Abstract: Embodiments described herein relate to anonymizing of trajectories of mobile devices. Methods may include: receiving an input chunk of probe data points, where the input chunk includes probe data points spanning an input duration, where the input chunk represents at least a first input portion of a trajectory; generating, based at least in part on the input chunk, an output chunk of one or more probe data points, where the output chunk includes one or more probe data points spanning an output duration, where the output duration is different from the input duration, where the output chunk represents at least an output portion of the trajectory, where the first input portion of the trajectory and the output portion of the trajectory share at least a common portion of the trajectory; and providing the output chunk of one or more probe data points to a location-based service provider.

Abstract: Embodiments described herein relate to anonymizing of trajectories of mobile devices through the obfuscation of stay points. Methods may include: receiving probe data points of a trajectory in real-time or near real-time from a probe apparatus as it travels along the trajectory; calculating, for each probe data point, a probability of the trajectory reaching a stay point within a predetermined distance; providing sequential sub-sets of probe data points of the trajectory to a location-based service provider in response to the sequential sub-sets of probe data points including probe data points having a probability failing to satisfy a predetermined value; and identifying a last sub-set of probe data points of the sequential sub-sets of probe data points to provide to the location-based service provider in response to identifying a probe data point having a probability of the trajectory reaching a stay point within the predetermined distance satisfying the predetermined value.

Abstract: Route information data records are received from a navigation system indicating road elements and maneuvers between a starting point and a destination point. An estimated time of arrival is established using the route information data records. A personalized correction value based on the road elements, maneuvers, and a driver profile is determined. A personalized time of arrival is calculated based on the estimated time of arrival value and the personalized correction value.

Abstract: An apparatus comprising a processor and memory including computer program code, the memory and computer program code configured to, with the processor, enable the apparatus at least to: determine a current location of a vehicle on a road network comprising a plurality of different paths of travel using respective recursive Bayesian filters for each of the different paths of travel, wherein each recursive Bayesian filter is configured to compare data received from a sensor on the vehicle with predetermined map data for the respective path of travel to calculate a likelihood of the vehicle being currently located on the respective path of travel and a probability distribution of possible locations along this path of travel.

Abstract: A plurality of instances of probe data are received and used to generate a plurality of probe trajectories. A set of selected probe trajectories is defined using spatial familiarity sampling wherein a familiarity score is determined for each instance of probe data of a probe trajectory based on a familiarity model corresponding to already selected probe trajectories. A least familiar familiarity score for a probe trajectory is identified from the familiarity scores determined for the probe trajectory and a determination of whether the probe trajectory is included in the set of selected probe trajectories is performed based on the least familiar familiarity score for the probe trajectory. Only the probe trajectories of the set of selected probe trajectories are map-matched. The map-matched probe trajectories are then used to generate traffic and/or map information/data which is provided to consumer apparatuses for use in performing navigation functions, for example.

Abstract: A method, apparatus, and computer program product are provided to reduce redundant data uploads, the method includes, for example, providing a collection indicator for a specific data type on a given road. The method further includes separating a plurality of data points for the specific data type collected during travel of a vehicle along the given road into a transmission group of data points and a non-transmission group of data points. The separating of the plurality of data points may be done by determining an amount of data points to be included in the transmission group by applying the collection indicator to the plurality of data points for the specific data type that are collected during travel of the vehicle along the given road. The method still further includes causing the transmission of the transmission group of data points.

Abstract: An apparatus including a processor and memory having computer program code, the memory and computer program code configured to, with the processor, enable the apparatus at least to: use a classification model to identify one or more anomalies between a monitored trajectory of a vehicle through a road network and predefined map data for the road network which are likely caused by errors in the predefined map data; and provide details of the one or more identified anomalies for use in obtaining additional data for the specific locations on the road network corresponding to the one or more identified anomalies in order to correct the errors in the predefined map data.

Abstract: An approach is provided for providing user control of historical mobility data accessed by a service related to a quality of the service to be delivered to the user. The approach involves receiving a request from the user to receive the service from a service provider. The quality of service is dependent on historical mobility data associated with the user. The approach also involves determining a first part of the historical mobility data that is to be provided to the service provider to receive the service. The approach further involves determining a second part of the historical mobility data that is predicted to increase the quality of service of the service. The approach further involves providing a user interface for the user to select between the first part, the second part, another part, or a combination thereof of the historical mobility data to provide to the service provider.

Abstract: A plurality of instances of probe data are received and used to generate a plurality of probe trajectories. A set of selected probe trajectories is defined using spatial familiarity sampling wherein a familiarity score is determined for each instance of probe data of a probe trajectory based on a familiarity model corresponding to already selected probe trajectories. A least familiar familiarity score for a probe trajectory is identified from the familiarity scores determined for the probe trajectory and a determination of whether the probe trajectory is included in the set of selected probe trajectories is performed based on the least familiar familiarity score for the probe trajectory. Only the probe trajectories of the set of selected probe trajectories are map-matched. The map-matched probe trajectories are then used to generate traffic and/or map information/data which is provided to consumer apparatuses for use in performing navigation functions, for example.

Abstract: An approach is provided for generating an optimized parking search route based on one or more other vehicle driving paths. The approach involves determining that a first vehicle has initiated a search for a parking space. The approach also involves determining a first detection and a second detection of a second vehicle by the first vehicle during the search. The approach further involves calculating a predicted route taken by the second vehicle based on a time difference between the first detection and the second detection. The approach further involves generating the parking search route for the first vehicle based on deprioritizing the predicted route taken by the second vehicle.

