Here Global B.v.

Alex Averbuch

Leon Stenneth

Amarnath Nayak

Gavril Adrian Giurgiu

Dongwook Jang

Bruce A Bernhardt

Eric Linder

Jingwei Xu

Anton Anastassov

Advait Mohan Raut

Joshua Thompson

Vladimir Boroditsky

Ram Marappan

Xiang Liu

Robert Camp

Kun Lee

An approach for traffic incident verification involves receiving a traffic message channel (TMC) message indicating a traffic incident. The TMC message indicates an extent of the traffic incident in a road graph using TMC location code(s)/offset(s). The approach also involves matching the TMC location code(s)/offset(s) to a first set of map road link(s) and offset(s) of a geographic database, determining sensor data collected from vehicle(s) travelling within the road graph. The sensor data indicates the extent as location point(s) of topology segment(s) (TSs) and TS offset(s), matching the location point(s) of the TS(s) and TS offset(s) to a second set of map road link(s) and offset(s) of the geographic database, determining an intersection set between the first and second sets, and initiating a confirmation of the traffic incident reported in the TMC message based on the sensor data of the location point(s) of the TSs in the intersection set.

Method, apparatus, and system for traffic incident verification

An apparatus, method and computer program product are provided for providing a tire pressure analysis. In one example, the apparatus receives first sensor data indicating a first tire pressure change associated with a first vehicle and causes a prediction model to generate a predicted cause of the first tire pressure change based on the first sensor data. The prediction model is trained based on historical data, the historical data defining a plurality of tire pressure signatures. Each of the plurality of tire pressure signatures correlates a cause of a second tire pressure change associated with a second vehicle to second sensor data indicating one or more tire pressure levels of the second vehicle over a period in which a wheel of the second vehicle completes a revolution. The apparatus further causes a notification of the predicted cause at a user interface associated with the first vehicle.

Apparatus and methods for providing tire pressure analysis

A system, a method, and a computer program product may be provided for processing event data. For example, event data relating to an occurrence of an event corresponding to a first tile is received, and a first count value associated with the received event data is determined. A threshold count value associated with the event within the first tile is obtained, and dynamic switching between a link-based processing and a tile-based processing is performed, based on a comparison between the first count value and the threshold count value, wherein on determining the first count value to be greater than the threshold count value, the tile-based processing is performed, and on determining the first count value to be lesser than the threshold count value, the link-based processing is performed.

System and method for processing event data

Embodiments described herein may provide a method for identifying the location of a hazard, evaluating how long that hazard is likely to be present at the location, and providing an indication of the time to live of the hazard. Methods may include: receiving an indication of a hazard event, where the hazard event includes a timestamp and a location; map matching the location of the hazard event to a map-matched road segment; determining a time to live of the hazard event based, at least in part, on the timestamp and the map-matched road segment; providing an indication of the time to live of the hazard event as at least one of a database entry or a map user interface element; and providing for at least one of route guidance or navigational assistance based, at least in part, on the time to live of the hazard event.

Method, apparatus and computer program product for estimating hazard duration

A method, apparatus and computer program product for activating a flood event warning are described herein. In the context of a method, a location may be identified as a flood prone location. Data relating to the flood prone location may be received from one or more remote devices. The method may determine a flood confidence for the flood prone location based upon the data. The method may identify an active flood event for the flood prone location based on the flood confidence and cause a flood event warning to be activated in an instance in which the active flood event is identified.

Method and apparatus for generating a flood event warning for a flood prone location

An approach is provided for estimating false positive reports of detectable road events. For example, the approach involves determining a first number of road reports from a fleet of vehicles, and operating in a geographic area during a first time period and a second number of road reports from the fleet operating in the geographic area during a second time period. The first number of road reports and the second number of reports relate to a road event detected by vehicle sensors. The approach further involves computing a difference between the first number and the second number. The approach further involves determining a percentage of defective vehicles in the fleet based on the difference. The defective vehicles are defective with respect to a detection of the road event. The approach further involves providing the percentage of defective vehicles as an output.

Method and apparatus for estimating false positive reports of detectable road events

A method, apparatus and computer program product for determining a rain event warning are described herein. In the context of a method, an indication of the rain event warning for one or more locations may be received. The method may obtain, for a respective rain event warning, sensor data corresponding to a weather condition within a region that includes the location with which the respective rain event warning is associated. The method may evaluate the sensor data to determine whether the sensor data is indicative of the weather condition (e.g., rain). The method may determine a rain event warning confidence based at least in part on evaluation of the sensor data. The method may cause the rain event warning to be published in an instance in which the rain event warning confidence satisfies a confidence threshold.

