Abstract: Implementations are described herein for analyzing vision data depicting undesirable plants such as weeds to detect various attribute(s). The detected attribute(s) of a particular undesirable plant may then be used to select, from a plurality of available candidate remediation techniques, the most suitable remediation technique to eradicate or otherwise eliminate the undesirable plants.

Abstract: Methods and apparatus are provided for generating a runway landing alert for an aircraft. The method comprises establishing a Runway Awareness Advisory System (RAAS) envelope for the designated target runway of the aircraft. A track of the aircraft is monitored with reference to a centerline of the target runway. Any deviation by the aircraft from the centerline of the target runway is detected and determined if it is within a margin of error. If the deviation is within the margin of error, an altitude parameter of the RAAS envelope is increased. If the aircraft is determined to still be maneuvering with respect to the centerline of the target runway, the altitude parameter of the RAAS envelope is decreased. Otherwise, an alert is generated if the aircraft is outside of the RAAS envelope.

Abstract: The disclosure relates to a method for calibrating a drive system for an axle of a motor vehicle; wherein the drive system includes at least one electric machine as the drive unit, a drive shaft driven by the drive unit, a first output shaft and a second output shaft, as well as a first clutch connecting the drive shaft to the first output shaft and a second clutch connecting the drive shaft to the second output shaft.

Abstract: In one embodiment, a computing system of a vehicle generates perception data based on sensor data captured by one or more sensors of the vehicle. The perception data includes one or more representations of physical objects in an environment associated with the vehicle. The computing system further determines simulated perception data that includes one or more representations of virtual objects within the environment and generates modified perception data based on the perception data and the simulated perception data. The modified perception data includes at least one of the one or more representations of physical objects and the one or more representations of virtual objects. The computing system further determines a path of travel for the vehicle based on the modified perception data, which includes the one or more representations of the virtual objects.

Abstract: An information processing system includes an acquirer configured to acquire a boarding request, a deriver configured to derive, when an action schedule of an automatic driving vehicle includes a standby state based on a boarding request acquired by the acquirer, a usage charge of the automatic driving vehicle reflecting a cost generated in a traveling state in which the automatic driving vehicle carries a user and travels and a cost generated in the standby state, and an output configured to output information including the usage charge derived by the deriver.

Abstract: A control system and a method for predicting a location of dynamic objects, for example, of pedestrians, which are able to be detected by the sensors of a vehicle. The control system includes a multitude of sensors and a processing system, which is configured to combine with a first program the objects that are detected by the multitude of sensors to form an object list, each entry of the object list encompassing the location, a speed and an open route for each of the objects, and the object list including a time stamp; and to determine with a second program for at least a portion of the dynamic objects an additional object list from a predefined number of object lists, the additional object list including a time stamp for a future point in time and encompassing at least the location of the dynamic objects.

Abstract: A system and method may track data from one or more sensors during vehicle driving. Based on the sensors data, one or more alerts or potential hazards may be identified. The system and method may generate a drive summary including information and optional statistics about the alerts or potential hazards.

Abstract: The technology relates to detecting and responding to processions. For instance, sensor data identifying two or more objects in an environment of a vehicle may be received. The two or more objects may be determined to be disobeying a predetermined rule in a same way. Based on the determination that the two or more objects are disobeying a predetermined rule, that the two or more objects are involved in a procession may be determined. The vehicle may then be controlled autonomously in order to respond to the procession based on the determination that the two or more objects are involved in a procession.

Abstract: An agricultural apparatus operable in agricultural fields includes one or more digital electronic weather stations affixed to the apparatus and optionally one or more GPS receivers and/or proximity sensors, each coupled to a mobile computing device such as a cab computer. The weather stations transmit data representing wind speed, temperature and/or other weather parameters, as measured on the apparatus, to the mobile computing device. Under control of program logic, the mobile computing device continuously compares real-time, then-current weather data received from the weather stations to programmed or configured threshold values relating to a current agricultural operation. If the weather data indicates weather conditions that exceed one of the thresholds, a warning message may be generated at the mobile computing device to prompt the operator to confirm whether to continue the operation.

Abstract: A computer, including a processor and a memory, the memory including instructions to be executed by the processor to determine a vehicle six degree of freedom (DoF) pose based on an image where the six DoF pose includes x, y, and z location and roll, pitch, and yaw orientation and transform the vehicle six DoF pose into global coordinates based on a camera six DoF pose. The instructions can include further instructions to communicate to the vehicle the six DoF pose in global coordinates.

Abstract: A method and a traffic control entity (100) for controlling a group of vehicles (104) capable of autonomous driving without requiring a driver, to allow an emergency vehicle (102) to pass the group of vehicles (104) which are travelling concurrently in multiple lanes on a road. When detecting that the emergency vehicle (102) is approaching the group of vehicles (104) e.g. from behind, the vehicles in the group (104) are identified based on information (108) about current position and movement of the vehicles (104). The traffic control entity (100) then issues a command (106) instructing the identified vehicles to adjust their lateral positions relative the lanes to create a passage along the group of vehicles (104). Thereby, the emergency vehicle (102) is able to move through the passage without having to slow down significantly.

