154 results about "Vehicle accident" patented technology

The invention discloses an accident analysis and intelligent intervention method and system based on an intelligent networked automobile, and particularly relates to the technical field of accident analysis, which comprises the following steps: when the intelligent networked automobile approaches an accident-prone place, extracting important features from historical traffic data in the accident-prone place of the intelligent networked automobile by using a t-SNE dimension reduction method; acquiring real-time traffic data of the intelligent networked automobile, and determining similar information of the traffic data of the intelligent networked automobile; bayesian inference is carried out based on historical traffic data in an accident-prone place of the intelligent networked automobile and real-time traffic data of the intelligent networked automobile, and probability information of the traffic data of the intelligent networked automobile is determined by analyzing statistical data and constructing a machine learning mode; through comprehensive analysis of the similar information and the probability information of the traffic data, the risk that the intelligent networked automobile enters the accident-prone place is evaluated, the road traffic safety can be improved, and the accident occurrence rate is reduced.

The invention relates to the related technical field of vehicle damage analysis, in particular to a multi-source data-based vehicle damage correlation analysis method and system, and the method comprises the steps: obtaining vehicle accident multi-source data, building a multi-dimensional feature matrix, recognizing vehicle damage leading factors and an effective correlation chain, generating a vehicle damage influence degree sequence, and constructing a vehicle damage correlation analysis network. And generating a vehicle damage diagnosis report in combination with the vehicle damage influence degree sequence. The technical problems that the identification capability of hidden linkage damage is insufficient, linkage damage caused by secondary factors is easy to ignore, and a vehicle damage diagnosis report cannot provide comprehensive and accurate decision support for accident handling are solved, and the purposes of determining an association strength value by utilizing forward propagation, identifying vehicle damage leading factors, effective association chains and generating influence degree sorting are achieved. And the incidence relation between the influence factors and the vehicle damage types is accurately quantified, a vehicle damage correlation analysis network is constructed, and a diagnosis report is generated in combination with influence degree sorting, so that the technical effects of comprehensiveness, accuracy and reliability of vehicle damage diagnosis are effectively improved.

A lockbar in a tongue of a seat belt system in a vehicle, wherein the crash locking tongue includes the lockbar, a base plate, and a cover material overmolded onto the base plate. The base plate is configured to be reversibly coupled to a buckle in the seat belt system and to have a slot through which a belt webbing extends in order to restrain the movement of a passenger in the vehicle. The lockbar includes one or more fins located on a bottom surface near a front edge, a pair of guide wings located on a back edge adjacent to opposite sides, a clamping surface that is in contact with the belt webbing, and an elastomeric spring. The lockbar undergoes a vertical translation upon a vehicle accident that causes a clamping surface to apply an inward pressure on the belt webbing, thereby, reducing movement of the belt webbing.

A system for recording event data of an autonomous vehicle is disclosed. The present disclosure suggests an EDR system operation scheme suitable for properly investigating the cause of a vehicle accident. Subsystems of an autonomous driving control system may determine whether an event satisfying a preconfigured condition has occurred, and send to an EDR system a trigger signal to trigger recording of data elements related to the event when the occurrence of the event is detected. The EDR system may record data elements that are useful to reconstruct a map of an external environment surrounding an autonomous vehicle at the time of the occurrence of the event or to reconstruct an internal environment of the vehicle.

The invention belongs to the technical field of vehicle risk assessment, and discloses a vehicle accident risk prediction method and device, a storage medium and computer equipment. The method comprises the following steps: acquiring operation parameters of a plurality of vehicles, including load data, operation road type, gradient data, vehicle speed, driving behavior data, night driving time proportion, active safety configuration data, operation weather data, accident frequency and fault frequency; determining a plurality of risk assessment features; taking the risk assessment features as a training set, training a random forest model, and taking the random forest model as an accident risk prediction model when the performance of the random forest model reaches a preset requirement; and inputting the risk assessment features of the to-be-predicted vehicle into the accident risk prediction model, obtaining a survival function output by multiple trees of the accident risk prediction model, and determining the accident occurrence probability of the to-be-predicted vehicle within a preset duration according to the survival function. And the accident risk of the vehicle can be accurately predicted by using the multi-dimensional operation data of the vehicle.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology, and discloses an early warning method, device and equipment based on multi-source accident data and a medium. Training a similarity matching model based on the dimension reduction feature set to generate a similar index structure, analyzing the real-time sensor data stream, converting the real-time sensor data stream into a real-time feature vector, and mapping the real-time feature vector to the similar index structure to obtain a candidate accident record set; and performing similarity comparison on the candidate accident record set and the real-time feature vector to generate a similarity index, and outputting abnormal early warning information when the similarity index exceeds a preset threshold. According to the method, the historical accident data and the real-time sensor data are fused, rapid retrieval and comparison are achieved in a similar index structure, and the real-time performance and accuracy of early warning are improved.

