649 results about "Safe driving" patented technology

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

The invention relates to the technical field of parking lot digital management, and discloses a digital twin enabling parking lot digital global management system. According to the system, a global digital twin model of a parking lot is generated, and multi-source sensing data such as parking space states, vehicle identities and environmental parameters are fused; generating a parking space distribution matrix with priorities and time windows in combination with the parking request of the user and the real-time parking space state; according to the parking space two-dimensional code hardware parameters, the digital twin model and the parking space distribution matrix, outputting a vehicle guiding path set with a timestamp; a real-time obstacle avoidance and dynamic adjustment system is constructed to generate a safe driving path set so as to dispatch vehicles; outputting a power distribution control instruction set and updating the digital twinborn model by combining the electric quantity of the energy storage unit, the power distribution network data and the safe driving path set; and finally, system knowledge evolution and end-to-end closed-loop optimization are realized through scheduling execution logs. According to the system, global efficient management of the parking lot is realized, and the parking space utilization, vehicle scheduling and energy utilization levels are improved.

The invention provides a heterogeneous motorcade prediction control method based on a path information protection mechanism, and relates to the technical field of network connection unmanned vehicle cooperative control and intelligent traffic. Firstly, a path information protection mechanism is provided for preventing an alien invading vehicle from tracking a motorcade and ensuring the safety of motorcade path information. In addition, a predictor model is established to improve the estimation performance of the adaptive law, and a variable gain nonlinear expansion state observer is designed to approach and compensate the total disturbance. Then, by introducing a variable-gain hyperbolic tangent tracking differentiator, the problem of'complexity explosion 'caused by repeated derivation of a virtual controller in a backstepping method is avoided; and finally, a distributed prediction cooperative controller is constructed, and stable and safe driving of the whole heterogeneous network connection fleet is ensured.

The invention discloses a bridge floor global driving wind environment early warning method, system and device based on limited measuring points and a storage medium, and relates to the technical field of wind speed early warning and artificial intelligence. Future short-time wind speed is predicted based on wind speed time history data, and a two-dimensional high-temporal-spatial-resolution prediction flow field of multiple planes is obtained according to the future short-time wind speed; main beam global wind-induced vibration response data are obtained based on the wind-induced vibration response data; obtaining three-dimensional high-temporal-spatial-resolution prediction flow field data according to the two-dimensional high-temporal-spatial-resolution prediction flow field and the girder global wind vibration response data; analyzing the three-dimensional high-temporal-spatial-resolution prediction flow field data to obtain a safe driving critical wind speed, and setting a wind speed-vehicle speed limiting criterion; and when the predicted wind environment exceeds the wind speed limit criterion, outputting the predicted data and the early warning level of the corresponding driving wind environment, and carrying out advanced early warning. According to the invention, the problem of low accuracy of existing driving safety early warning is solved, and wind speed multi-stage early warning for different vehicles in different driving environments is realized.

The invention provides a ramp energy-saving control method based on off-line speed planning and dual-mode model prediction tracking, and aims to solve the problems of insufficient precision of ramp driving energy consumption and safety cooperative control and frequent mode switching of an automatic driving vehicle. The method comprises the following steps: firstly, identifying a key road section based on high-precision road gradient data, and generating an optimal energy-saving reference speed matched with gradient characteristics in an off-line manner by adopting a dynamic planning and sequential quadratic planning hybrid optimization strategy; secondly, when the vehicle runs, relevant information is loaded after confirmation of a driver, the system takes over the longitudinal control right, two control modes are dynamically switched based on the front vehicle distance, and frequent mode switching is avoided through a hysteresis threshold value; and finally, taking the slope-fused vehicle longitudinal dynamics model as a prediction model, solving an optimal control instruction online by adopting a model prediction control algorithm, performing closed-loop execution, monitoring intervention operation of a driver, and immediately returning the driving right after the intervention operation is detected. According to the method, offline planning and online dual-mode tracking technologies are integrated, the method has the advantages of high energy consumption optimization precision, stable mode switching and good safety adaptability, and energy-saving and safe driving of the automatic driving vehicle in a ramp scene is realized.

