53 results about "Advanced driver assistance systems" patented technology

A method for detecting anomalies in image data captured by a vehicle sensor includes receiving first and second image frames, and first and second observation clouds generated based on LiDAR data capt

The disclosed technology teaches a system and method for providing driver assistance alerts to a driver using an end-to-end artificial intelligence advanced driver assistance system. The disclosed techniques further include receiving a series of environmental data of a driving state including at least video from a camera, return data from an optical sensor, and location data from a GNSS receiver, where the camera, the optical sensor, and the GNSS receiver are coupled to a processor carried by a vehicle; processing the environmental data as input to an end-to-end neural network, wherein the end-to-end neural network is trained to generate specified steering and speed control actions in response to a current driving state; analyzing hidden layer data and output data from the end-to-end neural network to estimate collision avoidance data; and presenting to the driver a user interface including a driver assistance alert based on the collision avoidance data.

A user equipment (UE) may obtain, from at least one memory, an indication of a first gaze pattern of a driver of a vehicle. The UE may obtain a second gaze pattern of the driver of the vehicle based on a first set of sensor data from a first set of sensors associated with the vehicle during a first time period. The UE may adjust a sensitivity of an advanced driver assistance system (ADAS) associated with the vehicle in response to a difference in visual engagement in a visual region of the driver between the second gaze mode and the first gaze mode greater than or equal to a threshold amount.

The application discloses a kind of integrated multifunctional advanced automatic driving auxiliary system, including five kinds of vehicle driving modes of constant speed cruise mode (CC), low performance adaptive cruise mode (LACC), high performance adaptive cruise mode (HACC), autonomous lane changing mode (ALC), automatic emergency braking mode (AEB). Vehicle detects the state information of surrounding vehicles and environment through sensing device, calculates characteristic quantity and correlation function in real time through extension control strategy, determines the extension set and measure mode of belonging, and further determines the driving mode of vehicle. When the state information of surrounding vehicles and environment changes, vehicle can switch between different driving modes. When the speed of current vehicle continues to drop and the surrounding environment meets the lane changing condition, vehicle can automatically switch to autonomous lane changing mode (ALC), switch the following object, and improve driving efficiency. When the current vehicle stops due to failure or suddenly appears obstacle in front, vehicle can automatically switch to automatic emergency braking (AEB) mode, shorten the reaction time, and improve driving safety.

This invention provides an advanced driver assistance system (ADAS) automatic lane changing method and system, relating to the field of vehicle control technology. The method includes: when a vehicle is preparing to change lanes from its current lane to a target lane, selecting an optimal lane gap from among target vehicles in the target lane; calculating a first passable speed based on the traffic flow speed of the target lane; and, in response to the first passable speed, the target distance required for the vehicle to cross the lane's dashed line when entering the optimal lane gap, and the target distance between target vehicles after entering the optimal lane gap all satisfying preset lane change activation conditions, initiating a lane change time counter; and, in response to the lane change time counter exceeding a counting threshold, generating a vehicle lane change request for the vehicle to change lanes from the optimal lane gap to the target lane; and, in response to the vehicle lane change request, controlling the vehicle to enter the optimal lane gap to complete the lane change. This invention addresses the problems of overly rule-based lane change decisions and a lack of monitoring for real-time risks and changes in lane change conditions during advanced driver assistance systems (ADAS) automatic lane changing.

1. Name of the product in this design: Automotive Camera (ADAS). 2. Purpose of this design: To be installed on a vehicle to capture images of the vehicle's interior or exterior. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

A method of operating an advanced driver assistance system (ADAS) can include performing a map data reload operation on a first map data buffer containing map data obtained from a first source. A switching operation can be performed to switch from the first map data buffer to a second map data buffer containing map data obtained from a second source. An electronic horizon can be generated based on the map data contained in the second map data buffer and used to perform a first ADAS operation. Another switching operation involves switching back from the second map data buffer to the first map data buffer, which now contains map data obtained from the first source during the map data reload operation. Then, another electronic horizon can be generated based on the map data contained in the first map data buffer and used to perform one or more ADAS operations.

A method for controlling an actuatable safety device for protecting an occupant of a vehicle includes utilizing an advanced driver assistance system (ADAS) to determine that a vehicle collision is imminent. In response to determining that an imminent vehicle collision exists, a mass-spring-damper model uses a sensed vehicle longitudinal acceleration (IMU_X) to estimate occupant movement that would result from the imminent vehicle collision. The estimated occupant movement is used to determine how to control deployment of the actuatable safety device in response to the collision.