A safety performance quantitative evaluation method for an autonomous driving system, comprising: establishing a vehicle accident rate decomposition model to decompose hazardous events at a vehicle level into hazardous events caused by functional deficiencies at a component level, the component level comprising a perception layer, a positioning layer, a planning layer, and a control layer; acquiring statistical probabilities of hazardous events caused by functional deficiencies in the planning layer, the control layer, and the positioning layer; performing scenario modeling on the probability of the hazardous events caused by the functional deficiency in the perception layer; obtaining confirmed objectives of functions at least on the basis of a natural driving data set, the vehicle accident rate decomposition model, the statistical probabilities of the hazardous events, and the scenario modeling of the perception layer; and using the confirmed objectives of the functions as standards for safety performance quantitative evaluation.

The invention discloses an auxiliary driving automobile accident risk cause chain mining method. The method comprises the following steps: 1) acquiring multi-source time sequence data including vehicle running state data, environment perception data and road condition data; 2) data preprocessing; 3) according to the obtained multi-source time sequence data, calculating a fusion risk index value of the vehicle at the t moment; 4) by taking the high-risk time sequence evolution time section as an analysis window, analyzing accident risk process influence factor variables based on correlation analysis and causality analysis to obtain a core dependent variable set; and 5) based on the identified core cause variable set, carrying out risk cause chain analysis in combination with a target risk event. According to the method, the risk field model fusing the vehicle kinetic energy field and the surrounding potential energy field elements is constructed, so that a high-risk evolution section before a potential collision event occurs can be identified more accurately, and the method has higher real-time response capability and environmental adaptability.

The application discloses a vehicle accident detection method, device and equipment and a storage medium. The method comprises the following steps: when the distance between a moving object around a vehicle and the vehicle is less than a preset threshold, acquiring the vehicle video of the time period when the distance between the moving object and the vehicle is within the preset threshold, the time point and the distance when the distance between the moving object and the vehicle is the shortest; detecting the relative position area of the moving object and the vehicle at the target time point; determining the vehicle accident risk level according to the vibration condition of the vehicle and the target distance; acquiring the image of the moving object, performing feature extraction on the image, determining the object type of the moving object, and identifying the object features of the moving object according to the object type; acquiring the current parking site of the vehicle, generating a corresponding vehicle accident report, and sending the vehicle accident report and the target video to a corresponding client. The application can improve the event backtracking efficiency of the vehicle owner when the accident occurs.

The present invention relates to a vehicle accident notification system which detects whether a vehicle accident has occurred with respect to a first vehicle, generates information thereon on the basis of state information of the first vehicle, and notifies other nearby vehicles of accident information through communication with an external server. More specifically, the present invention relates to a vehicle accident notification system, comprising: a first communication unit installed in the first vehicle and communicating with an external server; a first detection unit installed in the first vehicle and acquiring first state information of the first vehicle; a safety triangle installed in a trunk of the first vehicle; and a first control unit installed in the first vehicle and configured to generate vehicle accident information if it is determined that an accident of the first vehicle has occurred using the first state information, wherein if the vehicle accident information is generated, the first control unit opens the trunk so that the safety triangle is deployed, and transmits the generated vehicle accident information to the outside through the first communication unit.

