A system and a method are provided that are capable of providing map data for supporting a variety of user network environments and selecting data zones freely. navigation terminal includes a reception unit adapted to receive a file in which map data of a specific zone is stored, from a map provision server; and an execution unit adapted to execute a navigation function on the specific zone using the file. The file is produced by an individual unit with respect to each of geographic areas divided by a mesh unit having a variable size. The size of the mesh unit is decided according to the amount of information included in the geographic area such that the file has an equalized size.

A system and method for indoor positioning and tracking that uses beacon signal data, sensor data, and/or wireless network fingerprinting to create a moving map of radiofrequency (RF) devices in an indoor location. The moving map is continuously repaired and updated. The system incorporates user data into the moving map to enhance customer service and customer experience.

Systems and methods for navigational map version management are disclosed. In one aspect, a map management server includes a processor and a computer-readable memory having stored thereon a navigational map including a plurality of units, each of the units covering an area and including a plurality of objects within or adjacent to roadways within the area. The processor is configured to receive update data for the navigational map, the update data including object data to update the navigational map. The processor is also configured to create a released version of the navigational map that includes one or more updated units. The processor is further configured to provide the released version of the navigational map to an autonomous vehicle.

Provided is an information processing apparatus including: a motion control unit (107) that controls a motion of an autonomous moving body (10), in which, when transmitting/receiving internal data related to the autonomous moving body, the motion control unit causes the autonomous moving body to express execution of the transmission/reception of the internal data by an action.

A device is configured to estimate a gaze target of a user of an augmented reality headset based on vehicle sensor data and headset sensor data. The device is configured to generate visualization data based on the gaze target. Responsive to determining that the gaze target is inside a first vehicle, the visualization data includes a first visual depiction of a first point of interest that is outside the first vehicle. The first point of interest includes at least a portion of a particular route of a particular vehicle. The particular vehicle includes the first vehicle or a second vehicle. Responsive to determining that the gaze target is outside the first vehicle, the visualization data includes a second visual depiction of a second point of interest that is inside the first vehicle.

A control map information evaluation method is provided that includes acquiring control map information in which additional information pieces of plural kinds are given to a target area on a map. The additional information pieces are map information used for travel control of a vehicle. The method further includes determining whether consistency is present or absent between the additional information pieces of two or more of the plural kinds given to the same target area. The method further includes determining reliability of at least one of the additional information pieces, depending on presence and absence of the consistency determined.

An object is to provide a technique capable of estimating a blind area region which can be used in an automatic driving to optimize the automatic driving, for example. A blind area estimation device includes an acquisition part and an estimation part. The acquisition part acquires an object region based on object information. The object information is information of an object in a predetermined region detected by a detection part. The object region is a region of the object. The estimation part estimates a blind area region based on the object region. The blind area region is a region which is a blind area for the detection part caused by the object.

A system includes a network interface circuit and a processing circuit configured to receive a physical currency transaction request from a first user device, the physical currency transaction request including a currency exchange transaction parameter, match the physical currency transaction request to another physical currency transaction request based at least in part on the currency exchange transaction parameter, provide the physical currency transaction request to a second user device associated with the another physical currency transaction request, geo-fence an area based on at least one of the currency exchange transaction parameters or a current location of the first user device, determine an exchange location based on the geo-fenced area and the matched physical currency transaction request and another physical currency exchange request, and provide instructions to the first user device and the second user device for an exchange based on the determined exchange location.

A system, method, and computer-readable medium having instructions stored thereon to enable an ego vehicle having an autonomous driving function to estimate and traverse a curved segment of highway utilizing radar sensor data. The radar sensor data may comprise stationary reflections and moving reflections. The ego vehicle may utilize other data, such as global positioning system data, for the estimation and traversal. The estimation of the curvature may be refined based upon a lookup table or a deep neural network.

This document describes change detection criteria for updating sensor-based maps. Based on an indication that a registered object is detected near a vehicle, a processor determines differences between features of the registered object and features of a sensor-based reference map. A machine-learned model is trained using self-supervised learning to identify change detections from inputs. This model is executed to determine whether the differences satisfy change detection criteria for updating the sensor-based reference map. If the change detection criteria is satisfied, the processor causes the sensor-based reference map to be updated to reduce the differences, which enables the vehicle to safely operate in an autonomous mode using the updated reference map for navigating the vehicle in proximity to the coordinate location of the registered object. The map can be updated contemporaneously as changes occur in the environment and without hindering performance, thereby enabling real-time awareness to support controls and to improve driving-safety.