Abstract: In some embodiments, techniques are provided for analyzing time series data to detect anomalies. In some embodiments, the time series data is processed using a machine learning model. In some embodiments, the machine learning model is trained in an unsupervised manner on large amounts of previous time series data, thus allowing highly accurate models to be created from novel data. In some embodiments, training of the machine learning model alternates between a fitting optimization and a trimming optimization to allow large amounts of training data that includes untagged anomalous records to be processed. Because a machine learning model is used, anomalies can be detected within complex systems, including but not limited to autonomous vehicles such as unmanned aerial vehicles. When anomalies are detected, commands can be transmitted to the monitored system (such as an autonomous vehicle) to respond to the anomaly.

Abstract: To provide a work machine having a blade provided to a track structure, and a swing structure provided swingably on the upper side of the track structure, which work machine allows for computation of the horizontal coordinates of the blade. The work machine includes: a swing-structure-position acquiring device that acquires a horizontal coordinate and an orientation of the swing structure; a swing sensor that senses a swing of the swing structure; a travel sensor that senses travelling of the track structure; and a controller that computes an orientation of the track structure, and a horizontal coordinate of the blade.

Abstract: A specifying unit 51 of a flying body operation management device 50 specifies an airspace in which a propagation delay equal to or greater than a threshold value occurs in the uplink of a time-division duplex between a wireless communication terminal 30 and a wireless base station 41 to which wireless communication terminal 30 is wirelessly connected. Next, an assigning unit 52 of flying body operation management device 50 performs a process of assigning, with respect to each airspace, a flying body 10 having a wireless communication terminal 20. At this time, with respect to an airspace specified by specifying unit 51, assigning unit 52 limits the assigning of flying body 10 on which wireless communication terminal 20 is mounted.

Abstract: A system and method for automatically engaging an autonomous driving mode in a vehicle is disclosed. The method includes monitoring a driver and switching to the autonomous driving mode if an unsafe driving condition is detected. The method can include monitoring biometric data. The method can also include monitoring behavioral data using one or more kinds of vehicle sensors. The system and method ensure a vehicle is safely driven even if a driver experiences a health episode that could leave them unable to safely operate the vehicle.

Abstract: A map data construction method and device, where the method includes obtaining first basic safety information packets of a vehicle, where the first basic safety information packets include an information packet of the vehicle that is collected when a safety event occurs, obtaining first basic safety information data from the first basic safety information packets, where the first basic safety information data includes parameter information of the vehicle and extended safety information, the parameter information of the vehicle indicates a driving state and an appearance information of the vehicle, and the extended safety information is used to indicate a safety state of the vehicle and a safety state of a road, and performing model processing based on the first basic safety information data to generate the map data.

Abstract: A Coordinating Apparatus and Method is provided between Adaptive Cruise Control (ACC) and Predictive Cruise Control (PCC). The ACC system is configured to provide a target acceleration or deceleration based on maintaining a target distance from vehicles ahead. The PCC system is configured to provide a target acceleration or deceleration based on upcoming changes in elevation and maximizing fuel economy. The coordinating apparatus communicates with the ACC system and with the PCC system, and applies the lesser acceleration or greater deceleration between the ACC target acceleration or deceleration and the PCC target acceleration or deceleration. The apparatus and method may apply the target acceleration or deceleration by way of a vehicle speed control apparatus, such as a vehicle engine controller.

Abstract: An unmanned aerial vehicle (UAV) control system includes a first UAV, a second UAV that flies near the first UAV during a flight of the first UAV and is configured to obtain wind information about wind, and flight control means for controlling the flight of the first UAV based on the wind information obtained by the second UAV.

Abstract: A system and method for dynamic allocation of delivery resources is described. In an example implementation, the system may determine floating and static geographic areas based on delivery data, generate an initial mapping associating the static geographic area with addresses and/or routes, and generate one or more periodic routes based on the initial mapping. In some instances, the system may compute a route-value target for each of the periodic routes based on a load of the periodic routes and may then assign one or more floating addresses located in the one or more geographic regions to the periodic routes based on the route-value target. In some instances, the system may determine a delivery vehicle load plan based on the assignment to the routes and may automatically perform a defined operation using the delivery vehicle load plan.

Abstract: A system for transmitting and storing data based on a connection for a vehicle is presented. The system includes a computing device, the computing device configured to receive a vehicle data, communicatively connect the computing device to a second device as a function of a mesh network, authenticate a second device as a function of an authentication module, generate a vehicle collection datum as a function of the vehicle data, communicate the vehicle collection datum to the second device as a function of the mesh network, and store the vehicle collection datum in a recorder database as a function of a lack of identification of the mesh network.

Abstract: Embodiments described herein improve fuel economy by controlling a vehicle powertrain based on a predicted vehicle velocity. The vehicle velocity is predicted based on vehicle-to-vehicle data when a prediction horizon is a longer prediction horizon and the vehicle velocity is predicted based on historical drive cycle data when the prediction horizon is a shorter prediction horizon. A time duration of the shorter prediction horizon is shorter than the time duration of the longer prediction horizon. A plurality of drive cycles are established for both the longer and the shorter prediction horizons using a neural network. A shorter prediction horizon drive cycle uses nonlinear autoregressive exogenous model neural networks and the longer prediction horizon drive cycle uses two layer feedforward neural networks. The predicted vehicle velocity is determined from a similar drive cycle of the plurality of drive cycles of either the shorter and/or the longer prediction horizon drive cycles.