The invention relates to a calibration equipment pose calibration method, device and system, a medium, equipment and a vehicle. The calibration device is used for calibrating the installation position of a device to be calibrated in the vehicle advanced auxiliary driving system. The method comprises the steps that a measurement value obtained by measuring a preset point on the calibration device through a measurement device is acquired; converting the measurement value into a conversion value under a vehicle coordinate system according to a conversion matrix between a measurement coordinate system of the measurement equipment and the vehicle coordinate system; determining a current pose parameter value of the calibration equipment based on the conversion value; according to the current pose parameter value and a target pose parameter value, the pose compensation value of the calibration device is determined, and the target pose parameter value is the parameter value of the target pose of the calibration device under the vehicle coordinate system.

The present disclosure relates to a lane-related advanced driver assistance system and a control method, and a vehicle having the same. A system according to an embodiment of the present disclosure may include a memory for storing an image captured by a camera of a vehicle; and a processor for controlling a lane-related Advanced Driver Assistance System (ADAS) in the vehicle using information stored in the memory, wherein the processor is configured to: identify a driver's intention in a rear region of a target section, which is a divergence point section without an indication line, using the image; and determine whether to perform the lane-related ADAS function in the target section according to the identified driver's intention.

An advanced driver assistance system, method and vehicle for assisting a driver of a vehicle is provided. The system includes a sensor unit, a processing unit and a display unit. The sensor unit is configured to sense an environment of the vehicle. The processing unit is configured to determine at least one feature of the environment based on the sensing output. The processing unit is configured to determine a risk zone for the feature for a current time by estimating a respective risk with respect to the feature at each of two or more virtual positions of the vehicle based on at least one parameter of the vehicle at the current time, and forming a risk zone based on the two or more risks. The display unit is configured to display the environment of the vehicle with the feature and the risk zone of the feature.

A system for automatically parking a commercial vehicle includes a service braking system having at least one brake valve, a brake controller for controlling the service braking system, and an advanced driver assistance system (ADAS) controller. The ADAS controller communicates with the brake controller and requests activation of the foot brake of the commercial vehicle until the vehicle comes to a stop. In response to the ADAS controller's request to activate the service brake, the brake controller determines that the commercial vehicle should remain stationary and activates at least one brake valve to release system pressure, mechanically parking the vehicle.

A steering system for a vehicle that includes a driver-controllable steering device; a power steering actuator coupled to a steerable vehicle wheel; an advanced driver assistance system (ADAS) including a spatial monitoring system; and a steering controller. A steering control routine determines a target path and a target trajectory for the vehicle based upon an input from the spatial monitoring system; determines a driver steering command; determines external factors related to the target path and the target trajectory; determines a weighting factor for the driver steering command based upon the plurality of external factors; determines a steering angle command based upon the driver steering command, the weighting factor for the driver steering command, the target path, and the target trajectory; and controls the power steering actuator to control the steerable wheel responsive to the steering angle command.

The disclosure relates to a method and system for extracting disparity information out of a pair of stereo camera images for processing images of camera sensors for Automated Driving or Advanced Driver Assistance Systems in a vehicle. The method includes: a) receiving a pair of unrectified stereo camera images, b) performing a 2D-matching of the received pair of images using a trained convolutional neural network and providing the 2D-displacement on a pixel-by-pixel level as disparity information, and c) outputting the 2D-displacement on pixel level. The method is robust which does not require a high precision rectification. Applying rectification on the disparity values after the matching process leads to reduced algorithmic complexity with simultaneous preservation of all information.

1. Name of the product in this design: Calibration and calibration plate (ADAS). 2. Purpose of this design: To be attached to the surface of vehicle glass to assist advanced driver assistance systems in diagnostic testing and calibration. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention relates to an automotive glazing heating system with independent zone activation. An automotive glazing heating system with independent zone activation is designed to effectively manage defrosting and defogging of automotive glazing elements, such as a windshield. The system allows for independent control of a plurality of heating zones across the surface of the glazing, thereby enabling accurate and effective management of thermal energy distribution. The control unit manages activation of the heating zone based on various inputs, optimizing low voltage power consumption of the vehicle. The system also ensures compatibility with vehicle electronics and sensor systems, such as those used in advanced driver assistance systems (ADAS), by allowing selective heating of areas in front of the vehicle electronics and sensor systems.

