Abstract: Systems, methods, and computer program products for autonomous car-like ground vehicle guidance and trajectory tracking control. A multi-loop 3DOF trajectory linearization controller provides guidance to a vehicle having nonlinear rigid-body dynamics with nonlinear tire traction force, nonlinear drag forces and actuator dynamics. The controller may be based on a closed-loop PD-eigenvalue assignment and a singular perturbation (time-scale separation) theory for exponential stability, and controls the longitudinal velocity and steering angle simultaneously to follow a feasible guidance trajectory. A line-of-sight based pure-pursuit guidance controller may generate a 3DOF spatial trajectory that is provided to the 3DOF controller to enable target pursuit and path-following/trajectory-tracking. The resulting combination may provide a 3DOF motion control system with integrated simultaneous steering and speed control for automobile and car-like mobile robot target pursuit and trajectory-tracking.

Abstract: Systems and methods are disclosed for monitoring operations of an autonomous vehicle. For instance, a monitoring device receives sub-system data from one or more sub-systems of the autonomous vehicle. The device receives contextual data of the vehicle that comprises one or more situational circumstances of the vehicle during operation. The device receives control data from a control system of the vehicle and analyzes the sub-system data, the contextual data, and the control data to determine a control result. The device provides an assessment to a management system of the overall control status of the vehicle.

Abstract: Drone systems and method include, in an air traffic control system configured to manage Unmanned Aerial Vehicle (UAV) flight in a geographic region, communicating to one or more UAVs over one or more wireless networks; selecting a delivery technique for a UAV to drop a package at a delivery location, the delivery technique being selected from a plurality of techniques including a technique of the UAV maneuvering to swing the package; and directing the UAV to deliver the package and communicating delivery instructions to the UAV, the delivery instructions including the delivery technique selected.

Abstract: Provided are methods for controlling loading/unloading of a material (from a load-delivering unit to a load-receiving unit, wherein at least one of the load-delivering unit and the load-receiving unit is a working machine vehicle configured to transport a load of material from a first location to a second location, and wherein at least the load-delivering unit is provided with a control unit configured to control operation of the load-delivering unit. Methods include receiving a first signal indicative of the material associated with the load-delivering unit; receiving a second signal indicative of the material intended to be received by the load-receiving unit; and comparing material information related to the first signal with material information related to the second signal.

Abstract: An energy consumption predicting device includes: an acquisition unit acquiring a parameter correlated with at least one of a vehicle speed when a vehicle traveled on a route from a first point to a second point on which a vehicle traveling using only a power source consuming an energy source supplied from outside of the vehicle and stored therein is able to travel, a different vehicle speed when a different vehicle traveled on the route, an output of the power source when the vehicle traveled on the route, and an output of a different power source when the different vehicle traveling using only the same type of different power source as the power source traveled on the route; and a calculation unit calculating a predicted consumption of the energy source which is predicted when the vehicle travels on the route from the first point to the second point.

Abstract: A vehicle control apparatus includes: a road recognizer that recognizes a road form around a vehicle; a second-vehicle recognizer that recognizes a state of another vehicle around the vehicle; and a driving controller that allows the vehicle to travel by controlling one or both of steering and acceleration/deceleration of the vehicle and that prevents, upon passing of the vehicle through an intersection, passing of the vehicle through the intersection based on a presence of the other vehicle recognized by the second-vehicle recognizer, wherein in a case where the driving controller recognizes, by the road recognizer, that a plurality of lanes are present in a road of a right/left turn destination of the vehicle and recognizes, by the second-vehicle recognizer, that the other vehicle, which was an opposing vehicle approaching from a direction opposing the vehicle, has entered a lane on a rear side in a view from the vehicle among the plurality of lanes in the road of the right/left turn destination, the drivin

Abstract: A vehicle is equipped with a docking station for a driver's smart device. The smart device displays engine related and other information to the driver while operating the vehicle. The smart device provides a supplementary screen to the screen installed in the vehicle at manufacture, or acts as an alternative to having a screen installed at manufacture. The docked smart device replaces one or more of the instruments normally present in a vehicle dashboard or motorcycle instrument cluster. The smart device also controls operation of the vehicle.

Abstract: A method comprises obtaining one or more parameters of an autonomous vehicle, the parameters including any of a position, path, and/or speed of the autonomous vehicle. The method further includes identifying, based on the one or more parameters of the autonomous vehicle, a region of interest from a plurality of regions surrounding the autonomous vehicle. The method further includes controlling, based on the region of interest, one or more sensors mounted on a surface of the autonomous vehicle to capture sensor data of the region of interest and not capture sensor data from the one or more other regions of the plurality of regions surrounding the autonomous vehicle. The method further includes providing the captured sensor data to a processor, the processor being capable of facilitating, based on the captured sensor data of the region of interest, one or more autonomous vehicle driving actions.

Abstract: A swerve assist to assist the driver of a transportation vehicle during an avoidance maneuver so that a collision with an obstacle is avoided. An additional steering torque for amplifying a current steering torque is applied when an avoidance maneuver of the transportation vehicle is detected. A single-wheel braking of the transportation vehicle is actuated to increase a transverse offset of the transportation vehicle.

Abstract: A controller can include an electronic processor unit configured to control the driving direction of a vehicle within a lane based on a first trajectory. The controller can be operable to receive a user input for directing the vehicle along a second trajectory that is different from the first trajectory, determine third trajectory data by at least comparing data associated with the first trajectory to data associated with the second trajectory, and output a control signal for controlling, using the electronic processor unit, the driving direction of the vehicle. The control signal can be based at least on the third trajectory data.

