Abstract: An apparatus includes at least one camera configured to capture an image of a traffic lane in front of a vehicle. The apparatus also includes a path tracking controller configured to detect lane boundaries and a path curvature for the traffic lane from the image, determine a lateral offset of the vehicle from a reference path for the traffic lane and a heading offset for the vehicle from the path curvature, determine a yaw rate maintaining the vehicle within the traffic lane using a kinematics control, determine a steering angle maintaining the vehicle within the traffic lane using a dynamics control and the yaw rate determined by the kinematics control, and activate a steering control based on the determined steering angle.

Abstract: The subject matter described in this specification is directed to a computer system and techniques for determining a location of an autonomous vehicle. The computer system is configured to determine the location using localization data from multiple data sources. When the localization data from the multiple data sources is unavailable or inaccurate, the computer system is configured to determine the location using predefined features of the environment.

Abstract: In some embodiments, techniques for updating a model that represents turning dynamics of a vehicle are provided. In some embodiments, an initial location and orientation of the vehicle with respect to an object outside the vehicle are determined using information from environment sensors including but not limited to image sensors and/or range sensors. In some embodiments, vehicle state information including but not limited to steering angle and wheel speed is received before determining a new location and orientation of the vehicle with respect to the object. In some embodiments, the model is updated using the initial location and orientation, the new location and orientation, and the vehicle state information.

Abstract: Among other things, techniques are described for receiving, from at least one sensor of a vehicle, a sensor measurement indicative of at least one of a sound or a vibration associated with a road element; identifying the road element based on a pattern in the sensor measurement; determining, based on the road element, a vehicle behavior for the vehicle; and controlling the vehicle to operate according to vehicle behavior.

Abstract: A system controls a work machine including a work implement, a rotating body, and a support body to load materials onto a conveyance vehicle. The system includes a first processor. The first processor acquires data indicative of a position of a predetermined reference point included in the conveyance vehicle. The first processor acquires data indicative of a position of a rotation center of the rotating body. The first processor acquires data indicative of a position of a blade tip of the work implement. The first processor determines a target rotation angle of the rotating body from a straight line connecting the position of the rotation center of the rotating body and the position of the reference point of the conveyance vehicle, and a current position of the blade tip of the work implement. The first processor controls the rotating body to rotate according to the target rotation angle.

Abstract: In an approach to mirage detection by autonomous vehicles, one or more computer processors monitor road conditions of a road on which an autonomous vehicle is traveling. One or more computer processors detect a visual indication of a water accumulation on the road. One or more computer processors determine whether one or more other vehicles are detected on the road ahead of the autonomous vehicle. Responsive to determining the one or more other vehicles are detected, one or more computer processors request information associated with road conditions of the road ahead of the autonomous vehicle from the one or more other vehicles. Based on a response to the request from the one or more other vehicles, one or more computer processors determine the one or more other vehicles did not detect the water accumulation. One or more computer processors determine the visual indication of the water accumulation is a mirage.

Abstract: The disclosure includes embodiments for processing a set of wireless messages by an ego vehicle. A method includes determining a location of an object of interest in a roadway environment that includes the ego vehicle and a set of remote connected vehicles. The method includes segmenting the roadway environment into a plurality of segments. The method includes assigning priority scores to each of the segments based on (1) whether the forward-facing sensors of the remote connected vehicles present in the segment are capable of measuring the object of interest and (2) proximity of the remote connected vehicles in the segment to the object of interest, wherein segments have higher priority scores if the remote connected vehicles present in the segment have forward-facing sensors that are capable of measuring the object of interest and the remote connected vehicles present in the segment are closer to the object of interest.

Abstract: Drive envelope determination is described. In an example, a vehicle can capture sensor data while traversing an environment and can provide the sensor data to computing system(s). The sensor data can indicate agent(s) in the environment and the computing system(s) can determine, based on the sensor data, a planned path through the environment relative to the agent(s). The computing system(s) can also determine lateral distance(s) to the agent(s) from the planned path. In an example, the computing system(s) can determine modified distance(s) based at least in part on the lateral distance(s) and information about the agents. The computing system can determine a drive envelope based on the modified distance(s) and can determine a trajectory in the drive envelope.

Abstract: A vehicle device may execute one or more neural networks (and/or other artificial intelligence), based on input from one or more of the cameras and/or other sensors, to intelligently detect safety events in real-time. The one or more neural networks may be an ensemble neural network that includes neural networks for detecting a head and hand of a user, neural networks for detecting hand actions of the user, neural networks for detecting the head pose of the user, neural networks for predicting an occurrence of an event, and neural networks for predicting a start time and end time of the event. Further, the neural networks can be segmented into a modular neural network based on metadata. The segmentation of the neural network can define a thin layer of the modular neural network to enable independent tuning of the thin layer of the modular neural network.

Abstract: The technology relates to detection of aberrant driving situations during operation of a vehicle in an autonomous driving mode. Aberrant situations may include potential theft or unsafe conditions, which are determined according to one or more signals. The signals are derived from information detected about the environment around the vehicle, such as from one or more sensors disposed on the vehicle. In response to an aberrant situation, the vehicle may take various corrective action, such as rerouting, locking down the vehicle or communicating with remote assistance. The type of corrective action taken may depend on a type of cargo being transported or whether one or more passengers are in the vehicle. If there are passengers, the system may communicate with the passengers via the passenger's client computing devices or by presenting visual or audible information via a user interface system of the vehicle.

