54 results about "Advanced driver" patented technology

A steer by wire steering system includes a steering wheel selectively coupled to a steering shaft, the steering wheel and steering shaft axially movable between a deployed position and a retracted position; an advanced driver assist system configured to steer the steerable wheels of a vehicle that is in communication with the steering wheel and steering shaft, the ADAS configured to selectively control the steering of the steerable wheels in an autonomous driving mode and a manual driving mode; and a steering system controller in communication with the ADAS, the steering system controller programmed to, while the steering wheel is in the retracted position, move the steering wheel to the deployed position and operatively couple the steering wheel to the steering shaft, in response to a vehicle operator request to deactivate a portion of the ADAS and transition from the autonomous driving mode to the manual driving mode.

A computer-implemented method and system are provided for driving assistance. The system includes an image capture device configured to capture image data relative to an outward view from a motor vehicle. The system further includes a processor configured to detect and localize objects, in a real-world map space, from the image data using a trainable object localization Convolutional Neural Network (CNN). The CNN is trained to detect and localize the objects from image and radar pairs that include the image data and radar data for different driving scenes of a natural driving environment. The processor is further configured to provide a user-perceptible object detection result to a user of the motor vehicle.

A heater system for resisting fog and ice buildup on advanced driver assistance cameras provides a chamber covering the camera lens and providing a transparent window through which the camera lens may be directed. A heating element communicates with an air gap between the lens and the transparent window and the periphery of the transparent window to provide heating of the transparent window without blocking an image received by the camera lens.

A system and method are provided for driving assistance. The system includes an image capture device configured to capture an actual image relative to an outward view from a motor vehicle and depicting an object. The system further includes a processor configured to render, based on a set of 3D CAD models, synthetic images with corresponding intermediate shape concept labels. The processor is further configured to form a multi-layer CNN which jointly models multiple intermediate shape concepts, based on the rendered synthetic images. The processor is also configured to perform an intra-class appearance variation-aware and occlusion-aware 3D object parsing on the actual image by applying the CNN to the actual image to output an image pair including a 2D and 3D geometric structure of the object. The processor is additionally configured to perform an action to mitigate a likelihood of harm involving the motor vehicle, based on the image pair.

The invention provides an ADAS (Advanced Driver Assistant Systems) map data processing method, an acquisition method, device and vehicle-mounted equipment. The acquisition method comprises steps: mapdata in a preset format and vehicle positioning information are acquired; according to the vehicle positioning information, standard map data in a preset format are read, and according to the road network relationship in the acquired map data, an ADAS road network in a certain range ahead of the current vehicle's road is reconstructed; key attribute data in the map data are acquired, and in combination of the ADAS road network, an ADAS message which can be recognized by a receiving object is generated and outputted. According to the ADAS map data processing method, the acquisition method, thedevice and the vehicle-mounted equipment, the ADAS accuracy is improved.

The invention discloses a vehicle lane-changing path tracking control method based on model prediction, and belongs to the technical field of intelligent vehicle control. The vehicle lane-changing path tracking control method is applied to an advanced driver-assistance system of a vehicle and comprises the steps of establishing an expected lane-changing path model based on obverse and reverse trapezoid yaw angle acceleration, performing force analysis on a lane-changing vehicle, establishing a 3-DoF vehicle dynamic model, converting the nonlinear 3-DoF vehicle dynamic model into a discrete linear prediction model, designing an objective function and constraint conditions of a model prediction controller, and calculating and outputting a physical quantity for controlling the motion of the vehicle according to an expected path. The expected lane-changing path planned according to the vehicle lane-changing path tracking control method improves the comfort of a driver. Control quantities comprise a driving force and a front wheel steering angle of vehicle driving so as to ensure high-precision vehicle speed control while satisfying the lateral lane-changing requirements. The robustnessof control tracking is high, and the control precision is high, so that lateral tracking errors can be effectively reduced.

The present invention discloses an ADAS (Advanced Driver Assistant System) development test system based on a driving simulator and a programmable touch screen. The system comprises: a vehicle drivingsimulator man-machine interaction operation entity seat cabin based on a CAN bus, a CAN bus information collection plugin, simulation driving simulation software, an ADAS function simulation plugin,a LCD programmable touch screen, and a scene display projector device; and the simulation driving simulation software is configured to output designed simulation scene information and output kinetic parameters of a vehicle model according to vehicle operation to achieve vehicle dynamics and kinematics simulation and perform feedback to the scene display projector device. The system provided by theinvention perform repeated arrangement of scenes of driving simulation to arrange different emergency scenes to perform development and test of the ADAS system in a condition without any danger so asto improve the test development efficiency.