The present invention relates to a safety steering device for manual intervention by a safety driver in an autonomous vehicle or a vehicle with a driver assistance system. The safety steering device comprises a control unit and a joystick operable by the safety driver, from which a steering intervention signal can be transmitted to the control unit, wherein the steering intervention signal overrides an autonomous steering signal. A safety control element is arranged on the joystick, which, when activated by the safety driver, generates a release signal to enable the transmission of the steering intervention signal to the control unit.

The invention discloses a real-time monitoring and early warning system for an abnormal driving state. The real-time monitoring and early warning system is applied to safe driving of road vehicles. The real-time monitoring and early warning system is provided with a vehicle-mounted data acquisition module, a cloud / edge calculation and analysis module and a non-positive driving behavior early warning and intervention module. The invention further discloses a monitoring and early warning method of the system. By adopting the technical scheme, multi-modal data fusion is adopted, so that the control is more accurate; angry or aggressive driving states are captured through real-time identification and behavior data; early warning intervention is performed to remind a driver or a traffic control department in time, so that accident risks are reduced; the control threshold value is dynamically adjusted, and false alarms are reduced; and through data analysis, a behavior pattern research basis is provided for traffic management.

The invention provides a vehicle fault identification and driving behavior early warning method based on multi-modal feature fusion, and relates to the field of vehicle fault diagnosis and safe driving, and the method comprises the steps: collecting a vibration signal, an acoustic signal and a driving operation signal, extracting a fault feature and a behavior feature, calculating a time delay cross-correlation function to obtain a time delay influence spectrum, and carrying out the early warning of a driving behavior. And performing recursive calculation to obtain an evolution trajectory curve, calculating a fault-behavior coupling risk index by detecting the deviation of the evolution trajectory curve from a preset stable region, and generating a multi-modal early warning signal of a corresponding intensity level according to the risk index. The method has the advantages that correlation analysis of faults and driving behaviors is achieved, and the accuracy and timeliness of early warning are improved.

The embodiment of the invention provides a vehicle interface information generation method and system and a vehicle, an interactive interface is deployed on the vehicle, in the process that the vehicle is safely driven by an interactive object, the interactive interface is presented in the visual range of the interactive object, and the method comprises the steps that the performance index type of the interactive interface is determined; determining test interface information associated with the performance index type; in the process that the interaction interface displays the test interface information, electroencephalogram data and / or eye movement data of the interaction object for the test interface information are / is collected; determining a test result of the test interface information based on the electroencephalogram data and / or the eye movement data; based on the test result, target interface information meeting the driving scene of the vehicle is generated for the interactive interface, and a performance index result of the target interface information under the performance index type meets a performance index threshold value under the performance index type. The technical problem that the interface information generation effect of the vehicle is poor is solved.

The invention discloses a train control system, method, equipment and medium based on active sensing and autonomous localization, and the system comprises a multi-source autonomous sensing system which collects and outputs the information of the environment in front of a train by fusing the sensing data of a plurality of sensors; the vehicle-mounted standby system is in communication connection with the multi-source autonomous sensing system, accesses a pre-stored digital track map and is used for dynamically generating route topology and movement authorization and generating a train control instruction according to the train front environment information, the train real-time position and the line data of the digital track map; a dual-mode communication switching unit is arranged in the vehicle-mounted standby system and used for monitoring the communication state of the main train control system, and when the main train control system breaks down, the train control right is automatically switched to the standby system. Compared with the prior art, after the main train control system loses efficacy, the train can be made to be independent of a central control system and a fixed electronic map, the real-time state of a line is automatically adapted, and the safe driving instruction is generated.

