Abstract: Controlling maximum appliable positive and negative torque for a vehicle is provided. Vehicle data indictive of a driver torque request is received. Maximum appliable positive and negative torques for the vehicle are estimated. Responsive to the driver torque request being positive, the driver torque request is limited to the maximum appliable positive torque. Responsive to the driver torque request being negative, the driver torque request is limited to the maximum appliable negative torque.

Abstract: A system for automatically parking a commercial vehicle comprises a service brake system having at least one braking valve, a braking controller for controlling the service brake system, and an advanced driver assistance system (ADAS) controller. The ADAS controller communicates with the braking controller and requests activation of the service brakes of the commercial vehicle until the vehicle is stationary. The braking controller, in response to the ADAS controller requesting activation of the service brakes, determines the commercial vehicle should remain stationary and activates at least one braking valve to exhaust system pressure to mechanically park the vehicle.

Abstract: A method for controlling a motor vehicle (10) traveling on a roadway (12) in a current lane (14) is described, wherein the roadway (12) has at least one additional lane (16) that is adjacent to the current lane (14) of the motor vehicle (10). The method has the following steps: Multiple different driving maneuvers are generated and/or received. At least two driving maneuver classes that are defined based on at least one characteristic variable of the driving maneuvers are determined, wherein the driving maneuvers of various driving maneuver classes differ by at least one characteristic variable. The driving maneuvers are classified in one of the at least two driving maneuver classes. In addition, a control unit (30) for controlling a motor vehicle (10) is described.

Abstract: An approach is provided for automatically verifying a road closure report. The approach, for example, involves determining one or more features of probe data collected from a plurality of vehicles traveling on a connected set of road links of a closure link graph. The closure link graph, for instance, comprises a road link indicated by the road closure report, one or more upstream links from the road link, one or more downstream links from the road link, or a combination thereof. The approach also involves evaluating a closure probability of the road link indicated by the road closure report based on the one or more features. The road closure report is then automatically verified based on the closure probability.

Abstract: Method and systems for operating a work vehicle with a selectively interchangeable implement. Image data is captured by a camera (and/or other type of optical sensor) mounted on the work vehicle. The captured image data includes at least a portion of a first implement and the implement type of the first implement is identified by processing the captured image data. Operation information correspond to the identified implement type is accessed from a non-transitory computer-readable memory and an operation of the work vehicle is automatically adjusted based on the accessed operation information for the identified implement type. In some implementations, the implement type is determined by providing the captured image data as input to an artificial neural network and, in some implementations, the artificial neural network is configured to also output an indication of a current operating position of the implement based on the captured image data.

Abstract: The invention relates to a control System (2) for a motor vehicle (1), comprising a central vehicle Controller (3) for Controlling vehicle functions (4) and a plurality of driver assistance Systems (5). The driver assistance Systems (5) are set up to transmit a task key describing the particular assistance function thereof to the vehicle Controller (3) and to transmit a security key assigned to the particular assistance function to the vehicle Controller (3).

Abstract: A method of manufacturing an autonomous cart is provided. The method includes determining a mission type for the autonomous cart and determining a power system for powering the autonomous cart based on the mission type. The method further includes determining a drive system suitable for converting a power delivered by the power system into motive power suitable for moving the autonomous cart based on the power system and the mission type. The method further includes installing the power system onto a chassis of the autonomous cart and installing the drive system onto the chassis of the autonomous cart, wherein the autonomous cart comprises a control system configured to drive the autonomous cart autonomously via the power system and the drive system.

Abstract: A method for controlling autonomous driving in a vehicle capable of the autonomous driving may include collecting vehicle travel status information and system status information during the autonomous driving, sensing a failure based on the system status information, identifying normally controllable actuators when sensing the failure, determining a risk degree corresponding to the sensed failure based on the normally controllable actuator information and the vehicle travel status information, determining a safety state based on normally controllable actuator information and the risk degree, and determining a failure safety strategy corresponding to the safety state.

Abstract: A control system for navigating a marine vessel employs at least a first motor and a second motor. The control system is configured to communicate with the first and second motors. The control system is configured to receive a position measurement and an orientation measurement for the marine vessel. The control system is further configured to generate at least one control signal for the first motor based on the position measurement and at least one control signal for the second motor based on the orientation measurement.

Abstract: An ADS performs processing including setting an immobilization command to “Applied” when an autonomous state has been set to an autonomous mode, when an acceleration command has a value indicating deceleration, when an actual moving direction indicates a standstill state, and when a wheel lock request is issued, setting the acceleration command to V1, and setting the acceleration command to zero when an immobilization status has been set to “11”.

Abstract: A method for automated unloading of items from a container includes moving a nose ramp of an unloader under a base belt, which is positioned over a floor of the container. A stack of items are located in the container over the base belt. The method includes removing items from a bottom of the stack of items via an extraction conveyor of the unloader. The method also includes measuring a density of items transitioning onto the extraction conveyor from the base belt. The method further includes controlling an unloader advance speed relative to the container in dependence of the measured density of items transitioning onto the extraction conveyor. Thereby, a bulk flow of items having a substantially steady density is delivered by an output conveyor of the unloader positioned downstream of the extraction conveyor.

