268 results about "Vehicle accident" patented technology

The invention provides a vehicle mutual-aid claim settlement method and system based on multi-modal data fusion. Wherein vision and depth sensing data and maintenance records in a vehicle accident are integrated, part types and collision mechanical parameters are extracted, and surface microscopic deformation and internal hidden cracks are captured through dual-band scanning; and carrying out time-space association on the two to construct a comprehensive damage map. And generating a standard damage sequence by using the generative adversarial network based on a normal damage rule of the component, comparing the standard damage sequence with accident damage data layer by layer, extracting an abnormal region deviating from an evolution rule, and calculating a fraud risk index according to the spatial density of the abnormal region. And when the index exceeds a dynamic threshold value, triggering multi-source data to cooperatively verify feature consistency, and outputting a claim settlement result with a fraud mark. According to the technical scheme provided by the invention, accurate identification of maintenance fraud and collaborative optimization of claim settlement risk control efficiency are realized.

The invention discloses an unmanned vehicle accident judgment and responsibility judgment system and method based on roadside perception, and the system comprises a roadside perception module which is used for obtaining target scene image data, physical environment information and point cloud data in real time, the accident identification and evaluation module is used for judging whether an accident exists in the target scene and classifying the accident type, and through multi-dimensional analysis of the accident, the problems that the accident judgment response is not timely and the data dimension is not comprehensive in the unmanned vehicle accident handling process are solved. Besides, the invention provides an accident escape system and an accident judgment system based on the accident judgment system, an escape strategy is formulated by combining a steering wheel control technology, and accident liability is judged, so that the problems that an unmanned driving strategy cannot reasonably avoid obstacles and accident liability processing is complex are solved, the claim settlement time is shortened, and the safety is improved. And a whole-process solution from accident perception, intelligent decision-making to responsibility judgment is provided for the unmanned vehicle.

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 discloses a CVaR-based highway hazardous chemical vehicle accident rescue and evacuation path planning method, and belongs to the technical field of traffic safety and emergency. The path planning method comprises the following steps: acquiring dangerous chemical vehicle transportation accident occurrence points, rescue vehicle rescue points, accident vehicle placement points (evacuation destinations) and road network related parameters; the rescue stage is a path from a rescue exit point to an accident occurrence point of a rescue vehicle, comprehensively considers that the response time of the rescue vehicle is shortest, the efficiency is highest and an upper-layer rescue vehicle travel time shortest model is established, considers that a secondary accident is extremely easy to occur in a dangerous chemical vehicle transportation accident on a highway, and constructs a lower-layer model with the minimum secondary accident risk based on CvaR; a highway dangerous chemical vehicle accident rescue double-layer game planning model is formed; in the evacuation stage, a dangerous chemical substance accident vehicle is a path from an accident occurrence point to a vehicle placement point, the possibility of pollution caused by dangerous chemical substance leakage in the evacuation stage is considered, and an accident vehicle evacuation path planning model based on the CVaR dangerous chemical substance leakage risk is established. According to the highway hazardous chemical vehicle accident rescue and evacuation path planning method provided by the invention, the road traffic safety level and the emergency rescue efficiency can be improved, and smooth and orderly operation of highway traffic is ensured.

The embodiment of the invention relates to the technical field of vehicles, and discloses a vehicle accident early warning method and device, electronic equipment and a storage medium, the method comprises the following steps: obtaining running state data in a vehicle based on a preset duration, the running state data being determined based on vehicle data obtained by at least one bus source in the vehicle; determining target time sequence characteristic data in the operation state data, wherein the target time sequence characteristic data indicates a change trend, a periodic rule and a sudden change condition of the operation state data in a time dimension and a dependency relationship among the data; and inputting the target time sequence characteristic data into a risk assessment model to obtain an assessment result of the accident risk of the vehicle after the preset duration. By applying the technical scheme of the invention, more accurate vehicle early warning can be realized, and the safety driving requirement of the vehicle can be better met.

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.

Methods and systems described herein are directed to automatedly generating and issuing accident data gathering recommendations for a vehicle accident occurrence. In response to a recommendation system detecting an occurrence of a vehicle accident, the system can retrieve initial accident data for the occurrence. Using the initial accident data, the system can generate accident data gathering recommendations to obtain additional accident data via mapping to one or more characteristics for the vehicle accident occurrence. The recommendations, when executed, can yield additional accident data that can be compiled with the initial accident data into a vehicle accident evidence package.

The invention discloses a vehicle accident detection method, a vehicle accident detection device, vehicle accident detection equipment and a storage medium. Obtaining a vehicle video in a time period when the distance between the moving object and the vehicle is within a preset threshold value, a time point when the distance between the moving object and the vehicle is shortest, and the distance; detecting a relative position area of the moving object and the vehicle at the target time point; determining a vehicle accident risk level according to the vibration condition of the vehicle and the target distance; acquiring an image of a moving object, performing feature extraction on the image, determining an object type of the moving object, and identifying object features of the moving object according to the object type; and obtaining a current parking place of the vehicle, generating a corresponding vehicle accident report, and sending the vehicle accident report and the target video to a corresponding client. According to the invention, the event backtracking efficiency of the vehicle owner when the accident occurs can be improved.

