A map updating method and apparatus (800), and a device (900) are disclosed, which can be used in automated driving (Automated driving), intelligent driving (Intelligent Driving), and other fields. The map updating method includes: when an abnormal scenario occurs, obtaining various types of sensing data of the abnormal scenario, calculating a minimum safety boundary based on the sensing data of the abnormal scenario; and updating a map based on the minimum safety boundary obtained through calculation. According to the map updating method, a map updating program can be triggered when the abnormal scenario occurs, without the need to wait for a collection vehicle/crowd-sourcing vehicle. This improves real-time performance of map refreshing, and ensures safety of an automated driving environment.

Described herein are methods of estimating a chance of precipitation in an area that include identifying one or more vehicles in the area and determining the likelihood of precipitation using telematics data for the one or more vehicles in the area. Also described herein are methods that include receiving telematics data from a plurality of vehicles, wherein the telematics data is associated with a location, analyzing the telematics data to identify vehicle events associated with one or more segments of road, analyzing weather information associated with the one or more segments of road, and determining a correlation between the weather information and the vehicle events.

A method for determining road surface conditions in a system with at least one vehicle and a data processing device. The vehicle exchanges data with the data processing device wirelessly. The vehicle has at least one sensor for determining measured values describing a road surface friction coefficient, and a computing unit. The data processing device includes a database, containing a road map having a plurality of route sections. The method includes determining measured values for a route section by the sensor, determining a first friction coefficient for the route section by the vehicle's computing unit, sending a data record, containing measured values and/or the first determined friction coefficient and a piece of information identifying the route section, to the data processing device, determining an average friction coefficient for the route section, sending the average friction coefficient determined for the route section to the vehicle, and determining the road surface condition.

A computer implemented method for determining the position of a vehicle, wherein the method comprises: determining at least one scan comprising a plurality of detection points, wherein each detection point is evaluated from a signal received at the at least one sensor and representing a location in the vehicle environment; determining, from a database, a predefined map, wherein the map comprises a plurality of elements in a map environment, each of the elements representing a respective one of a plurality of static landmarks in the vehicle environment, and the map environment representing the vehicle environment; matching the plurality of detection points and the plurality of elements of the map; determining the position of the vehicle based on the matching; wherein the predefined map further comprises a spatial assignment of a plurality of parts of the map environment to the plurality of elements, and wherein the spatial assignment is used for the matching.

A map information system includes: an in-vehicle device that executes automated driving control of a vehicle; and an external device having external map information used for the automated driving control. The in-vehicle device includes: a memory device in which map information is stored; and a control device configured to execute the automated driving control based on the map information stored in the memory device. The control device is further configured to: determine whether or not a takeover occurs during the automated driving control; set an upload target area including the takeover occurrence position, in a case where the takeover occurs during the automated driving control; and upload the map information regarding the upload target area to the external device. The external device updates the external map information based on the map information uploaded from the in-vehicle device.

An information processing device includes: a first storage unit configured to store a local map data set created or updated at a first time; a map information acquisition unit configured to acquire at least a part of a distribution map data set from a map data distribution system via a wireless communication network; a second storage unit configured to associate and store (i) data that is acquired by the map information acquisition unit, from among data constituting a first distribution map data set created or updated at a second time, and (ii) information indicating a first acquisition time when the data is acquired, or information indicating the second time; and a second determination unit configured to determine whether the map data distribution system has stored a second distribution map data set created or updated at a third time.

A method includes retrieving a map of a 3D geometry of an environment the map including a plurality of non-spatial attribute values each corresponding to one of a plurality of non-spatial attributes and indicative of a plurality of non-spatial sensor readings acquired throughout the environment, receiving a plurality of sensor readings from a device within the environment wherein each of the sensor readings corresponds to at least one of the non-spatial attributes and matching the plurality of received sensor readings to at least one location in the map to produce a determined sensor location.

Feedback for map information is based on an integrated navigation solution for a device within a moving platform using obtained motion sensor data from a sensor assembly of the device, obtained radar measurements for the platform and obtained map information for an environment encompassing the platform. An integrated navigation solution is generated based at least in part on the obtained motion sensor data using a nonlinear state estimation technique that uses a nonlinear measurement model for radar measurements. The map information is assessed based at least in part on the integrated navigation solution and radar measurements so that feedback for the map information can be provided.

A computer implemented method for determining the position of a vehicle, wherein the method comprises: determining at least one scan comprising a plurality of detection points, wherein each detection point is evaluated from a signal received at the at least one sensor and representing a location in the vehicle environment; determining, from a database, a predefined map, wherein the map comprises a plurality of elements in a map environment, each of the elements representing a respective one of a plurality of static landmarks in the vehicle environment, and the map environment representing the vehicle environment; matching the plurality of detection points and the plurality of elements of the map; determining the position of the vehicle based on the matching; wherein the predefined map further comprises a spatial assignment of a plurality of parts of the map environment to the plurality of elements, and wherein the spatial assignment is used for the matching.

Disclosed are aspects of a method, which is carried out in a vehicle, that includes downloading over-the-air from a host system a data collection target including a data value metric that is a function assigning a data value to a piece of data at a given point in time, which represents an amount of progress towards an atomic collection target. The method also includes collecting data from data sources in the vehicle over time while the vehicle is driving and recording the collected data in a storing module. The method additionally includes computing the data values of the recording data according to the data value metric and selecting, from the recording data, recording data snippets of high value within a time window based on the computed data values. The method further includes uploading only the selected recording data snippets of high value to the host system over-the-air.