Abstract: A method, apparatus, and computer program product are provided for organizing pedestrian movement data. The method includes receiving a set of travel data. The set of travel data includes one or more pedestrian trips including an origin and a destination. The method also includes generating a pedestrian flow matrix. The pedestrian flow matrix has one or more pedestrian flow compartments. The method further includes assigning at least one of the pedestrian trips to one or more of the pedestrian flow compartments based on the origin and the destination of the given pedestrian trip. Corresponding apparatuses and computer program products are also provided.

Abstract: A method, apparatus, and computer program product are provided for providing merging assistance for a vehicle. The method includes capturing a vehicle speed of the vehicle travelling in a lane of roadway. The method also includes receiving adjacent vehicle data relating to an adjacent vehicle in an adjacent lane. The method further includes receiving adjacent lane data relating to a speed of one or more vehicles in the adjacent lane. The method still further includes generating merger information for the vehicle based on the vehicle speed, the adjacent vehicle data, and the adjacent lane data. A corresponding apparatus and computer program product are also provided.

Abstract: A method, apparatus and computer program product are provided to determine a measure of probe quality, such as a level of accuracy with which the location of a probe point is defined. In the context of a method and for a plurality of probe points, a distance is determined between a respective probe point and a line representative of a link. For the plurality of probe points, the method also includes determining a difference between a bearing of the respective probe point and a bearing of the link. The method further includes determining the measure of probe quality based upon a product of a representation of the distance between the plurality of probe points and the line representative of the link and a representation of the difference between the bearing of the plurality of probe points and the bearing of the link.

Abstract: A plurality of instances of probe data are received. Each instance of probe data corresponds to travel of a vehicle apparatus along a first segment, comprises an indication of at least one parameter characterizing the travel of the vehicle apparatus along the first segment. The at least one parameter is extracted from the instances of probe data to generate a distribution of parameters. One or more clusters of instances of probe data are identified based on the distribution of parameters. Responsive to identifying two or more clusters, a representative at least one parameter is determined for each cluster, and an element of a data structure is modified based thereon for each cluster. Responsive to identifying only one cluster of instances of probe data, the data structure is not modified based on the cluster. A navigation application is configured to use the data structure to perform a navigation function.

Abstract: A method is disclosed, performed by at least one apparatus, the method comprising: obtaining probe data comprising a plurality of probe samples of a multi-dimensional probe sample space, the probe data being representative of a potentially multi-modal traffic scenario; performing a cluster analysis for at least a part of the probe samples of the probe data, said cluster analysis comprising: associating at least a part of the probe samples with respective clusters, each cluster being representative of a mode of the potentially multi-modal traffic scenario.

Abstract: An approach is provided for automatically detecting a merge lane traffic jam. The approach involves, for example, determining a plurality of road links in proximity to a merge point comprising a highway and a ramp. The method also involves processing probe data collected from the plurality of road links to classify the plurality of road links, one or more sublinks of the plurality of road links, or a combination thereof into at least one of a highway upstream class, a merging area class, a highway downstream class, a ramp downstream class, and a ramp upstream class. The method further involves determining vehicle speed data for the highway upstream class, the merging area class, the highway downstream class, the ramp downstream class, the ramp upstream class, or a combination thereof. The method further involves automatically determining an occurrence of the merge lane traffic jam based on the vehicle speed data.

Abstract: System and methods are provided for generating lane aware clusters for vehicle to vehicle communications. A vehicle uses lane level map matching to obtain a current travelling lane. Vehicles that are within a proximity radius exchange data such as location, lane, speed, direction. Sub clusters are creating with vehicles driving on the same lane based on proximity distance. The sub clusters are merged into one cluster based on sub cluster similarity in terms of spatial proximity, average speed, and direction.

Abstract: An approach is provided for an unknown moving object detection system. The approach, for instance, involves capturing a plurality of unknown object events indicating an unknown object detected by one or more computer vision systems. The approach also involves clustering the plurality of unknown object events into a plurality of clusters based on one or more clustering parameters. The approach further involves selecting at least one cluster of the plurality of clusters based on a selection criterion. The approach further involves determining at least one operating scenario for the one or more computer vision systems based on a combination of the one or more clustering parameters associated with the selected at least one cluster.

Abstract: A method is provided for establishing determining lane-level route guidance, and more particularly, to establishing recommended lane-level guidance between an origin and a destination based on a safe, efficient, or popular path. Methods may include receiving a plurality of probe data points from a plurality of probe apparatuses, each probe apparatus traveling between a respective origin and destination pair; determining a lane-level maneuver pattern for each probe apparatus between the origin and the destination; providing for storage of the lane-level maneuver patterns for each probe apparatus in the memory; grouping together lane-level maneuver patterns for probe apparatuses having an origin and destination pair within a predefined similarity of origin and destination pairs of other apparatuses; and generating a lane-level maneuver pattern for each group based on at least one of a popularity, efficiency, or relatively safe lane-level maneuver pattern for the respective group.

Abstract: One or more lane level dynamic profiles are received. Each lane level dynamic profile comprises at least one dynamic parameter corresponding to a lane of a traversable network. A lane level network graph is received for at least a portion of the traversable network. A cost is assigned to the lane based on the at least one dynamic parameter corresponding to the lane. A routing or navigation function is performed using the cost assigned to the lane and the lane level network graph to generate routing information. The routing information is provided such that a mobile apparatus receives the routing information.

