A rear axle center (RAC) locating system may include a tractor and a RAC location acquisition unit. The tractor may include a rear axle having a center, a global positioning system (GPS) antenna offset from the rear axle, and inertial measurement units. The RAC location acquisition unit may include a processing unit and a non-transitory computer-readable medium containing instructions to direct the processing unit to determine a geographic location of the GPS antenna based upon signals received by the GPS antenna and determine a geographic location of the center of the rear axle based upon the geographic location of the GPS antenna and combined data from the inertial measurement units.

A tracking problem detection system for a machine may include tracking diagnostic circuitry including one or more tracking diagnostic processors configured to receive a location signal indicative of a location of a machine and a path signal indicative of a path location associated with at least a portion of a path for the machine to follow while maneuvering. The tracking diagnostic processors may also be configured to determine a tracking difference between the path location and the location of the machine, and determine a frequency of a signal associated with the tracking difference and/or a frequency of a signal associated with a yaw rate associated with the maneuvering. The tracking diagnostic processors may also be configured to detect, based at least in part on the frequencies of the signals associated with the tracking difference and/or the yaw rate, a tracking problem associated with maneuvering the machine.

Aspects of the present disclosure relate to identifying points of interest by generating and storing virtual geofence information that is captured around a physical structure based in part on global positioning system (GPS) data from a plurality of devices that is then processed to identify GPS trajectory and kernel density estimation. Specifically, the techniques include receiving, at the network-based control computer, GPS data from a plurality of devices and grouping the GPS data from the plurality of devices to generate GPS trajectory information for each group of the plurality of devices. Based on the GPS trajectory information, the network-based control computer may calculate kernel density estimation and determine an isoline on a virtual map for the each group of the plurality of devices. By overlaying the isoline data on a geographic coordinate information of a physical structure, the network-based control computer may generate a virtual geofence around the physical structure and store, in a memory, geofence information for the facility.

A host vehicle position estimation device includes an observation position estimation unit configured to estimate an observation position of the vehicle based on a result of recognition of the target object performed, a prediction position calculation unit configured to calculate a prediction position of the vehicle from a result of estimation of the host vehicle position in the past based on a result of measurement performed by an internal sensor, a host vehicle position estimation unit configured to estimate the host vehicle position based on the observation position and the prediction position. The host vehicle position estimation unit is configured to give more weighting to the prediction position in the estimation of the host vehicle position such that the host vehicle position is estimated to be close to the prediction position if it is determined that a result of estimation of the host vehicle position is unsteady.

A method is provided for arranging a grid with respect to a vehicle position. An initial position and a state of movement of the vehicle are determined. A physical grid specifying a spatial location of grid cells with respect to an earth-fixed coordinate system and a logical grid representing the cells within a memory are defined. An initial arrangement of the physical grid is determined with respect to the initial vehicle position. A mapping is defined between the physical and logical grids, and a torus interconnection is defined between margins of the logical grid. A modification of the vehicle position is determined based on the state of movement of the vehicle. By applying the torus interconnection, a revised logical grid is determined based on the modification of the vehicle position. A current arrangement of the physical grid is determined by mapping the revised logical grid.

A device implementing a system for estimating device position includes at least one processor configured to receive a first sensor measurement of a device at a first time, the first sensor measurement having a first variance in measurement error, and to receive a second sensor measurement of the device at a second time, the second sensor measurement having a second variance in measurement error. The at least one processor is further configured to determine a speed of the device based on at least one of the first or second sensor measurements, and adjust the second variance in measurement error based on the determined speed. The at least one processor is further configured to estimate a device position based at least in part on the first variance in measurement error and the adjusted second variance in measurement error.

The disclosed subject matter relates to an Intelligent Transportation System station (ITS-S) for being carried by a Vulnerable Road User (VRU), comprising: a motion sensor for determining VRU motion data indicative of a VRU position, a VRU speed, and a VRU heading; a transmitter for transmitting a VRU message including the determined VRU motion data; a receiver for receiving, concerning a vehicle, vehicle motion data indicative of a vehicle position, a vehicle speed, and a vehicle heading; and a controller for controlling the transmitter; wherein the controller is configured to compare the determined VRU motion data with the received vehicle motion data and, when the result of the comparison meets a predetermined criterion, to suppress the transmitting of said VRU message.

A satellite positioning receiver includes a local oscillator, a front-end circuit with having an analog mixer, a number of signal processing channel circuits, and a processing circuit. The satellite positioning receiver performs a method that includes (i) acquiring a first satellite using a first frequency search space that spans both uncertainties due to the first satellite's orbit and uncertainties due to the clock bias or a time rate of change of the bias; and (ii) using the bias or the time derivative of the bias determined during the acquisition of the first satellite, acquiring a second satellite using a second frequency search space that spans substantially only uncertainties due to the second satellite's orbit.

A computer-implemented method utilizing a continuous discrete recurrent Kalman network, wherein the method includes receiving, at an encoder, an input from one or more sensors, wherein the input includes one or more time series data associating data at one or more points in time; outputting, to a Kalman filter, a latent observation and uncertainty estimate in response to the input at the encoder; determining a latent state prior and latent state posterior utilizing the Kalman filter; and outputting, via a decoder, a filtered observation utilizing at least the latent state posterior.

The techniques discussed herein may comprise an autonomous vehicle guidance system that generates a path for controlling an autonomous vehicle based at least in part on a static object map and/or one or more dynamic object maps. The guidance system may identify a path based at least in part on determining set of nodes and a cost map associated with the static and/or dynamic object, among other costs, pruning the set of nodes, and creating further nodes from the remaining nodes until a computational or other limit is reached. The path output by the techniques may be associated with a cheapest node of the sets of nodes that were generated.