The invention provides a safe driving method for a chemical goods freight vehicle, which comprises the following steps: judging whether a dynamic motor vehicle, a non-motor vehicle and a person enter a dangerous area or not when the vehicle reaches a turning area to turn by predicting the direction of a moving object, and marking the predicted dangerous vehicle and person. Therefore, the influence of a driving blind area on safe driving of a driver is reduced.

The invention discloses a safety system and method for preventing drunk driving of a vehicle, the vehicle and a medium, and relates to the technical field of safe driving. The safety system comprises a vehicle-mounted terminal and a cloud server which are in communication connection, the vehicle-mounted terminal comprises a detection module, a collection module, a processing module and a control module, and the processing module is used for verifying the identity of a driver through face data and voice data continuously collected by the collection module and sending the identity of the driver to the cloud server after verification is passed. The behavior state of a driver is determined according to voltage data continuously output by the comprehensive detection module, if the behavior state is drunk driving, a first control instruction is generated, early warning information is uploaded to the cloud server, and the control module is used for intelligently controlling the vehicle through the first control instruction or a second control instruction. Wherein the second control instruction is obtained by analyzing the early warning information through the cloud server to obtain the vehicle operation data and combining the traffic environment around the vehicle and the vehicle operation data until the vehicle stably stops, and safety is ensured.

The invention discloses a truck driver safe driving evaluation method based on SEDEA, and the method comprises the steps: regarding the vehicle characteristics, behavior characteristics, road characteristics and environment characteristics of a vehicle in a driving process as external resources of a driver safe driving task, and regarding the characteristics of overspeed driving, fatigue driving, distraction driving and the like as risk results after the resources are utilized; the method comprises the following steps: taking resource utilization efficiency evaluation as a core means to measure the safe driving ability of a truck driver, and constructing a weight system containing multiple inputs and multiple outputs and a resource utilization efficiency evaluation model to calculate a safe driving score of the driver; and various safety indexes and quantitative classification management measures of the driver are given based on the model. The model is in close contact with the safe driving management situation of the truck driver, not only considers the resource input and the efficiency output of the safe travel task of the truck driver, but also sets the optimization direction between different inputs and outputs through a weight system.

The invention discloses a train safe driving guarantee control system based on the Internet of Things, and particularly relates to the field of train safe driving. Comprising a multi-node data interaction screening module, a data space-time alignment association module, an ice and snow environment comprehensive influence quantification module, a wheel-rail contact stability dynamic evaluation module, a safe driving boundary dynamic calculation module, a multi-dimensional control strategy execution module and a dynamic closed-loop feedback optimization module. The multi-node data interaction screening module is used for constructing a multi-node interaction link through a wireless communication technology to obtain multi-dimensional data and screening effective parameters; according to the method, the multi-dimensional space-time association data matrix is constructed through multi-node real-time interaction and in combination with the space-time alignment technology, the problems that data fragmentation is caused, space distribution monitoring is insufficient, and the global state is deduced only depending on single-point data are solved, the ice and snow environment assessment accuracy is improved, and reliable data support is provided for accurate control of a train.

The invention relates to the technical field of vehicle safe driving, in particular to an alcohol detection and vehicle control system for safe driving of a driver, which comprises an alcohol detection system, a core control system and an application monitoring system, the alcohol detection system comprises an air pressure detection sensor, a sound recognition sensor, a passive alcohol detection sensor, an active alcohol detection sensor, an infrared body temperature sensor, a camera, an NFC module and a fingerprint recognition module; the core control system comprises an ignition switch control circuit, a 4G communication module, a positioning module, a power supply circuit, a voice module, an automobile CAN bus module and a master control core system. The application monitoring system is connected with the cloud application system through the Internet, and the collected local data and the detection result are reported to the server application monitoring system, so that the risk of alcohol in the body of the driver to safe driving can be reduced.

