Here Global B.v.

Kyle Jackson

Arnold Sheynman

Daniela Radakovic

James Adeyemi Fowe

Leon Stenneth

Gavril Adrian Giurgiu

Mitchell McCuiston

Bruce A Bernhardt

Sam Radomy

Corrine Bradley

Corinne Bradley

An approach is provided for accurate travel time prediction. The approach involves, for example, determining probe data collected within a threshold proximity of a vehicle location and a pickup location. The probe data may be collected, for example, from a location sensor of at least one probe vehicle that has previously traversed the vehicle location and the pickup location. The approach also involves processing the probe data to identify a travel time of a route taken by the at least one probe vehicle from the vehicle location to the pickup location. The approach also involves providing the travel time as an output indicating a wait time for a vehicle at the vehicle location to reach the pickup location.

Method and apparatus for ridesharing pickup wait time prediction

A method, apparatus, and non-transitory computer readable storage medium for traffic report certainty estimation. The approach may include determining at least one data input to a traffic model for generating a traffic report estimation for a road segment. The approach may also involve determining at least one input characteristic value associated with the at least one data input based, at least in part, on probe data collected from one or more sensors of at least one probe device. The approach may further involve determining a coefficient of certainty value from a certainty table based on the at least one input characteristic value, wherein the certainty table respectively maps one or more value intervals of the at least one input characteristic value to a pre-assigned coefficient of certainty value, and providing the coefficient of certainty value as an output associated with the traffic report.

Method and apparatus for traffic report certainty estimation

A method, apparatus, and computer program product are provided for detecting changes in road traffic conditions based on vehicle probe data. Methods may include: receiving a plurality of probe data points; map-matching probe data points of the plurality of probe apparatuses to road segments of a candidate road of a road networks; for a plurality of time epochs, cluster probe speeds map-matched to road segments of the candidate road according to a clustering algorithm; establishing centroid speeds corresponding to clusters of probe speeds; spatially grouping said road segments according to probe-to-cluster mapping; and providing a road traffic condition change message in response to a difference between centroid speeds along the candidate road exceeding a predefined threshold, where the road traffic condition change message includes at least information about said road segment groups that correspond to said clusters.

Method, apparatus, and computer program product for detecting changes in road traffic condition

Precision traffic flow indication may involve receiving device data over a period of time representing a plurality traffic flow readings associated with a road involving a plurality of subsections. Calculating traffic flows and determining road subsections having similar traffic flows may also be involved. Also, indicating a different traffic flow level for a first subsection and a second subsection of road may be involved.

Precision traffic indication

An approach is provided for state classification for a travel segment with multi-modal speed profiles. A traffic processing platform processes and/or facilitates a processing of probe data associated with at least one travel segment to determine that probe data indicates a plurality of speed profiles. The plurality of speed profiles represent one or more observed clusters of speed states. The traffic processing platform also determine that the at least one travel segment exhibits a multi-modality with respect to travel speed based, at least in part, on the plurality of speed profiles. The traffic processing platform then determines at least one likely sequence of speed states for traversing the at least one travel segment based, at least in part, on the one or more observed clusters of speed states and state transition probability information, wherein the state transition probability information represents one or more probabilities for transitioning among the plurality of speed states and causes, at least in part, a classification of at least one hidden state of the at least one travel segment based, at least in part, on the at least one likely sequence of speed states.

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Chicago, IL, United States of America

Kyle Jackson