The invention discloses a vehicle accident emergency escape system which comprises an independent power supply module, a multi-mode sensor array, an intelligent control unit and an execution driving module. The state of a vehicle is monitored in real time through the multi-sensor fusion technology, when accidents such as collision, fire or falling into water are detected, the system is automatically switched to an independent power source, a glass lifting motor is directly driven to forcibly open vehicle windows, a skylight and a trunk door, and an emergency escape channel is provided for people in the vehicle. One-key forced full-open and voice prompt functions are configured, and the independent power supply part is waterproof and fireproof, so that reliable work in an extreme environment can be ensured.

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.

Methods and systems described herein are directed to automatedly detecting a vehicle accident occurrence based on a generated accident suspicion. An accident detection system can retrieve a myriad of information as data relating to a driver or a vehicle of the driver. The retrieved information can be assessed to determine assignment of a suspicion of a vehicle accident occurrence. The suspicion assignment can be based on, with respect to historical insurance data, predetermined thresholds and / or machine learning for the retrieved information. The retrieved information can be verified by auxiliary data remote from the driver or the vehicle of the driver. The accident detection system can verify the suspicion by dispatching one or more notifications to the driver, and in the absence of response, determine whether the suspicion is true via the collection of information for a suspected location of the accident or from individuals associated with the driver.

This utility model is applicable to a device for preventing vehicle accidents when an external object enters the space under the pedal unit, more specifically the gap between the pedal lever and the floor while the vehicle is moving, thereby preventing fatal road accidents. The device comprises at least one cutting element created to pierce a large external object and is in the form of a shaped cover plate, which is a semicircle with an outer and inner edge, the outer edge of which is in the form of the said at least one cutting element, and the inner edge is made for mounting to the pedal lever of the vehicle. The device has a simple design, is effective for piercing / cutting an external object that has entered the space under the control pedal unit, is easy to install on the pedal lever and prevents accidents.

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 relates to a vehicle accident handling method, device and equipment and a medium, and the method comprises the steps: obtaining vehicle driving data; performing accident prediction on the vehicle driving data based on a pre-trained identification model to obtain an accident prediction result; the accident prediction result represents whether a potential accident exists or not; acquiring sensor data under the condition that the accident prediction result is that a potential accident exists, and matching with a preset accident condition according to the sensor data to determine an accident identification result; and when the accident identification result is that the vehicle accident occurs, generating an accident report of the vehicle accident. According to the technical scheme, the vehicle accident can be accurately recognized, the accident report can be generated, and the vehicle accident handling accuracy and the accident handling efficiency are improved.

The invention provides a vehicle rescue method and device and a cloud platform, and is applied to the technical field of vehicle intelligent control, and the method comprises the steps: responding to the received vehicle accident data, determining a positioning data group after a vehicle accident based on the vehicle accident data, and the positioning data group comprises a preset number of historical positioning data; obtaining the latest positioning data of the vehicle, and determining the validity of the latest positioning data based on the positioning data set; and in response to determining that the latest positioning data is valid, creating a rescue work order based on the latest positioning data. Accurate transmission and efficient utilization of rescue information are ensured, so that the success rate and timeliness of rescue actions are improved, and the life safety of a user is guaranteed to the maximum extent.

The invention discloses an intelligent loss check and assessment multi-modal system based on vehicle accident scene online evaluation, and the system comprises a user interaction interface module which is used for receiving client input and correcting input deviation through a feedback cycle regulation and control mechanism, and a multi-modal data fusion module which is used for collecting vehicle accident damage data uploaded by a client, and outputting the vehicle accident damage data to a server. The system comprises an accident data acquisition module used for acquiring accident damage data, a three-dimensional reconstruction model module used for constructing a vehicle accident three-dimensional model based on the acquired accident damage data and accurately evaluating the vehicle damage condition, an intelligent loss assessment module used for generating a loss assessment report according to an assessment result and implementing intelligent loss assessment operation, and a data storage module used for storing the accident data, the assessment result and the loss assessment report; according to the on-line evaluation intelligent loss checking and assessment multi-mode system based on the vehicle accident scene, feedback circulation of a user interaction interface is regulated and controlled, so that the problem of inaccurate loss assessment caused by client input deviation is solved.

The invention provides a test file generation method and apparatus, an electronic device and a medium. The test file generation method comprises the steps of obtaining an accident report of a vehicle; wherein the accident report is a process of describing a vehicle accident by using a natural language; determining structured description information based on a behavior tree based on the accident report; wherein the structured description information is used for describing the process of the automatic driving test scene by utilizing a plurality of nodes of a behavior tree; generating a test file based on the structured description information; wherein the test file is used for simulating an automatic driving test scene. According to the technical scheme, the accuracy and the performability of test file generation can be improved, and the generation efficiency of the test file is improved.