Disclosed herein is a method and system for detecting, monitoring and / or controlling one or more of mobile services for a mobile communication device (also referred to herein as a Controllable Mobile Device or CMD), and in particular, when the device is being used and the vehicle, operated by the user of the device, is moving. In addition, one aspect of the invention generally relates to a method and system for modifying a user's driving behaviors, in particular to a system and method for modifying a user's unsafe driving behaviors, e.g., using one or more services of a controllable mobile device while driving.

The invention relates to the field of vehicle safe driving, in particular to a collision risk detection method and device. According to the invention, through receiving the traversing target motion data and the vehicle position uploaded by each vehicle in the control area, the cooperative sensing network is formed by means of the detection range coverage of multiple vehicles, when a certain vehicle has a sensor blind area due to the shielding of a static vehicle, other vehicles can upload the detected traversing target information to the cloud server, so that the information of the traversing target can be transmitted to the cloud server. Target omission of a single vehicle due to view limitation is avoided; the cloud server constructs a dynamic target sequence based on multi-source data, can more comprehensively track the movement track of the traversing target, analyzes the collision risk in combination with the position of each vehicle, can pre-judge the threat of the traversing target to the vehicle through the information of other vehicles when the traversing target is located in a certain vehicle blind area, and then carries out control operation on the corresponding vehicle in time. The problems that a blind area exists in a sensor, and when a static vehicle exists in the view field, the vehicle cannot find the crossing pedestrian in time, and injuries are easily caused are effectively solved.

A vehicle, a method of controlling a vehicle, and a non-transitory computer readable storage medium are described. The vehicle can comprise a management and control system associated to onboard systems and / or to a driving input interface and / or to the engine and / or powertrain and / or to at least one wheel and / or to the chassis. The management and control system can: determine aggregated command outputs; detect one or more dynamic parameters exceeding a threshold safety value; selectively prioritize each of the aggregated command outputs based on one or more of the dynamic parameters to change from a user-selected driving mode to a safety driving mode; and change the prioritized safety driving mode back to the user-selected driving mode in response to the one or more of the dynamic parameters no longer exceeding the threshold safety value.

According to aspects illustrated herein, methods and systems for driver behavior monitoring and intervention are disclosed. The method includes capturing vehicle-related data and driver-related data pertaining to a two-wheeled vehicle and a driver operating the two-wheeled vehicle, respectively, and analysing vehicle-related data to detect commencement of a trip by the driver. The method further includes, processing the driver-related data to identify one or more driver attributes associated with unsafe driving behavior, based on one or more predefined rules, and sending an alert to the driver upon the identification of the driver attributes. The alert comprises recommendations for corrective measures for the driver to be implemented within a pre-determined time period. The alert further comprises a notification indicating that preventive actions will be initiated if the corrective measures are not implemented. The method further includes executing the preventive actions if the driver does not implement the corrective measures.

The invention discloses a heavy truck safe driving dynamic scoring method and device based on road segment risks and a medium, and relates to the technical field of driving safety assessment, and the method comprises the steps: obtaining driving road condition parameters, and carrying out the time-space reference synchronization of the driving road condition parameters, so as to determine road segment risk field parameters; performing dynamic risk layer fusion on the road section risk field parameters to obtain a road section risk field; based on the road section risk field, determining a real-time risk value of the road section through risk propagation prediction; performing score logic dynamic switching of linear interpolation on the real-time risk value of the road section to obtain a safe driving score of the current road section of the heavy truck; and according to the safe driving score of the current road section of the heavy truck, updating the driving ability of the logistics service to obtain a driver ability portrait. According to the method, the technical problems that existing safe driving scoring cannot adapt to dynamic road risks, and dynamic scoring and decision basis timeliness are poor are solved.

