Abstract: The disclosure provides a system, and a method for quality estimation of a traffic congestion incident reported by traffic system based on the information from one or more probe vehicles. The system is configured to identify one or more road segments and location information associated with the traffic congestion incident reported by traffic system based on the information from the one or more probe vehicles. A probe-based space-time diagram is generated based on the identified one or more road segments and location information associated with the traffic congestion incident reported by traffic system based on the information from the one or more probe vehicles. Ground truth is inferred for the traffic congestion incident. The generated probe-based space-time diagram is compared with the inferred ground truth for quality estimation of the traffic congestion incident reported by traffic system based on the information from the one or more probe vehicles.

Abstract: A method, apparatus, and computer program product are provided for evaluating traffic conditions across a plurality of lanes to determine whether it is advantageous to travel in the restricted travel lane. Methods may include: receiving a plurality of probe data points, each probe data point received from a probe apparatus of a plurality of probe apparatuses; map-matching the probe data points of the plurality of probe apparatuses to a road segment of a road network; determining a distance of each probe data point from a centerline of the road segment; determining a range of distances for the probe data points from the centerline of the road segment; dividing the range of distances into a predefined number of spatial bins; identifying a speed associated with each spatial bin; and determining a restricted travel lane benefit based on an analysis of the speeds of each spatial bin.

Abstract: The disclosure provides a system, and a method for quality estimation of a traffic congestion incident reported by traffic system based on the information from one or more probe vehicles. The system is configured to identify one or more road segments and location information associated with the traffic congestion incident reported by traffic system based on the information from the one or more probe vehicles. A probe-based space-time diagram is generated based on the identified one or more road segments and location information associated with the traffic congestion incident reported by traffic system based on the information from the one or more probe vehicles. Ground truth is inferred for the traffic congestion incident. The generated probe-based space-time diagram is compared with the inferred ground truth for quality estimation of the traffic congestion incident reported by traffic system based on the information from the one or more probe vehicles.

Abstract: 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.

Abstract: 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.

Abstract: A method for asset identification string error detection can include receiving an asset identification string corresponding to an asset and aggregating data associated with the asset from multiple sources. The method can include creating one or more probabilistic tables linking the aggregated data to the asset and determining a likelihood that at least a portion of the asset identification string is correct based on the probabilistic tables. The method can indicate that the asset identification string includes an error when the likelihood is less than a selected threshold and otherwise indicate that the asset identification string is correct when the likelihood is greater than or equal to the selected threshold.

Abstract: A technique is directed to methods and systems for customer accounts association in multilingual environments. The data aggregation system can utilize a machine learning-based algorithm that identifies all the accounts belonging to the same customer based on relevant account information. Inputs can include customer name, customer address, email, phone number, type of industry, or type of fleet. The system utilizes feature creation and a coarse pass to identify likely account pairs, perform account association by preparing an input core dataset, and update the core dataset at a predefined time interval with identified new or changed records.

Abstract: A method for asset identification string error detection can include receiving an asset identification string corresponding to an asset and aggregating data associated with the asset from multiple sources. The method can include creating one or more probabilistic tables linking the aggregated data to the asset and determining a likelihood that at least a portion of the asset identification string is correct based on the probabilistic tables. The method can indicate that the asset identification string includes an error when the likelihood is less than a selected threshold and otherwise indicate that the asset identification string is correct when the likelihood is greater than or equal to the selected threshold.

Abstract: A method for object identification using multiple images. The method includes training an object identification model. Training the model includes collecting a training images for each of a plurality of objects, labeling each of the plurality of training images with a corresponding one of a plurality of object identifiers, and training a neural network with the plurality of labeled training images. At least two target images of a target object are receive and fed into the trained object identification model. The method further includes receiving, from the trained object identification model, for each of the at least two target images, an object identifier corresponding to the target object and a probability that the object identifier corresponds to the target object. A similarity value between the at least two target images is computed and the probabilities for the at least two target images are combined in proportion to the similarity value.

Abstract: The present disclosure is directed to systems and methods for updating asset ownership for telematics-enabled machinery. In some embodiments, the updating asset ownership system comprises asset entities that transmit telemetry data. A communication interface of the updating asset ownership system can receive the telemetry data. An asset ownership data store of the updating asset ownership system can be configured to store asset owner data that identify designated owners associated with the asset entities. An asset ownership comparator of the updating asset ownership system can process the received telemetry data. Based on the processing, the asset ownership comparator can update designated owners of asset entities stored in the asset ownership data store.

Abstract: 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.

Abstract: A method, apparatus, and computer program product are provided for evaluating traffic conditions across a plurality of lanes to determine whether it is advantageous to travel in the restricted travel lane. Methods may include: receiving a plurality of probe data points, each probe data point received from a probe apparatus of a plurality of probe apparatuses; map-matching the probe data points of the plurality of probe apparatuses to a road segment of a road network; determining a distance of each probe data point from a centerline of the road segment; determining a range of distances for the probe data points from the centerline of the road segment; dividing the range of distances into a predefined number of spatial bins; identifying a speed associated with each spatial bin; and determining a restricted travel lane benefit based on an analysis of the speeds of each spatial bin.

Abstract: A method for object identification using multiple images. The method includes training an object identification model. Training the model includes collecting a training images for each of a plurality of objects, labeling each of the plurality of training images with a corresponding one of a plurality of object identifiers, and training a neural network with the plurality of labeled training images. At least two target images of a target object are receive and fed into the trained object identification model. The method further includes receiving, from the trained object identification model, for each of the at least two target images, an object identifier corresponding to the target object and a probability that the object identifier corresponds to the target object. A similarity value between the at least two target images is computed and the probabilities for the at least two target images are combined in proportion to the similarity value.

Abstract: The present disclosure is directed to systems and methods for updating asset ownership for telematics-enabled machinery. In some embodiments, the updating asset ownership system comprises asset entities that transmit telemetry data. A communication interface of the updating asset ownership system can receive the telemetry data. An asset ownership data store of the updating asset ownership system can be configured to store asset owner data that identify designated owners associated with the asset entities. An asset ownership comparator of the updating asset ownership system can process the received telemetry data. Based on the processing, the asset ownership comparator can update designated owners of asset entities stored in the asset ownership data store.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.