data according to the inspection target. The system realizes accurate monitoring of the construction progress and intelligent allocation of resources, improves the construction management efficiency and quality, and is suitable for building construction scenes.

The invention discloses a new energy vehicle endurance display method and system based on a power battery SOH, electronic equipment and a vehicle. The method comprises the steps that a vehicle, a vehicle control unit, a battery management system and a display module are triggered to be started through a KL15 signal wake-up signal, and power-on initialization and self-inspection are executed; after the self-inspection is completed, reading the stored current state-of-health initial value SOH0 of the power battery and the stored current state-of-charge initial value SOC0 of the power battery from the EEPROM; performing dynamic correction on the read SOC value, performing fixed value locking on the SOH value, and sending the corrected SOC value and the locked SOH value to a CAN bus of the whole vehicle; based on the SOH0 and the SOC1 sent by the battery management system, the remaining endurance mileage S is calculated in combination with the total delivery mileage L of the new vehicle; and the instrument and large-screen display module is used for displaying the current remaining endurance mileage in real time. According to the method, the problem of display deviation caused by neglecting battery aging in a traditional method is solved, and the user driving experience and the battery management efficiency are improved.

The utility model discloses a battery swap station which comprises a battery swap position and a transportation system, the transportation system is used for transporting and guiding an electric vehicle to the battery swap position, and the battery swap position is used for replacing a battery pack of the electric vehicle, so that the time required by a user to drive the vehicle to find the corresponding battery swap position is saved, the battery swap efficiency is improved, and the battery swap efficiency is improved. The situation that the user needs to drive the vehicle to consume a long time to find the battery replacement potential when the battery replacement potential is too much is effectively avoided, and the battery replacement experience of the user is improved. According to the technical scheme, the transportation system can preferentially select the electric switching potential closer to the electric vehicle and the optimal route for transportation guidance, compared with the situation that a user may bypass or miss the nearest electric switching potential during self-driving, the electric vehicle can enter the corresponding electric switching potential in the shortest time, the time used for electric switching can be further shortened, and the electric switching experience is improved. And the battery replacing station can coordinate the battery replacing position of each electric vehicle as a whole, so that the vehicles in the whole battery replacing station can be parked more regularly.

The invention discloses a personalized recommendation method and device based on a large language model and logical relationship mining. According to the method, user-driven logic relation extraction is constructed, the semantic reasoning ability and graph structure analysis of the large language model are fused, the high-order logic relation in the heterogeneous graph is mined, and the problems that an existing method is incomplete in logic relation and insufficient in semantic understanding are solved. The method comprises the following steps: analyzing user-article interaction data through a user-driven logic relationship extraction module, and identifying implicit association; performing rule expansion by utilizing a large language model, and generating a high-order logic rule in combination with semantic and structural information; screening high-quality rules through confidence score to construct an enhanced heterogeneous graph; and finally, demand perception recommendation is realized in combination with user preference embedding and logic relation characteristics.

The invention discloses a camera parameter calibration method and device, a computer readable storage medium and a vehicle, and the method comprises the steps: collecting a checkerboard image shot by at least one camera, and extracting a line contour in the checkerboard image based on an edge detection algorithm; in the line contour, detecting a straight line segment based on Hough transformation or an LSD algorithm, and fitting the straight line segment based on a least square method; determining an internal reference matrix and a distortion coefficient of the camera based on the fitted straight line segment and a nonlinear optimization algorithm; and determining a rotation matrix and a translation vector of the camera based on the straight line segment, the internal reference matrix and the distortion coefficient. According to the method, the robustness of parameter calibration in a calibration field aging, fouling or reflective scene can be improved, the success rate, the automation degree and the efficiency of the calibration process are improved, and the driving safety of a user is improved.

A system that generates relevant and vetted training data using intelligent simulated users and evaluation of conversation data. A simulated user and an automated agent engage in a conversation to generate conversation and / or interaction data. The simulated user is guided by scenarios which are generated based on one or more controls to be followed by the automated agent. Using a simulated user driven by control-derived scenarios ensures the ensuing conversation data is relevant to the desired scope of operation for the automated agent. The conversation data is evaluated based on the controls to confirm the automated agent actions and responses followed the controls properly. Evaluating the conversation data based on the controls ensures that conversation data associated with properly followed controls is used as subsequent training data.