Abstract: Disclosed embodiments include systems, vehicles, and methods for receiving inputs indicative of a destination and a potential intermediate destination and determining a time potentially available at the intermediate destination. In an illustrative embodiment, a system includes a computing device having computer-readable media storing computer-executable instructions configured to cause the computing device to receive a first input indicative of a destination. A second input is received that is indicative of a desired arrival time at the destination. A third input is received that is indicative of an intermediate destination to be visited before traveling to the destination. A first travel time to the intermediate destination, a second travel time to the destination, and a time available at the intermediate destination are determined. The time available at the intermediate destination is communicated to a user.

Abstract: The present disclosure discloses a method for managing liquefied natural gas (LNG) tanking safety based on location matching and an Internet of Things system. The method includes that an intelligent terminal perceives and acquires terminal operation information, generates a request for tanking, and sends the request to a management platform; the management platform obtains vehicle information of an LNG tanker after receiving the request, generates a task plan for tanking and sends the task plan to the LNG tanker and the intelligent terminal respectively; the LNG tanker drives to a location of the terminal according to the task plan, and the management platform performs real-time tracking and monitoring on a driving path of the LNG tanker; the LNG tanker completes a two-way location matching authentication with the intelligent terminal through the management platform after arriving at the location of the terminal and performs tanking for the LNG distributed energy intelligent terminal.

Abstract: A radar device for a vehicle includes: a radar sensor disposed on either one or both of a front surface of a vehicle and a rear surface of the vehicle, and configured to emit an electromagnetic wave signal toward a road having a lane at least partially containing an electromagnetic wave absorbing paint; and a radar control unit configured to determine whether a target is an object, the road, or the lane, based on an intensity of an electromagnetic wave reflected by the object, the road, or the lane, by using a radar signal received from the radar sensor.

Abstract: A vehicle travel control device includes computation circuitry, and a device controller that controls actuation of a traveling device mounted on a vehicle, based on a result from the computation circuitry. The computation circuitry identifies a vehicle outdoor environment based on an output from image circuitry that acquires image information of vehicle outdoor environment, sets a route on which the vehicle is to travel, in accordance with the vehicle outdoor environment previously identified, determines a target motion of the vehicle to follow the route previously set, calculates a target physical quantity to be executed by the traveling device to achieve the target motion previously determined, and calculates a controlled variable of the traveling device such that the target physical quantity calculated is achieved, and the device controller outputs a control signal to the traveling device so as to control the traveling device to control a motion of the vehicle.

Abstract: A vehicle control system includes: a vehicle control unit that remotely controls a PW, which is a control object, based on a signal from a mobile device; a mobile-side stop processing unit that performs stop process for stopping the PW upon transition to a predetermined operation state in which user operations are restricted while the PW is in operation by the remote control.

Abstract: The present invention obtains a controller and a control method capable of securing a driver's comfort during adaptive cruise control for a straddle-type vehicle. In the controller and the control method according to the present invention, during the adaptive cruise control in which the straddle-type vehicle is made to travel according to a distance from the straddle-type vehicle to a preceding vehicle, motion of the straddle-type vehicle, and a driver's instruction, when a state where a braking force is generated on at least one of wheels of the straddle-type vehicle is switched to a state where a drive wheel is driven using drive power output from a drive source of the straddle-type vehicle, the braking force generated on the at least one of the wheels is controlled such that a reference braking force is generated on the drive wheel at a time point at which the drive wheel starts being driven due to transmission of the drive power output from the drive source to the drive wheel.

Abstract: Providing an open interface to a navigation system is provided herein. A single partition (or more than one partition) of a partitioned operating system can be utilized to provide connectivity between a navigation system and one or more user equipment devices. Thus, the navigation system and the one or more user equipment devices can be communicatively coupled via the at least one partition. Further, a Software Development Kit (SDK) can be configured to enable bi-directional communication between the navigation system and the one or more user equipment devices. In addition, the SDK can provide security for the navigation system when communicating with the one or more user equipment devices.

Abstract: An unmanned aerial vehicle may include a flight system, a wireless communication system, a processor, and a power system having a battery and a battery charging port. The power system may be operable to power the flight system, the wireless communication system, and the processor. The processor may be configured to operate the flight system to fly the unmanned aerial vehicle from a ground position to an in-air position while the battery charging port is attached to an air-to-ground tether, trigger a release of the air-to-ground tether from the battery charging port after determining the unmanned aerial vehicle has reached the in-air position and the battery is charged, and operate the flight system to execute a flight pattern while operating the wireless communication system to search for a wireless communication device.

Abstract: The system comprises an interface and a processor. The interface is configured to receive vehicle data, comprising data associated with a vehicle over a period of time; and receive driver location data, comprising location data associated with one or more drivers of a roster of drivers. The processor is configured to determine a likely pool of drivers based at least in part on the driver location data and the vehicle data; and process the vehicle data and the likely pool of drivers using a model to determine a most likely driver.

Abstract: Provided is a driver assistance system including an internal camera installed in a vehicle to detect whether a driver is in a drowsy driving, and configured to photograph a state of eyes of the driver to acquire drowsiness data, a first sensor installed in the vehicle to have a front-side view of the vehicle, and configured to acquire first sensor data to detect an object in the front-side view, a second sensor installed in the vehicle to have a rear-side view of the vehicle and configured to acquire second sensor data to detect an object in the rear-side view, and a controller including at least one processor configured to process the drowsiness data, the first sensor data, and the second sensor data, wherein the controller is configured to: if a result of processing the drowsiness data is that the driver has closed the driver's eyes for a predetermined time or longer, transmit a control signal to at least one of a braking device or a steering device to perform a lane change for stopping the vehicle based on