Abstract: Enclosed are embodiments for navigation with drivable area detection. In an embodiment, a method comprises: receiving a point cloud from a depth sensor, receiving image data from a camera; predicting at least one label indicating a drivable area by applying machine learning to the image data; labeling the point cloud using the at least one label; obtaining odometry information; generating a drivable area by registering the labeled point cloud and odometry information to a reference coordinate system; and controlling the vehicle to drive within the drivable area.

Abstract: A method for inertia drive control is provided. The method includes performing advanced inertia drive control by an inertia drive controller. The controller detects a speed reduction event during road driving of a vehicle, lane division together with road type division for a road, and performs inertia drive control guide and the inertia drive control based on drive conditions of lane change and lane maintenance.

Abstract: A method for weeding crops includes, at an autonomous machine: recording an image at the front of the autonomous machine; detecting a target plant and calculating an opening location for the target plant longitudinally offset and laterally aligned with the location of the first target plant; driving a weeding module to laterally align with the opening location; tracking the opening location relative to a longitudinal reference position of the weeding module; when the weeding module longitudinally aligns with the first opening location, actuating the blades of the first weeding module to an open position; recording an image proximal to the weeding module; and in response to detecting the blades of the weeding module in the open position: calculating an offset between the opening location and a reference position of the weeding module, based on the image; and updating successive opening locations calculated by the autonomous machine based on the offset.

Abstract: This disclosure relates to a system and method for detecting vehicle events. The system includes sensors configured to generate output signals conveying information related to the vehicle. The system detects a vehicle event based on the information conveyed by the output signals. The system selects a subset of sensors based on the detected vehicle event. The system captures and records information from the selected subset of sensors. The system transfers the recorded information to a remote server or provider.

Abstract: This application is directed to augmenting training images used for generating vehicle driving models. A computer system obtains a first image of a road, identifies within the first image a drivable area of the road, obtains an image of a traffic safety object, and determines a detour path on the drivable area. The computer system determines positions of a plurality of traffic safety objects to be placed adjacent to the detour path, and generates a second image from the first image by adaptively overlaying a respective copy of the image of the traffic safety object at each of the positions of the plurality of traffic safety objects on the drivable area within the first image. The second image is added to a corpus of training images to be used by a machine learning system to generate a model for facilitating driving a vehicle (e.g., at least partial autonomously).

Abstract: Systems/methods for operating an autonomous vehicle. The methods comprise: detecting an object in proximity to the autonomous vehicle; determining a path of travel for the object that comprises a number of data points that is equal to a given number of vehicle locations selected based on a geometry of a lane in which the object; generating cost curves respectively associated with the data points, each cost curve representing a displacement cost to be at a particular location along a given cross line that (i) passes through a respective data point of said data points and (ii) extends perpendicular to and between boundary lines of the lane; determining a polyline representing displacements of the cost curves from a center of the lane; defining a predicted path of travel for the object based on the polyline; and using the predicted path of travel for the object to facilitate autonomous driving operation(s).

Abstract: An autonomous robot vehicle includes a front side and an energy absorbing system. The front side includes a front bumper and a front face including a frame defining a cavity. The energy absorbing system includes an energy absorbing member mounted in the cavity of the frame, and an inflatable airbag. The energy absorbing member is configured to reduce impact on an object struck by the autonomous robot vehicle. The inflatable airbag is mounted on the front side of the autonomous robot vehicle such that when the inflatable airbag is deployed, the inflatable airbag is external to the autonomous robot vehicle.

Abstract: A driver assistance system for an ego vehicle, and a method for a driver assistance system is provided. The system is configured to refine a coarse geolocation method based on the detection of the static features located in the vicinity of the ego vehicle. The system performs at least one measurement of the visual appearance of each of at least one static feature located in the vicinity of the ego vehicle. Using the at least one measurement, a position of the ego vehicle relative to the static feature is calculated. The real world position of the static feature is identified. The position of the ego vehicle relative to the static feature is calculated, which is, in turn, used to calculate a static feature measurement of the vehicle location. The coarse geolocation measurement and the the static feature measurement are combined to form a fine geolocation position. By combining the measurements, a more accurate location of the ego vehicle can be determined.

Abstract: Methods and devices for generating data for controlling a Self-Driving Car (SDC) are disclosed. The method includes: (i) acquiring a predicted object trajectory for an object, (ii) acquiring a set of anchor points along the lane for the SDC, (iii) for each one of the set of anchor points, determining a series of future moments in time when the SDC is potentially located at the respective one of the set of anchor points, thereby generating a matrix structure including future position-time pairs, (iv) for each future position-time pair in the matrix structure, using the predicted object trajectory for determining a distance between a closest object to the SDC as if the SDC is located at the respective future position-time pair, and (v) storing the distance between the closest object to the SDC in association with the respective future position-time pair in the matrix structure.

Abstract: A system and method of path planning utilizing a clothoid curve to connect a start point and an end point is provided. The method includes receiving at a path planning system inputs including the start point and the end point of a desired path. The method further includes calculating clothoid parameters for a clothoid curve connecting the start point and the end point based the received start point, the received end point, and a closed-form expression, wherein the closed-form expression is generated based on a relationship between a plurality of unique center point values associated with a plurality of unique clothoid curves and the clothoid parameters associated with each of the plurality of unique clothoid curves. A clothoid curve is generated based on the determined clothoid parameters, wherein the generated clothoid curve represents a planned path from the start point to the end point.

