Abstract:
The disclosure provides a method, a system, and a computer program product for updating map data. The method comprises obtaining vehicle sensor data associated with first spatial data and first temporal data related to one or more hazard-based event. The method may further include obtaining image data associated with second spatial data and second temporal data related to one or more hazard-based event. The method may further include combining the first spatial data with the second spatial data based on a match between the first spatial data and the second spatial data and between the first temporal data and the second temporal data respectively. The method may further include updating the map data based on the combining.
Abstract:
A system, a method and a computer program product are provided for evaluating quality of data, such as sensor data and map data, using a machine learning model. The system may include at least one memory configured to store computer executable instructions and at least one processor configured to execute the computer executable instructions to obtain first sensor features of the first sensor data associated with a road object in a first geographic region, first map features of the first map data associated with the road object and ground truth data associated with the road object. The processor may be configured to generate the machine learning model by configuring the ground truth data and calculating first information scores for each of the first sensor features and the first map features by recursively splitting each of the first sensor features and the first map features.
Abstract:
An approach is provided for machine learning of physical dividers. The approach, for instance, involves retrieving map data, sensor data, or a combination thereof for a segment of a road. The approach also involves retrieving ground truth data for the segment of the road. The ground truth data, for instance, indicates a true presence or a true absence of the physical divider on the segment of the road. The approach further involves processing the map data, the sensor, or a combination thereof and the ground truth data to train a machine learning model to predict the physical divider using the map data, the sensor data, or a combination thereof as an input. The approach further involves using the trained machine learning model to a generate a physical divider overlay of a map representation of a road network.
Abstract:
An approach is provided for prioritizing notification to one or more vehicles based on the ranking of one or more road links. The approach involves determining one or more road links that are associated with at least one curvature value greater than at least one curvature threshold value. The approach also involves determining humanized speed information and speed limit information for the one or more road links. The approach further involves processing and/or facilitating a processing of the at least one curvature value, the humanized speed information, and the speed limit information to determine danger level information for the one or more road links. The approach also involves causing, at least in part, a ranking of the one or more road links based, at least in part, on the danger level information. The approach further involves causing, at least in part, a prioritization of one or more notifications to one or more vehicles approaching or traveling the one or more road links based, at least in part, on the ranking of the one or more road links.
Abstract:
The disclosure provides a method, a system, and a computer program product for updating map data. The method comprises obtaining vehicle sensor data associated with first spatial data and first temporal data related to one or more hazard-based event. The method may further include obtaining image data associated with second spatial data and second temporal data related to one or more hazard-based event. The method may further include combining the first spatial data with the second spatial data based on a match between the first spatial data and the second spatial data and between the first temporal data and the second temporal data respectively. The method may further include updating the map data based on the combining.
Abstract:
An apparatus, method and computer program product are provided for providing a the map including a binary representation of a weather-based hazard. In one example, the apparatus receives data indicating a polygon defining a region being impacted by a weather condition and overlays the polygon on a tile map. The apparatus receives attribute data indicating one or more functional classes of one or more road portions within each tile of the tile map that is partially covered by the polygon and determines a subset of tiles within the tile map that defines the weather condition based on the attribute data.
Abstract:
An approach is provided for determining bicycle lane deviations for autonomous vehicle warning or operation. The approach, for example, involves retrieving probe data associated with a bicycle transportation mode. The approach also involves determining a plurality of probe points of the probe data that are map-matched outside of a bicycle lane. The approach further involves clustering the plurality of probe points into at least one location cluster. The approach further involves storing the one or more location clusters in a geographic database as respective one or more hazard areas where a plurality of bicycles deviates outside of the bicycle lane. By way of example, the approach can further involve using the at least one location cluster to perform at least one of providing a warning message or determining a driving parameter for an autonomous vehicle.
Abstract:
System, method and computer program products are provided for detecting an environmental zone, generating a time schedule of an environmental zone in a region and providing route navigation instructions. The method may include obtaining at least one observation associated with the environmental zone in a region. The method may further include determining a confidence value associated with the at least one observation in the region and detecting the environmental zone in the region based on the confidence value associated with the at least one observation. The detection of the environmental zone comprises determining either one of a presence or an absence of the environmental zone in the region. Further, the detection of the environmental zone may be used to generate a time schedule indicating presence or absence of the environmental zone in the region for different time intervals.
Abstract:
A method, apparatus and computer program product for activating a flood event warning are described herein. In the context of a method, a location may be identified as a flood prone location. Data relating to the flood prone location may be received from one or more remote devices. The method may determine a flood confidence for the flood prone location based upon the data. The method may identify an active flood event for the flood prone location based on the flood confidence and cause a flood event warning to be activated in an instance in which the active flood event is identified.
Abstract:
An apparatus, method and computer program product are provided for assessing geospatial aerial images for image processing. In one example, the apparatus receives a plurality of geospatial aerial images, where each of the plurality of geospatial aerial image data represents a zone within a map. The apparatus selects a bounding zone within the map for image processing and, in response to the bounding zone including a subset of the plurality of geospatial aerial images, the apparatus accepts or rejects the subset for the image processing based on one or more attributes of the subset. The one or more attributes is a resolution of each of the subset, an amount of area within the bounding zone covered by the subset, a clarity of each of the subset, an amount of gap or overlap between the subset, or a combination thereof.