Abstract: An exemplary method to determine an airspeed and an angle of attack of a propeller powered vehicle includes determining the power delivered to the propeller, the air density, a propeller power coefficient, an advance ratio for the propeller, and the airspeed using the advance ratio and determining the angle of attack using the airspeed.

Abstract: Among other things, techniques are described for operating an autonomous vehicle station. One technique involves receiving information indicating arrival of a vehicle at a station designated for a primary service. The technique further involves measuring, using at least one sensor located in the station, a first parameter associated with the vehicle. Also, the technique involves performing, based on the information and the first parameter, a first action to provide the primary service to the vehicle. Additionally, the technique involves determining, while performing the first action, a secondary service to provide to the vehicle.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, are described for implementing an unmanned aerial vehicle or drone with ducted fans. The drone includes a housing having a first surface and multiple ducts that each extend from the first surface to a second surface of the housing. The first surface is substantially flat. A respective fan assembly is installed in each of the ducts. The drone includes an internal cavity at a location intermediate two respective ducts and circuitry positioned in the internal cavity. The circuitry is operable to generate control signals used to operate the respective fan assemblies.

Abstract: Systems, methods, and autonomous vehicles for automated lane conflict estimation may obtain map data associated with a map of a geographic location including a roadway, determine, based on the map data, a relative lane geometry between a first lane segment and a second lane segment of a pair of overlapping lane segments; process, with a machine learning model, the relative lane geometry and a type of a traffic signal or sign associated with the pair of overlapping lane segments to generate a prediction of whether the first lane segment yields to the second lane segment for a given state of the traffic signal or sign; and use the prediction to at least one of generate a map including the lane segment associated with the prediction, facilitate at least one autonomous driving operation of an autonomous vehicle, or any combination thereof.

Abstract: One general aspect includes a system having a memory configured to include one or more executable instructions and a processor configured to execute the executable instructions, where the executable instructions enable the processor to estimate a rate of change of a hitch angle between a trailer and vehicle, the estimated rate of change of the hitch angle being based on a turn angle for a plurality of rear wheels of the vehicle as well as a speed of the vehicle.

Abstract: A computer-implemented method includes obtaining a weed map of a field including a crop, the weed map representing weed plant locations on the field, identifying, based at least in part on the weed map, weed seed locations that represent presence of weed seeds on the field, and generating a control signal for a pre-emergence weed mitigation operation based on the weed seed locations.

Abstract: An aerial vehicle including a body, a first ranging device, a second ranging device and a controller is provided. The first ranging device is disposed on the body and is configured to detect a first distance between the first ranging device and the reflector. The second ranging device is disposed on the body and is configured to detect a second distance between the second ranging device and the reflector. The controller is configured to obtain an included angle between a direction of the body and the reflector according to the first distance and the second distance.

Abstract: In one embodiment, a process is performed during controlling Autonomous Driving Vehicle (ADV). A confidence level associated with a sensed obstacle is determined. If the confidence level is below a confidence threshold, and a distance between the ADV and a potential point of contact with the sensed obstacle is below a distance threshold, then performance of a driving decision is delayed. Otherwise, the driving decision is performed to reduce risk of contact with the sensed obstacle.

Abstract: An object sensor test system includes a sensor and a test bench. The sensor includes a receiver configured to receive a simulated optical signal and a processing chain that includes a plurality of processing components configured to process at least one measurement signal generated in response to the simulated optical signal to generate processed test data. The sensor also includes a test interface configured to receive a control signal, and selectively extract processed test data at a selected output of the processing chain based on the control signal. The test bench is configured to transmit the control signal to the test interface, receive the processed test data from the sensor, compare the received processed test data with expected data to generate a comparison result, and determine that a segment of the processing chain is operating normally or abnormally based on the comparison result.

Abstract: A driver's vehicle sound perception method during the autonomous traveling of a driver sound control system applied to an autonomous vehicle is provided. The method includes determining a mobile device and Bluetooth earphones held by a driver within a cabin, and setting the driver position and face direction for the driver, a driver relative distance for the individual controller, and the sound pressure and cycle of an alert for a failure situation of the individual controller by a DSM controller of the DSM system. The method confirms the utterance position of the alert for the driver by an AVNT controller of the AVNT system, and reproduces the failure situation of the individual controller by a vehicle speaker or the Bluetooth earphones to reproduce the vehicle alert through the left/right Bluetooth earphones in the driver's ears at autonomous Lv.4, freeing the driver from driving.

Abstract: In an example method, a computer system receives first data representing a plurality of scenarios for estimating a performance of a vehicle in conducting autonomous operations. Further, the computer system determines, for each of the scenarios: (i) a first metric indicating an observed performance of the vehicle in that scenario, where the first metric is determined based on at least one rule, and (ii) a second metric indicating a degree of information gain associated with that scenario. The computer system selects a subset of the scenarios based on the first metrics and the second metrics, and outputs second data indicative of the subset of the scenarios.