Aspects presented herein may enable a user equipment (UE) to dynamically adjust map data to be downloaded from a server based on currently available information and the specifications / demands of advanced driver assistance systems (ADAS) and / or autonomous driving (AD) features, thereby reducing / optimizing the overall map data transferred over-the-air. In one aspect, a UE identifies whether at least one vehicle feature meets a set of thresholds based on at least one of stored map data, sensor information, or vehicle-to-everything (V2X) information. The UE transmits, to a server based on an identification of whether the at least one vehicle feature meets the set of thresholds, a request for map data. The UE receives, from the server based on the request, the requested map data.

A method for adjusting a response of a vehicle equipped with an advanced driver assistance system (ADAS) includes collecting telemetry data. The telemetry data includes map-related collision events and proximity collision events. The method also includes collecting environmental data and performing an analysis of the telemetry data relative to the environmental data to determine collision risk factors. The collision risk factor is associated with an increased collision risk. The method further includes determining a region of increased collision risk based on the collision risk factor. The method also includes determining a location of a vehicle equipped with the ADAS relative to a map and collecting vehicle data from one or more sensors. The method also includes calculating a vehicle collision risk increase index (IRVCI) based on a location of the vehicle equipped with the ADAS and the collected vehicle data. The method also includes adjusting a response of the vehicle equipped with the ADAS based on the IRVCI.

The steering system includes a controller in communication with the sensors. The controller is configured to determine a counter torque to apply to the steering system using a side slip and pull compensation system based on inputs to the steering wheel, apply the counter torque to the steering system, and determine an operating state of an advanced driver assistance system. The controller is further configured to determine an angle of a road surface based on the plurality of sensors when the advanced driver assistance system is activated, and apply an updated counter torque to the steering system when at least one of a magnitude or a direction of the angle of the road surface changes while the advanced driver assistance system is activated.

A retractable inlay door and enclosure assembly includes a fascia, an inlay door cover, a first and second bracket, a radar and at least one bumper. The fascia defines an opening and includes engaging members configured thereon. The inlay door cover has at least one clip thereon configured to interface with an engaging member of the fascia in an installed position and release from the engaging member in an uninstalled position. A first bracket is coupled to the inlay door cover. A second bracket coupled to the first bracket. The radar is disposed between the first and second brackets. At least one bumper is positioned between the first and second brackets, constructed from a force-absorbing material. This design allows for relative movement of the first bracket toward the second bracket through the compression of the bumper.

The invention discloses a driving risk assessment method, and belongs to the field of data processing. According to the evaluation method, a risk entropy concept is introduced, the uncertainty of three types of core risk sources of vehicles, roads and vulnerable participants in a driving system is converted into quantifiable entropy values, and a vehicle risk entropy model, a road risk entropy model and a vulnerable participant risk entropy model are constructed respectively; based on a combined optimization strategy of an analytic hierarchy process and an entropy weight method, a man-vehicle-road coupling risk entropy model is established, and comprehensive quantitative evaluation of multi-dimensional risks is realized; the method can accurately capture the dynamic risk in the driving process, is timely and effective in intervention response, and can be widely applied to the fields of intelligent driving and advanced auxiliary driving systems.

A system and computer-implemented method detect and act upon deactivated vehicle components. The system and method include receiving measurements data associated with driving activity. The measurements data includes an indication that at least one feature of an Advanced Driver Assistance System (ADAS) of a vehicle has been deactivated for a driving activity. The system and method may include receiving historical driving data including a history of at least one driving activity aided by activation of the alert from the ADAS feature. The system and method may compare the measurements data to the historical driving data, determine a likelihood level that the feature of the ADAS would have provided the alert had the feature been activated based upon the comparing, and set, based at least upon the determining, at least a portion of an operator profile associated with an operator of the vehicle with the likelihood level.

The present invention relates to systems and methods for verification-as-a-service that enables continuous verification for advanced driver assistance systems and autonomous vehicles. A motor vehicle continuous verification system includes a backend that collects data from a vehicle fleet and wirelessly communicates with the vehicle fleet. The backend wirelessly communicates with at least one customer. A vehicle module is provided on-board each motor vehicle of a plurality of motor vehicles of the vehicle fleet and performs on-board vehicle verification analysis. A fleet-based verification module that manages data defining configurations and capabilities of the plurality of motor vehicles of the vehicle fleet is provided at the backend or cloud-based. A verification manager generates verification tasks based on user-defined or desired outcomes of verification analysis and vehicle fleet availability. A client module, which is remote with respect to the plurality of motor vehicles of the vehicle fleet, has interface items applied by at least one customer seeking to perform verification analysis.

