Abstract: A damper control system includes: a lane module configured to identify boundaries of a present lane of a vehicle in an image of a road in front of the vehicle captured using a forward facing camera; an oil module configured to, from the image, determine whether an area of oil is present on the road between the boundaries of the present lane of the vehicle; and a damping module configured to, when the area of oil is present on the road between the boundaries of the present lane of the vehicle, selectively adjust damping coefficients of adjustable dampers of the vehicle before the vehicle reaches the area of oil on the road.

Abstract: A system provides descriptor-based feature matching during terrain relative navigation (TRN). A scale and orientation (SO) module acquires a source image, image and slope pixel windows, and ring mask. The SO module combines corresponding pixels from the image pixel window and the slope pixel window to generate intermediate values, accumulates the intermediate values into ring accumulators, sums the accumulated values to generate a final ring value, and determines an orientation stability measure, and final scale and orientation values. An extract descriptors (ED) module acquires the source image, the image and slope pixel windows, final scale and orientation values, sector values, and a rink mask value. The ED module identifies pixels of interest, reorients the sector values. combines corresponding pixels from the image pixel window and the slope pixel window, accumulates and normalizes the intermediate values, and generates an image feature descriptor per coordinate.

Abstract: A navigation method for a disinfection robot includes: obtaining an initial map within a field of view of the robot; generating a disinfection grid having multiple disinfection squares on the initial map, and determining multiple disinfecting consideration points in the disinfection squares; determining a disinfection order of disinfecting targets corresponding to the disinfection squares according to distances between the robot after the robot completes disinfection of one of the targets corresponding to one of the disinfection squares and to-be-disinfected ones of the disinfection squares; according to distances between the position and the disinfecting consideration points in to-be-disinfected ones of the disinfection squares, combined with priority levels of the disinfecting consideration points in to-be-disinfected ones of the disinfection squares, determining disinfecting planning points in the disinfection squares; and performing disinfection to the targets corresponding to the disinfection squares acc

Abstract: An electronic control unit includes: a target information acquiring section that acquires information about a target around a user's vehicle; a storage section that stores management information related to at least either an entrance position or exit position of the target in a predetermined subject area on a basis of the information about the target acquired by the target information acquiring section; and a driving trajectory planning section that plans a driving trajectory of the user's vehicle on a basis of the management information stored in the storage section.

Abstract: The present invention relates to a system and method for use in navigating a vehicle within an environment, and in one particular example, to a system and method for navigation planning in an unstructured environment including unobservable features, such as negative obstacles and/or occluded regions.

Abstract: An authentication system for a voice controlled autonomous driving system of a vehicle includes a plurality of perception sensors for collecting perception data indicative of an environment surrounding the vehicle and one or more controllers in electronic communication with one or more autonomous driving controllers of the voice controlled autonomous driving system and the plurality of perception sensors. The voice controlled autonomous driving system determines the trajectory of the vehicle based on a voice command generated by an occupant of the vehicle. The one or more controllers execute instructions to calculate a credibility score of the occupant that quantifies a reliability of one or more voice-based commands generated by the occupant. In response to determining an overall credibility score of the occupant is less than the threshold access score, the one or more controllers adjust an access level of the voice controlled autonomous driving system for the occupant.

Abstract: A device includes a memory configured to store a first position estimate of a first vehicle. The device also includes a receiver configured to receive a second position estimate of a second vehicle. The device further includes a sensor configured to generate sensor data indicating a first relative position estimate of the first vehicle relative to the second vehicle. The device also includes one or more processors configured to determine, based on a comparison of the first position estimate and the second position estimate, a second relative position estimate of the first vehicle relative to the second vehicle. The one or more processors are also configured to determine whether the first position estimate is reliable based at least in part on determining whether the first relative position estimate matches the second relative position estimate.

Abstract: Systems and methods are disclosed for sending vehicle information and health data over a wireless network. An example method may include receiving, from an on-board diagnostic (OBD) device associated with a vehicle and over a LoRaWAN network, a first message including first data, wherein the first data is a first category of data received by the OBD device from the vehicle. The example method may also include receiving, from the OBD device and over the LoRaWAN network, a second message including second data, wherein the second data is a second category of data received by the OBD device from the vehicle.

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: 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: 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 and methods for collision imminent detection are provided. A method includes collecting sensor data generated by one or more sensors of a vehicle; detecting, by a fallback control system of the vehicle based on the sensor data, an imminent collision between the vehicle and an object in an environment of the vehicle using a first process different from a second process of a primary control system of the vehicle, wherein the first process and the second process are associated with at least one of a perception or a prediction; and transmitting, by the fallback control system to the primary control system, an indication of the detected imminent collision.

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.

Abstract: A system and method compute a transit time for travel of a vehicle from a first site to a second site. The system and method include determining a dwell time at the second site, computing an initial predicted transit estimated time of arrival of the vehicle based on the dwell time and the transit time, and updating the initial predicted transit estimated time of arrival based upon a user workflow.

Abstract: The disclosure relates to systems, methods and programs for maneuvering unmanned vehicles. More specifically, the disclosure relates to systems, methods and programs for controlling maneuverability of unmanned vehicles (ground, aerial and marine) by coupling vehicle controls with point of regard (PoR) in a 2D plane, translated to a continuously updating flight vector in a 3D space, based on 12 DOF head pose and/or hand gesture of a user.

Abstract: Techniques are disclosed for locating a user device in an indoor environment such as a building based at least on a building topology model using one or more Internet of Things (IoT) devices. Certain aspects of the techniques include detecting a presence of a user device in communication with an IoT device in a building, wherein the IoT device is associated with device attributes. The building is identified based at least on a building topology model that is associated with the building and the device attributes. The location of the IoT device is determined based at least on the building topology model. The user device is located relative to the location of the IoT device.

Abstract: Techniques for verifying a reliability of map data are discussed herein. In some examples, map data can be used by a vehicle, such as an autonomous vehicle, to traverse an environment. Sensor data (e.g., image data, lidar data, etc.) can be received from a sensor associated with a vehicle and may be used to generate an estimated map and confidence values associated with the estimated map. When the sensor data is image data, images data from multiple perspectives or different time instances may be combined to generate the estimated map. The estimated map may be compared to a stored map or to a proposed vehicle trajectory or corridor to determine a reliability of the stored map data.

Abstract: A vehicle control method and apparatus, a device and a computer storage medium are disclosed, which relates to the technical fields of autonomous driving and intelligent transportation. A specific implementation solution involves: determining vehicles in a preset geo-fencing region; determining a vehicle weight of each said vehicles according to a vehicle type and a waiting duration of each said vehicles; estimating, according to the vehicle weights of the vehicles in each of lanes in the geo-fencing region and positions of the vehicles in each said lanes, a duration to be waited in each said lanes; and generating a control instruction for each said vehicles according to the respective durations to be waited in each said lanes and the respective positions of the vehicles in each said lanes, the control instruction including a state instruction and/or a target speed instruction.

Abstract: An electronic device is provided. The electronic device includes a management apparatus for providing a route in a wireless communication system that includes: at least one transceiver; and at least one processor operatively connected to the at least one transceiver, wherein: at least one processor receives service information related to a service, receives cell information related to a first cell and second cells provided by a first cellular network and a second cellular network, respectively, and provides the electronic device with a service route which includes at least one second cell among the second cells and is determined on the basis of the service information and the cell information; and the service is provided by the at least one second cell.