Abstract: Examples described herein provide a computer-implemented method that includes receiving, by a processing device, a current state of a vehicle. The method further includes predicting, by the processing device using an output of an artificial intelligence model, a future state of the vehicle based at least in part on the current state of the vehicle. The method further includes calculating, by the processing device using a tunable reward function, a reward associated with the future state of the vehicle, the tunable reward function comprising multiple tunable coefficients. The method further includes training, by the processing device, the artificial intelligence model based at least in part on the reward.

Abstract: A control device 6 acquires an output signal front a lidar unit 7 that can detect a feature existing around a vehicle, and calculates a reference angle ?tag, indicating a tilt angle of a feature to be recognized based on an output signal from the lidar unit 7, with respect to a detection area of the lidar unit 7. The control device 6 then controls the detection area of the lidar unit 7 according to the reference angle ?tag and the tilt information stored in the storage unit 2 and indicating an angle of the feature with respect to a road surface.

Abstract: Methods and systems are provided for guiding or otherwise assisting operation of an aircraft en route to an airport. One method involves identifying a reference point in advance of a runway, dynamically determining a gliding vertical trajectory for the aircraft en route to the reference point based at least in part on a current altitude of the aircraft at a current aircraft location and gliding characteristics of the aircraft, and providing a graphical indication of a difference between a predicted altitude of the aircraft at a location corresponding to the reference point resulting from the gliding vertical trajectory and an altitude criterion associated with the reference point. The graphical indication of the difference dynamically updates as the aircraft travels.

Abstract: Methods and systems are provided for controlling an engine idle-stop based on upcoming traffic and road conditions. In one example, a method may include receiving data including traffic information and road characteristics immediately ahead of a vehicle from one or more remote sources, and adjusting one or more vehicle thresholds based on the received data. A duration of a prospective engine idle-stop may be estimated based on the received data and an engine idle-stop may be initiated based on the duration of the prospective engine idle-stop and the adjusted one or more vehicle threshold.

Abstract: A control system for a hybrid vehicle configured to shift an operating mode from a single-motor mode to a hybrid-low mode without causing a temporal drop in a drive force. A controller is configured to predict an execution of a mode change from the single-motor mode to the first hybrid mode, and to execute the mode change from the single-motor mode to the hybrid-low mode via a hybrid-high mode, if the execution of the mode change from the single-motor mode to the hybrid-low mode is predicted.

Abstract: An example operation may include one or more of receiving, by a transport, a request for a service from a transport occupant, determining, by the transport, a profile of the transport occupant, identifying, by the transport, at least one profile shared with the transport occupant based on the profile of the transport occupant, and providing the service to the transport occupant based on the at least one profile shared with the transport occupant.

Abstract: A driving support device that controls a steering unit such that a hitch angle between a tow vehicle, which tows a towed vehicle, and the towed vehicle becomes a target angle set as a target includes: an image control unit that causes a display unit to perform display of a captured image obtained by an imaging unit provided in the tow vehicle or the towed vehicle in a mirror image state and display of a setting image including a slider indicating the target angle input through an input unit; an acquisition unit that acquires input of the target angle at the time of backward movement of the tow vehicle from the input unit, in a state where the setting image is displayed; and a setting unit that sets the target angle based on the input.

Abstract: A vehicle controller includes a target position recognition unit configured to recognize a target position, a parking route generation unit configured to generate a parking route, and an automatic steering unit configured to automatically operate a steering device. The parking route generation unit generates a first route and a second route. The first route is a parking route to a temporary target position that is obtained by laterally moving the target position toward inside of the parking route in a turning direction. The second route is a parking route to the target position from a designated position in the middle of the first route. The automatic steering unit automatically operates the steering device to cause the subject vehicle to follow the first route until the subject vehicle reaches the designated position and to follow the second route from the designated position until the subject vehicle reaches the target position.

Abstract: An apparatus for post-processing of a decision-making model of an autonomous vehicle receives a decision-making model including a plurality of states. The model is processed using multivariate data that comprises values for at least three observations of a vehicle operational scenario. A slice of the model decision space is generated by fixing values of all except two observations, and modifying the values of the two observations to obtain multiple alternative solutions for the model. The alternative solutions and the modified values form the slice. Each alternative solution is associated with a respective first value of a first observation and a respective second value of a second observation. The apparatus also generates a solution to a modified decision-making model that is the model modified by, for at least one state and at least one of the two observations, modifying a probabilistic transition matrix, a probabilistic observation matrix, or both.

Abstract: A method for operating a safety system of a motor vehicle includes correcting an output signal of a measuring sensor as a function of a current temperature value measured by a temperature sensor. The motor vehicle includes a sensor device with the measuring sensor to detect a collision and the temperature sensor. The method further includes determining an intrinsic heat of the measuring sensor generated by the operation of the measuring sensor and correcting the output signal as a function of the determined intrinsic heat.