126 results about "Impaired driving" patented technology

The invention discloses a dangerous driving critical state identification method, and relates to the technical field of intelligent driving safety. According to the method, multi-mode signals of eye movement, electrocardio, skin electricity, vehicle operation and the like are collected and converted into a unified phase field, and the synchronous coherence of the unified phase field is analyzed; the individual phase dynamics manifold of the driver is learned on line by using a Shenchang differential equation, and a system instability precursor is identified by detecting the behavior that a state point escapes from a steady state attractor; further, multi-dimensional indexes such as synchronous collapse and topological fracture are fused, collapse time is estimated in combination with a Lyapunov index, and an advanced early warning instruction is generated; and finally, based on the model predictive control and the personalized phase response curve, generating and executing targeted multi-mode phase reset intervention, and forming a sensing-early warning-intervention active safety closed loop. According to the invention, normal form transformation from post-event alarm to beforehand regulation and control is realized, and early warning advancement and intervention accuracy are improved.

The invention relates to the technical field of driver monitoring, in particular to a dangerous driving behavior detection method based on heterogeneous federal ensemble learning. The client extracts a feature vector of the driving behavior data, and maps the feature vector into a low-dimensional category prototype by using a prototype adapter network; a local dynamic differential privacy technology is adopted to carry out noise injection encryption processing on parameters of the prototype adapter and then upload the parameters to a server; the server performs cross-client prototype alignment and aggregation to generate a global prototype; the client downloads global prototype parameters and updates a local model, incremental learning is carried out based on a dynamic prototype library, and when a novel dangerous driving behavior is detected, a newly-added prototype and a historical prototype are separately stored; and the client performs similarity matching with the global prototype according to the driving behavior characteristics acquired in real time to obtain a detection result. According to the method, an extensible and high-reliability federal learning framework is provided for landing of an intelligent automobile safety system from three dimensions of heterogeneous compatibility, privacy-efficiency balance and personalized dynamic updating.

The invention provides a vehicle dangerous driving evaluation method based on a large model, and relates to the field of traffic control systems. The vehicle dangerous driving evaluation method based on the large model comprises the following steps: step 1, data acquisition: setting a data acquisition layer to acquire multi-source heterogeneous data, and acquiring driving state data of a vehicle in real time through cameras and sensor equipment deployed along a highway; 2, data preprocessing: setting a data preprocessing layer, and performing whole-chain data management and alignment; step 3, data extraction: setting a feature extraction layer to construct a multi-dimensional feature engineering system; step 4, identification: setting a large model identification layer: establishing a large model based on a Transform architecture; and step 5, outputting a result: outputting a result judged and identified by the large model for evaluating dangerous driving of the vehicle. According to the scheme, the dangerous driving behavior of the vehicle is accurately identified, the danger index is provided, and a reliable risk assessment result is provided.

A method for operating a driver assistance system of a vehicle includes initiating an autonomous or semi-autonomous driving process of the vehicle, collecting data associated with surrounding vehicles within an external environment of the vehicle, and transmitting the data associated with the surrounding vehicles to a Central Processing Unit (CPU) comprising one or more processors. The method further includes determining, with one or more machine learned models, safety concerns of the surrounding vehicles based on the data associated with the surrounding vehicles, determining, with the one or more machine learned models, a safety score of each surrounding vehicle of the surrounding vehicles located within a predetermined distance from the vehicle based on the respective safety concerns of each surrounding vehicle, and updating, with the one or more machine learned models, a driving trajectory of the autonomous or semi-autonomous driving process of the vehicle based on the safety scores of the surrounding vehicles.

The invention discloses a driver dangerous driving behavior visual identification method and device, a terminal and a medium. The method comprises the following steps: acquiring image data when a driver drives; detecting and identifying the image data of the driver during driving by adopting a dangerous driving behavior identification model, and outputting whether the driver has a dangerous driving behavior or not; the dangerous driving behavior recognition model is obtained through the following steps: collecting image data of a driver during dangerous driving, and constructing a driver dangerous driving state data set according to the image data; a dangerous driving behavior recognition model is constructed, the dangerous driving behavior recognition model is an improvement on a YOLOv8n model, a C2f module in a backbone network of the YOLOv8n model is reconstructed into a C2f-DC module by using a DC module, and a loss function is modified into an SAIOU loss function; and training the dangerous driving behavior identification model by using the driver dangerous driving state data set. The method has the advantage of being higher in driver dangerous driving behavior recognition accuracy.