The invention provides an electric vehicle electric quantity state and remaining mileage prediction method, which comprises the following steps: carrying out regional division on a battery pack, deploying a sensor, collecting electric quantity data of each region in real time, constructing an anomaly detection model to identify an abnormal region, carrying out local data adjustment, and combining user driving behaviors and environmental parameters to predict the electric quantity state and remaining mileage of an electric vehicle. A long-short-term memory network is adopted to dynamically predict the power consumption trend, the remaining mileage is calculated according to real-time road conditions and temperature changes, meanwhile, an adaptive correction mechanism is introduced, and model parameters are dynamically adjusted through comparative analysis with historical prediction records, so that the prediction accuracy is improved. According to the method, accurate monitoring of the electric quantity state of the electric vehicle and dynamic prediction of the remaining mileage can be achieved, the problem that a traditional method is large in prediction deviation in a complex driving environment is effectively solved, more reliable electric quantity and mileage information is provided for a user, and the use experience and safety of the electric vehicle are improved.

The utility model relates to the technical field of fitness equipment, in particular to a motion detection device applied to the fitness equipment, which can acquire the acting condition and the weight of a counter weight in the motion process. Comprising a weight bearing module, a distance detection module and a control electronic watch, the weight bearing module comprises a movable rod, a balancing weight and a plug pin, a user selectively inserts the plug pin into the balancing weight according to exercise requirements, and the user drives the movable rod and the balancing weight to vertically move upwards for exercise; specifically, the distance detection module selects a gyroscope or a pull box to detect the movement distance and the movement speed of the movable rod, and the movement distance and the movement speed are displayed by controlling an electronic watch; the control electronic meter is electrically connected with the bolt and displays the total weight of the corresponding balancing weight according to the magnitude of the passing current; and the user can intuitively obtain own motion parameters.

The invention relates to an electric vehicle V2G scheduling method considering consumption of photovoltaic power and off-peak power, and the method comprises the steps: building an EV disordered charging model based on a user driving behavior in a power distribution network system containing photovoltaic power generation; establishing peak clipping-oriented price excitation; combining the established EV disordered charging model and price excitation to construct a photovoltaic and EV cooperative power generation optimization scheduling model; solving the photovoltaic and EV cooperative power generation optimal scheduling model by adopting an improved multi-target particle swarm algorithm, and outputting to obtain an EV ordered charging and discharging strategy; and correspondingly controlling the charging and discharging behaviors of the EV according to the EV ordered charging and discharging strategy. Compared with the prior art, the method can reduce the load variance of the power grid, achieves the efficient utilization of photovoltaic and off-peak power, and improves the V2G income of the electric vehicle.

A method for constructing a 3D panoramic view model is provided using a vehicle-mounted device. The method includes identifying a target object in an environment image, and determines first coordinates of the target object in a first coordinate system corresponding to the environment image. The environment image is converted to an aerial view, and second coordinates of the target object are determined in a second coordinate system corresponding to the aerial view. A third coordinate of the target object is determined in a third coordinate system. A fourth coordinate of the target object is determined in a fourth coordinate system, and an initial distance is determined between the target object and a vehicle. A target distance is determined and a target 3D panoramic view model of the vehicle is constructed according to the target distance and the environment image. The method improves the safety of users driving.

The invention relates to a traffic freight employment qualification certificate handling service system and method based on artificial intelligence. The method comprises the following steps: in response to a traffic freight employment qualification certificate service instruction triggered by a user, determining a certificate service type needing to be handled based on the service instruction; collecting identity verification information of the user, and performing identity verification on the user based on the identity verification information; if the identity verification is passed, generating and pushing a service information input interface to the user according to the type of the certificate service needing to be handled; acquiring user driving qualification information uploaded in the service information input interface, and performing service preprocessing on the user driving qualification information by adopting a driving qualification review model; pushing a certificate service confirmation interface to the user, so that the user confirms the to-be-examined information in the certificate service confirmation interface; and in response to a confirmation instruction of the target user for the certificate business confirmation interface, pushing the to-be-examined information in the certificate business confirmation interface to an examination end to complete a business handling process.