Abstract: Systems for automatically warning at least one nearby vehicle of a potential safety hazard in or near a roadway, including one or more sensors configured to detect a potential safety hazard in or near a roadway; a memory containing computer-readable instructions for generating a message including at least one of a location of the one or more sensors and a location of the potential safety hazard; a processor configured to read the computer-readable instructions from the memory and generate the message; and a transmitter configured to wirelessly transmit the message to at least one nearby vehicle. Systems for coordinating actions of a first vehicle and a second vehicle upon detection of a potential safety hazard in or near a roadway, including in part evaluating whether the actions conflict and, if so, requesting that the first vehicle execute alternative actions for avoiding or mitigating risk of collision. Corresponding methods are disclosed.

Abstract: Methods and systems for adjusting operating parameters of a machine in anticipation of a transition from a current operational state to a predicted subsequent operational state. An electronic controller receives a data stream indicative of actuator settings, sensor outputs, and/or operator control settings and applies a pattern detection AI that is configured to determine a current operational state of the machine based on patterns detected in the data stream. The controller then applies a reinforcement learning AI that is configured to produce as an output one or more target operating parameters based at least in part on a predicted subsequent operational state of the machine. The one or more target operating parameters are applied to the machine and at least one performance metric of the machine is monitored. The reinforcement learning Ai is retrained based at least in part on the monitored performance metric(s).

Abstract: An autonomous lawn mower includes removable batteries, one or more electric motors, a cutting blade, one or more wheels, an angle sensor, and a controller. The cutting blade is driven by one of the electric motors. The wheels are driven by one of the electric motors. The controller is configured to allow the lawn mower to perform a grass cutting function at a jobsite without human interaction. The controller is configured to determine whether a roll angle is greater than a first predefined amount using data from the angle sensor. In response to determining the roll angle is greater than the first predefined amount, the controller is configured to stop operation of one of the one or more electric motors configured to provide rotational drive power to the cutting blade.

Abstract: Systems and methods are directed to determining autonomous vehicle scenarios based on autonomous vehicle operation data. In one example, a computer-implemented method for determining operating scenarios for an autonomous vehicle includes obtaining, by a computing system comprising one or more computing devices, log data representing autonomous vehicle operations. The method further includes extracting, by the computing system, a plurality of attributes from the log data. The method further includes determining, by the computing system, one or more scenarios based on a combination of the attributes, wherein each scenario includes multiple scenario variations and each scenario variation comprises multiple features. The method further includes providing, by the computing system, the one or more scenarios for generating autonomous vehicle operation analytics.

Abstract: Various embodiments include methods and vehicles that may include determining whether to initiate a configuration change protocol to implement a configuration change for modifying the arrangement of the vehicle internal structure in response to a planned or predicted future operating mode, event or environment. Also, determining whether an occupancy status of the vehicle conflicts with an occupancy status allowed for in a configuration called for by a configuration change input or indication. Further, modifying an arrangement of the vehicle internal structure in accordance with the configuration change input or indication in response to determining that the occupancy status of the vehicle does not conflict with the occupancy status allowed for in the configuration called for by the configuration change.

Abstract: Embodiments of the present disclosure relate to the technical field of autonomous driving, and in particular to methods for updating an autonomous driving system, autonomous driving systems, and on-board apparatuses. In the embodiments of the present disclosure, the autonomous driving system, in a manual driving mode, senses the surrounding environment of a vehicle, performs vehicle positioning, and plans a path for autonomous driving for the vehicle. However, the autonomous driving system does not issue an instruction to control the driving of the vehicle. Instead, it compares the path with a path along which a driver drives the vehicle in the manual driving mode to update a planning and control algorithm of the autonomous driving system. As such, the updated autonomous driving system better caters to the driving habits of the driver and improves the driving experience for the driver without compromising the reliability of planning and decision-making of autonomous driving.

Abstract: A control apparatus includes a Wi-Fi communication module, a processor, a controller that controls a component of a vehicle, and a memory, wherein the memory stores at least one piece of position information corresponding to a position in the vehicle, and at least one registered pattern of a gesture, face, or shape, the Wi-Fi communication module transmits a transmission signal to the position corresponding to the at least one piece of position information by a Wi-Fi communication method at a preset frequency and receives a reflection signal reflected from an object in response to the transmission signal, the processor acquires an input pattern of a gesture, face, or shape of the object by analyzing the reflection signal, and retrieves a registered pattern matching the input pattern from the at least one registered pattern, and the controller controls the component according to an instruction corresponding to the retrieved registered pattern.

Abstract: An apparatus for controlling autonomous driving of a vehicle includes a processor to control autonomous driving, and a storage to store data and an algorithm to control the autonomous driving. The processor determines whether a target vehicle in front of a host vehicle in a travelling lane of the host vehicle is stopped, and performs a passing control when the target vehicle is stopped.

Abstract: The present invention relates to a system for determining the mass of a payload moved by a working device of a machine, comprising: a lifting-gear element that is movable along a path and is designed to move the working device; a sensor system that is designed to provide a plurality of machine-status signals which indicate a status of the machine; a force sensor system that is designed to provide a lifting-force signal that indicates a force on the lifting-gear element; and a control device that is designed: to use system parameters for load determination that originate from pre-configured CAD data, preferably CAD data that has been pre-configured at the factory, and/or from continuous calibration of system parameters; to carry out calibration using the pre-configured parameters as initialisation if unsatisfactory results are achieved; to carry out the calibration in an unloaded state, i.e.