A computer-implemented method for controlling a vehicle includes receiving, via a processor, from two or more IX control devices disposed at a two or more stationary positions having known latitudes longitudes and orientations, first sensory data identifying the position and dimensions of a feature in a mapped region. The processor generates a plurality of IX nodes based on the first sensory data received from the IX control devices, and receives LiDAR point cloud that includes LiDAR and other vehicle sensory device data such as Inertial Measurement Unit (IMU) data received from a Vehicle (AV) driving in the mapped region. The LiDAR point cloud includes a simultaneous localization and mapping (SLAM) map having second dimension information and second position information associated with the feature in the mapped region. The processor generates, without GPS and/or real-time kinematics information, an optimized High-Definition (HD) map having Absolute accuracy using batch optimization and map smoothing.

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.

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.

Disclosures herein may be directed to a method, technique, or apparatus directed to a computer-assisted or autonomous driving (CA/AD) vehicle that includes a system controller, disposed in a first CA/AD vehicle, to manage a collaborative three-dimensional (3-D) map of an environment around the first CA/AD vehicle, wherein the system controller is to receive, from another CA/AD vehicle proximate to the first CA/AD vehicle, an indication of at least a portion of another 3-D map of another environment around both the first CA/AD vehicle and the another CA/AD vehicle and incorporate the at least the portion of the 3-D map proximate to the first CA/AD vehicle and the another CA/AD vehicle into the 3-D map of the environment of the first CA/AD vehicle managed by the system controller.

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.

Systems and methods of collaborative localization for a vehicle are provided. In particular, one or more vehicles that are able to localize themselves with high accuracy may transmit timestamped localization information (i.e. localization packets) to a nearby vehicles which lack high-accuracy localization sensors. Each localization packet may include the location of the transmitting vehicle with respect to a global reference frame. Upon receiving the localization packets, a vehicle may use radiolocation techniques to estimate its location relative to the transmitting vehicle(s). Based on this estimation and the information in the localization packets, the vehicle may then estimate its location with respect to the global reference frame with a high degree of accuracy.

A display device includes a display that displays a map based on map data and Hypertext Markup Language data, a communicator that obtains the map data through Hypertext Transfer Protocol communication, and a display controller that updates, based on the map data obtained by the communicator and corresponding to location data obtained at predetermined time intervals, the map displayed on the display.

A detector detects an overall fill level of a receiving vehicle. A mobile device on the receiving vehicle includes a mobile application that receives and displays the overall fill level of the receiving vehicle. The overall fill level can be overlaid on a geographic map that shows locations of multiple receiving vehicles, in which case an overall fill level indicator for each receiving vehicle is displayed on the geographic map as well.

A data updating device sets, with respect to map data in which road links are represented as line segment sequences, a plurality of first straight lines extending in a first direction and a plurality of second straight lines extending in a second direction that intersects with the first direction, to thereby generate mesh map data. Then, the data updating device sets a set L of points or line segments that represent the update location, sets a set V including a plurality of first straight lines, and sets a set H including a plurality of second straight lines. Then, the data updating device sets the state of each mesh based on the set L, the set V, and the set H.

A map management system includes: at least one cloud server including a first processor configured to manage map data for a preset area; a plurality of edge servers, each edge server including a second processor configured to manage map data for a preset area; at least one vehicle including a third processor configured to collect raw data for updating map data during traveling; and a plurality of blockchains including the at least one cloud server and the plurality of edge servers.