Method of adapting a multi-task machine learning model of an advanced driver assistance system (ADAS) 16 to an updated set of tasks, comprising: providing a pre-trained machine learning model defined

System (100) for verifying partial functions of advanced driver assistance systems (ADAS) and / or automated driving systems (ADS) at synchronization points (750, 755), wherein a synchronization point (750, 755) is a predefined point in time or phase in the development process of an ADAS / ADS system at which all necessary changes to the system architecture, software or hardware are integrated, and wherein specific test cases (350) are executed at this synchronization point (750, 755) to ensure that all relevant functional groups (450) function properly, comprising an input module (200) for inputting available functional groups (450) and synchronization points (750), in particular with specifications relating to the system architecture or software updates;a test case generation module (300) configured to generate a set of test cases (350) for testing and verifying an ADAS / ADS system; a function grouping module (400) configured to divide the set of test cases (350) into function groups (450), each function group (450) representing a sub-function of the ADAS / ADS system; a prioritization module (500) configured to assign priority classes (550) to the function groups (450) based on the probability of errors occurring and the effort required to correct them; a synchronization module (700) configured to assign the corresponding function groups (450) and the test cases (350) associated with the function groups (450) to the synchronization points (750, 755);a test management module (800) configured to consider the maximum number of test cases (350) per synchronization point (750) and, if this number (350) is exceeded, to move test cases (350) with a low priority class (550) to subsequent synchronization points (755); and an output module (900) configured to output the selected test cases (950) for a synchronization point (750) to increase the efficiency of verification tests and reduce resource requirements.

Aspects presented herein may enable a UE (e.g., a vehicle, an autonomous vehicle, an onboard unit (OBU) of a vehicle, an advanced driver assistance system (ADAS) of a vehicle) to calculate and output a safety margin for the UE or objects around the vehicle. In one aspect, a UE receives or sends a request to provide security margin visualization assistance. The UE obtains, in response to the request, an indication of a security margin associated with the object based on a distance between the UE and the object and at least one of: a size of the object, a speed of the object, a position of the object, a type of the object, a direction of the object, or a pattern of movement of the object. The UE outputs a security margin associated with the object.

A camera device for vehicle safety. The camera device is connected to hardware and software systems installed in a vehicle and is equipped in the vehicle. The camera device facilitates autonomous driving systems including advanced driver assistance systems (ADAS), by utilizing its algorithms in conjunction with an electric power control unit (EPCU) and an electronic control unit (ECU), including a vehicle control unit (VCU). Further, the camera device facilitates real-time wired and wireless video transmission and storage through antenna modules of a display device and a camera device inside the vehicle, and can record emergency situations caused by traffic accidents during vehicle operation, as well as the on-site situation for before and after the accident, for use as video evidence. Additionally, the camera device operates when sensors in the vehicle detect physical and chemical changes during parking or stopping, allowing video footage of the vehicle damage site to be recorded.

A method includes receiving a desired state from a path planner, the desired state including at least a first desired yaw rate and a first desired lateral velocity of the vehicle. The method further includes determining a second desired yaw rate and a second desired lateral velocity of the vehicle by a path tracing controller, at least in part based on the first desired yaw rate and the first desired lateral velocity. The method further includes determining an active rear steering command and a torque vector control command by a vehicle motion controller, at least in part based on the second desired yaw rate and the second desired lateral velocity. The method further includes controlling the vehicle using at least one of the active rear steering command and the torque vector control command to cause the vehicle to follow a path generated by the path planner.

A radar enhancement system for a vehicle includes a radar sensor having an operating frequency and configured to detect a target, the radar sensor configured to capture radar data including a signal, and a controller communicatively coupled with the radar sensor. The controller includes a radar enhancement application and an Advanced Driver Assistance System (ADAS) function with a first confidence level. The radar enhancement application includes a pair of alternating center frequencies including a first center frequency and a second center frequency different from the first center frequency. The radar enhancement application is configured to alter the operating frequency of the radar sensor using a pair of alternating center frequencies and to define a second confidence level of the ADAS function. The second confidence level is greater than the first confidence level.

The invention concerns a method for controlling a vehicle which can determine if the vehicle is located on a railway crossing and depending on the vehicle's speed or driving direction generate actions. The method comprises the steps to determine if the vehicle is located on a railway crossing; determine if the vehicle speed is below a threshold or if the vehicle is reversing; based on the combined outcome of the determinations, generate a vehicle control signal and / or generate a user information output. The invention further concerns a vehicle control system and an advanced driver assistance system.