Abstract: Techniques to generate driving scenarios for autonomous vehicles characterize a path in a driving scenario according to metrics such as narrowness and effort. Nodes of the path are assigned a time for action to avoid collision from the node. The generated scenarios may be simulated in a computer.

Abstract: A method, apparatus, system, and computer program product for managing a vapor cycle machine. Data is received for the vapor cycle machine in an aircraft. The data comprises a pressure, a temperature, and a speed for a set of compressors in the vapor cycle machine. A ratio of the pressure to the temperature is determined for the set of compressors that ran during a flight of the aircraft. A set of actions is performed when the ratio of the pressure to the temperature for the set of compressors that ran during the flight of the aircraft exceeds a threshold more than a selected number of times over a range of flights for the aircraft.

Abstract: In various examples, sensor data may be received that represents a field of view of a sensor of a vehicle located in a physical environment. The sensor data may be applied to a machine learning model that computes both a set of boundary points that correspond to a boundary dividing drivable free-space from non-drivable space in the physical environment and class labels for boundary points of the set of boundary points that correspond to the boundary. Locations within the physical environment may be determined from the set of boundary points represented by the sensor data, and the vehicle may be controlled through the physical environment within the drivable free-space using the locations and the class labels.

Abstract: A path controller for guiding an autonomous vehicle along a desired path may include an input module that may receive input signals such as, a normal error signal that indicates an off-path deviation of the autonomous vehicle relative to a desired path, a heading signal, and a curvature signal associated with the autonomous vehicle. The path controller may also include a curvature rate module that calculates a curvature rate output signal to guide the autonomous vehicle along the desired path and a communication module that communicates the curvature rate output signal to a steering control system.

Abstract: An autonomous vehicle can obtain state data associated with an object in an environment, obtain map data including information associated with spatial relationships between at least a subset of lanes of a road network, and determine a set of candidate paths that the object may follow in the environment based at least in part on the spatial relationships between at least two lanes of the road network. Each candidate path can include a respective set of spatial cells. The autonomous vehicle can determine, for each candidate path, a predicted occupancy for each spatial cell of the respective set of spatial cells of such candidate path during at least a portion of a prediction time horizon. The autonomous vehicle can generate prediction data associated with the object based at least in part on the predicted occupancy for each spatial cell of the respective set of spatial cells for at least one candidate path.

Abstract: Systems and methods for detecting out-of-bounds behavior of an agent in a simulation including multiple agents and an ego vehicle may include: providing a scenario governing behavior of an agent in the simulation; operating the simulation in accordance with the scenario across multiple occurrences; collecting data regarding behavior of the agent in the scenario for each occurrence; comparing collected data regarding behavior of the agent in the scenario with a governing data set for the scenario; and reporting an out-of-bounds condition to a system user when the results of the comparison indicate that the behavior of the agent in the scenario deviates from the agent behavior in the governing data set scenario by more than a predetermined amount.

Abstract: A method for actuating a parking brake system of a vehicle with at least three brake calipers associated with one or more axles of the vehicle is described. The method may include the following steps: providing at least one detection device for detecting the vehicle status, acquiring a value of the vehicle status with the detection device, comparing the detected value with a reference value of the vehicle status, and actuating two brake calipers of the at least three brake calipers if the detected value is lower than the reference value or actuating all the at least three brake calipers if the detected value is equal to or greater than the reference value.

Abstract: An autonomous vehicle uses machine learning based models to predict hidden context attributes associated with traffic entities. The system uses the hidden context to predict behavior of people near a vehicle in a way that more closely resembles how human drivers would judge the behavior. The system determines an activation threshold value for a braking system of the autonomous vehicle based on the hidden context. The system modifies a world model based on the hidden context predicted by the machine learning based model. The autonomous vehicle is safely navigated, such that the vehicle stays at least a threshold distance away from traffic entities.

Abstract: The present disclosure provides a method comprising identifying at least one of a characteristic and an identity of an item for delivery from an origin to a destination and selecting one of a plurality of possible routes between the origin and the destination. For each of a plurality of route segments of the selected route, mapping information is used to characterize the route segment and one of a plurality of driving modes is selected for the route segment based on the characterization of the route segment and the at least one of the item characteristic and the item identity. A driving plan comprising a collection of the selected driving modes corresponding to the plurality of route segments comprising the selected route is provided to a vehicle and the vehicle delivers the item from the origin to the destination via the selected route using the driving plan.

Abstract: A vehicle control device is applied to a vehicle including at least a shift control system configured to switch a shift range. The vehicle control device is configured to control the vehicle to perform autonomous driving travel without depending on an operation of a driver in at least one driving operation. The vehicle control device includes a controller. The controller is configured to determine the propriety of travel by the autonomous driving travel according to a type of abnormality that occurs in the shift control system. The controller is configured to perform travel control of the vehicle according to the propriety of the travel by the autonomous driving travel.

Abstract: A system for controlling a working implement connected to a vehicle, the system comprising: at least one tool mounted on the working implement, the implement and the at least one tool configured to perform an agricultural operation; an automatic steering device associated with the vehicle, the automatic steering device configured to guide the vehicle on an intended vehicle path; an actuator for controlling the lateral position of the working implement relative to the vehicle, the actuator connected to an implement control unit that can be operated to control the actuator in such a way that the working implement is moved on an intended path of the working implement and the implement control unit is set up to compensate a lateral deviation of the vehicle from the intended path of the vehicle through actuation of the actuator; and wherein the implement control unit is programmed to pre-set the actuator after a turning operation in a position in which the effects of the turning operation is compensated.

