Abstract: A machine charging system includes a machine, a charging unit, at least one user locator, and a control system. The machine may include one or more batteries, a cab, and a temperature control system. The charging unit may be configured to be removably coupled to the machine via a cable. The control system may include a controller in communication with the at least one user locator and the cab temperature control system. When the controller detects that the at least one user locator is within a predetermined distance from the machine while the machine is coupled to the charging unit, the controller may initiate one or more pre-start or pre-conditioning procedures with the temperature control system to control a temperature of one or more components of the machine.

Abstract: Systems, methods, and non-transitory computer-readable media can detect an occurrence of a condition in an environment based on sensor data captured by a vehicle. A determination is made whether the occurrence of the condition satisfies a threshold associated with a likelihood that a behavior associated with an object in the environment will occur based on an interaction between the condition and the object, wherein the likelihood is based on prior observations of one or more objects. Subsequent to determining that the threshold is satisfied, a vehicle operation that is associated with the likelihood that the behavior associated with the object will occur is performed.

Abstract: The subject matter described in this specification is directed to a system and techniques for operating an autonomous vehicle (AV) at a multi-way stop intersection. After detecting the AV is at a primary stopline of the multi-way stop intersection, a planned travel path though the multi-way stop intersection is obtained. If the planned travel path of the AV through the multi-way stop intersection satisfies a set of one or more clearance criteria, the AV proceeds past the primary stopline. The clearance criteria include a criterion that is satisfied in response to detecting the AV is clear to safely merge into a travel lane corresponding to the planned travel path.

Abstract: A controller for a hybrid electric vehicle executes an engine starting process including a first starting process and a second starting process. The first starting process drives a motor generator. The second starting process is executed when a shifting condition is satisfied in the first starting process. The second starting process includes suspending the supply of power to the motor generator and then driving the motor generator. When an engine rotation speed becomes greater than or equal to an engine rotation speed threshold value and an elapsed time is within a second time threshold value during the second starting process, the controller determines that an engine is successfully started. The second time threshold value is greater than a first time threshold value that is compared with the elapsed time during the first starting process.

Abstract: A control device includes a storage device which has stored a program, and a hardware processor, in which the hardware processor executes the program stored in the storage device, thereby acquiring a peripheral image of the mobile object, which is an image captured by a fisheye camera mounted on a mobile object, calculating an instruction regarding future traveling of the mobile object as a base trajectory in an orthogonal coordinate system, coordinate-converting the acquired base trajectory in the orthogonal coordinate system into a base trajectory in a fisheye camera coordinate system, calculating a risk of the base trajectory in the fisheye camera coordinate system on the basis of the peripheral image, and the base trajectory in the fisheye camera coordinate system, and calculating a traveling trajectory by modifying the base trajectory in the orthogonal coordinate system on the basis of the risk of the base trajectory in the fisheye camera coordinate system.

Abstract: An apparatus for assisting driving of a host vehicle includes a camera mounted to the host vehicle and having a field of view outside of the host vehicle, the camera configured to obtain image data; and a controller configured to process the image data, identify at least one object obstructing the host vehicle's driving based on the image data, predict a collision with the at least one object, identify whether the host vehicle is moving forward or backward based on the image data and control a braking device of the host vehicle to brake the host vehicle depending on whether the host vehicle is moving forward or backward.

Abstract: A system and method for controlling the velocity and heading of a vehicle includes a processor, a steering controller in communication with the processor, and a speed controller in communication with the processor. The steering controller is arranged within the vehicle and is configured to control the steering angle of the vehicle. The speed controller is arranged within the vehicle and is configured to control the velocity of the vehicle. The processor is configured to receive an array of control commands, the array of control commands include steering angle positions and velocities of the vehicle for a present time and a preview time and generate a control request for instructing the steering controller and the speed controller based on the steering angle positions and velocities of the vehicle for both the present time and the preview time.

Abstract: A method of controlling occupant thermal comfort includes the steps of driving a temperature in a seating zone to a temperature set point (54), holding the temperature set point in the seating zone for a predetermined time (56), and regulating the temperature in the seating zone to a corrected temperature set point based upon an equivalent homogenous temperature relating to vehicle cabin conditions and occupant gender (58).

Abstract: A harvester receives obstacle and turn information indicative of positions of obstacles and the locations of turns. A relative position of the harvester and a receiving vehicle is detected and control signals are generated to control unloading functionality, which may include an unloading auger, a spout position and/or a flap position during unloading, while the obstacle is being avoided and/or while a turn is being navigated. An indication of some or all of the relative position, obstacle and turn information, and control signals can be uploaded to a remote server computing system for use in performing future machine control and analytics.

Abstract: A system and method of planning a path for an autonomous vehicle from the vehicle's initial configuration to the goal configuration which is collision-free, kinematically-feasible, and near-minimal in length. The vehicle is equipped with a plurality of perception sensors such as lidar, camera, etc., and is configured to operate in an autonomous mode. An onboard computing device is configured to process the sensor data and provide a dynamic occupancy grid map of the surrounding environment in real-time. Based on the occupancy grid map, the path planner can quickly calculate a collision-free and dynamically feasible path towards the goal configuration for the vehicle to follow.

Abstract: The technology relates to detection of a nearby occluded object based on illumination emitted from that object. Illumination by the occluded object of one or more areas in the surrounding area, for instance by headlights of an occluded vehicle, is detected by a perception system of a self-driving vehicle. The self-driving vehicle can classify the detected object to determine whether the illumination is caused by a vehicle or other road user, or from objects in the surrounding environment. Illumination data and other information can be evaluated by the self-driving vehicle, for instance to identify a type of the object, a location of the object along a roadway, to disambiguate the direction of travel of the other object, etc. As a result, the self-driving vehicle may infer the behavior of the other object and modify its own driving operations to account for the other object's presence and likely behavior.