The invention relates to a mining trackless rubber vehicle centralized control method, which comprises the steps of obtaining an elastic wave signal generated by surrounding rock fracture at the position of a mining trackless rubber vehicle, obtaining surrounding rock three-dimensional principal stress component data at the position of the mining trackless rubber vehicle, processing the elastic wave signal through an edge processing module to obtain micro-seismic event parameters, and outputting the micro-seismic event parameters. The micro-seismic event parameters comprise a seismic source position and an energy characteristic of a micro-seismic event; converting the surrounding rock three-dimensional principal stress component data into a strain energy density field, fusing the strain energy density field with energy characteristics, and calculating to obtain a total energy value of a micro-seismic event; generating a surrounding rock health state evaluation result based on the micro-seismic event total energy value; determining a rockburst risk level and a high-risk area boundary based on the seismic source position of the micro-seismic event and a surrounding rock health state evaluation result; calculating a safe driving track based on the rockburst risk level and the high-risk area boundary; and sending the safe driving track to a vehicle control system of the mining trackless rubber vehicle.

The utility model discloses a vehicle front windshield shielding device, a sunshade device and a vehicle glass shielding device.The vehicle front windshield shielding device comprises a sunshade curtain, and the front end of the sunshade curtain can be installed on the front portion of a vehicle front windshield or the front portion of a vehicle bridge. The rear end of the sunshade curtain can be unfolded into a first unfolded state through the two adjustable connecting frames, the first shielding area covers a vehicle driving platform, and the inclination angle between the sunshade curtain in the first unfolded state and a front windshield of the vehicle can be adjusted by adjusting the length or angle of the telescopic rod. According to the vehicle front windshield shielding device, the sunshade device and the vehicle glass shielding device, sunlight can be shielded from irradiating into a vehicle from the vehicle front windshield in the vehicle driving process, so that sun protection of a vehicle console in the vehicle driving process is achieved, and safe driving is facilitated; in addition, the sunshade can adapt to drivers of different heights and meet the requirements of different sunshade ranges, and the practicability is very high.

3D objection detection is a computer vision task that generally refers to detecting (e.g. classifying and localizing) an object in 3D space from an image or video that captures the object. This computer vision task has many useful applications, such as autonomous driving applications which rely on the detection of 3D objects in a local environment to make autonomous driving decisions. State-of-the-art 3D object detectors generally rely on machine learning, but current training processes for these detectors do not specifically address false negative detections, or missed objects, which are often caused by occlusions and / or cluttered backgrounds in the given image / video. Reducing false negatives is crucial for many downstream applications, particularly autonomous driving applications which rely on accurate detection of obstacles for making safe driving decisions. The present disclosure provides for a multi-stage training process that reduces false negative detections by 3D object detectors.

An intelligent vehicle active obstacle avoidance control method based on visual perception is used for improving the driving safety of a vehicle in a complex traffic scene. The invention relates to the field of intelligent driving. The system comprises an upper layer and a lower layer, the upper layer is an environment sensing module, and the lower layer comprises a risk assessment module, a path planning module and a pure tracking algorithm. The upper-layer environment sensing module comprises RRW-YOLOv11n, multi-scale features are extracted through an RGCEBlock module, feature fusion is enhanced through a Re-calibration FPN structure, the bounding box regression precision is optimized by using a WPIOU loss function, and finally sensing information is output; a lower-layer risk assessment module performs multi-source risk assessment to obtain a multi-source risk probability, calculates a posterior risk probability through Bayesian risk fusion, and plans a path through a path planning module; path tracking control is carried out through a pure tracking algorithm, and safe driving of the vehicle in a complex traffic scene is achieved.

The application provides a parent-child entertainment intelligent cockpit system and a control method thereof, an HMI system can realize baby entertainment mode switch, baby entertainment mode setting item, baby entertainment mode pop-up window prompt, a multimedia system can adjust volume, sound area, sound area use, a baby entertainment mode APP can control entering and exiting the baby entertainment mode; the intelligent cockpit system can consider different hardware configuration differences and different signal sources, realize control, playing and display of different configuration vehicle models, provide rich audio and video entertainment programs such as children's songs, animation, history, story and science popularization for children, provide entertainment programs in the case of ensuring safe driving, realize various vehicle use requirements, and can reduce investment and test verification caused by different vehicle models and different configuration software differentiation development, and can realize one-time development and verification and simultaneously loading multiple vehicle models.