Abstract: Systems and methods for detecting a surprise or unexpected movement of an actor with respect to an autonomous vehicle are provided. An example computer-implemented method can include, for a first compute cycle, obtaining motion forecast data based on first sensor data collected with respect to an actor relative to an autonomous vehicle; and determining, based on the motion forecast data, failsafe region data representing an unexpected path or area where a likelihood of the actor following the unexpected path or entering the unexpected area is below a threshold. For a second compute cycle after the first compute cycle, the method can include obtaining second sensor data; determining, based on the second sensor data and the failsafe region data, that the actor has followed the unexpected path or entered the unexpected area; and in response to such determination, determining a deviation for controlling a movement of the autonomous vehicle.

Abstract: An obstacle recognition device includes: a first sensor and a second sensor, which are configured to detect an object near a vehicle; a calculation unit configured to calculate, based on first detection data on a first object detected by the first sensor and second detection data on a second object detected by the second sensor, an index value for identifying whether the two objects are the same object; a determination unit configured to determine whether the two objects are the same object by comparing the index value with a threshold value set in advance; and a correction unit configured to calculate, when the determination unit has determined that the two objects are the same object, a detection error between the two sensors based on the two detection data, and generate corrected detection data so as to remove the detection error.

Abstract: An apparatus and a method for remote crane control, the apparatus comprising: a memory for storing instructions; and a processing unit configured to execute the instructions stored in the memory to control the apparatus to: receive one or more images comprising a view of a location on which a crane spreader is to land; display the one or more images on a display; receive user input to mark one or more markers on the one or more received images to facilitate landing of the crane spreader; and transmit position data of the one or more markers in the one or more received images to a processor for determining values defining positioning of the crane spreader relative to the position data of the one or more markers to offset so that the crane spreader proceeds to land based on the determined values.

Abstract: A method and apparatus for annotating a virtual lane at a crossing is provided, which relates to the field of intelligent transportation, and specifically includes: calculating a virtual connecting probability of various lanes that do not connected to each other at the crossing based on driving trajectory data of a vehicles that passing through the crossing within a detection time, and generating the virtual lane at the crossing for two disconnected lanes whose virtual connecting probability is greater than a threshold, and annotating the virtual lane on a map. In this process, the virtual lane at the crossing can be automatically generated according to the driving trajectory data of the vehicles passing through the crossing, and because the driving trajectory data of the vehicles passing through the crossing is real trajectory data, which is more in conformity with actual driving rules of the vehicles, and has a higher annotation accuracy.

Abstract: Technology described in this document can be embodied in a method that includes generating, using one or more processing devices of a vehicle operating in an environment, a discretized representation of the environment, including a plurality of cells. The cells are occupied by particles representing at least one of: an object, or a free space in the environment. Sensor data indicative of a state of at least one particle is received, and an update to a time-varying particle density function associated with a location of the particle in the dynamic occupancy grid is calculated from the sensor data and one or more models. The method further includes generating a prediction of occupancy of at least one cell in the discretized representation based on the updated particle density function, and operating the vehicle, using a controller circuit of the vehicle, based at least in part on the prediction.

Abstract: A decision method, device, equipment in a lane changing process and storage medium are provided. The method includes: acquiring a first planned track of a driverless vehicle for travelling to a first lane and a second planned track of the driverless vehicle for travelling to a second lane within a preset time period, in a lane changing process of the driverless vehicle; predicting a predicted track of at least one obstacle within the preset time period according to a travelling state of the obstacle, wherein the obstacle is in a preset range around the driverless vehicle; and determining a travelling motion of the driverless vehicle according to the first planned track, the second planned track and the predicted track of the obstacle.

Abstract: Systems, devices, products, apparatuses, and/or methods for generating a driving path for an autonomous vehicle on a roadway by determining one or more prior probability distributions of one or more motion paths for one or more objects that have previously moved in a geographic location and/or for controlling travel of an autonomous vehicle on a roadway by predicting movement of a detected object according to one or more prior probability distributions of one or more motion paths for one or more objects that have previously moved in a geographic location.

Abstract: Systems, methods, tangible non-transitory computer-readable media, and devices associated with trajectory prediction are provided. For example, trajectory data and goal path data can be accessed. The trajectory data can be associated with an object's predicted trajectory. The predicted trajectory can include waypoints associated with waypoint position uncertainty distributions that can be based on an expectation maximization technique. The goal path data can be associated with a goal path and include locations the object is predicted to travel. Solution waypoints for the object can be determined based on application of optimization techniques to the waypoints and waypoint position uncertainty distributions. The optimization techniques can include operations to maximize the probability of each of the solution waypoints. Stitched trajectory data can be generated based on the solution waypoints. The stitched trajectory data can be associated with portions of the solution waypoints and the goal path.

Abstract: A system may receive information indicating a service area of a shared mobility service, calculate information indicating one or more of risk or revenue associated with the provision of shared mobility services in the service area, determine an adjusted service area, wherein the adjusted service area is associated with one or more of a reduction in risk or an increase in revenue, and transmit information indicating the adjusted service area to a device associated with the shared mobility service.