One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Methods, apparatuses, systems, and computer program products are provided. An example method comprises receiving a change trigger; and providing two or more map versions to a plurality of vehicle apparatuses. The map versions may comprise a stable map version and a changed map version. The example method further comprises receiving two or more responses from at least two of the plurality of vehicle apparatuses. A response comprises an indicator of a preferred map version selected by a vehicle apparatus of the plurality of vehicle apparatuses from the two or more map versions. The example method further comprises analyzing the responses to determine a most preferred map version; and when it is determined that the most preferred map version is a changed map version, updating one or more map databases based at least in part on the changed map version.

A method is described for performing a real time analysis of traffic flow control device related data using a plurality of vehicles connected in at least one vehicle cell network. The method compares position data from vehicles defining a traffic flow with received data for a traffic flow control device and geometry and topology data concerning a transport engineering construction related to the traffic flow control device to evaluate if a discrepancy can be detected between the geometry and topology data concerning the transport engineering construction and the traffic flow defined by the vehicles positions. The method may be used for updating and/or finding errors in the geometry and topology data concerning the transport engineering construction.

Techniques are disclosed for collaborative map construction using multiple vehicles. Such a system may include a ground vehicle including a first computing device and a first scanning sensor, and an aerial vehicle including a second computing device and a second scanning sensor. The ground vehicle can obtain a first real-time map based on first scanning data using the first scanning sensor, and transmit a first real-time map and position information to the aerial vehicle. The aerial vehicle can receive the first real-time map and the position information from the first computing device, obtain a second real-time map based on second scanning data collected using the second scanning sensor, and obtain a third real-time map based on the first real-time map and the second real-time map.

A method for mapping an environment by an electronic device is described. The method includes obtaining a set of sensor measurements. The method also includes determining a set of voxel occupancy probability distributions respectively corresponding to a set of voxels based on the set of sensor measurements. Each of the voxel occupancy probability distributions represents a probability of occupancy of a voxel over a range of occupation densities. The range includes partial occupation densities.

Disclosed is a coverage path planning method for multiple unmanned surface mapping vehicles, comprising: simultaneously creating submaps and an overall map; outputting its own position information and obstacle information, transmitting to BL.sub.l.sup.i and updating BL.sub.l.sup.m; defining a behavior strategy list (BS); determining the BS with priority for path planning, outputting a to or th state if any criterion is satisfied; when trapped in a local optimum, updating map layers layer-by-layer going upwards, searching for tp in the corresponding layers, performing a BS determination, and outputting a tr instruction; if no target point is found even at the highest layer, checking each CS.sub.P.sub.i∈{FN.sub.i,UFN.sub.i}, and determining a termination. As such, the coverage rate and coverage effect of multiple unmanned surface mapping vehicles in a complex environment can be increased, thus increasing the operational efficiency of the unmanned surface mapping vehicles.

A method for aligning digital maps, in particular by a control unit. Data of a first map present in a first coordinate system and data of a second map present in a second coordinate system are received. At least one trajectory within the first map and at least one trajectory within the second map are ascertained based on the received data. The data of the first coordinate system and the data of the second coordinate system are aligned with one another based on the respective trajectories. A transfer system, a control device, a computer program, and a machine-readable memory medium are also described.

Provided is a computer-implemented method of determining a point of interest and/or a road type in a map, comprising the steps of: acquiring processed sensor data collected from one or more vehicles; extracting from the processed sensor data a set of classification parameters; and determining based on the set of classification parameters one or more points of interest (POI) and its geographic location and/or one or more road types.

A system for collecting and distributing navigation information relative to a road segment is disclosed. In one embodiment, the system includes at least one processor programmed to receive drive information collected from each of a plurality of vehicles that traversed the road segment, wherein the drive information received from each of the plurality of vehicles includes indicators of speed traveled by one of the plurality of vehicles during a drive traversing the road segment; determine, based on the indicators of speed included in the drive information received from each of the plurality of vehicles, at least one aggregated common speed profile for the road segment; store the at least one aggregated common speed profile in an autonomous vehicle road navigation model associated with the road segment; and distribute the autonomous vehicle road navigation model to one or more autonomous vehicles for use in navigating along the road segment.

An apparatus and the like for controlling a mobile body that are capable of adjusting a detection result by a radar device in accordance with a three-dimensional shape for each region of a three-dimensional map generated from an image captured by an image-capturing device are provided. A mobile body control unit 105 is an apparatus for controlling the vehicle (mobile body) including an image-capturing device 101 and a millimeter wave radar device 102 (radar device). A three-dimensional map generation unit 203 generates a three-dimensional map around the vehicle from an image captured by the image-capturing device 101. A radar weight map estimation unit 204 (weight estimation unit) estimates the weight of the detection result by the millimeter wave radar device 102 for each region of the three-dimensional map from the three-dimensional shape for each region of the three-dimensional map. A weight adjustment unit 205 (adjustment unit) adjusts a detection result by the millimeter wave radar device 102 on the basis of a weight.