Abstract: Micro-weather risk mapping for very low-level aerial vehicles includes receiving data indicating a first geographic area and obtaining meteorologic data for a second geographic area. The first geographic area is smaller than and entirely bounded by the second geographic area. Mapping includes determining topographic parameters associated with the first geographic area. Mapping includes performing a comparison of the topographic parameters associated with the first geographic area to topographic parameters associated with a plurality of predetermined micro-weather models. Mapping includes selecting a micro-weather model from among the plurality of predetermined micro-weather models based on the comparison. Mapping includes determining, based on the meteorologic data for the second geographic area and the micro-weather model, risk data indicative of risk of particular meteorological conditions in the first geographic area.

Abstract: A method of navigating a plurality of vehicles along a roadway includes, at a first vehicle, navigating along a section of a roadway by following a first moving position-target, the first moving position-target determined in accordance with a first tracking function defining position along the section of the roadway as a function of time, and at a second vehicle, navigating along the section of the roadway by following a second moving position-target, the second moving position-target determined in accordance with a second tracking function defining position along the section of the roadway as a function of time. A distance between the first vehicle and the second vehicle may change as the first vehicle and the second vehicle navigate along the section of the roadway.

Abstract: A vehicle includes a level difference detector and a running controller. The level difference detector is configured to detect a level difference. The running controller is configured to perform in parallel level-difference override suppression control to suppress erroneous start for override of the level difference and level-difference override support control to support override of the level difference.

Abstract: A hybrid dump truck for surface mining, comprising a cyber-physical system including a sensing system and a control system, and a driving unit for performing autonomous driving of the dump truck along a travel path using at least the sensory data of the sensing system, wherein the closed cycle path is determined based on topographical data, wherein the control system is configured to control a cyclic energy level of the electric energy storage unit, wherein rates of change of power during autonomous or semi-autonomous driving of the hybrid dump truck from a predetermined reference point of the closed cycle path along said closed cycle path are controlled based on a desired velocity such as to reduce a difference in energy levels of the electric energy storage unit at the reference point of the closed cycle path.

Abstract: Provided are a safety performance evaluation apparatus, a safety performance evaluation method, an information processing apparatus, and an information processing method, which enable evaluation of safety performance of a driving assistance processing unit. The safety performance evaluation apparatus includes: an acquisition unit that acquires information regarding a driving assistance function of a mobile object; and an evaluation unit that evaluates safety performance of the driving assistance function of the mobile object on the basis of the acquired information.

Abstract: A parking assistance device includes a blind spot area calculation unit, a parking position determination unit, and a parking assistance unit. The blind spot area calculation unit is configured to calculate a size of a blind spot area of a subject vehicle created when the subject vehicle is parked at a specific position in a parking space scheduled for the subject vehicle. The parking position determination unit is configured to determine, as a parking position, the specific position where a predetermined condition related to the size of the blind spot area is satisfied. The parking assistance unit is configured to assist parking of the subject vehicle at the determined parking position.

Abstract: A control and navigation device for an autonomously moving system, which includes: a sensor device, configured to acquire sensor data, and a LiDAR sensor installation, which is configured for 360-degree acquisition; a fisheye camera installation, configured for 360-degree acquisition; and a radar sensor installation, configured for 360-degree acquisition; a data processing installation with an AI-based software application, configured to determine control signals for purposes of navigating an autonomously moving system; and a data communication interface, connected to the data processing installation, and is configured to provide the control signals. The sensor device, the data processing installation, and the data communication interface are arranged at an assembly component to assemble, in a detachable manner, the sensor device, the data processing installation, and the data communication interface together as a common module. Furthermore, an autonomously moving system is provided.

Abstract: A method for determining the payload mass resting on a wheel of a vehicle is disclosed. The method involves using a level sensor system, in a time period in which the vehicle is moved, a time series of measured values is detected, which each indicate the vertical position of the vehicle body in relation to the wheel. In the method, a model is provided for the temporal development of the vertical position under the influence of the gravitational force of vehicle body and payload, an elastic suspension between the vehicle body and the wheel of the vehicle, and a damping of the vertical relative movement between the vehicle body and the wheel of the vehicle. The model is parameterized at least using the sought payload mass. The wheel of the vehicle and the connection of the wheel to the roadway are assumed to be rigid.

Abstract: A technique for assessing a vehicle condition is provided that determines whether damage has occurred to the vehicle using electrical property data acquired by one or more electrical property detection systems disposed on one or more surfaces of the vehicles. The electrical property detection system include a conductive polymer material that changes in response to chemical deformations and/or mechanical deformations in the conductive polymer material, which may result from objects and/or other vehicles damaging the conductive polymer material. Based on the electrical property data, a control system may generate a damage assessment output, such as an alert for a vehicle owner.

Abstract: An obstruction avoidance system may include a agronomy vehicle, at least one sensor configured to output signals serving as a basis for a three-dimensional (3D) point cloud and to output signals corresponding to a two-dimensional (2D) image, and instructions to direct a processor to capture a particular 2D image and to obtain signals serving as a basis for a particular 3D point cloud; identify an obstruction candidate in the particular 2d image; correlate the obstruction candidate to a portion of the particular 3D point cloud to determine a value for a parameter of the obstruction candidate; classify the obstruction candidate as an obstruction based upon the parameter; and output control signals to alter a state of the agronomy vehicle in response to the obstruction candidate being classified as an obstruction.