Abstract: A method, apparatus and computer program product are provided to identify a lane level traffic surprise. In the context of a method, historical lane level traffic information is received including a representation of a speed of travel along a respective lane of a link. The method also receives recent lane level traffic information including a representation of a speed of travel along the respective lane of the link. The recent lane level traffic information is indicative of more recent traffic conditions, than the traffic conditions represented by at least some of the historical lane level traffic information. The method further includes determining a representation of a difference between representations of the speed of travel provided by the historical lane level traffic information and the recent lane level traffic information, and identifying the lane level traffic surprise based upon representation of the difference.

Abstract: An apparatus for matching probe measurements to a path in a geographic location includes a receiver, a window manager, a location generator, a path calculator, and an output. The receiver is configured to receive a stream of probe measurements. The window manager is configured to fill a window with the measurements, to select an additional measurement from the stream, and to select an oldest measurement in the window. The location generator is configured to generate candidate locations for the measurements in the window and the additional measurement. The path calculator is configured to match the oldest measurement to a candidate location. The output is configured to output a path-matched probe measurement based on the oldest measurement and the candidate location matched to the oldest measurement.

Abstract: A method is disclosed, performed by at least one apparatus, the method comprising: obtaining probe data comprising a plurality of probe samples of a multi-dimensional probe sample space, the probe data being representative of a potentially multi-modal traffic scenario; performing a cluster analysis for at least a part of the probe samples of the probe data, said cluster analysis comprising: associating at least a part of the probe samples with respective clusters, each cluster being representative of a mode of the potentially multi-modal traffic scenario.

Abstract: An approach is provided for creating an origin-destination matrix from probe trajectory data. The approach includes determining, via an outdoor positioning system, that at least one probe device has entered a point-of-interest (POI). The approach also includes initiating an indoor positioning system to determine indoor location data associated for the at least one probe device while the at least one device is within the POI. The approach further includes processing the indoor location data to generate an origin-destination (OD) matrix. The OD matrix represents an indoor movement of the at least one probe device among a plurality of sub-POIs located within the POI indicated by the indoor location data. The approach further includes providing the OD matrix as an output.

Abstract: An approach is provided for automatically detecting a merge lane traffic jam. The approach involves, for example, determining a plurality of road links in proximity to a merge point comprising a highway and a ramp. The method also involves processing probe data collected from the plurality of road links to classify the plurality of road links, one or more sublinks of the plurality of road links, or a combination thereof into at least one of a highway upstream class, a merging area class, a highway downstream class, a ramp downstream class, and a ramp upstream class. The method further involves determining vehicle speed data for the highway upstream class, the merging area class, the highway downstream class, the ramp downstream class, the ramp upstream class, or a combination thereof. The method further involves automatically determining an occurrence of the merge lane traffic jam based on the vehicle speed data.

Abstract: A system, a method, and a computer program product for generating maneuver data for a vehicle are disclosed herein. The system comprises at least one non-transitory memory configured to store computer program code instructions and at least one processor configured to execute the computer program code instructions to obtain direction share data from at least one mobile device, wherein the direction share data comprises immediate route data and immediate direction data associated with the corresponding at least one mobile device, determine localized direction share data for the at least one mobile device from the direction share data, wherein the localized direction share data indicates location, exact lane and direction of the corresponding at least one mobile device, and generate the maneuver data for the vehicle, based on the localized direction share data and map data, using at least one machine learning model.

Abstract: An approach is provided for an unknown moving object detection system. The approach, for instance, involves capturing a plurality of unknown object events indicating an unknown object detected by one or more computer vision systems. The approach also involves clustering the plurality of unknown object events into a plurality of clusters based on one or more clustering parameters. The approach further involves selecting at least one cluster of the plurality of clusters based on a selection criterion. The approach further involves determining at least one operating scenario for the one or more computer vision systems based on a combination of the one or more clustering parameters associated with the selected at least one cluster.

Abstract: System and methods are provided for generating lane aware clusters for vehicle to vehicle communications. A vehicle uses lane level map matching to obtain a current travelling lane. Vehicles that are within a proximity radius exchange data such as location, lane, speed, direction. Sub clusters are creating with vehicles driving on the same lane based on proximity distance. The sub clusters are merged into one cluster based on sub cluster similarity in terms of spatial proximity, average speed and direction.

Abstract: An approach is provided for inferring vehicle location data using a reference vehicle. The approach includes processing sensor data collected from one or more sensors of the reference vehicle to identify a relative location of one or more vehicles represented in the sensor data, wherein the relative location is with respect to the reference vehicle. The approach also includes computing a vehicle location of the one or more vehicles based on the relative location and a reference location of the reference vehicle. The approach also includes providing the vehicle location of the one or more vehicles as an output comprising the inferred vehicle location data.

Abstract: System and methods are provided for calculating a lane maneuver delay for different lane maneuvers and different road segments at different times of the day to generate a predicted lane maneuver delay for use in routing and navigation services. A lane-level map-matcher identifies the lane a vehicle is driving on using positional sensors. Sensor data is obtained from vehicle sensors using the left-turn and right-turn signal lights sensor. A lane maneuver delay value is calculated from the time period a left-turn or right-turn signaling light was kept on before a vehicle completed a lane maneuver. The lane maneuver delay values are aggregated to generate a predicted lane maneuver delay that may be used in lane level routing instructions.