Abstract: An object of the present invention is to realize a control device having operation continuity at the time of failure with less redundancy and reduce cost. Provided is a vehicle control system including a transmission unit that transmits energy to a driving wheel, a first control unit that controls the transmission unit, a first source that inputs energy to the transmission unit, a second source that inputs energy to the transmission unit, a second control unit that controls the first source, and a third control unit that controls the second source, wherein when the first control unit fails, the second control unit or the third control unit controls the transmission unit.

Abstract: An agricultural work machine includes a geographic position sensor that detects a geographic location of the agricultural work machine. An in-situ sensor detects a value of a dynamic response characteristic of the agricultural work machine corresponding to the geographic location. A predictive model generator generates a predictive model that models a relationship between the terrain feature characteristic and the dynamic response characteristic based on a value of the terrain feature characteristic in a prior information map at the geographic location and a value of the dynamic response characteristic sensed by the in-situ sensor at the geographic location. A predictive map generator generates a functional predictive dynamic response map of the field, that maps predictive values of the dynamic response characteristic to the different geographic locations in the field, based on the values of the terrain feature characteristic in the prior information map and based on the predictive model.

Abstract: The subject disclosure relates to features that improve safety for autonomous vehicle (AV) driving maneuvers. In some aspects, a process of the disclosed technology includes steps for detecting an unprotected maneuver, navigating an AV into an intersection, and detecting a wheel safety angle relative to the intersection. In some aspects, the process further includes steps for automatically adjusting a wheel angle of the AV based on the wheel safety angle. Systems and machine-readable media are also provided.

Abstract: A high-definition map system receives sensor data from vehicles travelling along routes and combines the data to generate a high definition map for use in driving vehicles, for example, for guiding autonomous vehicles. A pose graph is built from the collected data, each pose representing location and orientation of a vehicle. The pose graph is optimized to minimize constraints between poses. Points associated with surface are assigned a confidence measure determined using a measure of hardness/softness of the surface. A machine-learning-based result filter detects bad alignment results and prevents them from being entered in the subsequent global pose optimization. The alignment framework is parallelizable for execution using a parallel/distributed architecture. Alignment hot spots are detected for further verification and improvement. The system supports incremental updates, thereby allowing refinements of sub-graphs for incrementally improving the high-definition map for keeping it up to date.

Abstract: A vehicular control system for controlling a vehicle includes a vehicle control, an acceleration sensor and a camera. The vehicle control includes an image processor for processing image data captured by the camera as the vehicle is driven along a route by a driver of the vehicle. The vehicle control detects traffic and road topography and determines acceleration of the vehicle as the vehicle is driven along the route by the driver. The vehicle control learns the route during multiple repetitive drives of the route by the driver of the vehicle. The vehicle control increases a confidence level of the learned route during multiple repetitive drives of the route by the vehicle. When the confidence level exceeds a threshold value, the vehicle control is operable to at least semi-autonomously control the vehicle to drive the vehicle along the route.

Abstract: The automatic driving assist system includes a traveling information acquirer that acquires vehicle width information, passing date and time, and position information when passing the measurement point, on preceding vehicles, from the preceding vehicle passing through the measurement point for each measurement, a traveling environment information acquirer that acquires traveling environment information at each measurement point, a calculator that acquires a travelable width at the measurement point based on information of the preceding vehicles and the traveling environment information, and a determiner that determines whether the own vehicle can travel to pass through the measurement point by automatic driving by comparing the travelable width with an own-vehicle travelable width.

Abstract: A vehicle control system includes a traveling environment detector configured to detect a traveling environment in a traveling direction of a vehicle, an acceleration state detector configured to detect an acceleration state due to a driver's operation, a driver state monitor configured to monitor a state of a driver based on a captured driver's image and detect an expression centered on the driver's face, an expression sudden change determinator configured to determine a sudden change in the driver's expression based on a detection result by the driver state monitor, an acceleration suppressor configured to suppress acceleration of the vehicle when the traveling environment detector detects no object for which collision avoidance is required in the traveling direction of the vehicle and the expression sudden change determinator determines that the driver's expression has suddenly changed immediately after the acceleration state detector detects the rapid acceleration due to the driver's operation.

Abstract: This document describes techniques and systems for selecting a parking space using a probabilistic approach. An example system includes a processor that can determine whether multiple parking spaces are available in proximity to a host vehicle using sensor data. Parking-space characteristics (e.g., a width, entry turning radius, and longitudinal distance to the parking space) of each available parking space are determined using the sensor data. The processor can then choose a selected parking space among the multiple parking spaces based on the parking-space characteristics. The processor or another processor can then control the host vehicle to park in the selected parking space using an assisted-driving or autonomous-driving system. In this way, the described system can select and navigate to a parking space using a probabilistic approach. The processor can choose the parking space and parking maneuver based on programmable and customizable parking-space characteristics in some implementations.

Abstract: In an onboard processing device, a parking path when a vehicle, which is a target vehicle, enters a parking place and a parking map including the parking place are obtained by an information obtaining unit, a peripheral environment of the vehicle is detected by a periphery detection unit, a vehicle position on the parking map is estimated by a vehicle position estimation unit, and a drive-out path when the vehicle is driven out from the parking place is set based on the estimated vehicle position, the parking path, and the detected peripheral environment by a path setting unit.