The invention provides a vehicle accident data processing method and device and a storage medium, and the method comprises the steps: S1, obtaining the vehicle state information of a vehicle within a preset time range before and after the accident time according to the accident time after a triggering event of an accident is received; s2, inputting the vehicle state information into a pre-trained vehicle accident analysis model, and judging whether the vehicle has an accident or not; s3, when it is judged that the vehicle has the accident, determining the latest effective parking time point; s4, according to the effective parking time point, judging whether at least one piece of alarm data of a predetermined type exists or not; if yes, determining the time corresponding to the first piece of alarm data of the pre-type as the accident occurrence time; otherwise, determining the time corresponding to the vehicle positioning record which is closest to the effective parking time point and has the vehicle speed greater than 0 as the accident occurrence time. By means of the technical scheme, the accident occurrence time can be determined more accurately.

The utility model discloses a traffic tool safety warning device, and relates to the field of automobile accident safety warning. The vehicle safety warning device comprises a triggering unit which can trigger a smoke warning unit to release smoke to the air; the smoke warning unit can be triggered by the triggering unit to release smoke for warning to the air, the smoke warning unit comprises a tank body, a smoke outlet guide pipe and a valve, the tank body is used for storing the warning smoke, the smoke outlet guide pipe is a warning smoke spraying channel, and the valve is used for controlling spraying of the warning smoke; the fixing unit is connected with the vehicle, the smoke warning unit and the triggering unit are fixed to the vehicle, and the fixing mode of the fixing unit is nut fixing and magnetic strip fixing; the vehicle safety warning device solves the problem that when a vehicle is difficult to move to a safe position after a fault or an accident occurs, a vehicle coming behind cannot be warned.

This invention discloses a method for accurate identification of the moment of an accident in a new energy vehicle based on multimodal data fusion. The method acquires vehicle motion sensor data, dynamic parameters, and visual image data, and then performs the following parallel processing: The physical layer processes the data to obtain motion features and compares them with preset trigger conditions; when a suspected collision is detected, it outputs the physical layer trigger time and acceleration amplitude; the dynamic layer processes the data based on the deviation between the vehicle's dynamic model and its actual motion state, outputting a vehicle trajectory status label; the visual layer processes the data to detect targets and analyze their motion state; when visual evidence of a collision is detected, it outputs the visual layer trigger time and the type of collision object; the fusion layer performs spatiotemporal alignment of the three layers' outputs and makes a comprehensive judgment, outputting the fused accurate collision trigger time and accident scene classification information. This invention effectively filters false alarms and improves the detection rate of low-speed accidents through multimodal fusion, achieving accurate identification of the moment of an accident and scene reconstruction.

This invention provides a pneumatically controlled fence control group for tunnel boring machines, relating to the field of control group technology, including road passages. After the centralized control system is implemented, personnel control the opening and closing of the fence from a fixed, safe position, eliminating the need for frequent movement along vehicle auxiliary transport routes, thus ensuring the safety of personnel operating the fence and achieving "safety without human intervention." With the centralized control system, shift leaders can closely monitor the on-site safety production situation, ensuring smooth and safe production. This solves the problem of personnel being easily collided with vehicles during operation, which increases the risk of vehicle accidents. Furthermore, manually opening the fence is inefficient, and automatically opening the fence using sensors is prone to errors, leading to lower safety. During use, collisions between vehicles and the fence can cause damage, increasing maintenance costs.

The invention discloses a networked vehicle accident battery cloud assessment method based on internal and external field coupled twinbodies, which comprises the following steps: firstly, defining a transient accident data window, extracting sensor data in the window by an Internet of Vehicles cloud platform, and constructing a multi-field incomplete time sequence data set of external impact and internal monomer voltage; secondly, constructing an internal and external field coupled twinborn body model, deducing and repairing an accident data blind area by using a damping and RC polarization attenuation algorithm, and obtaining an impact-voltage twinborn enhancement vector; and then, through a multi-source moment collaborative dynamics unit and a voltage entropy time-space outlier mining unit, calculating a mechanical clamping force decline value and a battery cell thermodynamic anomaly deviation degree, constructing a full-dimensional failure degree matrix, carrying out normalized weighted calculation to generate a quantitative evaluation vector, and outputting a risk positioning report. According to the invention, accurate quantification and graded early warning of the failure state of the battery pack accident can be realized under the extreme accident condition, and important technical support is provided for battery safety emergency disposal and management strategy optimization.

