106results about "Automatic control systems" patented technology

The invention relates to the technical field of driving control, in particular to a new energy automobile safe driving control method and system. The method comprises the following steps that a historical urgent danger avoiding data set and a corresponding user misoperation braking state are obtained through a new energy automobile control center, sample undersampling processing is conducted firstly, and an urgent danger avoiding balance sample is obtained; thirdly, analyzing user misoperation braking abnormity by using a balance sample, and performing disordered vector intensity calculation under a time dimension based on braking abnormity data to generate disordered vector segmentation clustering data; then, braking time sequence intervention correction sensing is carried out according to the clustering data, optimized braking intervention correction data are generated, finally, the optimized data are transmitted to a new energy automobile control terminal, and safe driving control is executed. According to the invention, the driving control technology is optimized, so that the driving control technology is more perfect.

A vehicle control system including a sensor for detecting an object location, a memory for storing an environment map indicative of a driving environment coordinated with a host vehicle location, a processor configured to estimate a line and object quality, to determine an uncertainty in response to historical motion of the objects, to detect a loss of sensor data in response to the data signal, to generate a frozen scene construction in response to the line and object quality and the uncertainty, to localize a host vehicle location with respect to the frozen scene construction, to regenerate an object data and a lane data in response to the frozen science and the localized host vehicle location, and to generate a vehicle motion path in response to the object data and lane data, and a vehicle controller for controlling the host vehicle in response to the vehicle motion path.

A system for detecting a vehicular collision (i) receives occupant data from at least one internal sensor; (ii) receives external data from at least one external sensor; (iii) determines positional information for at least one occupant of a vehicle; and (iv) generates a virtual reconstruction of the vehicle collision. The virtual reconstruction indicates a severity of vehicle damage and a severity of injury to the at least one occupant caused by the vehicle collision. The system may also utilized vehicle occupant positional data, and internal and external sensor data to detect potential imminent vehicle collisions, take corrective actions, automatically engage autonomous or semi-autonomous vehicle systems, and / or perform at least one action to reduce a severity of a potential injury.

The embodiment of the invention provides a vehicle control method which comprises the steps that first road condition data and second road condition data of a preset road are obtained, the first road condition data are from a platform data source, and the second road condition data are from a vehicle-mounted data source; performing risk classification processing based on the first road condition data to obtain a target risk type of the preset road; determining a target risk level corresponding to the target risk type based on the second road condition data; based on the target risk type and the corresponding target risk level, determining a target driving strategy when driving on the preset road; and performing driving control on the vehicle based on the target driving strategy. Due to the fact that the first road condition data of the platform data source and the second road condition data of the vehicle-mounted data source are integrated, the road condition of an emergency can be obtained in advance, the corresponding driving strategy is determined, prospective vehicle control is achieved, and the response speed during vehicle control can be increased.

The present application provides an autonomous driving method, an auxiliary controller, a main controller, an autonomous driving system, an electronic device and a computer-readable storage medium, and relates to the technical field of autonomous driving. The method is applied to an auxiliary controller and comprises: acquiring state monitoring information, the state monitoring information being information obtained by monitoring an operation state of a main controller; and in response to determining, according to the state monitoring information, that the main controller is operating abnormally, controlling an operation state of an autonomous vehicle.

A method and system for estimating lane changing intention of a target vehicle is provided, and a method for estimating lane changing intention of a target vehicle according to an embodiment of the present disclosure comprises: detecting the target vehicle and at least one peripheral vehicle of the target vehicle using at least one sensor installed at a host vehicle; accumulating driving risk data of the target vehicle with respect to at least one peripheral vehicle while the target vehicle is driving straight; determining whether the driving risk data has been accumulated for a predetermined time; if the driving risk data has been accumulated for the predetermined time, generating a risk adaptability model based on the accumulated driving risk data; estimating the lane changing intention of the target vehicle based on the generated risk adaptability model; and controlling the host vehicle based on the lane changing intention of the target vehicle.

Aspects of the present disclosure relate switching between autonomous and manual driving modes. In order to do so, the vehicle's computer may conduct a series of environmental, system, and driver checks to identify certain conditions. The computer may correct some of these conditions and also provide a driver with a checklist of tasks for completion. Once the tasks have been completed and the conditions are changed, the computer may allow the driver to switch from the manual to the autonomous driving mode. The computer may also make a determination, under certain conditions, that it would be detrimental to the driver's safety or comfort to make a switch from the autonomous driving mode to the manual driving mode.

