Abstract: Methods and systems are provided that include one or more sensors configured to obtain sensor data pertaining to both a driver of a vehicle and an environment surrounding the vehicle; and a processor that is coupled to the one or more sensors and that is configured to at least facilitate determining, using the sensor data, when the driver is incapacitated; determining, using the sensor data, when a threat is detected for the vehicle; and taking action to avoid the threat when the driver is incapacitated and the threat is detected, via instructions provided by the processor.

Abstract: A collision avoidance system includes a periphery monitoring system which detects vehicles in proximity to a subject vehicle by use of a sensor, an approaching vehicle notifying system which communicates with another vehicle in proximity to the subject vehicle in vehicle-to-vehicle communication, and a detected vehicle comparison/determination system which is connected to the periphery monitoring system and the approaching vehicle notifying system, determines common vehicles detected by both the periphery monitoring system and the approaching vehicle notifying system, and controls the periphery monitoring system and the approaching vehicle notifying system.

Abstract: Techniques are described for providing a hands-off steering wheel detection warning. An example method can include a vehicle computer determining a real-time level of fatigue of a driver of an autonomous vehicle. The vehicle computer can determine an operating parameter associated with an environment in which the autonomous vehicle is traveling. The vehicle computer can generate, using a machine learning model, a predicted driving pattern of a second vehicle traveling in the environment. The vehicle computer can determine a time interval for providing a hands-off steering wheel detection warning based at least in part on the real-time level of fatigue of the driver, the operating parameter, and the predicted driving pattern of the second vehicle. The vehicle computer can identify a final time interval for providing a hands-off steering wheel detection warning. The vehicle computer can output the hands-off steering wheel detection warning after the final time interval has elapsed.

Abstract: Systems, methods, and computer-readable media are provided for maintaining cleanliness of an autonomous vehicle. In some examples, an autonomous vehicle fleet management device may receive cleanliness data corresponding to at least one autonomous vehicle. In some aspects, the autonomous vehicle fleet management device may determine, based on the cleanliness data, one or more parameters corresponding to at least one cleanliness issue associated with the at least one autonomous vehicle. In some cases, a remediation plan for the at least one cleanliness issue may be determined based on the one or more parameters. In some instances, at least one driving instruction may be sent to the at least one autonomous vehicle that is based on the remediation plan.

Abstract: Influence of risks, such as sound and light generated by the host device, on surroundings is reduced. An information processing device (100) according to an embodiment includes a planning unit (105) configured to plan behavior executed by a drive unit (107) based on an influence target existing in a predetermined area and affected by a risk propagating in space.

Abstract: A device for proposing autonomous driving includes a processor configured to identify an autonomously travelable section in which a vehicle is capable of traveling under autonomous driving control, make a proposal for travel under autonomous driving control to a driver of the vehicle via a notification device when a proposal determination value corresponding to the length of the identified autonomously travelable section satisfies a first proposal criterion, stop proposing travel through the autonomously travelable section under autonomous driving control to the driver when the proposal determination value corresponding to the length of the identified autonomously travelable section does not satisfy the first proposal criterion, and add a predetermined addition value to the proposal determination value corresponding to the length of the identified autonomously travelable section when an action of the driver to consent to the proposal for travel under autonomous driving control to the driver is not detected.

Abstract: This invention provides a vehicle control device for controlling a vehicle, which comprises a first detection unit configured to detect an out-of-lane region outside a lane in which the vehicle is traveling; a second detection unit configured to detect an obstacle; and a determination unit configured to determine that performing steering control in the out-of-lane region is approved by a driver when the vehicle enters the out-of-lane region in response to a steering operation by the driver in a case where the second detection unit detects the obstacle, the first detection unit detects the out-of-lane region, and the vehicle and the obstacle have a predetermined relationship.

Abstract: A vehicle agent device receives a captured image and vehicle information from an on-board unit, identifies an occupant from the captured image, specifies attributes of the occupant it identified, searches for vehicle functions corresponding to the attributes it specified, and sends, as description information to an on-board unit, a moving image that introduces the vehicle functions.

Abstract: A computer-implemented method comprises sensing an environment of the ego-agent that includes at least one other agent. The method predicts possible behaviors of the at least one other agent based on the sensed environment, and plans trajectories of the ego-agent for each possible behavior of the at least one other agent to generate a set of planned trajectories. The method proceeds with determining an actual trajectory of the ego-agent, and comparing the determined actual trajectory of the ego-agent with each of the planned trajectories of the ego-agent and determining a planned trajectory with a largest similarity to the actual trajectory of the ego-agent. Subsequently, a perceived situation as perceived by the ego-agent based on a particular predicted possible behavior of the predicted possible behaviors corresponding to the planned trajectory with the largest similarity is determined. The method executes an action in an assistance system based on the determined perceived situation.

Abstract: Techniques for determining environmental data of an environment associated with a vehicle are discussed herein. The vehicle can use the data to determine a vehicle configuration data, a trajectory for the vehicle to traverse, a route to a destination, or orientation for ingress/egress. The vehicle can determine control data based on the vehicle configuration data, the trajectory, or the route. The vehicle configuration data may be associated with a setting of a suspension component, a speed, or other component. The trajectory may be biased based on a source of the wind. The route may be selected from a first candidate route and a second candidate route using a first wind score associated with the first candidate route and a second score associated with the second candidate route. The vehicle can use a sensor, such as a wind sensor, to capture or otherwise determine the wind data.