The invention relates to the technical field of driving early warning, in particular to a mining rubber-tyred vehicle omnibearing safe driving early warning system which comprises an image reflection monitoring module, a brightness gradient recognition module, a path deviation extraction module, a control trend judgment module and a risk linkage early warning module. According to the method, reflective characteristics and edge contour information are comprehensively analyzed on the basis of image data, brightness gradient distribution evolution trend identification is introduced to distinguish static and moving light source interference signals, and continuous tracking of a pixel displacement direction and a lane center deviation trend is combined to determine a lane center deviation trend. The behavior consistency judgment is carried out with the assistance of a reverse verification mode of a steering angular velocity change trend and a path offset relationship, so that dynamic coupling identification among obstacle stability, an offset trend and a driving control behavior can be realized, and the early perception capability of potential risks in a complex working condition is effectively improved; and the joint early warning judgment of the actual driving deviation and the obstacle risk in the running environment of the mining rubber-tyred vehicle is ensured.

The invention relates to the technical field of vehicle automatic driving, and discloses a mine vehicle trajectory prediction method based on deep learning and related equipment. The method comprises the steps of collecting multi-source sensing data and a site capacity state in a target mine operation environment, and performing coordinate system conversion and noise filtering to generate a standard sensing data set; mine car interaction scene feature vectors are constructed through mine operation scene feature coding and multi-source information fusion, and space-time relation extraction is carried out on the mine car interaction scene feature vectors to obtain deep space-time feature representation; based on the depth spatial-temporal feature representation and the site capacity state, carrying out point position rotation target selection on the mine cars, and determining a target operation point position of each mine car to obtain a point position distribution decision result; and performing Frey internal coordinate conversion and safe driving area construction on the point location distribution decision result, and performing trajectory planning on the safe driving area to generate a final prediction result. According to the invention, intelligent point position rotation decision-making of mine multi-vehicle cooperation is realized, and the trajectory prediction accuracy and the operation safety are improved.

The present invention relates to the adaptive utilization of road surface information. The system comprises at least one of an information distribution device or an information processing device. The information distribution device collects vehicle information from vehicles traveling a pre-identified infrastructure deficient section in which the amount of road surface detection information collected about a road is not greater than a preset reference amount, and the information processing device determines the road surface condition of the infrastructure deficient section on the basis of the vehicle information provided by the information distribution device, detects the level of travel risk for each vehicle type with respect to the determined road surface condition, generates a warning message for safe driving according to the detected level of travel risk for each vehicle type, and provides the warning message and road surface information to the vehicle via the information distribution device.

The invention relates to a road traffic sign detection method, device and equipment and a medium, and the method comprises the steps: embedding a focusing linear attention mechanism module in a feature pyramid path of a neck network of a preset first traffic sign detection model, and adding a P2 detection layer in a detection head network, updating a CIoU loss function of the first traffic sign detection model into a WIoU loss function to construct a second traffic sign detection model; inputting the to-be-detected traffic scene image into a second traffic sign detection model trained to a convergence state to determine traffic sign categories and traffic sign key information corresponding to one or more road traffic signs in the traffic scene image; and transmitting the road traffic sign type corresponding to the road traffic sign and the traffic sign key information to an instrument panel of the target vehicle, and performing voice broadcast on the road traffic sign type and the traffic sign key information to prompt a driver to perform safe driving. According to the invention, the positioning and identification precision of traffic sign small target detection is greatly improved.

An AR signage display device interlocked with a vehicle, according to the present invention, may detect that a forward looking situation has occurred, on the basis of driving environment information of the vehicle and sensing data of the vehicle, and accordingly, carry out, for safe driving, display limitations on at least part of an AR digital signage included in a front image. Accordingly, on the basis of the driving environment information, such as traffic congestion zones or reduced visibility of the vehicle, the driver's front view is not blocked, and a region related to the driving environment information is not covered.