74 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 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 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.

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 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 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 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.

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.

The invention discloses a driving behavior intelligent analysis method and system based on multi-modal feature fusion, and the method comprises the steps: obtaining a driving behavior data set and a data flow, which comprise a vehicle time sequence signal and image data; respectively decomposing the image data and the vehicle time sequence signal to obtain a small image feature map and a time-frequency feature vector; constructing a multi-task network pre-training model, carrying out interaction and enhancement on the image wavelet feature map and the time-frequency feature vector to obtain a fusion feature vector, carrying out deep extraction on the fusion feature vector to obtain feature output data, and carrying out evaluation and mapping based on the feature output data to obtain a dangerous driving probability and a dangerous driving safety score; training the multi-task network pre-training model to obtain a multi-task network model; and obtaining a corresponding driving behavior label, confidence and a driving behavior score through model reasoning. According to the method, feature extraction and interactive fusion are carried out on the multi-modal data, and accurate analysis of driving behaviors is realized.

An object of the system according to the embodiment is to analyze moving image data of a drive recorder and feed back a dangerous driving point or a point at which there is a possibility of an accident to a driver.SOLUTION: A system includes a moving image data collection unit, an analysis unit, and a feedback unit. The moving image data collection unit collects moving image data of a drive recorder. The analysis unit analyzes the moving image data collected by the moving image data collection unit. The feedback unit feeds back the dangerous driving point or the point at which there is a possibility of an accident specified by the analysis unit to the driver.SELECTED DRAWING: Figure 1

The system according to the embodiment aims to detect driver drowsiness and dangerous driving and take appropriate measures. [Solution] A system according to an embodiment includes a collection unit, an analysis unit, a notification unit, and a conversation unit. The collection unit monitors the driver's face or driving behavior. The analysis unit analyzes the data collected by the collection unit. The notification unit notifies the driver when the analysis unit detects drowsiness or dangerous driving. The conversation unit converses with the driver notified by the notification unit.

To provide a driver assistance system that can suppress misjudgments regarding dangerous driving. [Solution] The driver assistance system according to this disclosure is a driver assistance system that determines dangerous driving by a vehicle, and determines dangerous driving based on vehicle static information, which is predetermined information about the vehicle, and environmental information, which is information about the surrounding environment of the vehicle.

An autonomous driving system could create or exacerbate a hazardous driving situation due to incorrect machine learning, algorithm design, sensor limitations, environmental conditions or other factors. This technology presents solutions that use machine learning to detect when the autonomous driving system is in this state e.g., erratic or reckless driving and other behavior, in order to take remedial action to prevent a hazard such as a collision.

This invention provides a driving alert method. During vehicle operation, if a preset traffic event is detected, the method acquires the driver's physical monitoring information and the driver's attention information. Based on the driver's physical monitoring information and the driver's attention information, it determines whether the driver's driving state is dangerous. If the driver's driving state is dangerous, the method provides an alert to the driver. By analyzing the driver's physical monitoring information and the driver's attention information, it is possible to determine whether the driver's driving state is dangerous, thereby promptly alerting the driver to pay attention to driving safety.

To make determination of dangerous driving easily convincing to a driver.SOLUTION: A driving evaluation device for detecting and evaluating dangerous driving stores a position and a time at which the dangerous driving is detected as a dangerous driving position and a dangerous driving time, and adjusts a weight of the dangerous driving on the basis of dangerous driving eyewitness information within a predetermined distance from the dangerous driving position acquired from the outside and within a predetermined time from the dangerous driving time. For example, the weight is set to be larger as the age of the witness of dangerous driving is lower, the witness is larger in the order of pedestrian, bicycle rider, and car rider, the type of road is larger in the order of community road, main road, and expressway, the weight is larger on weekdays than on holidays, and the weight is larger in the school commuting time zone than in other time zones.SELECTED DRAWING: Figure 3