The invention discloses a vehicle key cabinet based on driver health examination and a using method thereof, and relates to the field of vehicle management. The vehicle key cabinet based on driver health examination comprises a vehicle key cabinet unit, a touch operation screen, a multi-mode verification module, a health detection module and a key sensing module, the vehicle key cabinet unit comprises a key cabinet main body and a key placing lattice, and the key placing lattice is used for placing a vehicle key; the multi-mode verification module is used for verifying the identity of a driver, the health detection module is used for detecting the health state of the driver, and the key sensing module is used for sensing whether a key is in place or not. According to the vehicle key cabinet based on driver health examination, the multi-mode verification module is utilized to pass face, fingerprint and card triple-modular redundancy verification, the safety risks of false claim and embezzlement are effectively prevented, the health detection module is utilized to monitor the health state in real time, and dangerous driving behaviors of drunk driving and fatigue driving are completely eradicated from the source of physiological indexes.

The invention provides a method for automatically monitoring and identifying dangerous driving behaviors based on a driving scene, and the method achieves the comprehensive monitoring of a vehicle driving state and a vehicle driving road section through the installation of a satellite positioning device, the collection of CAN bus data, the deployment of high-precision map road network data, and the data fusion. By setting a behavior threshold value and combining time sequence analysis and map data, the judgment accuracy is enhanced, a real-time monitoring algorithm engine is developed, and dangerous driving behaviors are accurately monitored and recognized in a complex and changeable driving scene. According to the method, dangerous driving behaviors of the driver can be corrected in time, dangerous driving events are recorded and managed at the same time, the running safety risk is reduced, the driving safety is improved, and losses caused by traffic accidents are reduced. Various dangerous driving scenes are covered, a driver is helped to reasonably control the vehicle speed, digitization of motorcade management and transparency of risk management are achieved, and the requirement for supervision compliance is met.

The invention relates to the technical field related to intelligent traffic driving safety, in particular to a dangerous driving behavior recognition method and system based on multi-modal data fusion. According to the method, driver behaviors and vehicle operation data are collected in real time through a vehicle-mounted sensing system, hardware-level synchronization of multi-source data is achieved based on GPS-PPS pulses, and a unified timestamp system is established; extracting multi-modal features of vision, vehicle dynamics and biological signals under a unified time sequence; cross-modal feature deep fusion is realized by using a graph neural network and an attention mechanism; performing risk quantification by adopting a secondary decision model in combination with an environment adaptive weight; and finally, according to the risk score, triggering graded early warning and linkage with vehicle control, and meanwhile, generating an event report and uploading the event report to a cloud platform to form closed-loop management. According to the method, the problem of misjudgment caused by data asynchronization in a traditional scheme is effectively solved, and the recognition accuracy and the system reliability in a complex environment are remarkably improved.

The application discloses a kind of dangerous driving behavior monitoring method, comprising: obtaining the real-time driving data of driver end, and the driving order that hits preset driving rule is marked with exception label;Real-time traffic data of current driving path is obtained, and traffic rule is generated according to real-time traffic data;Real-time driving data carrying exception label is detected by traffic rule;If real-time driving data hits traffic rule, the exception label is removed;If real-time driving data does not hit traffic rule, the exception label is converted into dangerous driving label.By the way of marking exception label, first find out those real-time driving data of driver end that exceed normal driving data range, and by calling real-time traffic data, the generation scene of real-time driving data marked as exception label is further verified by traffic rule generated by traffic data, effectively identify the real-time driving data generated under unexpected accident, avoid to bring misjudgment to driver end and cause punishment.

The embodiment of the invention provides a method for adjusting a human-computer interface in a vehicle, the vehicle and a computer readable storage medium. The method comprises the steps that a crisis perception test is conducted on a test object based on a preset test device, a first adjustment strategy is obtained, the preset test device comprises an electroencephalogram instrument, an eye movement instrument and an electrocardio instrument, and the first adjustment strategy is used for adjusting the opportunity that a human-computer interface of a vehicle transmits dangerous driving scene information to a driver; driving distraction tests are conducted on the test object based on a preset test device, a second adjustment strategy is obtained, and the driving distraction tests comprise a visual distraction test, an auditory distraction test, a cognitive distraction test and a manual distraction test; determining a human-computer interface adjustment strategy based on the first adjustment strategy and the second adjustment strategy; and adjusting the human-computer interface based on the human-computer interface adjustment strategy. According to the method and the device, the technical problems that the safety assessment of the HMI design is not accurate enough and the HMI design still has potential safety hazards in related technologies are solved.