Abstract: A vehicle control apparatus starts driving trouble tackling control designed to decelerate and stop an own vehicle when it is determined that a driver is in a driving trouble state where the driver has trouble driving the own vehicle, then start a deceleration process at a predetermined timing as a process of driving trouble tackling control, and then start a hazard lighting process at a predetermined timing as another process of driving trouble tackling control. The vehicle control apparatus stops driving trouble tackling control when a hazard switch is operated during the performance of the hazard lighting process, and starts the hazard lighting process without stopping the driving trouble tackling control when the hazard switch is operated between a timing when it is determined that the driver is in the driving trouble state and a timing when the hazard lighting process is started.

Abstract: Various control systems and methods for a working machine such as a compactor are disclosed. The control system can include any one or combination of components including a controller in communication with at least a steering system and a position sensor. The controller can be configured to: receive position data from the position sensor including during operator implemented steering of the compactor, save the position data to a memory, determine from the position data saved in the memory a possible intent by an operator to create a compaction area, generate a prompt on an operator interface to confirm an actual intent of the operator, and generate a compaction plan for autonomously steering the compactor to compact in the compaction area. The compaction plan can be based at least partially upon the operator implemented steering of the compactor. The controller can implement the compaction plan via autonomous steering.

Abstract: The present invention provides a system and method for identifying, tagging and reporting hazardous drivers in the vicinity of a host vehicle. A system comprises a sensor array on the host vehicle for detecting one or more adjacent vehicles in a vicinity of the host vehicle, a host display inside the host vehicle visible to the occupant of the host vehicle, and at least one adjacent vehicle display inside the one or more an adjacent vehicles visible to at least one adjacent vehicle occupant of the one or more adjacent vehicles. A server electronically coupled to the sensor array and the host display is configured to facilitate identification and tagging.

Abstract: The technology relates to autonomous vehicles for transporting cargo and/or people between locations. Distributed sensor arrangements may not be suitable for vehicles such as large trucks, busses or construction vehicles. Side view mirror assemblies are provided that include a sensor suite of different types of sensors, including LIDAR, radar, cameras, etc. Each side assembly is rigidly secured to the vehicle by a mounting element. The sensors within the assembly may be aligned or arranged relative to a common axis or physical point of the housing. This enables self-referenced calibration of all sensors in the housing. Vehicle-level calibration can also be performed between the sensors on the left and right sides of the vehicle. Each side view mirror assembly may include a conduit that provides one or more of power, data and cooling to the sensors in the housing.

Abstract: The present invention provides a vehicle control device and a control method therefor. A vehicle control device according to one embodiment of the present invention comprises: an interface unit communicatively connected to a display unit provided in a vehicle; and a processor for controlling the display unit provided in the vehicle through the interface unit, wherein the processor receives destination information through the interface unit, acquires, from map information, spatial coordinates of a building corresponding to the destination information, and controls, on the basis of the spatial coordinates of the building corresponding to the destination information, the display unit so that a graphic object related to the destination information overlaps with the building and is displayed.

Abstract: The present disclosure discloses a method, apparatus, medium, and device for vehicle automatic navigation control.

Abstract: A vehicle system includes a fuel cell system, a battery, a drive device that operates with power, a load different from the drive device, a positional information acquisition unit, a traveling route setting unit, and a control device configured to control power to be supplied to the load from the fuel cell system and the battery based on positional information acquired by the positional information acquisition unit and a traveling route set by the traveling route setting unit.

Abstract: The technology involves communicating the reachability status associated with an autonomous vehicle to a user such as a rider within the vehicle, a person awaiting pickup, or a customer that scheduled a package deliver. Reachability information about pickup and/or drop off locations is presentable via an app on a user device, which helps set expectations with customers about where the vehicle is most likely to be able to perform a pickup and/or drop off. This may include indicating how much variance there may be based on current congestion, parking or idling regulations, or weather conditions. The reachability information may be presented via one or more visualization tools to indicate the uncertainty and/or likely final location. Presenting such contextual information may be done based on real time information, and the presentation may be updated as needed. Historical information about the location may also be used to lower the level of uncertainty.

Abstract: An on-board navigation system for an unmanned aircraft system (UAS) operating in an unknown environment. A point-cloud sensor system generates point cloud data representing the unknown environment. An on-board processing system processes the point cloud data to generate both a 2-D occupancy grid and a 3-D voxel map, with the 2-D occupancy grid having cells with known (seen) and unknown data. Additional processing determines an amount of known-to-unknown (transitional) data in each cell, thereby determining unexplored regions. A cost is assigned to each unexplored region, based at least in part on the amount of transitional data in cells of the region. The unexplored regions are then sorted based on their costs, thereby determining an optimal region to explore. The 3-D voxel map is used to find a safe area within the optimal region where the UAS may fly. A flight path to the optimal region is then calculated.

Abstract: A robot cleaner includes a driving device, a sensor, a memory, and a processor. The processor controls the driving device to drive the robot cleaner at a space and generates generate a map of a space based on sensor data obtained while the robot cleaner driving in the space. The map is stored in the memory. The processor divides the space on the generated map into a plurality of rooms and recognizes an object and a position of the recognized object in the space on the generated map based on the information obtained through the sensor. The processor stores information about the recognized object and the position of the recognized object on the map, and generates a name of each of the plurality of rooms based on information about the recognized object positioned in each of the plurality of rooms.