An advanced driver assistant system and a method for assisting a driver of a vehicle in driving the vehicle. The system includes sensing means for sensing an environment of the vehicle, a storing unit for storing a database for storing prototypical situations associated with risk information, a processing unit and an output unit to output an assistance signal on the basis of which driver information can be output and/or vehicle operators can be actuated. The processing unit is configured to determine parameters of the vehicle and/or objects in the environment of the vehicle based upon the sensing means output, to classify a traffic situation on the basis of the determined parameters by comparing the determined parameters with parameters of the prototypical traffic situations, to extract risk information from the database and to calculate an expected risk for the encountered traffic situation on the basis of the extracted risk information.

A system and method are provided for identifying a potential road hazard in a host vehicle based on a remote vehicle. The host vehicle has a host vehicle-to-vehicle (V2V) module and a host advanced driver assistant system (ADAS) module, such as a system employing the ADASIS standard. The remote vehicle also has a remote V2V module that provides position data, and one or more of, longitudinal acceleration data, steering angle change rate data, braking system data, anti-lock braking status and stability control system status of the remote vehicle. The host vehicle receives the position data of the remote vehicle using the host V2V module and determines if the remote vehicle is in the main path zone (MPZ) of the host vehicle. The system determines a potential road hazard when it receives a signal indicating any of the following are true, the longitudinal acceleration data and/or the steering angle change rate data of the remote vehicle exceeds a predetermined threshold, the anti-lock braking system of the remote vehicle is activated, or the stability control system of the remote vehicle is activated. The system indicates the potential road hazard to a driver of the host vehicle when a potential road hazard is identified and the remote vehicle is in the MPZ of the host vehicle.

A method for operating an advanced driver assistance (ADAS) system of a motor vehicle includes a vehicle controller receiving, from side and end cameras mounted to the vehicle, camera signals indicative of real-time images of outboard-facing side and end views of the vehicle. The controller determines a region of interest (ROI) inset within each end/side view within which is expected foreign objects and/or hazards. These ROIs are analyzed to detect if a foreign object/hazard is present in the vehicle's end and/or side views. Responsive to detecting the foreign object/hazard, movement of the foreign object/hazard is tracked to determine if the foreign object/hazard moves towards or away from the vehicle's underbody region. If the foreign object/hazard moves to the underbody region, control signals are transmitted to the vehicle's propulsion and/or steering system to automate preventative action that prevents collision of the vehicle with and/or removes the foreign object/hazard from the underbody.

The invention relates to the field of safe automobile driving, in particular to an event data recording method which comprises the following steps: cameras on an automobile are utilized for acquiring videos and/or photos about events around the automobile; the acquired videos and/or photos are allowed to enter an event data recording computer for circuit buffering; when receiving an event data recording trigger instruction, the event data recording computer saves the buffered videos/photos in a hard disk in the automobile, so that even data recording can be realized. According to the event data recording method, images acquired in real time by a 360-degree surround view camera system and an advanced driver assistant system (ADAS) can be recorded by a hard disk player (HDD), namely the hard disk in the automobile, so that the HDD can serve as an event data recorder, and the expense of a customer can be reduced.

The embodiment of the present invention discloses an advanced driving assistance system, method, equipment, program and medium, wherein the advanced driving assistance system includes: a camera device, more than two distance sensors, and at least one driving assistance subsystem; the camera device collect image information and transmit it to the driving assistance subsystem; the distance sensor collects distance information and transmit it to the driving assistance subsystem; the at least one driving assistance subsystem At least one of the distance information collected by the sensor outputs corresponding driving safety information to the device. In the embodiment of the present invention, through the fusion of various sensors, they complement each other in function, improve the perception ability of the whole system to the environment, and ensure the use safety of the function.

A method is provided in an Advanced Driver-Assistance System (ADAS). The method extracts, from an input video stream including a plurality of images using a multi-task Convolutional Neural Network (CNN), shared features across different perception tasks. The perception tasks include object detection and other perception tasks. The method concurrently solves, using the multi-task CNN, the different perception tasks in a single pass by concurrently processing corresponding ones of the shared features by respective different branches of the multi-task CNN to provide a plurality of different perception task outputs. Each respective different branch corresponds to a respective one of the different perception tasks. The method forms a parametric representation of a driving scene as at least one top-view map responsive to the plurality of different perception task outputs. The method controls an operation of the vehicle for collision avoidance responsive to the at least one top-view map indicating an impending collision.