The invention relates to a driving data dynamic adaptive method and device, a vehicle and a storage medium. Comprising the steps of preprocessing actual driving data of a current vehicle, and determining current driving condition characteristics of the current vehicle based on the preprocessed actual driving data and GIS map information; determining at least one group of to-be-switched driving calibration data from a preset scene driving calibration database based on the basic hardware configuration data of the current vehicle and the current driving condition characteristics, and matching the preprocessed actual driving data with the at least one group of to-be-switched driving calibration data and the current driving calibration data of the current vehicle, and determining target driving data according to a matching result, so that the current vehicle drives based on the target driving data. Therefore, more adaptive vehicle driving calibration data is provided for the user in real time based on the actual driving scene, and the problem that the performance of existing driving calibration data in actual use cannot achieve the optimal cost performance in the whole scene is solved.

The invention relates to a method for providing a plurality of driving modes (12) for at least one motor vehicle (14) by a central electronic computing device (10), comprising the steps of receiving a plurality of driving behaviors (16) of a plurality of motor vehicles (18) by the electronic computing device (10); (S1) extracting similarities in the plurality of driving behaviors (16) by the electronic computing device (10); (S2) clustering the plurality of driving behaviors (16) depending on the similarities by the electronic computing device (10); (S3) generating a distinct plurality of driving modes (12) depending on the clustering by the electronic computing device (10); (S4) and providing the plurality of driving modes (12) for the at least one motor vehicle (14). Furthermore, the invention relates to a computer program product, a non-transitory computer-readable storage medium, as well as to a central electronic computing device (10).

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 computer-implemented method for verifying a software-based behavior planner of an automated driving function. The method includes: providing a verification environment model to limit the state space of the behavior planner according to a specifiable traffic scene; providing a formal requirement as a criterion for the correctness of decisions of the behavior planner; generating a model checker representation of the behavior planner taking into account the provided verification environment model; analyzing the model checker representation using a model checking procedure with respect to the formal requirement. The verification environment model is used to determine a physically meaningful parameter interval for at least one location parameter and / or movement parameter of the participants of the given traffic scene. The model checking procedure systematically samples the parameter interval and thus checks the behavior planner for a representative selection of the possible temporal and spatial developments of the given traffic scene.

The present application provides a vehicle control method, a vehicle, and a storage medium, relating to the technical field of vehicle control. The method includes: receiving sensing data transmitted by an external vehicle sensing device to obtain first sensing data; screening the first sensing data to obtain second sensing data; and controlling the vehicle according to the second sensing data and third sensing data, where the third sensing data is obtained by a data acquisition module scanning the surrounding environment of the vehicle. The present application not only expands the sensing range of the vehicle but also improves the driving safety of the vehicle.

A method of coordinating road users via a server device which determines instruction data by a central model and transmits the instruction data as action instruction to respective control circuits of the road user, the central model being a virtual image of a real environment created by the server device from environment data, includes when a road user reaches the real environment a local model is created by onboard sensor data and delta data relating to the central model is determined. The delta data is transmitted to the server device by the control circuit of the road user which creates an updated central model by the delta data and the central model. The server device determines and transmits updated instruction data to the road user as readjustment of the instruction data.

An approach for operating a motor vehicle that is designed for an autonomous and / or partially autonomous driving operation in which the motor vehicle is moved along a predetermined driving trajectory. During the autonomous or partially autonomous driving operation, a driving trajectory running centrally or substantially centrally along the lane traveled is shifted to the edge of the lane on the basis of lane information describing the lane currently traveled by the motor vehicle, and on the basis of speed information describing a current speed of the motor vehicle, and on the basis of at least one piece of traffic information describing a current traffic volume in the surroundings of the motor vehicle. Alternatively, or in addition, the motor vehicle is stopped before a bottleneck or an intersection is entered on the basis of road-course information describing the bottleneck or the intersection along the road course to be traveled, and additionally on the basis of emergency vehicle information describing the presence of an emergency vehicle in the surroundings of the motor vehicle, and / or on the basis of accident information describing an accident along the road course to be traveled.

The present invention provides a vehicle driving assistance device that can prevent the vehicle's speed from temporarily falling below the legal minimum speed, even when performing driving assistance control that allows the vehicle to coast. [Solution] The vehicle driving support device 10 performs a first driving support control to drive the vehicle 100 by autonomously alternating between accelerating and coasting the vehicle so that the vehicle's speed is maintained within a range between a target upper speed and a target lower speed. The vehicle driving support device sets the target upper speed by adding a predetermined upper limit to the set vehicle speed set by the vehicle's user as the target value for the vehicle's speed, and sets the target lower speed by subtracting a predetermined lower limit from the set vehicle speed. When the first driving support control is executed, if the target lower speed is lower than the legally mandated minimum speed applicable to the vehicle, the predetermined lower limit is changed so that the target lower speed is equal to or greater than the legally mandated minimum speed.