The application provides a vehicle-machine interaction mode switching method, device, equipment and storage medium, the method comprises the following steps: acquiring the vehicle driving speed and the road information including the current road speed limit, calculating the speed difference value according to the current road speed limit and the vehicle driving speed, calculating the differential speed threshold according to the current road speed limit and the preset differential speed threshold, judging the speed difference value according to the differential speed threshold, if the speed difference value exceeds the differential speed threshold, it is confirmed as a dangerous driving state, and the duration of the dangerous driving state is recorded, the target interaction mode is matched based on the duration, and the vehicle-machine is switched to the target interaction mode, the application can adaptively adjust the switching trigger standard of the vehicle-machine interaction mode according to the vehicle speed and the speed limit, reasonably select the interaction mode under different vehicle speeds and different working conditions, effectively reduce the risk brought by the interaction operation in the driving process, and has the characteristics of ingenious idea, high controllability and strong adaptability.

The invention discloses a motorcade driving safety management method, device and equipment oriented to the Internet of Vehicles, and a medium, and relates to the field of artificial intelligence, and the method comprises the steps: collecting multi-dimensional data through an Internet of Vehicles terminal; performing data cleaning and real-time threshold initial judgment on the acquired multi-dimensional data, and generating and pushing a first-level early warning when data meeting a preset primary risk condition is identified; and carrying out real-time monitoring analysis and identification on the multi-dimensional data after data cleaning, displaying dangerous driving behaviors and pushing second-level early warning. Multi-dimensional data of vehicles, drivers, acceleration behaviors, environments and the like are collected through an Internet of Vehicles terminal, second-level first-level early warning is achieved through data cleaning and real-time threshold initial judgment, complex risk identification and second-level early warning are conducted through real-time monitoring analysis, a motorcade safety management scheme of data fusion, real-time analysis and accurate identification is constructed, and the safety management efficiency of the motorcade is improved. Post-event processing is effectively changed into pre-event prevention and in-event intervention, and the safety management level and the operation efficiency are comprehensively improved.

To provide an information processor and an information processing method capable of analyzing and evaluating driving behavior.SOLUTION: An estimation unit configured to estimate a driving behavior of a driver of a vehicle based on information including an acceleration or a speed acquired via a network, using a learning model generated or updated using observation information regarding the driving behavior of the driver of the vehicle and the information including the acceleration or the speed, wherein the information regarding the driving behavior of the driver of the vehicle estimated by the estimation unit is information used to generate information regarding the occurrence positions of the dangerous driving incidents of the drivers of the plurality of vehicles.SELECTED DRAWING: Figure 3

The embodiment of the application relates to the field of vehicle monitoring, and provides a dangerous driving behavior real-time early warning method and device based on driver state monitoring, which comprises the following steps: obtaining body posture data and hand action data of a user through a pressure sensor and a motion capture module built in a target vehicle during user riding; judging whether the user is in a dangerous state in real time based on the body posture data and the hand action data; if it is judged that the user is in a dangerous state, sending early warning information corresponding to the dangerous state in real time through a local display unit of the target vehicle and a mobile terminal associated with the user; and synchronously uploading the early warning information to a cloud server to monitor whether the user is still in the dangerous state in a preset time period after the user, and timely triggering secondary early warning to the user. The embodiment of the application can realize real-time driving behavior recognition and dangerous early warning in a two-wheeled vehicle use scene, improve two-wheeled vehicle safety, and reduce the traffic accident rate.

