Abstract:
A method, system, and computer program product is provided, for example, for matching a road sign observation information on a map application. The method may include receiving the road sign observation information. The method may further include identifying a plurality of candidate links based on a first distance between a location of the road sign observation information detection and a plurality of shape points. Additionally, the method may include calculating a heading difference between each of the plurality of candidate links and the location of the road sign observation information detection. Furthermore, the method may include identifying one or more qualified links from the plurality of candidate links, wherein the heading difference between each of the one or more qualified links from the plurality of candidate links and the location of the road sign observation information detection is within a predetermined heading difference threshold. Also, the method may include matching the road sign observation information to at least one of the one or more qualified links based on a second distance. Finally, the method may include changing the map-matched link from the candidate link to its downstream link if the road sign is too close to the end of the map-matched candidate link.
Abstract:
An approach is provided for traffic sign learning. The approach involves, for example, receiving a plurality of traffic sign observations generated using sensor data collected from a plurality of vehicles. Each of the plurality of traffic sign observations includes location data and sign property data for an observed traffic sign corresponding to said each of the plurality of traffic sign observations. The approach also involves clustering the plurality of traffic speed sign observations into at least one cluster based on the location data and the sign property data. The approach further involves determining a learned sign for the at least one cluster, and determining a learned sign value indicated by the learned sign based on the location data, the sign property data, or a combination of the plurality of traffic sign observations aggregated in the at least one cluster.
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 publishing a road event message according to a hysteresis. For example, the approach involves processing a road report to determine a road event associated with a geographic location and a confidence metric of the road event. The approach also involves initiating a publishing of a road event message to indicate the road event for the geographic location based on determining that the confidence metric is greater than an upper threshold of a hysteresis. The approach further involves processing one or more other road reports to update the confidence metric of the road event. The approach further involves initiating a cancelling of the road event message based on determining that the updated confidence metric is less than a lower threshold of the hysteresis.
Abstract:
An approach is provided for triggering vehicle sensors based on human accessory detection. The approach involves receiving a location of a detection of a human accessory object in a travel network. The human accessory object is a physical object associated with a probability that a human or an animal is within a vicinity of the human accessory object. The approach also involves generating a location-based record of the human accessory object in a map database based on the location. The approach further involves a sensor of a vehicle being activated to detect the human or the animal when the vehicle is detected to enter a geographic area of the travel network associated with the location-based record of the human accessory object.
Abstract:
An approach is provided for processing and transmitting sensor data in a bandwidth efficient manner. The approach involves causing, at least in part, a specification of one or more prioritization attributes for one or more sensors associated with at least one transmitting entity. The approach further involves processing and/or facilitating a processing of the one or more prioritization attributes to determine whether to cause, at least in part, (a) a transmission of sensor data associated with the one or more sensors to at least one receiving entity, (b) a caching of the sensor data prior to a batch transmission of the sensor data to the at least one receiving entity, or (c) a combination thereof.
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:
An approach is provided for processing and transmitting sensor data in a bandwidth efficient manner. The approach involves causing, at least in part, a specification of one or more prioritization attributes for one or more sensors associated with at least one transmitting entity. The approach further involves processing and/or facilitating a processing of the one or more prioritization attributes to determine whether to cause, at least in part, (a) a transmission of sensor data associated with the one or more sensors to at least one receiving entity, (b) a caching of the sensor data prior to a batch transmission of the sensor data to the at least one receiving entity, or (c) a combination thereof.