A vehicle control method includes obtaining sensor information of different modalities of different onboard devices of a vehicle, performing modality transformation on the sensor information to generate short-cycle message information of a unified modality, sending the short-cycle message information to a first data model at a remote end, generating long-cycle message information by a second data model configured at the vehicle based on the sensor information with the different modalities, sending the long-cycle message information to the first data model at the remote end, receiving the vehicle control information returned by the first data model at the remote end, and controlling the vehicle based on the vehicle control information. The short-cycle message information has better real-time performance than the long-cycle message information, and the long-cycle message information is used to trigger the first data model to generate vehicle control information.

A method and system for estimating a lane change intention of a target vehicle are provided, and a method for estimating a lane change intention of a target vehicle according to an embodiment of the present disclosure includes: detecting the target vehicle and at least one peripheral vehicle of the target vehicle using at least one sensor installed on a host vehicle; collecting driving risk data of the target vehicle with respect to at least one peripheral vehicle while the target vehicle is traveling straight; determining whether the driving risk data has been collected for a predetermined time; when the driving risk data has been collected for the predetermined time, generating a risk adaptability model based on the collected driving risk data; estimating the lane change intention of the target vehicle based on the generated risk adaptability model; and controlling the host vehicle based on the lane change intention of the target vehicle.

An autonomous driving method, an auxiliary controller, a main controller, an autonomous driving system, an electronic device, and a computer-readable storage medium, which relate to the field of autonomous driving technology. The method is used in an auxiliary controller, and includes a step of acquiring state monitoring information that is information obtained by monitoring the operating state of the main controller, and a step of controlling the operating state of an autonomous vehicle when an operating abnormality of the main controller is determined based on the state monitoring information.

The technology disclosed teaches a system and methods for providing driver assistance alerts to a driver using an end-to-end artificially-intelligent advanced driver assistance system. The technology disclosed further includes receiving environmental data for a sequence of driving states including at least video from a camera, returns from an optical sensor, and location data from a GNSS receiver, wherein 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 prescriptive steering and speed control actions in response to a present 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 driver assistance alerts based on the collision avoidance data.

The application provides a driving data collection and analysis method, system, readable storage medium and vehicle. The method comprises the following steps: obtaining a wake-up request sent by a CAN network of a whole vehicle, and making the vehicle wake up according to the wake-up request; actively obtaining driving data of a target vehicle every first preset time, obtaining driving behaviors of a driver in a current period according to a vehicle speed, an engine speed, a throttle pedal stroke value, a brake pedal stroke value, a steering wheel rotation angle and a steering wheel rotation angle acceleration; generating a trip report of the target vehicle according to driving behaviors corresponding to multiple continuous periods respectively, and uploading the trip report to a cloud service platform. The driving data collection and analysis method can intuitively reflect existing bad driving behaviors of a customer by collecting real-time data, and can help the customer to improve the existing bad driving habits, so that the behaviors of the customer are more standardized and economical.

An electronic instrument includes a first distance information acquisition unit acquiring first distance information corresponding to an object included in an image signal, at least one of a second distance information acquisition unit acquiring second distance information on the basis of at least one of information of an end position of the object included in the image signal and a third distance information acquisition unit configured to acquire third distance information based on information of a size of the object included in the image signal, and a distance information integration unit generating integrated distance information by combining and integrating at least two of the first distance information, the second distance information, and the third distance information.

The invention provides a method and a system for adaptive navigation and autonomous driving. A method includes defining an original travel route for an autonomous vehicle (AV) to a desired destination; detecting a restricted object in the AV based on an input signal for recognizing an object; defining a conditional route through one or more geographic areas to the desired destination, the one or more geographic areas allowing the restricted object using one or more route-object conditions in response to detecting the restricted object; and causing the AV to travel to the desired destination via the conditional route in response to detecting that the object is the restricted object or via the original travel route in response to not detecting that the object is the restricted object.

The invention relates to lane selection using networked vehicle data including lane connectivity and input uncertainty information. A method may include generating a dynamic lane level forward graph including a plurality of nodes for a road. The method may include calculating a weight for each action of a vehicle traveling from one node to a next node. The method may include determining values for different actions of the vehicle based on a dynamic lane level forward graph starting from a node of the vehicle to a node of the destination and a weight for each action of the vehicle. The method may include selecting an action among the different actions based on a comparison of values of the different actions. The method may include instructing the vehicle to perform a selected action for the vehicle.

A vehicle electronic control device includes a detection device configured to detect an occupant's state, a first control device, and a second control device. The second control device is configured to refer to a database defining a relationship between the occupant's state and a first time, and autonomously drive the vehicle at a speed equal to or lower than a maximum permissible speed from a switching time, which is the time when the first control device becomes unable to control the vehicle. The database is configured such that when the first time corresponding to the occupant's second state is longer than the first time corresponding to the occupant's first state, the maximum permissible speed corresponding to the second state is lower than the maximum permissible speed corresponding to the first state.