The invention provides a vehicle-mounted eye protection lamp and display screen linkage control method, device and equipment and a medium, and relates to the technical field of linkage control, and the method comprises the steps: obtaining user driving behavior data, the external environment illumination intensity of a vehicle-mounted display screen and the current display content type; determining a driving state and a fatigue level based on the user driving behavior data, and determining a day and night mode based on the external environment illumination intensity; based on the driving state, the fatigue level, the day and night mode and the current display content type, generating a display screen control parameter and an eye protection lamp illumination parameter; adjusting backlight of the display screen based on the display screen control parameters; and controlling a projection area of the eye-protection lamp based on the eye-protection lamp illumination parameters. In the mode, the external vehicle-mounted eye protection lamp and the display screen are jointly controlled, the driving state and the fatigue level of the user and the day and night mode of the external environment are considered, light display is completed in public, and a comfortable eye use environment is provided for the user.

The present invention relates to a continuously variable transmission for a bicycle. The continuously variable transmission for a bicycle can automatically shift gears continuously in response to changes in driving force and load according to the bicycle-riding environment without user intervention, recharges, by means of a generator, with power generated during riding and shifting, prevents reverse rotation of the central shaft, and also allows transmission to be manually controlled by means of a load-providing unit when necessary. To that end, the continuously variable transmission for a bicycle comprises: a transmission unit which receives rotational power from the central shaft, which is driven and rotated by a user, and automatically shifts gears in response to resistance when rotating, the rotational power being delivered in the order of a first carrier, a first planetary gear, a first ring gear, a first sun gear, and an output shaft; and a load-providing unit which is installed to engage with the transmission unit and selectively provides a load to the transmission unit. Therefore, the continuously variable transmission for a bicycle facilitates gear changes based on the bicycle-riding environment.

The invention discloses a driving parameter acquisition method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a first user driving parameter of a target vehicle in a driving mode; responding to the condition that the target vehicle enters the simulated driving mode, and acquiring a second user driving parameter of the target vehicle in the simulated driving mode; adjusting the first user driving parameter by using the second user driving parameter to obtain a target user driving parameter; wherein the target user driving parameters are driving parameters used for representing user driving preferences. In this way, the target user driving parameters which accurately and truly reflect the user driving preference can be obtained.

The invention discloses an electric vehicle highway energy supplement demand prediction system and method combining a physical model and a neural network. The system comprises a vehicle terminal, a cloud server, a third-party API interface platform, a user behavior monitoring module, a user driving mode setting module and a user behavior monitoring module. The cloud server comprises a model training module, a data storage module, a physical model and neural network combined prediction model and an energy supplement demand judgment module; the physical model and neural network combined prediction model firstly calculates basic energy consumption through the physical model, and then performs error correction on nonlinear factors by using the neural network to obtain final predicted energy consumption; the nonlinear factors comprise environment temperature, wind speed and user driving habits; and the energy supplement demand judgment module is used for comparing the current battery remaining capacity with the final predicted energy consumption, and judging the energy supplement demand of the expressway in combination with a safe endurance threshold. According to the method, the physical model and the neural network are combined, and energy consumption can be accurately predicted.

A modular flow monitoring package (MFMP) is provided for use in an additive delivery system. The MFMP may be manufactured as an add-on to be added to an existing additive delivery system, or may be incorporated into a cartridge or container structure. The MFMP includes a flow sensor for sensing flow of a base fluid and user actuator position sensors for sensing the position of one or more user actuated additive flow adjustment levers. A visual display, which may comprise an array of multi-color LED's may convey information to a user that is relevant to a user's use of the additive delivery system or the user's nutritional needs. Such information may include a current dosage of additive, being delivered, whether a recommended dosage of additive has been consumed, remaining life of a cartridge or supply of additive, and other data relative to health or performance monitoring.

The invention relates to the technical field of lithium battery safety, in particular to an electric tricycle lithium battery charging and discharging management method and system, and the method comprises the steps: obtaining lithium battery state data, environment data, tricycle load data and historical driving data; clustering analysis is carried out on the user driving data, and electro-tricycle scene types are divided; performing health degree evaluation on the battery state, automatically matching a charging mode according to the health degree, generating a charging current limiting value through a multi-objective optimization algorithm, performing dynamic matching on charging parameters, and executing charging operation according to the matched parameters; the scene type is recognized, a discharge current limiting value is generated through a multi-target optimization algorithm, discharge parameter dynamic matching is carried out, discharge operation is executed according to matched parameters, and energy recovery is started during downhill braking; and establishing a battery abnormal state identification model, and triggering graded early warning when an abnormal state is identified. Therefore, the problems of fixed charging and discharging modes, single abnormity monitoring, insufficient scene adaptation and the like in the prior art are solved.