The application relates to a communication method and device. The method comprises the following steps: in response to an accident of a vehicle, selecting a target communication device from preset terminals and a public safety answering point (PSAP) according to a communication priority of the preset terminals and the PSAP; wherein the preset terminals are communication terminals of accident contacts associated with the vehicle; in response to the target communication device only comprising the PSAP, sending communication data to the PSAP to establish a communication connection with the PSAP, and recording a communication process with the PSAP to obtain communication audio data; in response to the communication with the PSAP being ended, sending a target communication request to the preset terminals to establish a communication connection with the preset terminals, and playing the communication audio data to the preset terminals. The method can enable the accident contacts associated with the vehicle to learn relevant information of the vehicle accident in time after the accident of the vehicle.

The application discloses a digital twin-enabled unmanned vehicle post-accident maintenance method, and mainly solves the low vehicle accident processing rate of the prior art.The implementation scheme is as follows: a task model and a network model under a digital twin network are constructed; maintenance information of each maintenance provider is published; a maintenance response strategy of the unmanned vehicle after an accident at time t is established; a maintenance strategy of each unmanned vehicle at each network edge device is determined; a bid of each network edge device for the unmanned vehicle is determined; matching between the network edge device and the unmanned vehicle is completed; a maintenance price to be paid by the unmanned vehicle is determined according to a VCG pricing mechanism; and the price is paid after the maintenance is completed.The application effectively solves the two-way selection problem between the accident vehicle and the maintenance provider, improves the vehicle accident processing rate, the average income of the maintenance provider and the average social welfare, and can be used for maintenance processing of the unmanned vehicle after an accident in a city traffic system.

The present application relates to the stress simulation method and storage medium of vehicle-mounted controller, first build vehicle-mounted controller simulation model, use finite element simulation analysis to carry out modal analysis, random vibration, impact load strength analysis and check to the equipment structure, determine whether resonance occurs; Whether the load working condition meets the checking standard; Can ensure that the given structure, material and other properties meet the safety factor; If the safety factor is not met, the structure, material and other properties of the vehicle-mounted controller need to be improved and adjusted, and correct guidance is given to the design to avoid deformation, rupture and other risks caused by unreasonable design, leading to vehicle accidents, and protecting the safety of life and property.

The invention discloses a serious vehicle accident reminding method and system, and the method comprises the steps that a vehicle-mounted monitoring device obtains the current state information of a current vehicle, and when it is judged that a serious vehicle accident happens to the current vehicle according to the current state information, serious accident information is generated and uploaded to a cloud monitoring platform; when the cloud monitoring platform judges that a serious vehicle accident actually occurs according to the serious accident information, serious accident reminding information is generated according to the serious accident information; and the cloud monitoring platform obtains related position information of nearby vehicles in the accident signal receiving range according to the serious accident information, and sends serious accident reminding information to the nearby vehicles according to the related position information. Whether a serious vehicle accident happens to the vehicle or not is detected by monitoring the state data of the vehicle during running in real time, and when the serious vehicle accident happens, accident information is uploaded to the cloud monitoring platform, so that emergency rescue of the accident vehicle and warning prompt of nearby vehicles are achieved.

The invention relates to the technical field of artificial intelligence and insurance claim settlement, can be applied to the financial field, and discloses a claim settlement method and device for a vehicle accident, computer equipment and a storage medium. The driving parameters are sent by the vehicle-mounted terminal when the vehicle has an accident; identifying field damage information of the target part in the damaged image; calculating damage verification information corresponding to the driving parameters based on a mechanics principle mathematical model; the three-dimensional physical simulation engine based on the accident scene simulates the collision process of the scene damage information, and outputs driving verification parameters; and determining a claim settlement scheme of the vehicle based on a comparison result between the driving parameter and the driving verification parameter and a comparison result between the field damage information and the damage verification information. Therefore, the problems of high difficulty and low efficiency of vehicle insurance loss assessment and claim settlement are solved.

