An improved system and method is disclosed of accessing mapping data for a geographical area comprising speed limit data for a first road segment, accessing second mapping data providing speed limit data for a plurality of corresponding road segments from a second source, determining an overlap amount between the candidate road segments and the first road segment, using overlap data to identify a first subset of the candidate road segments, identifying a first speed limit that has a highest likelihood of being accurate from speed limits respectively associated with road segments in the second subset of the candidate road segments, transmitting the first speed limit in association with a map comprising the first geographical area to a vehicle device.

According to various embodiments, a system for training a machine learning model with a geographical location is provided. The system comprises: an input device configured to obtain a geolocation index for the geographical location; and a processor configured to train the machine learning model in relation to the geographical location, wherein the processor is further configured to split the geolocation index into a plurality of geolocation indexes each having different scales, embed each of the plurality of geolocation indexes to obtain a plurality of values relating to latitude and longitude for the plurality of geolocation indexes respectively, aggregate the plurality of values to obtain the representation value of the geographical location, and train the machine learning model using the representation value of the geographical location.

Disclosed is a low memory based indoor positioning method performed by a computing device including at least one processor. The method may include: extracting coordinate information in which a sensing value is not recorded as empty space information from map data in which each of a plurality of sensing values measured in a plurality of coordinates is recorded; generating a sensing value array including the plurality of sensing values; and storing the empty space information and the sensing value array in a memory.

Provided are a mapping apparatus, a tracker, a mapping method, and a program that can accurately map a given geographic position on an environmental map. An environmental map data storing unit (80) stores environmental map data indicating an environmental map in which a position expressed by a Euclidean coordinate system is associated with a position expressed by a geographic coordinate system. A SLAM processing executing unit (84) estimates, on the basis of sensing data acquired by a tracker and the environmental map data, a position of the tracker (12) expressed by the Euclidean coordinate system. A target position data acquiring unit (88) acquires target position data indicating a target position expressed by the geographic coordinate system. A coordinate converting unit (90) identifies the target position expressed by the Euclidean coordinate system based on the target position data and the environmental map data.

Embodiments of the present disclosure relate to a method of translating routes between maps. The method may include obtaining a graph based on data of an area. The graph may include one or more nodes representing different locations along one or more navigable paths as defined by the map. The method may also include obtaining one or more waypoints that define a route to traverse in the area and selecting, from the nodes, one or more path nodes based on locations of the path nodes corresponding to locations of the way points. The selected path nodes may define a path in the data that corresponds to the route.

A method and an assistance system predicts a driving path of a motor vehicle. According to the method, a respective surroundings scenario lying ahead of the motor vehicle in the driving direction is ascertained. The trustworthiness of a plurality of different data sources and/or of the data which originates therefrom and on the basis of which the driving path can be predicted are ascertained for the surroundings scenario. A plurality of the data originating from the different data sources is then fused together in a weighted manner according to the ascertained trustworthiness and is used to predict the driving path of the motor vehicle.

A vehicle control system includes: a storage device configured to store map data in which a vertical motion parameter is associated with a position on a map, the vertical motion parameter being relevant to vertical motion of a wheel of a vehicle; and one or more processors configured to control an objective vehicle based on the vertical motion parameter to be acquired from the map data. The one or more processors are configured to more preferentially select, as a traveling route of the objective vehicle, a route for which the amount of the map data is large than a route for which the amount of the map data is small.

A method and system for determining a route map and a route for a vehicle. Generating the route map comprises obtaining historical data comprising a plurality of data points for each of a plurality of vehicles from storage and determining a plurality of nodes each representing a subset of the data points. The historical data is applied to the plurality of nodes to determine the closest node for each vehicle. The nodes are ordered for each of the plurality of vehicles in the historical data by time; and a directed edge is generated between a first and second node of the plurality of ordered nodes, based on when the historical data indicates that a given vehicle has transited from the first node and the second node. A route is determined for the vehicle based on the generated route map and outputted route to a control system.

A method for providing a high-resolution digital map includes locating a device and providing sensor data at a located position during a test drive of the located device. The method further includes ascertaining detection indicators for at least one object detected based on the provided sensor data at the located position, and adding at least one additional layer to the high-resolution digital map. The at least one additional layer includes the ascertained detection indicators for the at least one detected object.