A method is provided for creating at least one map of vehicle surroundings with the aid of a control unit. It is checked based on a comparison between received measured data and stored or received map data, whether first features, for example semantic features, are present and complete. First features available in a vehicle surroundings are extracted from the received measured data if no or incomplete map data are present. It is checked whether a localization is possible within the vehicle surroundings with the aid of the first semantic features. If a localization is imprecise or not possible with the aid of the ascertained first features, second features are extracted from the received measured data. A digital map of vehicle surroundings is created based on the ascertained first features and/or the second features. Furthermore, a control unit, a computer program as well as a machine-readable memory medium are provided.

A method comprises receiving, at a vehicle system of a vehicle, sensor data from one or more sensors; detecting an object based on the sensor data; determining whether a dynamic map maintained by a remote computing device includes the detected object; upon determination that the dynamic map includes the detected object, determining a remaining time-to-live associated with the detected object based on data associated with the dynamic map; and transmitting data about the detected object to the remote computing device if the determined remaining time-to-live associated with the detected object is less than a predetermined threshold time.

Described herein are methods of generating learning data to facilitate de-biasing the labeled location of an object of interest within an image. Methods may include: receiving sensor data, where the sensor data is a first image; determining reference corner locations of an object in the first image using image processing; generating observed corner locations of the object in the first image from the determined reference corner locations; generating a bias transformation based, at least in part, on a difference between the reference corner locations and the observed corner locations of the object in the first image; receiving sensor data from another image sensor of a second image; receiving observed corner locations of an object in the second image from a user; and applying the bias transformation to the observed corner locations of the object in the second image to generate de-biased corners for the object in the second image.

An apparatus for updating a map detects a feature in an area around a vehicle traveling on a road from situation data representing the situation around the vehicle, and updates a lane network representing a connection relationship between lanes included in road sections into which the road is divided. The lane network is stored in a storage unit and updated to match a connection relationship between lanes indicated by the detected feature.

Techniques for determining distortion in a map caused by measurement errors are discussed herein. For example, such techniques may include implementing a model to estimate map distortion between the map frame and the inertial frame. Data such as sensor data, map data, and vehicle state data may be input into the model. A map distortion value output from the model may be used to compensate vehicle operations in a local region by approximating the distortion as linearly varying about the region. A vehicle, such as an autonomous vehicle, can be controlled to traverse an environment based on the trajectory.

A computer-implemented method may include monitoring an age of a tile of a map, where the map includes multiple tiles including the tile. The method may also include, based on the age exceeding a threshold age, determining that the tile of the map is to be updated, and receiving a location indicator from a vehicle. The method may additionally include transmitting an update message to a vehicle traversing a track within the tile as indicated by the location indicator, where the update message includes instructions to cause the vehicle to gather and submit sensor data to a computing system. The method may also include receiving the sensor data from the vehicle, and updating the tile of the map based on the received sensor data.

A system for collecting traffic information includes a vehicle having at least one sensor for collecting dead reckoning (DR) information, and a global positioning system (GPS) receiver configured to receive GPS information, and a server that maps the DR information and the GPS information to a server map to generate first map matching information, and collects the first map matching information as the traffic information when it is determined that a version of a software platform of the vehicle is a latest version and all the DR information and the GPS information are received.

Methods and systems for updating digital maps by refining map feature positions and improving map position accuracy are disclosed. Geographic map updating may include a base map element and an update element where the base map element may include a representation of the map area displaying features thereof and the update element may include a geographic feature identification element and one or more positioning elements. One embodiment includes identifying a point of interest's position data and updating the map data within a map region surrounding the point of interest.

A navigation apparatus and a method for providing an individualization map service of the navigation apparatus are provided. The navigation apparatus includes a detector configured to sense a vehicle state and a travelling environment during travelling, and a processor configured to recognize a drive context based on the vehicle state and the travelling environment, and to make an individualization map to be serviced based on the recognized drive context.

A self-propelled floor processing device with an evaluation unit, which is designed to navigate the floor processing device within an environment based on an area map and, during a movement, to determine a behavior parameter of the floor processing device and a movement path of the floor processing device. The evaluation unit is set up to analyze the behavior parameter and movement path, automatically determine a no-go area which the floor processing device must not traverse depending on the result of the analysis, and enter the determined no-go area in the area map or change a no-go area already entered in the area map.