The utility model discloses a mechanical structure for automatically forcibly opening a vehicle door, which relates to the technical field of vehicle-mounted machinery and comprises a vehicle door plate, one side of the vehicle door plate is connected to the side wall of an A-pillar mounting plate, and a mechanical mechanism for forcibly opening the vehicle door plate is fixedly arranged on one side of the A-pillar mounting plate and is used for forcibly damaging an electromagnetic lock in the vehicle door plate. The forced door opening mechanical mechanism comprises a servo motor and a transmission shaft, an output shaft of the servo motor is fixedly connected with the transmission shaft through a coupler, one end of the transmission shaft is fixedly connected with a worm, and the servo motor is fixedly connected to the A column mounting plate through a motor fixing base. A bearing seat is fixedly installed on one side of the A column installation plate, one end of the worm penetrates through and is rotationally installed in the bearing seat, the device recognizes a vehicle accident through a mechanical system circuit or a detection sensor, a transmission mechanism is driven by an automatic motor, the connecting position of the electromagnetic lock is forcibly damaged, and safety is improved.

The application provides a driver fatigue prediction method and device, electronic equipment and storage medium, which obtains a monitoring video; obtains facial state features and a fatigue score according to the monitoring video; trains a fatigue prediction regression model by taking the facial state features as an input vector and the fatigue score as a target result; extracts facial state features of a to-be-detected driver from a to-be-detected image or video, inputs the facial state features of the to-be-detected driver into the trained fatigue prediction regression model, obtains a fatigue score corresponding to each time in a future period of time, and then can infer the time required to reach different fatigue levels according to the current time and the time corresponding to different fatigue levels, so as to achieve the purpose of predicting the fatigue condition of the driver in advance, help early warning, avoid vehicle accidents, and the same model can obtain corresponding prediction time according to different fatigue level requirements, and has high expansibility.

This disclosure relates to the field of data processing technology, providing a method, apparatus, electronic device, and vehicle for generating a body injury prediction model. The method includes: acquiring a curve showing the change in body acceleration of a driver or passenger during a simulated vehicle accident, and seat parameters; fitting the curve to obtain a fitted curve, determining the curve parameters of the fitted curve, and establishing a correlation between the curve parameters and the seat parameters; determining a computational relationship between body acceleration and the injury value of a target body part; and combining the correlation and the computational relationship to obtain a body injury prediction model, so as to determine the injury value of the target body part based on the seat parameters at the time of the vehicle accident using the body injury prediction model. Thus, it is not necessary to collect body acceleration data to calculate the injury value of the target body part; the body injury prediction model can directly determine the injury value of the target body part based on the seat parameters, achieving the prediction of the injury value of the target body part.

The invention relates to a commercial vehicle accident high-risk scene portraying method and system. The method comprises the following steps: acquiring original data; constructing a high-risk scene index system, and defining a risk level; preprocessing the original data based on the high-risk scene index system to obtain preprocessed data; training the self-organizing mapping neural network by utilizing the preprocessed data, and adjusting network node weights by adopting a forgetting suboptimal rule to obtain an initial clustering center; and taking the initial clustering center as a starting point, taking the risk level as an initial K value, and carrying out K-means clustering analysis on the preprocessed data to obtain a commercial vehicle accident high-risk scene portrait result. According to the method, the SOM neural network and the weight updating mechanism with the forgetting factor are introduced to optimize the clustering effect, and the pendulum effect generated in the later period is avoided; through methods of clustering analysis, multiple correspondence analysis and the like, accurate description of an accident high-incidence scene of the commercial vehicle is realized, and a support is provided for comprehensively improving the safety of the road transport vehicle.

The application discloses a kind of vehicle remote takeover systems and methods.The vehicle remote takeover system includes remote cockpit end and car end;Remote cockpit end includes cabin end diagnostic module;Car end includes car end diagnostic module, communication gateway, controller area network CANBUS module;Cabin end diagnostic module, for remote driver to initiate remote takeover instruction in response, obtain the takeover level contained in remote takeover instruction, in the case where takeover level is vehicle accident level, by communication gateway, remote takeover instruction is transmitted to car end diagnostic module;Car end diagnostic module, for receiving remote takeover instruction, obtain the takeover level contained in remote takeover instruction, in the case where takeover level is vehicle accident level, remote takeover instruction is transmitted to CANBUS module;CANBUS module, for receiving remote takeover instruction in response, modify remote takeover identification.The technical scheme of the embodiment of the application can improve the efficiency of remote takeover.