The present invention discloses a method, device, storage medium and apparatus for dangerous driving intervention. The method includes: when establishing a connection with a smart wearable device, obtaining the physical state information of the driver and passenger uploaded by the smart wearable device; when it is determined according to the physical state information that the driver has an abnormal physical state, collecting the driving behavior information and driving image information of the driver, and determining whether to activate the intelligent driving function according to the driving behavior information and the driving image information; since the present invention obtains the physical state information of the driver through the smart wearable device, obtains the driving behavior and driving image information of the driver when the driver has an abnormal physical state, and determines whether to turn on the intelligent driving mode according to the driving behavior and driving image information, it can know the unexpected situations that occur during the driving process of the driver and take reasonable relevant measures in time to prevent the occurrence of danger.

The invention provides a driving assistance method and system for a vehicle and the vehicle, and the driving assistance method comprises the steps: collecting the voice features of a driver when a first vehicle runs, and judging whether the voice features are matched with a preset voice database or not; if yes, acquiring first vehicle environment information of a vehicle-mounted sensor, calculating a driving state parameter based on the first vehicle environment information, and judging whether the first vehicle is in a dangerous driving environment or not according to the driving state parameter; if yes, the braking opportunity and the braking force of the first vehicle are calculated according to the driving state parameters, and a braking system of the first vehicle is controlled to execute active braking according to the braking opportunity and the braking force. The technical problems that an existing driving assistance system depends on sensor data to achieve automatic braking, but in an emergency, voice response often reflects danger faster than sensor data or a manual starting system, but in the prior art, a voice starting system cannot be combined in time, intervention lags, and potential safety hazards exist are solved.

A detection function control device includes: a vehicle situation determining unit configured to determine a situation of a vehicle on the basis of detection results of one or more of an ignition state, whether a driver is seated in a seat, the acceleration of the vehicle, the position of the vehicle, the speed of the vehicle, and sound which is collected; and a detection function control unit configured to determine which of one or more detection functions for detecting dangerous driving is to be activated on the basis of the situation determined by the vehicle situation determining unit.

The embodiment of the invention relates to the field of open pit coal mine transportation safety, and discloses a dynamic early warning method, system and device for the driving risk of a mining truck and a medium. The dynamic early warning method for the driving risk of the mining truck comprises the steps that driving information of a vehicle is collected in real time based on a vehicle-mounted positioning system, the driving information comprises driving time, a geographic position, a driving state and topographic features; extracting key risk features for reflecting driving risks based on the driving information, wherein the key risk features include dangerous driving behavior features and terrain-related features; and constructing a risk prediction model based on the key risk features so as to carry out classified early warning on the driving risk of the vehicle. According to the technical scheme disclosed by the invention, the limitation of a single data dimension is broken through, the evaluation comprehensiveness is improved, and real-time perception, multi-dimensional analysis and accurate early warning of the driving risk are realized.

The travel information sensor (14A) detects travel information of the own vehicle. The living body information sensor (13A) detects living body information of the driver. The camera section (12A) detects an expression of the driver. The communication section (32A) acquires, via the network (4), a degree of involvement indicating a degree to which the own vehicle is being subjected to an involvement behavior by other vehicles. The involved degree calculation section (313A) calculates an involved degree indicating a degree to which the own vehicle is being subjected to an involvement behavior from other vehicles. The danger degree judgment section (312A) calculates a danger degree including whether the own vehicle is being subjected to an involvement behavior from other vehicles, based on the involved degree and the degree of involvement. The prompting section (33A) warns of the danger degree when it is judged that the involvement behavior is being subjected to.

The present invention relates to the field of new energy vehicle technology, and more specifically, to a lateral protection control method and system for a smart rail vehicle in manual mode. The present invention provides a lateral protection control method for a smart rail vehicle in manual mode, the method comprising: a vehicle network control system obtains a lateral deviation parameter based on multi-source data fusion, the lateral deviation parameter including a lateral deviation value and a lateral deviation threshold provided by an on-board signal system; the lateral deviation value is compared with the lateral deviation threshold, and the vehicle network control system outputs a corresponding result for achieving lateral protection of the vehicle in manual driving mode, wherein the lateral deviation value includes a lateral deviation value based on visual recognition and / or a lateral deviation value based on combined inertial navigation, effectively avoiding safety hazards caused by driver distraction or dangerous driving behavior, and ensuring vehicle driving safety.