Abstract: A vehicle controller includes a processor configured to determine whether to transfer driving control of a vehicle under autonomous driving control to a driver, notify the driver of a transition demand via a notification device in the case where driving control will be transferred to the driver, execute deceleration control of the vehicle at predetermined timing after notification timing of the transition demand, and continue deceleration control of the vehicle even after a predetermined period from the notification timing in the case where the speed of the vehicle decreases to a predetermined speed threshold or less within the predetermined period and where operation by the driver to take over driving is not detected.

Abstract: This document describes techniques and systems related to tracking different sections of articulated vehicles. A vehicle uses a radar system that can discern between unarticulated vehicles and articulated vehicles, which by definition have multiple sections that can pivot in different directions for turning or closely following a curve. The radar system obtains detections indicative of another vehicle traveling nearby. When the detections indicate the other vehicle is articulated, the radar system tracks each identifiable section, rather than tracking all the sections together. A bounding box is generated for each identifiable section; the radar system separately and concurrently monitors a velocity of each bounding box. The multiple bounding boxes that are drawn enable the radar system to accurately track each connected section of the articulated vehicle, including to detect whether any movement occurs between two connected sections, for accurately localizing the vehicle when driving.

Abstract: A system for determining a geolocation of a mobile object movable through a terrain in a Global Navigation Satellite System (GNSS) signal attenuated environment is provided herein.

Abstract: Techniques for validating operation of vehicle systems using map data are described herein. The techniques may include receiving sensor data associated with an environment in which a vehicle is operating and generating estimated map data based at least in part on the sensor data. Additionally, stored map data may be received and compared with the estimated map data. If it is determined that an inconsistency exists between the estimated map data and the stored map data, the techniques may include determining whether the inconsistency is attributable to an error associated with the stored map data, the sensor data, or a localization system of the vehicle. As such, one or more specific remedial actions may then be performed based at least in part on determining that the error is associated with at least one of the stored map data, the sensor data, or the localization system.

Abstract: Devices, systems, and methods are provided for indoor localization. A self-driving vehicle may detect a first fiducial marker located at a first location within a building, wherein the first fiducial marker comprises first fiducial marker information associated with the first location. The self-driving vehicle may retrieve the first fiducial marker information from the first fiducial marker. The self-driving vehicle may generate localization information of the self-driving vehicle based on the first fiducial marker information. The self-driving vehicle may utilize the localization information to transition to a second location within the building, wherein the second location comprises a second fiducial marker.

Abstract: Systems, methods, and computer-readable media are disclosed for determining obstacle data based on sensor data such as greyscale data and depth data. Based on the obstacle data navigation data may be determined and used by an autonomous vehicle to navigate an environment such as a warehouse or storage facility. The obstacle data may be determined by determining three-dimensional representations of the greyscale data and the depth data and segmented and combining or fusing the three-dimensional representations of the greyscale data and the depth data. The system used to determine the obstacle data may be trained to avoid false obstructions and omitted obstructions.

Abstract: In one embodiment, a method includes receiving sensor data associated with an object external to a vehicle. The sensor data includes a sequence of data packets. Each data packet corresponds to a time frame in a sequence of time frames. The method includes determining a classification of the object based at least on the sensor data, determining that a particular data packet corresponding to a particular time frame in the sequence of time frames is corrupt or missing, generating a replacement data packet based on one or more data packets that correspond to one or more time frames adjacent to the particular time frame, generating a sequence of visual representations of the object corresponding to the sequence of time frames. At least one visual representation in the sequence of visual representations corresponding to the particular time frame is generated based on the replacement data packet.

Abstract: A method for controlling movement of an unmanned aerial vehicle (UAV) includes controlling one or more propulsion units of the UVA to cause the UAV to operate according to a first set of altitude restrictions; assessing, with aid of the one or more processors and based on one or more criteria, whether to control the UAV to operate according to a second set of altitude restrictions; and controlling the one or more propulsion units to cause the UAV to operate according to the second set of altitude restrictions in response to the one or more criteria being fulfilled according to an assessing result. The first set of altitude restrictions constrain an altitude of the UAV relative to a first reference altitude. The second set of altitude restrictions constrain the altitude of the UAV relative to a second reference altitude.

Abstract: This invention provides a vehicle control device for controlling a vehicle, which comprises a first detection unit configured to detect an out-of-lane region outside a lane in which the vehicle is traveling; a second detection unit configured to detect an obstacle; and a determination unit configured to determine that performing steering control in the out-of-lane region is approved by a driver when the vehicle enters the out-of-lane region in response to a steering operation by the driver in a case where the second detection unit detects the obstacle, the first detection unit detects the out-of-lane region, and the vehicle and the obstacle have a predetermined relationship.

Abstract: The present application discloses a vehicle control and task processing method and apparatus, a computing device and a system. The vehicle control method comprises: acquiring a driving control task to be executed and target parameters associated with the driving control task; and executing a corresponding algorithm based on the target parameters to enable a driving control system to complete the driving control task. Through the above-mentioned technical solution, accurate vehicle parameters are acquired according to the driving control task, thereby improving the reliability of driving control.