A system for providing an output signal based on a generated surroundings model of surroundings of a mobile platform is proposed. The system includes: a first subsystem, a second subsystem, wherein the second subsystem is configured to redundantly provide a functionality of the first subsystem, and a third subsystem, wherein the third subsystem is configured to redundantly provide the functionality of the first subsystem and / or of the second subsystem; a first comparison system, a second comparison system, wherein the first comparison system and / or the second comparison system are configured to detect at least one fault in the first subsystem and / or a fault in the second subsystem and / or a fault in the third subsystem and / or to identify the corresponding faulty subsystem.

Drive control device (1) for providing drive control for a hybrid vehicle by controlling a machine (2) and motor-generators (4, 5) which can be operated to output a charge of electrical power to a battery (21) and to receive a supply of electrical power from the battery (21) to supply the hybrid vehicle with a motive force obtained from the machine (2) and the motor-generators (4, 5), wherein the drive control device has a power sharing and composition system having four axes connected to each of the rotating elements of the two planetary gear sets (8, 9); wherein two motor generators (4, 5) are connected to the battery (21); wherein one of the motor generators (4, 5), the machine (2), a drive shaft (7) connected to a traction wheel (6), and the other of the motor generators (4, 5) lie on a collinear diagram, wherein the four axes of the power sharing and composition system are each connected to one motor generator (4, 5), the machine (2), the drive shaft (7), and the other motor generator (4, 5); the drive control device further comprises the following: a drive power target calculation function (42) for calculating a drive power target based on an accelerator pedal position and a vehicle speed; a charge / discharge power target calculation function (43) for calculating an electrical charge / discharge power target to / from the battery (21) based on a charge / discharge state of the battery (21); a first machine power target calculation function (44) for calculating a first machine power target based on the drive power target calculated by the drive power target calculation function (42) and the electrical charge / discharge power target calculated by the charge / The discharge power target calculation function (43) is calculated; a first machine operating point target calculation function (46) for calculating a first machine speed target and a first machine torque target, both of which correspond to the first machine power target calculated by the first machine power target calculation function (44), based on information about a machine operating point identified by a relationship between a machine speed and a machine torque; a first calculation function (47) for an upper machine speed target limit for calculating an upper limit of the first machine speed target based on the vehicle speed, wherein the upper limit of the machine speed is limited by an upper limit of the speed of one motor-generator (4, 5) and is subject to changes depending on the vehicle speed, and wherein the calculation function (47) of the upper first machine speed target limit calculates the upper limit of the first machine speed target based on the vehicle speed and the upper limit of the speed of one motor-generator (4, 5); a machine operating point target calculation function (48) to determine whether the first machine speed target calculated by the first machine operating point target calculation function (46) is greater than the upper limit, wherein the machine operating point target calculation function (48) is designed to: to set a second machine speed target to the upper limit and to calculate a second machine torque target corresponding to the second machine speed target, based on the information about the machine operating point, when it is determined that the first machine speed target calculated by the first machine operating point target calculation function (46) is greater than the upper limit; and to set the second machine speed target and the second machine torque target as the first machine speed target and as the first machine torque target if it is determined that the first machine speed target calculated by the first machine operating point target calculation function (46) is less than or equal to the upper limit; a second machine power target calculation function (49) for calculating a second machine power target based on the second machine speed target and the second machine torque target; a calculation function (50) for an electrical power target for calculating an electrical power target that specifies an amount of electrical power to be generated by driving the motor generators (4, 5) to charge the battery (21), or to be supplied from the battery (21) to the motor generators (4, 5) to drive the motor generators (4, 5), based on a difference between the drive power target calculated by the drive power target calculation function (42) and the second machine power target calculated by the second machine power target calculation function (49); a machine control (40) that is configured to to control a moment of the machine (2) based on the second machine moment target; and a motor-generator control unit (60) configured to control the motor-generators (4, 5) based on the second machine speed target, the second machine torque target, and the electrical power target.

A system for navigating a vehicle may include a processor programmed to receive outputs provided by vehicle sensors and determine a navigation maneuver for the vehicle along a road segment based on the outputs provided by the vehicle sensors. The processor may also be programmed to determine a yaw rate command and a velocity command to implement the navigation maneuver. The processor may also be programmed to determine, using a first control subsystem, a first vehicle steering angle based on the yaw rate and velocity command, and to determine, using a second control subsystem, a second vehicle steering angle based on the yaw rate and velocity command. The processor may further be programmed to determine an overall steering command for the vehicle based on a combination of the first and second steering angles, and to cause actuators associated with the vehicle to implement the overall steering command.