Here Global B.v.

Marcelo Savignano

Daniel Schmidt

Alexander Maryanovsky

Marina Ousov Fridin

Yelena Shnaider

Inna Branevich

Ofri Rom

Ron Begleiter

An approach is provided for discovery of semantic nodes for map-based dynamic location sampling. The approach, for instance, involves identifying a semantic node occurring on a road segment. The semantic node is a point of interest on or near the road segment that is different from beginning node and end node of the road segment. The approach also involves calculating an estimated time of arrival at the semantic node based on historical traversal time data for the road segment. The approach further involves determining a sampling rate for a location sensor of vehicle traveling the road segment based on the estimated time of arrival. The approach further involves configuring the location sensor to collect location data using the sampling rate.

Method and apparatus for discovery of semantic nodes for map-based dynamic location sampling

An approach is provided for path recovery when using map-based dynamic location sampling. The approach, for instance, involves initiating a capture of a current location of a vehicle on a road segment by a location sensor based on a keep-alive sampling rate. The location sensor is configured to operate at a sampling rate that is reduced from a default sampling rate in addition to the keep-alive sampling rate. The approach also involves determining a predicted location of the vehicle based on an estimated time of arrival of the vehicle at an end node of the road segment. The estimated time of arrival is based on historical traversal time data for the road segment. The approach further involves reconfiguring the location sensor to operate at the default sampling frequency based on determining that the predicted location differs from the current location by more than a threshold distance.

Method and apparatus for path recovery when using map-based dynamic location sampling

An approach is provided for map-based dynamic location sampling. The approach, for instance, involves calculating an estimated time of arrival at an end node of a road segment from a beginning node of the road segment based on historical traversal time data for the road segment. The approach also involves determining a sampling rate for a location sensor of a vehicle traveling the road segment based on the estimated time of arrival. The approach further involves configuring the location sensor to collect location data using the sampling rate.

Method and apparatus for map-based dynamic location sampling

An approach is provided for recommending services based on map-based dynamic location sampling. The approach, for instance, involves determining a predicted location of a vehicle on a road segment based on an estimated time of arrival at an end node of the road segment. The approach also involves calculating a difference between the predicted location and an actual location sensed by a location of the vehicle. The approach further involves recommending a service for installation on or near the road segment based on the difference.

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Berlin, Germany

Marcelo Savignano