The information processing device according to the present technology comprises a dangerous driving extraction unit, a road feature acquisition unit, a calculation model generation unit, a determination model generation unit, and a driving danger evaluation unit. The dangerous driving extraction unit extracts dangerous driving behaviour on the basis of sensor data. On the basis of the sensor data, the road feature acquisition unit acquires a road feature of a road on which the vehicle was travelling at the time of the dangerous driving behaviour. On the basis of the dangerous driving behaviour and the road feature, the calculation model generation unit generates a calculation model for calculating a degree of driving danger of a driver. The determination model generation unit generates a determination model in which the relationship between accident probability and the degree of driving danger is modelled. The driving danger evaluation unit uses the calculation model and the determination model to evaluate the degree of driving danger of the driver on a specific road according to the accident probability.

The invention provides a condition adjustment method and device, equipment, a medium and a program product. Comprising the steps that in the running process of a vehicle in a first driving mode, if the driving behavior of the vehicle meets a first condition, the first driving mode is quitted; if the dangerous driving behavior of the driver is detected, the first condition is adjusted to be a second condition; wherein the second condition is different from the first condition. By means of the method and device, condition adjustment of differentiation and flexibility of the vehicle exiting the first driving mode is provided, the vehicle can be controlled to exit the first driving mode in a diversified mode on the whole, and therefore accurate control over the vehicle exiting the first driving mode can be achieved.

The invention provides a system which comprises a safety score calculation module and belongs to the technical field of intelligent auxiliary driving, and the system comprises the safety score calculation module which calculates a safety score according to the actual condition of vehicle driving; the driving behavior analysis module is used for evaluating the overall driving behavior of the driver; according to the driving risk early-warning system, through specific analysis and scene induction of dangerous driving scenes and real-time calculation of vehicle driving safety scores, comprehensive, accurate and timely driving risk early-warning information is provided for the driver, the driving risk early-warning effect is improved, and the driving risk early-warning effect is improved. And the driving safety is effectively improved.

The present invention discloses a dangerous driving control method and system based on multi-feature fusion, comprising the following steps: obtaining driver state features and vehicle control features, and calculating the driving behavior riskiness based on a weight coefficient; inputting the driving behavior riskiness into a first neural network to determine whether the driver's current state involves dangerous driving, and issuing an alarm when dangerous driving occurs; after the alarm meets set conditions, sending vehicle information to a cloud control system, which plans a parking route for the current vehicle based on the vehicle information; switching vehicle control to the cloud control system, which controls the vehicle to park at a designated location based on the parking route; and releasing vehicle control from the cloud control system after safety is detected. The present invention not only provides auxiliary reminders but also actively intervenes in dangerous driving behavior, thereby fundamentally eliminating dangerous driving and possessing greater practicality and safety.

The present disclosure relates to a behavior recognition method and device, electronic equipment and vehicle. The method comprises: obtaining a first image set and a second image set of a driver; obtaining a first optical flow vector field according to the first image set and a second optical flow vector field according to the second image set; obtaining a vector numerical difference value of the first optical flow vector field and the second optical flow vector field; and determining whether the driver has dangerous driving behavior according to the vector numerical difference value. The method provided in the present disclosure can analyze the change of the optical flow vector field based on image analysis to recognize whether the driver has dangerous driving behavior, and can monitor in real time whether the driver has dangerous driving behavior to avoid safety hazards in time.

The invention provides a dangerous driving behavior prevention and control method, electronic equipment and a vehicle, and belongs to the technical field of vehicles. When the protection type is straight-going protection, whether a retrograde driving risk exists or not is determined according to the position of a target wheel in a road environment image; and when the retrograde driving risk exists, dangerous driving behaviors of the user on the target type of road section are avoided through straight-going protection control, and the driving safety of the user is ensured. And when the protection type is turning protection, whether the risk of turning into the retrograde lane exists or not is determined according to the real-time curvature radius and the safe curvature radius, and when the risk of turning into the retrograde lane exists, dangerous driving behaviors of the user on the target type of road section are avoided through turning protection control, so that the driving safety of the user is ensured. Different protection control schemes are provided for different real-time vehicle states, and the driving safety of a user on different target type road sections with safety risks is ensured.

The invention relates to a dangerous driving remote control method and system based on vehicle-road cooperation and a medium, and the method comprises the steps: M1, when a driver drives a vehicle into a certain given area, a vehicle end actively reports speed and position information to roadside equipment, and obtains the speed data information and position data information of the vehicle in real time; and M2, based on the speed data information of the vehicle and the position data information of the vehicle, fusing the data of the vehicle by adopting a multi-modal fusion algorithm based on feature extraction to obtain data information of motion parameters of the fused vehicle. According to the method, dangerous driving behaviors of the vehicle can be rapidly inhibited, road traffic injury events can be reduced, road traffic accidents can be reduced, social hazard events can be reduced, and the method has good harmony and stabilization effects on the society and families.