A computing device of a vehicle and / or a remote computing device may generate a driving score tor a driver based on risky or unsafe driving behavior the driver engages in. The computing device can generate a driving score for the driver and monitor the driver over time to adjust or update the driving score. Tire computing device can initiate virtual coaching sessions in which the driver can access videos of tire driver engaging in. risky driving behavior to see when the risky driving behavior occurred. The computing device can determine whether the driver improved based on the driving score and / or determine whether the driver interacted with the 2024 / 186657 virtual coaching sessions. Responsive to determining the driver did not improve and / or interact with the virtual coaching sessions, the computing device can subsequently instruct the vehicle to generate alerts when the driver engages in similar risky driving behavior. WO

The invention discloses a vehicle test driving scene generation method and device, equipment and a storage medium. The method comprises the steps that a first state set is acquired; searching through a binary search tree algorithm according to the first state set to obtain a second state pair; simulating the second state pair through a driver model to obtain a driving state of the second state pair; under the condition that the driving state indicates that the second state pair forms the dangerous driving scene, determining that the second state pair is a target state pair; under the condition that the search frequency is smaller than the preset frequency, the first state set is updated according to the driving state of the second state pair, searching is carried out through the binary search tree algorithm according to the first state set, the second state pair is obtained till the search frequency is equal to the preset frequency, and at least one target state pair is obtained; and according to the at least one target state pair, generating a vehicle test driving scene, so that the coverage rate of the vehicle test driving scene to a dangerous scene can be improved.

This information processing method causes at least one controller to execute: processing (S1) for determining whether or not a first vehicle is being tailgated by a second vehicle, or whether or not there is a risk to the first vehicle due to dangerous driving of the second vehicle; when it is determined that the first vehicle is being tailgated by the second vehicle, or when it is determined that there is a risk to the first vehicle due to dangerous driving of the second vehicle, processing (S3) for predicting a path that the second vehicle is likely to follow; and processing (S4, S5) for assisting driving of the first vehicle so that the first vehicle follows a different path from the path of the second vehicle.

We provide the system. [Solution] A means of capturing rear-view video of a vehicle using a rear camera, A method for detecting dangerous driving and aggressive driving by analyzing rear-view video captured by AI in real time, A means of sending a warning message to the driver in response to detected abnormal driving behavior and providing advice on countermeasures, A means of uploading and saving the detected abnormal operation data to the cloud, A voice support system for reporting to external organizations such as the police, based on the driver's instructions, A system that includes this.

The invention relates to a dangerous driving behavior monitoring method, device and equipment, a medium and a vehicle. The method comprises the following steps: acquiring monitoring data of a vehicle, wherein the monitoring data comprises at least two kinds of data in a driver image of the vehicle, voice data of a driver, driving data, user data of the driver, vehicle condition data and an external image of the vehicle; inputting at least two kinds of data in the monitoring data into a pre-established dangerous driving prediction model, and performing driving risk analysis on the at least two kinds of data in the monitoring data based on the dangerous driving prediction model to obtain a driving risk coefficient corresponding to each kind of data, determining whether the driver has a dangerous driving behavior or not according to the driving risk coefficient corresponding to each type of data; and when it is determined that the driver has the dangerous driving behavior, dangerous driving behavior generation reason analysis is performed on the at least two kinds of data based on the dangerous driving prediction model to obtain the target generation reason of the dangerous driving behavior, and the dangerous driving behavior identification accuracy is improved.

This invention discloses an integrated identification method and monitoring platform for dangerous driving behaviors of road transport vehicles, relating to the field of vehicle safety alarm system technology. It addresses the problems of existing alarm systems, which are prone to false alarms and have delayed alarms due to their reliance on single thresholds. First, by analyzing the frequency domain characteristics of line of sight and steering torque, the phase lag of the driver's intended action and the low-frequency coupling coefficient are extracted. Then, a dynamic state space matrix is ​​constructed by combining the vehicle's underlying mechanical response lag, and a cognitive-mechanical decoupling index is extracted to quantify the trend of human-machine collaborative loss of control. This index is then fused with the forward continuous collision time margin to construct an alarm modulation transfer function, outputting a time-varying risk warning gradient. Finally, the warning gradient is converted into a trigger signal envelope, triggering multimodal audio-visual and tactile vibration graded alarms and remote telemetry based on high and low frequency components, thus constructing an interference-resistant active warning closed loop, greatly improving driving safety.