Abstract: A method for operating an electromechanical brake booster. A pedal force is ascertained, a brake pressure is ascertained from the pedal force by an actuator, and the brake pressure applied to frictional brakes is set, thereby producing a vehicle deceleration. The actuator has a standard configuration wherein, in response to the pedal force, a brake pressure is ascertained that produces a specified standard deceleration of the motor vehicle if a specified disturbance variable has a specified standard value. The influence of the disturbance variable on the vehicle deceleration is compensated. The actuator has at least one control parameter for setting a compensation configuration, an actual value of the disturbance variable is detected, and the compensation configuration is set based on the respective difference between the ascertained actual value and the standard value.

Abstract: The present invention provides a control system and a control method capable of appropriately supporting driving of a motorcycle by a rider. The control system includes a tracking target vehicle identifying unit that identifies a tracking target vehicle of adaptive cruise operation, a vehicle position information acquiring unit that acquires information on the relative position of the tracking target vehicle with respect to the motorcycle during traveling, a control amount setting unit that sets a control amount in the adaptive cruise operation, and an execution unit that causes the motorcycle to execute the adaptive cruise operation, and further includes a lane position information acquiring unit that acquires information on the relative position of a lane boundary with respect to the motorcycle during traveling, in which the tracking target vehicle identifying unit identifies the tracking target vehicle, based on the position information acquired by the lane position information acquiring unit.

Abstract: In a system trigger mode and a driver trigger mode, when a start condition for an automated lane change function by autonomous travel control is satisfied, lane change information as to whether to accept execution of the automated lane change function is presented; when an acceptance input of accepting the execution is detected, a determination is made as to whether the lane change is possible; and the automated lane change function is executed when it is determined possible. In the driver trigger mode, when a predetermined lane change instruction operation is performed, a determination is made as to whether the lane change is possible, and when a determination is made that lane change is possible, the automated lane change function is executed. The time for the lane change determination by the driver trigger mode is set shorter than the time for the lane change determination by the system trigger mode.

Abstract: A work vehicle includes a first detection unit that detects an optical beam emitted from a beam projector disposed at one end of a reference travel path, a first position deviation calculation section that calculates position deviation by a vehicle body from the reference travel path based on a detection signal from the first detection unit, a second detection unit that detects a work boundary line that occurs due to work travel, a second position deviation calculation section that calculates position deviation of the vehicle body traveling along successive travel paths from the work boundary line based on a detection signal from the second detection unit, and a steering information generation section that, based on the position deviation calculated by the first position deviation calculation section and the second position deviation calculation section, generates steering information for correcting the position deviation.

Abstract: A method or system for adaptive vehicle spacing, including determining a current state of a vehicle based on sensor data captured by sensors of the vehicle; for each possible action in a set of possible actions: (i) predicting based on the current vehicle state a future state for the vehicle, and (ii) predicting, based on the current vehicle state a first zone future safety value corresponding to a first safety zone of the vehicle; and selecting, based on the predicted future states and first zone future safety values for each of the possible actions in the set, a vehicle action.

Abstract: A method for the automatic control of the longitudinal dynamics of a vehicle is provided by which vehicles traveling ahead are detected. If an upcoming traffic jam is detected, the vehicle is decelerated until a predefined distance behind the tail end of the traffic jam is reached. When the predefined distance from the traffic jam tail end has been reached, the vehicle automatically controlled in its longitudinal dynamics is able to close the remaining, predefined distance to the traffic jam tail end at a low differential velocity in comparison to the velocity of the traffic jam tail end. Using an additional rear sensor system that senses trailing vehicles, the controlled vehicle is made to close the distance to the traffic jam tail end only if a trailing vehicle was detected.

Abstract: A system and method automatically sets vehicle functions of a vehicle, while taking account of external influencing factors. The system includes at least one back-end server which is configured to receive vehicle data of the vehicle and, while taking account of at least part of the vehicle data, to determine data with regard to external influencing factors. The back-end server is configured to determine optimal settings of the vehicle functions of the vehicle, while taking account of the vehicle data and the data with regard to the external influencing factors, and to transmit the optimum settings of the vehicle functions to the vehicle. The vehicle is configured to control the vehicle functions such that the optimum vehicle functions determined by the back-end server are adopted.

Abstract: A method of predictive navigation control for an ego vehicle includes: comparing a cue node to each of a plurality of episodic memory nodes in an episodic memory structure, wherein the cue node represents a new event representing distances, speeds and headings of one or more newly observed objects about the ego vehicle, and wherein the episodic memory structure includes a network of nodes each representing a respective previously existing event and having a respective node risk and likelihood; determining which of the nodes has a smallest respective difference metric, thus defining a best matching node; consolidating the cue node with the best matching node if the smallest difference metric is less than a match tolerance, else adding a new node corresponding to the cue node to the episodic memory structure; and identifying a likeliest next node and/or a riskiest next node.

Abstract: A system may include an in-vehicle component, including a first control set to configure the component, configured to identify a device associated with a user approach to the component; and send an interaction request to the device to cause the device to display a user interface for the component including a second control set to configure the component, the second control set including at least one function unavailable in the first control set. A personal device may receive, from an in-vehicle component including a first control set to configure the component, a user interface definition descriptive of a second control set to configure the component; and receive, from the component, a request to display a user interface for the component including the second control set to configure the component, the second control set including at least one function unavailable in the first control set.

Abstract: Method and system for controlling the behavior of an object. Behavior of the object is controlled during a first time period by using a first agent that applies a first behavior policy to map observations about the object and the environment in the first time period to a corresponding control action. Control is transitioned from the first agent to a second agent during a transition period following the first time period. Behavior of the object during a second time period following the transition period is controlled by using a second agent that applies a second behavior policy to map observations about the object and the environment in the second time period to a corresponding control action that is applied to the object. During transition the first agent applies the first behavior policy control the object and the second agent applies the second behavior policy to map observations about the object and the environment to corresponding control actions that are not applied to the object.