Method and apparatus for verifying rain event warnings

A system, a method and a computer program product are provided for evaluating quality of data, such as sensor data and map data, using a machine learning model. The system may include at least one memory configured to store computer executable instructions and at least one processor configured to execute the computer executable instructions to obtain first sensor features of the first sensor data associated with a road object in a first geographic region, first map features of the first map data associated with the road object and ground truth data associated with the road object. The processor may be configured to generate the machine learning model by configuring the ground truth data and calculating first information scores for each of the first sensor features and the first map features by recursively splitting each of the first sensor features and the first map features.

Method and system to generate machine learning model for evaluating quality of data

A system is disclosed for determining a driving direction. The system may include a memory configured to store computer-executable instructions; and at least one processor configured to execute the computer-executable instructions to obtain sensor data associated with a vehicle. The sensor data may include at least location data of the vehicle and lateral position data of the vehicle. Further, the processor is configured to execute the computer-executable instructions to identify a link associated with the sensor data, based on the location data and map data. Furthermore, the processor is configured to execute the computer-executable instructions to calculate half width data associated with the link based on the lateral position data and determine the driving direction for the vehicle based on the half width data, the lateral position data, and vehicle width data.

System and method for determining a driving direction

A method is provided for verifying and/or updating map geometry based on a probe data. A method may include: receiving probe data from a plurality of probes within a region, where the probe data includes at least one of heading information and location information for each probe data point; matching the probe data to a link segment to generate map-matched probe data; calculating a difference between the at least one of heading information and location information of the map-matched probe data points and of the link segment; determining a statistical mean of the data; determining an error of the statistical mean of the data; and flagging the link segment for manual review in response to the statistical mean being greater than the error of the statistical mean multiplied by a biasing factor.

Method, apparatus, and computer program product for verifying and/or updating road map geometry based on received probe data

A system, a method, and a computer program product are disclosed for detecting a driving direction. The system may include: a memory to store computer-executable instructions; and one or more processors to execute the instructions to receive sensor data associated with a plurality of locations and determine trajectory data associated with the plurality of locations based on the sensor data and map data. Further, the one or more processors may execute the instructions to identify, based on the trajectory data, a set of unmatched locations from the plurality of locations. The set of unmatched locations comprises at least a first predetermined number of unmatched locations. Furthermore, the one or more processors may execute the instructions to detect the driving direction based on the set of unmatched locations and the map data.

System, method, and computer program product for detecting a driving direction

A method, a system, and a computer program product may be provided for updating map data in a map database to indicate presence of a road sign. The method may include obtaining first sensor data associated with a road sign. The first sensor data may comprise at least one of one or more first positive observations of a road sign or one or more first negative observations of the road sign. The method may further include obtaining second sensor data for the road sign, for example, based on the first sensor data. The second sensor data may comprise cumulative historic road sign observation data for time duration. The method may include determining a sign confidence ratio based on the first sensor data and the second sensor data. The method may include updating the map data based on the sign confidence ratio.

System and method for updating map data in a map database

An approach is provided for detecting a presence of a physical divider on a road segment. The approach, for example, involves receiving sensor data from a vehicle traveling a road segment. The sensor data indicates a distance from the vehicle to the physical divider, a cross-sensor consistency of detecting the physical divider between at least two sensors of the vehicle, or a combination thereof. The approach also involves determining that the sensor data indicates the presence of the physical divider based on determining that the distance is within distance criteria, the cross-sensor consistency is within consistency criteria, or a combination thereof. The approach further involves updating data provided by a physical divider signal from the vehicle to indicate the presence of the physical divider on the road segment.

Method, apparatus, and system for detecting a physical divider on a road segment

An approach is provided for detecting false positive slippery road reports. For example, the approach involves receiving a slippery road report from a vehicle. The slippery road report, for instance, indicates that a slippery road event is detected at a location based on sensor information collected by the vehicle. The approach also involves map matching the location of the slippery road report to the mapping data to evaluate a proximity of the location to at least one geographic feature that is designated as an area where driver behavior is expected to be at least one cause of the slippery road event. The approach further involves classifying the slippery road report as the slippery road false positive report based on the evaluation.

Method and apparatus for detecting false positive slippery road reports using mapping data

A method is provided for prediction of a physical divider on a road. The method comprises retrieving vehicular sensor data, map data, or a combination thereof captured over a predefined period of time for at least one segment of the road. The method further comprises aggregating the respective vehicular sensor data, map data, or the combination thereof for the at least one segment of the road to generate one or more aggregated values. The method further comprises generating output data corresponding to presence of the physical divider in the at least one segment of the road by a machine learning model based on the one or more aggregated values as an input to the machine learning model.

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Buffalo Grove, IL, United States of America

Alex Averbuch