The embodiment of the invention provides a vehicle control method and device, a vehicle and a storage medium, and belongs to the field of vehicle engineering.The vehicle control method comprises the steps that under the condition that it is determined that a driver is in a dangerous driving state based on detection data of the driver, the vehicle is controlled to be locked, and a vehicle-mounted terminal is controlled to display a verification button; in response to a trigger operation on a verification button, controlling the vehicle-mounted terminal to output a cognitive verification task; determining whether the driver passes the cognitive verification task or not based on the condition that the driver completes the cognitive verification task; and under the condition that the driver passes the cognitive verification task, the vehicle is controlled to be unlocked. According to the embodiment of the invention, the driver state is detected based on the detection data, and the cognitive ability of the driver is detected according to the condition that the driver completes the cognitive verification task, so that the vehicle is accurately controlled.

A method, apparatus and non-transitory computer-readable storage medium for warning of dangerous driving behavior, the method comprising: acquiring point cloud data collected by a LiDAR and dividing the point cloud data into ground point cloud data and non-ground point cloud data. Ground objects are identified based on the ground point cloud data, while non-ground objects are identified based on the non-ground point cloud data. Based on the motion changes of the vehicle relative to the ground objects and / or non-ground objects, it is determined whether the driver exhibits dangerous driving behavior, and real-time warnings are provided when dangerous driving behavior occurs.

1. The name of the design product: fatigue driving warning camera assembly. 2. The use of the design product: for analyzing whether the driver has fatigue driving or dangerous driving behavior during the vehicle journey, and timely reminding the alarm to ensure the safety of driving. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The invention belongs to the technical field of vehicle insurance assessment, and discloses a vehicle operation risk assessment method and device, computer equipment and a storage medium. An accident record of a to-be-evaluated vehicle and driving behavior characteristic data of a driver are acquired, and the driving behavior characteristic data comprise bad driving behavior frequency, night driving duration, fatigue driving duration, load data, speed data and dangerous driving behavior frequency; determining a plurality of risk evaluation parameters based on an accident record and the driving behavior characteristic data; determining the risk level of each risk evaluation parameter according to a preset risk level division standard; and inputting the risk evaluation parameters and the corresponding risk levels into a risk evaluation model to obtain an estimated operation risk value of the to-be-evaluated vehicle, the risk evaluation model being constructed based on a dendritic cell algorithm. And the operation risk of the heavy-duty truck can be estimated more accurately.

To make a driver aware of an occurrence factor of a dangerous state detected while driving.SOLUTION: A vehicle 1 comprises: a dangerous driving information storage unit 121 that stores dangerous driving information which links information about a warning and a driving support function that are actuated while driving with information about a driving condition when the warning and the driving support function are actuated; a driving risk degree calculation unit 112 that calculates a risk degree of driving based on the dangerous driving information; and a display unit 700 that displays accident information which includes an accident image and an accident moving image related to the dangerous driving information when it is determined that the risk degree of driving calculated in the driving risk degree calculation unit 112 is greater than a predetermined value. The display unit 700 displays the accident information when the vehicle 1 stops or stops driving.SELECTED DRAWING: Figure 6

This information processing method causes at least one controller (25, 27) to execute: a process (S1) of determining whether or not a first vehicle (3) is targeted by road rage of a second vehicle (100) or whether there is a risk for the first vehicle due to dangerous driving of the second vehicle; a process (S4) of acquiring information on a road attribute of a road on which the first vehicle is currently traveling; and a process (S7) of, when it is determined that the first vehicle is targeted by road rage of the second vehicle or when it is determined that there is a risk for the first vehicle due to dangerous driving of the second vehicle, selecting a road with a road attribute capable of suppressing road rage or dangerous driving of the second vehicle, as a target course to be traveled by the first vehicle, in accordance with the road attribute of the road on which the first vehicle is currently traveling.

The invention relates to a driving state detection method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a friction electric signal output by a friction electric sensor; a passenger face image of the passenger is collected through an in-vehicle camera of the intelligent vehicle; electric signal change features are extracted from the friction electric signals, and passenger expression features are extracted from the passenger face image; performing feature fusion on the electric signal change features and the passenger expression features to obtain fused features; determining a driving state detection result of the passenger according to the fused features; the driving state detection result includes that the passenger is in a dangerous driving state or is not in the dangerous driving state. By adopting the method, the detection accuracy of the driving state can be improved.