The invention discloses a thermal management method and system of a vehicle, the vehicle and a storage medium. The method comprises the steps that multi-source data collected by a vehicle are obtained, and the multi-source data at least comprise vehicle state data, environment data and driving behavior data; performing clustering analysis on the multi-source data, and determining a user driving behavior portrait; based on the user driving behavior portrait and a multi-objective optimization decision algorithm, generating a thermal management control parameter of the vehicle; and performing thermal management on the vehicle based on the thermal management control parameters. According to the invention, the technical problem of low reliability of the thermal management method of the vehicle in the related art is solved.

The invention provides a care mode control method and device and a vehicle, and the method comprises the steps: obtaining a mode triggering instruction of the vehicle, and the mode triggering instruction is generated in any one mode of face recognition, voice recognition or key pressing; in response to the mode triggering instruction, the vehicle is controlled to enter a care mode so as to adjust the vehicle configuration, and the care mode at least comprises a driving strategy. The driving strategy that the vehicle is controlled to be in the care mode is considered that the physiological and psychological ability of the elderly user is reduced along with age increase, so that when the elderly user drives or rides the vehicle, the vehicle is controlled to run safely and stably through smoother torque, the driving comfort of the user is improved, and the driving experience of the user is improved. And safer and more convenient riding experience is provided for the elderly users.

The invention discloses a control method and device and intelligent driving equipment, and the method comprises the steps: controlling the transverse offset of the intelligent driving equipment away from one side of a target vehicle door according to the position information and vehicle door information of the target vehicle, and / or controlling the longitudinal speed of the intelligent driving equipment. Wherein the target vehicle door is located on the side, close to the intelligent driving equipment, of the target vehicle door, and the vehicle door information indicates at least one of the following items: the opening duration of the target vehicle door of the target vehicle or the detection result of a driver at the target vehicle door. The technical scheme can be applied to the field of intelligent vehicles such as electric vehicles and new energy vehicles, the vehicle can be controlled to achieve different degrees of transverse avoidance and / or longitudinal braking in the scene that the door of the front vehicle is opened, and the driving safety and the user driving experience of the vehicle can be improved.

The invention provides a parking method and device and a vehicle. The parking method can be applied to the field of intelligent driving. The method comprises the steps of obtaining pose information, wherein the pose information comprises pose information of a vehicle in the process that a user drives the vehicle to park in a target parking space; and controlling the vehicle to be automatically parked in the target parking space according to the pose information. The embodiment of the invention can be applied to an intelligent vehicle or an electric vehicle, and the pose information of the vehicle in the process that the user drives the vehicle to park in the target parking space is memorized, so that when the user hopes to park the vehicle in the target parking space next time, the vehicle can park the vehicle in the target parking space through an automatic parking function and the previously memorized pose information. And controlling the vehicle to be automatically parked in the target parking space.

The invention discloses a battery thermal management control method and device, equipment and a medium. The method comprises the steps that current driving data and battery state data of a target vehicle are acquired; a user driving habit database is inquired according to the current driving data, whether current driving conforms to a user driving habit rule or not is determined, and when the current driving conforms to the user driving habit rule, target user driving habit data are obtained, and the target user driving habit data comprise at least one of habit driving power and habit driving time; according to the driving habit data of the target user and the battery state data, determining a battery adaptive thermal management strategy; and performing thermal management control on the battery of the target vehicle according to the battery self-adaptive thermal management strategy. According to the method, the battery self-adaptive thermal management strategy can be dynamically adjusted and implemented according to driving habits of different users and actual vehicle using scenes, unnecessary energy consumption under a traditional fixed threshold strategy is effectively avoided, the energy utilization efficiency is remarkably improved, and the driving range of the vehicle is prolonged.

The invention discloses a vehicle interaction method and device, equipment and a storage medium, and relates to the technical field of vehicles. The method comprises the following steps: acquiring eye movement information and / or semantic information of a user driving a vehicle; determining correspondingly triggered interaction operation according to the eye movement information and / or the semantic information, responding to the interaction operation and generating projection information incident to the human eyes; and when it is detected that the vehicle is in a non-linear driving state, the projection information is hidden or shrunk to be displayed in the corner area. Through the technical means, the problem that the eyes of a driver leave the front of the vehicle when the driver interacts with the vehicle in the prior art is solved, the driving risk is reduced, and safe driving of the vehicle is guaranteed.