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 automatic driving vehicle accident cause analysis method. The method comprises the steps of obtaining a data set of an automatic driving vehicle accident report; pre-processing the data set, wherein the pre-processing comprises abnormal value cleaning, error data correction and missing data repair; constructing an explanation variable system of an automatic driving vehicle accident, and carrying out statistical description on accident characteristics; an accident cause analysis model is provided by integrating existing automatic driving vehicle accident research data and conclusions based on a random parameter Logit method for solving a heterogeneity problem; based on priori knowledge and an analysis result, designing a random parametric variable, and constructing an RPL model: sampling a probability density function for multiple times by adopting a Monte Carlo method, and taking a simulated probability mean value as an integral approximate solution; and the analysis of the variable random parameter effect in the automatic driving vehicle accident is realized through the RPL model. According to the invention, the cause explanation of the heterogeneity of the important characteristics and influence factors of the accident of the automatic driving vehicle is realized.

The present invention relates to a method and an apparatus for processing accident relevance information. The method, according to an embodiment of the present invention, is performed by an electronic apparatus and comprises the steps of: generating an embedding vector by performing an embedding process on raw information which is text information describing an accident occurrence situation of another vehicle; classifying into a plurality of clusters by performing a clustering process on the generated embedding vector; extracting, for each cluster, a feature element related to the occurrence of a vehicle accident with respect to raw information belonging to the corresponding cluster; and when driving description information, which is text information related to a driving situation of a target vehicle, is input as input information, generating an embedding vector for the driving description information and then generating accident relevance information regarding the target vehicle according to the driving description information on the basis of the cluster, the feature element, and the embedding vector of the generated driving description information.

The embodiments of the present application belong to the field of financial technology and relate to a vehicle loss estimation method, apparatus, computer equipment, and storage medium. The method comprises the following steps: identifying, classifying, and extracting features from sample data to obtain vehicle image features, vehicle description features, and vehicle information features, and calculating vehicle loss estimation pricing; combining vehicle image features, vehicle description features, and vehicle information features to obtain vehicle loss features, vehicle accident features, vehicle configuration features, and vehicle insurance policy features; inputting vehicle loss features, vehicle accident features, vehicle information features, vehicle insurance policy features, and vehicle loss estimation pricing into a preset learner for training, and performing integrated learning on the trained learner to obtain a vehicle loss estimation model; and inputting repair report data into the vehicle loss estimation model to obtain loss estimation data. The present application can effectively realize automated and efficient accurate estimation of vehicle losses.

The invention relates to the technical field of automobiles, in particular to a vehicle accident rescue method. Based on the vehicle accident rescue method, under the condition that a vehicle determines to request rescue, if a vehicle-mounted accident emergency call system is detected to have a fault, rescue information related to the request rescue is sent to a background cloud through a mobile terminal which establishes communication connection with the vehicle based on a near field communication mode. Thus, under the condition that the vehicle-mounted accident emergency call system has a fault, it can be ensured that the rescue information related to the request for rescue is sent to the background cloud through the mobile terminal, so that rescue workers can obtain the rescue information in time to carry out rescue in time, and a user can be rescued in time.

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 invention provides a risk control analysis method and system based on Internet of Vehicles accident big data, and the accuracy and robustness of risk control knowledge prediction are effectively improved. According to the method, multiple pieces of template accident monitoring data in Internet of Vehicles accident big data are acquired, and a data set containing a target risk control description tag and a disturbance risk control description tag is constructed for each piece of template accident monitoring data, so that the diversity of training samples is enriched. A sample Internet of Vehicles accident monitoring data sequence is generated in combination with an accident feature logic chain, and high-quality training data is provided for a risk control knowledge prediction network. Furthermore, parameter optimization is performed on the initialized risk control knowledge prediction network by using the sample Internet of Vehicles accident monitoring data sequences, and the finally generated target risk control knowledge prediction network can more accurately predict and identify the risk control knowledge category in the Internet of Vehicles accident, so that risk control and safety management in the Internet of Vehicles environment are facilitated, and the risk control accuracy is improved. And the intelligent level and practicability of risk control analysis are remarkably improved.

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.

A battery cell casing, a battery cell, and a battery pack. The battery cell casing comprises a casing body, and the casing body comprises a first connecting edge and a second connecting edge, wherein the first connecting edge and the second connecting edge are joined, and an accommodating cavity is formed inside; and joining portions of the first connecting edge and the second connecting edge are welded to form a weld seam, the solder seam comprises a first boss that protrudes from an inner wall of the casing body, the height of the first boss that protrudes from the casing body towards the accommodating cavity is t1, the thickness of the casing body is t, and the height and the thickness satisfy ((t1+t) / t)≥1.08. In the battery cell casing, the strength of the weld seam is greater than the strength of the casing body, such that the pressure-bearing capability of the battery cell casing can be improved, thereby ensuring that the casing does not crack at the weld seam under the action of internal pressure. By means of increasing the requirements for the weld seam in the battery cell casing, the pressure resistance of the casing is improved, and the safety performance of the battery cell is improved, thereby reducing the risk of vehicle accidents caused by insufficient pressure resistance of the casing due to welding of the casing.

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.