Abstract: In various examples, a path perception ensemble is used to produce a more accurate and reliable understanding of a driving surface and/or a path there through. For example, an analysis of a plurality of path perception inputs provides testability and reliability for accurate and redundant lane mapping and/or path planning in real-time or near real-time. By incorporating a plurality of separate path perception computations, a means of metricizing path perception correctness, quality, and reliability is provided by analyzing whether and how much the individual path perception signals agree or disagree. By implementing this approach—where individual path perception inputs fail in almost independent ways—a system failure is less statistically likely. In addition, with diversity and redundancy in path perception, comfortable lane keeping on high curvature roads, under severe road conditions, and/or at complex intersections, as well as autonomous negotiation of turns at intersections, may be enabled.

Abstract: The disclosure generally relates to autonomous or semi-autonomous driving vehicles. An exemplary embodiment of the disclosure relates to a system to provide one or more threat vectors to a cluster of vehicles. An exemplary vehicle detection system includes a communication module configured to receive a first threat vector from a first vehicle in a cluster of vehicles. The first threat vector may include a plurality of primary attributes associated with a moving object. The vehicle detection system may also include a detector module configured to detect the moving object and to provide one or more secondary attributes associated with the moving object; and a controller to construct a second threat vector as a function of one or more of the first threat vector, the primary attributes and the secondary attributes associated with the moving object.

Abstract: A method for applying fluid to a travel lane is disclosed. The method may include receiving information related to a travel lane including a first set of tire paths and a second set of tire paths to be traveled by one or more vehicles, generating spray pattern control information for a fluid application machine having multiple spray heads based on the first set of tire paths and the second set of tire paths to be traveled by the one or more vehicles, and selectively triggering the multiple spray heads of the fluid application machine to alternately apply fluid to the first set of tire paths and the second set of tire paths based on the spray pattern control information and based on a current position of the fluid application machine on the travel lane.

Abstract: Image data is used to determine wind speed and wind direction during takeoff and landing by an unmanned aerial vehicle (UAV). The flight data, including image data, may be received using sensors onboard the UAV and/or the flight data may be received from other sources, such as nearby anemometer, cameras, other UAVs, other vehicles, and/or local weather stations. Machine learning models may train using the flight data gathered by the UAVs to determine the wind velocity based on image data. The UAV may adjust flight control settings to generate side forces to overcome the predicted wind velocity.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating vehicle intent predictions using a neural network. One of the methods includes obtaining an input characterizing one or more vehicles in an environment; generating, from the input, features of each of the vehicles; and for each of the vehicles: processing the features of the vehicle using each of a plurality of intent-specific neural networks, wherein each of the intent-specific neural networks corresponds to a respective intent from a set of intents, and wherein each intent-specific neural network is configured to process the features of the vehicle to generate an output for the corresponding intent.

Abstract: A vehicular hazard mitigation system includes one or more processors and a memory communicably coupled to the processors. The memory may store a vehicular hazard mitigation module including computer-readable instructions that when executed by the processors cause the processors to determine a base vehicle currently driving in an enhanced response driving mode. After determining the base vehicle, at least one alert zone of the base vehicle is determined. A determination is then made as to whether at least one other vehicle is currently in the at least one alert zone of the base vehicle. If at least one other vehicle is currently in the at least one alert zone of the base vehicle, the vehicular hazard mitigation module may autonomously control operation of the base vehicle to shift the driving mode of the base vehicle from the enhanced response driving mode to a non-enhanced response driving mode.

Abstract: According to one aspect, uncertainty prediction based deep learning may include receiving, using a memory, a trained neural network policy ? trained based on a first dataset in a first environment, implementing, via a controller, the trained neural network policy ? in a second environment by receiving an input and generating an output y, calculating an uncertainty array U[T] for a time window T, wherein the uncertainty array is indicative of a level of uncertainty associated with an output sample distribution of the output across the time window T based on a temporal divergence, an entropy H, a variational ratio VR, and a standard deviation SD of the output y, and executing, via the controller and one or more systems, an action based on the uncertainty array U[T], such as discontinuing use of the trained neural network policy ?.

Abstract: Provided are distance detection method and device for a cleaning robot, a cleaning robot, an electronic device and a non-transitory computer readable storage medium. The method includes: acquiring detection data of an obstacle detector of the cleaning robot, determining, according to the detection data, whether a distance between the cleaning robot and an obstacle reaches a first distance, where the first distance is a distance between the cleaning robot and the obstacle at a moment when a changing trend of the detection data fits a pre-set changing trend. In the embodiments of the present disclosure, whether the cleaning robot is moving to a specific position a certain distance away from the obstacle may be detected precisely. As the specific position is determined precisely, collision with obstacles can be avoided efficiently for the cleaning robot during working, and thus the distance detection method for the cleaning robot is improved.

Abstract: An artificial intelligence system for an autonomous vehicle includes one or more processors and a memory in communication with the one or more processors and storing a target-orientated navigation system module. When executed, the target-orientated navigation system module causes the one or more processors to receive sensor data from one or more sensors of a vehicle, synchronize the sensor data, preprocess the synchronized sensor data by transforming the sensor data into a common data format, concatenate the transformed sensor data into a K-dimensional array, which acts as an input state array, apply a navigation policy to the input state array to estimate an action-value array, direct a vehicle control system to guide the vehicle to a location representative of a cell in the action-value array that has a highest reward value.