Abstract: A construction machine for building or finishing a road, such as a road finisher, comprises at least a working equipment, a display unit and a plurality of sensors. Each sensor is adapted to measure a value of an operating parameter of the construction machine. The sensors are adapted to output data corresponding to the measured values to the display unit, and the display unit is adapted to output a representation of at least a part of the construction machine together with the measured values of the operating parameters.

Abstract: An agricultural work system for the optimization of operating parameters, with at least one agricultural work machine having a work unit for carrying out or supporting agricultural work. The agricultural work machine has a driver assistance system for detecting, processing and outputting data relating to an agricultural work order. The driver assistance system is configured to detect a plurality of operating parameters and to allow the operator to rank the detected operating parameters or operating parameter sets with a plurality of different detected operating parameters. Individual ranked operating parameters or sets of operating parameters or all of the ranked operating parameters or sets of operating parameters are retrievably filed in a data pool, and the operating parameters are submitted based on ranking to an algorithm for generating optimized operating parameters for adjustment of the agricultural work machine and/or of the at least one work unit.

Abstract: When an EMV performs an action comprising moving a tool of the EMV through soil or other material, the EMV can measure a current speed of the tool through the material and a current kinematic pressure exerted on the tool by the material. Using the measured current speed and kinematic pressure, the EMV system can use a machine learned model to determine one or more soil parameters of the material. The EMV can then make decisions based on the soil parameters, such as by selecting a tool speed for the EMV based on the determined soil parameters.

Abstract: An autonomous earth moving system can select an action for an earth moving vehicle (EMV) to autonomously perform using a tool (such as an excavator bucket). The system then generates a set of candidate tool paths, each illustrating a potential path for the tool to trace as the earth moving vehicle performs the action. In some cases, the system uses an online learning model iteratively trained to determine which candidate tool path best satisfies one or more metrics measuring the success of the action. The earth moving vehicle the executes the earth moving action using the selected tool path and measures the results of the action. In some implementations, the autonomous earth moving system updates the machine learning model based on the result of the executed action.

Abstract: A parking assist system includes: a control device configured to control a vehicle so as to move the vehicle autonomously from a current position to a target position; and an external environment sensor configured to detect an obstacle. During control of the vehicle to the target position, the control device is configured to recognize the obstacle present in a first area and a second area based on information from the external environment sensor. In a case where the control device recognizes the obstacle in the first area, the control device stops the vehicle, and in a case where the control device recognizes the obstacle in the second area and the obstacle in the second area is a moving object and/or a moving creature, the control device moves the vehicle in a decelerated state in which the vehicle is decelerated to a prescribed speed.

Abstract: Upon determining a first vehicle is moving on a two-way road in a first direction of travel in an only lane of the two-way road, vehicle sensor data is input to a first neural network that identifies a yield area along the two-way road via image segmentation. A second vehicle is detected traveling toward the first vehicle on the only lane of the two-way road. Then, upon determining the first vehicle is to yield to the second vehicle, one or more vehicle components are actuated to move the first vehicle to the yield area.

Abstract: A vehicle control apparatus includes a time-to-collision acquisition unit that acquires time to collision that is a time period until a time of collision of an own vehicle with a front obstacle, an overlap rate acquisition unit that acquires an overlap rate indicating a relative positional relationship between the own vehicle and the front obstacle in a lateral direction perpendicular to a traveling direction of the own vehicle, a determination unit that performs execution determination of automatic braking control of the own vehicle, on the basis of the time to collision and the overlap rate, and that, when the overlap rate is increasing by the front obstacle approaching the own vehicle in the lateral direction, determines start timing of the automatic braking control as earlier timing than when the overlap rate is not increasing, and an automatic controller that executes the automatic braking control at the start timing.

Abstract: A tractor trailer monitoring system includes a network having a server and a database; a first computing device; a monitoring platform to be accessible from the first computing device; a tractor trailer system, having a tractor unit; an air supply control system to control air supply to a brake system of the trailer, the air supply control system having a CPU to receive commands from the first computing device; the first computing device and monitoring platform are to receive an identifying code from a user to activate air supply to the brake system of the trailer.

Abstract: A passenger drone includes a processing device communicatively coupled to the flight components, cameras, radar, and wireless interfaces; and memory storing instructions that, when executed, cause the processing device to receive notifications from an air traffic control system via the one or more wireless interfaces, the notifications related to previously detected obstructions in a flight path associated with a flight plan of the passenger drone, wherein the previously detected obstructions include objects at or near ground level; monitor proximate airspace with at least one of the one or more cameras and radar; detect an obstruction based on monitoring the proximate airspace, wherein the detected obstruction includes one or more objects at or near ground level in the flight path; alter the flight plan, to be carried out by the flight components, if required, based on the detected obstruction.

Abstract: This description provides an autonomous or semi-autonomous excavation vehicle that is capable of navigating through a dig site and carrying an excavation routine using a system of sensors physically mounted to the excavation vehicle. The sensors collect one or more of spatial, imaging, measurement, and location data representing the status of the excavation vehicle and its surrounding environment. Based on the collected data, the excavation vehicle executes instructions to perform an excavation routine by excavating earth from a hole using an excavation tool positioned at a single location within the site. The excavation vehicle is also able to carry out numerous other tasks, such as checking the volume of excavated earth in an excavation tool, navigating the excavation vehicle over a distance while continuously excavating earth from a below surface depth, and preparing a digital terrain model of the site as part of a process for creating the excavation routine.