The invention discloses a signal processing method and device which are applied to advanced driver auxiliary systems. After a first signal generated by an advanced driver auxiliary system and a second signal generated by the advanced driver auxiliary system are acquired, and signals to be executed are determined according to priorities of the first signal and the second signal and finally executed. Based on the method and the device, the priorities are set for the signals corresponding to subsystems of the advanced driver auxiliary system, a sole signal to be executed is determined according to the priorities when a plurality of signals are generated, the problem of compatibility among the subsystems of the advanced driver auxiliary system can be effectively solved, so that a user is rapidly and accurately helped to make decision, and driving safety is ensured.

The present invention provides a method and system of historical reaction based driver advanced assistance. In this method, a combination of external environment to a vehicle on which the advanced driver assistance system (ADAS) is mounted fetched by forward looking cameras is combined with rear looking camera for internal environment or driver state, is generated. The generated combination is utilized to analyze is there is any critical situation that is upcoming. For providing feedback for such situation, processor within the ADAS fetches current vehicle state by utilizing multiple parameters stored within a storage. The intensity of the feedback is varied upon the current vehicle state of the vehicle.

The present invention provides a method and system of historical reaction based driver advanced assistance. In this method, a combination of external environment to a vehicle on which the advanced driver assistance system (ADAS) is mounted fetched by forward looking cameras is combined with rear looking camera for internal environment or driver state, is generated. The generated combination is utilized to analyze is there is any critical situation that is upcoming. For providing feedback for such situation, processor within the ADAS transmits the current combination situation to a remote server that stores historical feedback and driver reactions for various combination of situations. For the current combination situation, a historical combination situation is fetched and corresponding feedbacks analyzed and an ideal feedback, that has comparatively least number of negative driver reactions, is determined.

The invention discloses an intelligent vehicle-mounted system realization method, and particularly relates to a user classification method based on adas (advanced driver assistant system) and obd (on-board diagnostic) data. An adas device, an obd module, and a Gps device are arranged on the vehicle for acquiring data. A communication module is arranged for realizing communication with the Internet. Through computing the information acquired by the above devices in a scientific computation method, the risk factor and the possibility of a driver can be judged, and a necessary prompt can be given. The method of the invention has the advantages that the risk probability of the driver can be accurately judged for mechanisms such as an insurance company, and the driver is correctly guided to form standard driving and other good habits.

The invention discloses a self-adaptive interface display method based on an ADAS (Advanced Driver Assistant System), a system and a storage device, wherein the self-adaptive interface display methodbased on an ADAS comprises the following steps of: extracting a preview image acquired by a camera, and calculating picture information of the preview image; then carrying out feature point recognition on the preview image according to the picture information and feeding back first coordinate information of feature points; then acquiring dimension information of the actually-displayed picture, carrying out scaling on the first coordinate information according to the dimension information of the actually-displayed picture and the picture information of the preview image and outputting second coordinate information; then combining the second coordinate information of the feature points, and carrying out overlapped display after drawing a corresponding recognition image on the actually-displayed picture. The self-adaptive interface display method, the system and the storage device disclosed by the invention have the beneficial effects that the recognized picture can be accurately displayed in an overlapping manner according to the sizes of the actually-displayed picture, and an accurate driving reference picture can be provided for a driver, so that the driving safety is improved.

The application relates to the field of vehicle calibration, and provides a calibration system and a calibration bracket thereof. The calibration bracket comprises a base, a fixed vertical rod, a mobile vertical rod, a brake piece and a mounting piece, wherein one end of the fixed vertical rod is mounted on the base; the mobile vertical rod can move relative to the fixed vertical rod in the lengthdirection of the fixed vertical rod; the brake piece is used for providing friction force for driving the mobile vertical rod to fix relative to the fixed vertical rod in the length direction of thefixed vertical rod; the mounting piece is mounted on the mobile vertical rod, and is used for mounting a calibration element; and the calibration element is used for calibrating an advanced driver assistant system of a vehicle. By configuring the brake piece, the brake piece provides the friction force for driving the mobile vertical rod to fix relative to the fixed vertical rod in the length direction of the fixed vertical rod, so that a cross beam can be stable after the calibrating element is mounted.

The invention relates to predictive landing for a drone and a moving vehicle. A method for predictive drone landing is provided. The method includes obtaining a relative position of the drone with respect to a landing dock mounted on a vehicle, obtaining a relative velocity of the drone with respect to the landing dock, estimating a time of landing based on the relative position and the relative velocity of the drone with respect to the landing dock, and predicting a location of the vehicle at the estimated time of landing as a drone landing location based on driving data of the vehicle and flight conditions of the drone. In particular, the drone landing location is predicted based on at least one of a speed of the vehicle, a calculated vehicle route from a navigation system, a road traffic condition, a 2-D map data, a 3-D map data, advanced driver-assistance system (ADAS) data, and traffic data received via a vehicle-to-everything (V2X) communication.