A vehicle accident detection and automatic reporting system is disclosed. A vehicle accident detection and automatic reporting system includes a vehicle terminal which is mounted in a vehicle and acquires driving information of the vehicle and a user terminal owned by a user who rides in the vehicle, and the user terminal includes a sensor module which detects movement information of the vehicle, a communication unit which communicates with the vehicle terminal and receives the vehicle driving information, and a control unit which determines whether an accident of the vehicle occurs using the vehicle driving information and the vehicle movement information.

According to the automobile electronic data forensics analysis method and device and the storage medium, EDR and VDR data are extracted through a portable automobile electronic data forensics device, and on the basis of the following analysis processes, two automobile driving track points with unified time and space are automatically generated in combination with field investigation data, so that quick reproduction analysis of accident tracks at a software side is realized; the analysis process comprises the steps that a Cartesian simulation coordinate system of the passenger car is established, and simulation track points are generated; based on Kruger-n series expansion of a WGS84 ellipsoid, mapping track points of a simulation coordinate system to a geographic coordinate system through a mapping relation between simulation coordinates corresponding to an anchor point, namely a passenger car collision point and corresponding GPS coordinates; performing affine transformation from a Cartesian simulation coordinate system to a UTM coordinate system; and back projection is carried out, i.e., the UTM coordinate system to the latitude and longitude. According to motor vehicle accident data evidence obtaining and accident analysis, the accident investigation evidence obtaining and analysis efficiency is improved through evidence obtaining tool innovation and accident track reconstruction analysis method innovation.

The present disclosure relates to an accident handling system, method, device, storage medium and vehicle. The system is applied to a vehicle and comprises a plurality of domain controllers. Each domain controller comprises an application layer and a service layer. The application layer integrates one or more vehicle function modules, which are used to implement vehicle functions. The service layer integrates one or more vehicle service modules, which are used to provide vehicle services. The plurality of domain controllers comprises a general domain controller. The vehicle function modules integrated in the application layer of the general domain controller comprise an accident handling function module. By layering the system of the vehicle and modularizing the function and service modules, a service-oriented architecture is formed, and flexible expansion of the function and service is achieved. The embodiments of the present disclosure can achieve flexible expansion of the vehicle accident handling function and application scenarios, and make it possible to quickly and flexibly deploy more demand experience functions.

This application provides a method, device, equipment, and medium for alarming vehicle accidents, relating to the field of accident alarm technology. The method includes: acquiring a vehicle collision signal; if the collision signal exceeds a preset threshold, acquiring the status of the vehicle's communication module; if the vehicle's communication module status is abnormal, determining the status of the occupants and controlling the vehicle's drone to fly to a target observation location to collect external environmental data of the vehicle; controlling the drone's communication module to send vehicle accident alarm information to a target service device; the alarm information includes the collision signal, the status of the occupants, and the external environmental data. The vehicle accident alarm method, device, equipment, and medium provided by this application can enrich alarm information and improve the success rate of vehicle accident alarms.

The invention discloses an online claim settlement loss assessment method and system based on artificial intelligence, and relates to the technical field of insurance claim settlement, and the method comprises the steps: obtaining vehicle accident field data, and carrying out the analysis of the vehicle accident field data based on AI, and obtaining the vehicle state information; matching damage cost information in an insurance platform based on the vehicle state information to obtain a loss assessment report; and generating an accident claim report from the vehicle accident scene data, the vehicle state information and the loss assessment report based on the insurance platform, and providing the accident claim report to the user side. According to the invention, the related data of the vehicle accident can be obtained for AI identification analysis, the vehicle state information can be rapidly given, the accident claim settlement report can be rapidly determined after the accident occurs, the accident processing efficiency is improved, and the time for processing the accident process is reduced.