Abstract: A virtual railroad of vehicles is disclosed. In one aspect of the disclosure, a system includes one or more passenger vehicles of a peloton, and a first engine vehicle of the peloton. The first engine vehicle communicatively connected to the one or more passenger vehicles, wherein the first engine vehicle comprises: a processor communicatively connected to a memory and is configured to receive status information of the one or more passenger vehicles, determine, based on the received status information, a set of current values for a set of vehicle attributes for each of the one or more passenger vehicles, and adjust, based on the set of current values for the set of vehicle attributes, a position of a corresponding passenger vehicle of the one or more passenger vehicles.

Abstract: A system for determining a travel direction that avoids objects when a vehicle travels from a current location to a target location is provided. The system determines a travel direction based on an attract-repel model. The system accesses external object information provided by an external object system. The external object information may include, for each of a plurality of objects, location, type, and constraint. The system assigns a repel value to the location of each object based on the type of and constraint on the object. The system assigns an attractive value to the target location. The system calculates a cumulative force based on the attractive and repulsive forces and sets the travel direction based on the cumulative force.

Abstract: A vehicle driving assist apparatus acquires a collision index value which represents a magnitude of a collision of an own vehicle and a dozing level of a driver of the own vehicle, and executes a secondary collision reducing control of executing a forcibly-decelerating process of forcibly decelerating the own vehicle when a light collision condition is satisfied, and a dozing condition is satisfied. The vehicle driving assist apparatus executes the forcibly-decelerating process so as to decelerate the own vehicle with controlling a deceleration of the own vehicle such that the deceleration of the vehicle realized when the light collision condition and the dozing condition become satisfied, and the dozing level is relatively low, is smaller than the deceleration of the own vehicle realized when the deceleration when the light collision condition and the dozing condition become satisfied, and the dozing level is relatively high.

Abstract: A method for controlling a non-propulsive power generation turbine engine configured to supply power to a plurality of propulsion rotors of an aircraft, each propulsion rotor being connected to a power distribution module through at least one power supply bus, the turbine engine supplying each power supply bus via the power distribution module at a supply rate, the control method comprising a step of determining the power requirement of each power supply bus depending on the power requirement of each propulsion rotor, a step of determining the basic power requirement of each power supply bus, a step of determining the overall power requirement based on all the basic power requirements of the power supply buses and a step of determining an anticipation parameter based on the overall power requirement.

Abstract: An approach is provided for determining tunnel speed for a vehicle travelling through a tunnel. A tunnel processing platform aggregates probe data associated with at least one vehicle into at least one tunnel path based, at least in part, on a network geometry topology for at least one tunnel. The tunnel processing platform also designates at least one probe point collected upstream of the at least one tunnel as at least one starting point of the at least one tunnel path and at least one temporary probe point as at least one endpoint of the at least one tunnel path, wherein the at least one temporary probe point is downstream of the at least one tunnel. It then determines at least one temporary tunnel speed for the at least one tunnel path based, at least in part, on the timestamp for the at least one probe point and the current time associated with the at least one temporary probe point.

Abstract: Techniques are disclosed for systems and methods to provide docking assist for mobile structures. A docking assist system includes a logic device, one or more sensors, one or more actuators/controllers, and modules to interface with users, sensors, actuators, and/or other modules of a mobile structure. The logic device is adapted to receive docking assist parameters from a user interface for the mobile structure and perimeter sensor data from a perimeter ranging system mounted to the mobile structure. The logic device determines docking assist control signals based, at least in part, on the docking assist parameters and perimeter sensor data, and it then provides the docking assist control signals to a navigation control system for the mobile structure. Control signals may be displayed to a user and/or used to adjust a steering actuator, a propulsion system thrust, and/or other operational systems of the mobile structure.

Abstract: A vehicle includes a controller. The controller is configured to perform authentication of a portable device by communication with the portable device when startup of a system of the vehicle is instructed, when the system is off, or when the startup of the system of the vehicle is instructed and the system is off. The controller is configured to perform the startup of the system of the vehicle when the startup of the system of the vehicle is instructed, under a condition that the authentication of the portable device is successful. The controller is configured to perform reauthentication of the portable device when predetermined movement of the vehicle is detected after the startup of the system of the vehicle, and perform theft prevention processing when the reauthentication of the portable device fails.

Abstract: A control system for a vehicle using a forward-facing camera includes a look ahead module configured to determine a distance to a look ahead point. A lane center module determines a location of a lane center line. A vehicle center line module determines a location of a vehicle center line. A first lateral offset module determines a first lateral offset based on the look ahead point and the determined lane center line. A second lateral offset module determines a second lateral offset based on the determined lane center line and the vehicle center line. A yaw angle offset calculating module receives the first lateral offset, the second lateral offset and the distance to the look ahead point, calculates a yaw angle offset, and compensates a yaw angle error based on the yaw angle offset.

Abstract: The present disclosure relates to a system that comprises: a control station intended to be operated; an unmanned aerial vehicle for multiple tasks (UAM) which is supported, by unmanned aerial devices (UAV), unmanned ground vehicle (UGV), and by a centralised mobile reel unit which feeds cables and hoses for supplying multiple additive and subtractive fluids (e.g. paint, air suction, etc.) and for charging power; wherein the cables and hoses comprise a device that makes it possible to predict trajectories, without interfering with flight maneuvers or the environment. The UAM comprises a robotic arm with specific tools that make it possible, for example, to paint fences, as well as a device that allows it to be attached to various surfaces.