The invention discloses a vehicle core control unit domain control system integrated with a networking function, which relates to the technical field of vehicle control, and comprises a networking data fusion module for establishing a multi-source data interaction channel; the domain control collaborative decision-making module is used for generating a global optimization control strategy; the dynamic control execution module is used for adjusting vehicle operation parameters in real time; the remote upgrading operation and maintenance module is used for realizing remote iterative updating of a control algorithm and functional firmware through a network connection channel and synchronously finishing system state diagnosis; and the closed-loop optimization feedback module is used for collecting vehicle operation data, user driving behaviors and environment feedback information and continuously optimizing cross-domain cooperative control logic. According to the invention, through integration of multi-module cooperative work such as network connection data fusion, domain control cooperative decision, dynamic control execution, remote upgrade operation and maintenance and closed-loop optimization feedback, high intelligence and adaptive control of each domain of the vehicle are realized, and further development of an intelligent driving technology is promoted.

The invention provides a parking method, device and equipment of a shared intelligent parking lot and a storage medium. The method comprises the steps of receiving vehicle information input by a user through a mobile terminal and a parking space reserved by the user through the mobile terminal; guiding the user to park the vehicle on the reserved parking space according to the vehicle information and the reserved parking space; and receiving time information when the user drives the vehicle to leave, calculating parking fees according to the time information, and guiding the user to leave. Through data linkage and automatic management and control, the convenience of the whole process of the user is improved, the labor cost of the parking lot is reduced, and efficient utilization of parking space resources is guaranteed.

Disclosed in the present application are a vehicle control method and apparatus, and a vehicle, a storage medium and a program product. The method comprises: acquiring historical traveling parameters of a vehicle during the process of a user driving the vehicle within a historical time period; performing feature extraction on the historical traveling parameters to obtain a user driving feature; recognizing the user driving feature on the basis of a style recognition model, so as to obtain a user driving style of the user; and in response to detecting that the user is driving the vehicle, controlling the operation of the vehicle on the basis of the user driving style, so as to assist the user in driving the vehicle. The present application solves the technical problem in the related art of the effect of assisting a user in driving a vehicle on the basis of a user driving style being relatively poor.

The invention relates to a system (100) for generating real-time causal reasoning insights in real time. The system (100) comprises a global causal graph creation module (101), a natural language query processing module (102), an information extraction module (103), a query-centric subgraph generation module (104), and an adaptive causal reasoning engine (105). The queries from users are processed to identify relevant causal relationships in the global causal graph. The adaptive causal reasoning engine (105) refines the insights iteratively based on user feedback, improving accuracy. The system (100) converts technical insights into structured narratives. A visualization module presents causal relationships through graphs and charts. The feedback mechanism allows users to correct errors and adjust outputs, facilitating user-driven data analysis and causal reasoning, delivering actionable insights for a variety of applications.

The embodiment of the application relates to the technical field of vehicle linkage, and discloses a vehicle and smart home equipment linkage method and system, the method comprises the following steps: acquiring multi-source data, wherein the multi-source data at least comprises current time information, user driving state data, current user position information, historical home-coming time information, historical home-coming route and outdoor environment information; based on the multi-source data, a home-coming time prediction model is used for prediction to determine a home-coming intention confidence and an estimated home-coming time; and the smart home equipment is controlled according to the home-coming intention confidence and the estimated home-coming time. The technical scheme of the application can realize timely linkage between a vehicle home-coming scene and smart home.

The invention provides a driving behavior type determination method and device, electronic equipment, a vehicle and a chip, and relates to the field of machine learning. The method comprises the following steps: acquiring driving behavior data of a plurality of vehicles, wherein the driving behavior data comprises vehicle data and environment data; performing cleaning and feature extraction on the driving behavior data, and determining a plurality of feature samples corresponding to the plurality of target vehicles; clustering the plurality of feature samples based on one or more feature values in the plurality of feature values to obtain a plurality of category sets; and obtaining evaluation scores of the plurality of category sets to determine the driving behavior type of each category set. According to the technical scheme provided by the invention, the portrait features of the user can be extracted and classified through a large amount of unsupervised user driving behavior data, and the evaluation score of the data sample in each category is obtained, so that the driving behavior type of each category of portrait is determined, the efficiency can be improved, and a new type of the user portrait can be obtained.