Abstract: An approach is provided for mobility-based language model adaptation for navigational speech interfaces. The approach involves receiving a word lattice resulting from a speech recognition process applied on a speech input received from a user via a navigational speech interface. The word lattice includes a respective speech recognition score for each word in the word lattice. The approach further involves adapting a language model comprising a plurality of location entities according to a mobility relevance and a search relevance of the plurality of location entities to the user. In one embodiment, the mobility relevance and the search relevance are determined by computing a probability of the user visiting the location entities associated with said each word after the user queries for said each word. The approach further involves initiating a re-scoring of said each word in the word lattice using the adapted language model to generate a speech recognition output.

Abstract: An apparatus receives at least one set of sensor data from at least one mobile device. The sensor data was measured at a particular site and comprises at least motion related sensor data. The apparatus selects a set of parameter values for a parametric site model from a plurality of possible sets of parameter values. The set of parameter values is selected which has the highest likelihood that the parametric site model configured with the set of parameter values correctly represents the particular site in view of the received at least one set of sensor data.

Abstract: A method, apparatus, and computer program product are provided in accordance with an example embodiment described herein for providing a recommendation for a parking strategy. A method may be provided for providing the recommendation for a parking strategy for a vehicle in vicinity of a link that includes: determining an availability metric for the link; determining a turnover metric of vehicles in the link; calculating, by a processor, a strategy metric based on a function of at least the availability metric and the turnover metric, for identifying a strategy for providing parking related recommendation, and providing data for indicating the identified strategy for parking to a user interface. The data for indication may include data for indicating a route for the vehicle on the user interface to navigate to a favorable parking spot in the vicinity of the link, in accordance with the identified strategy for parking.

Abstract: Embodiments described herein may provide a method for presenting a list of relevance-ranked milestone locations in a navigation system user interface. Methods may include: determining a current, map-matched location and a direction of travel; determining a plurality of milestone locations based on the current, map-matched location and the direction of travel; determining a priority ranking of the plurality of milestone locations; and providing for display of a subset of the plurality of milestone locations having the highest priority. Methods may optionally include providing for display of an estimated travel time to each of the milestone locations of the subset of the plurality of milestone locations, where the estimated travel time is based on a distance from the current, map-matched location and dynamic traffic awareness.

Abstract: Methods are provided for modeling mobility based on one or more devices of the user. Methods may include: receiving at least a portion of a first mobility model from a first device, where the first mobility model may be established based on learning algorithms performed on the first device; updating a shared mobility model to become a first shared mobility model based on the at least a portion of the first mobility model; providing the first shared mobility model to the first device; receiving at least a portion of a second mobility model from a second device, where the second mobility model may be established based on learning algorithms performed on the second device; updating the first shared mobility model to become a second shared mobility model based on the at least a portion of the second mobility model; and providing the second shared mobility model to the second device.

Abstract: Route information data records are received from a navigation system indicating road elements and maneuvers between a starting point and a destination point. An estimated time of arrival is established using the route information data records. A personalized correction value based on the road elements, maneuvers, and a driver profile is determined. A personalized time of arrival is calculated based on the estimated time of arrival value and the personalized correction value.

Abstract: An approach is provided for global voice-based entry of location information. The approach involves partitioning a global speech decoding graph into spatial partitions. The approach also involves determining key entities occurring in each spatial partitions to construct a combined set of key entities. The approach further involves creating a retrieval index to map the key entities in the combined set of key entities to a corresponding partition. A first partition, the combined set of key entities, and the retrieved index are stored in a memory of a device for processing a voice input signal. A second partition that is not in the memory of the device is retrieved based on the combined set of key entities and the retrieval index to automatically re-process the voice input signal when an out-of-vocabulary result is obtained from the first partition.

Abstract: Route information data records are received from a navigation system indicating road elements and maneuvers between a starting point and a destination point. An estimated time of arrival is established using the route information data records. A personalized correction value based on the road elements, maneuvers, and a driver profile is determined. A personalized time of arrival is calculated based on the estimated time of arrival value and the personalized correction value.

Abstract: Embodiments described herein may provide a method for identifying geo-tagged objects or events and estimating the probability that a vehicle path will intersect with the geo-tagged object or event. Methods may include: determining a first map-matched location and a second map-matched location; determining a plurality of road segments emanating from or leading to the first map-matched location, a portion of which connect between the first map-matched location and the second map-matched location; calculating at least one of a weight or a turn probability for turning onto a road segment for each road segment of the plurality of road segments; and determining, from the weight or the turn probability associated with each road segment of the portion of road segments that connect between the first map-matched location and the second map-matched location, a probability of a path taken between the first map-matched location and the second map-matched location.

Abstract: An approach is provided for parking availability detection based on vehicle trajectory information. A trajectory processing platform processes and/or facilitates a processing of trajectory data associated with at least one journey of at least one vehicle to determine at least one portion of the at least one journey that is associated at least one parking search by the at least one vehicle. The trajectory processing platform also determines one or more street segments associated with the at least one portion of the at least one journey. The trajectory processing platform further causes, at least in part, a classification of the one or more street segments as associated with the at least one parking search. The trajectory processing platform further determines parking availability information for the one or more street segments based, at least in part, on the trajectory data.