Here Global B.v.

Leon Stenneth

Jeremy Michael Young

Leo Modica

Jerome Beaurepaire

Zhenhua Zhang

Alex Averbuch

Gavril Adrian Giurgiu

James Adeyemi Fowe

Amarnath Nayak

Advait Mohan Raut

Vladimir Boroditsky

Ram Marappan

Eric Linder

Bruce A Bernhardt

Catalin Capota

Sebastian Zaba

Robert Camp

James D Lynch

Jingwei Xu

Dongwook Jang

Anton Anastassov

Kyle Jackson

Donta White

Mitchell McCuiston

Michael Finn

Prashant Chauhan

Yu Yang Bai

Pradeepa Kavindapadi Nagarajan

Lakshmi Nookala

Yuxin Guan

Weimin Huang

Toby Tennent

Deekshant Saxena

Rakesh Singh

Michael Weinberger

Mark Pundurs

Justin M Spelbrink

Timur Perelmutov

Danny Savla

Hitesh Baid

Dereje Befecadu

Kun Lee

Adekunle Afolabi

Pranil Pandit

Garvil Giurgiu

Sarah Fatima

Matthew Vachlon

Carol Walz

Andrew Dean

Corrine Bradley

Joel Ponder

Preeti Sharma

Corinne Bradley

A system to assist an owner of a low-profile vehicle to avoid damages related to vehicle impact upon a raised feature of a road is disclosed. The system may be configured to obtain one or more locations of a vehicle impact upon the raised feature by detecting an occurrence of the vehicle impact and recording contextual factors related to the vehicle impact upon the raised feature, where the one or more obtained locations are clustered into a first location bucket defined by a manual detection of the vehicle impact and a second location bucket defined by an automatic detection of the vehicle impact. The locations may be map-matched to map locations. The system may cluster the map-matched locations and automatically predict, using a trained machine learning model trained on ground truth of a region, potential locations of vehicle impact relevant to the owner of the low-profile vehicle.

Method to support low-profile vehicles

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

A method, apparatus, and computer program product are therefore provided for emulating vehicle features of a first vehicle in a second vehicle having different features. Methods may include: receiving an indication of a user operating an unfamiliar vehicle; determining vehicle features familiar to the user; and providing emulation of one or more features of the vehicle features familiar to the user in the unfamiliar vehicle. According to some embodiments, the vehicle features familiar to the user are determined based on one or more vehicles familiar to the user. According to certain embodiments, vehicle features familiar to the user include one or more of vehicle size, vehicle performance, or vehicle autonomy level.

Method, apparatus and computer program product for vehicle feature emulation

The disclosure provides a system, a method, and a computer program product for updating map data. The system, for example, obtains sensor data from one or more user equipment. The sensor data is associated with a road object. Further, the system, determines a first location of a road observation sight and a second location of the road object based on a timestamp associated with the first location. Further, a distance associated with the second location of the road object and a center point of a link, is calculated. The link is a map matched link associated with the second location. Further, the system updates the map data based on the calculated distance.

System and method for updating map data

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 method, apparatus, and user interface are provided for generating personalized splines. For example, one or more geometries that represent a portion of a road network are identified and a first spline curve is calculated from the one or more geometries. One or more additional geometries that represent a different portion of the road network are then interpolated, by a processor, and the processor then calculates at least a second spline curve from the one or more additional geometries, wherein the second spline curve is derived, at least in part, from personalized driving preference data.

Method and apparatus for generating personalized splines

Embodiments described herein may provide a method for analyzing traffic congestion at a toll plaza and identifying a preferred lane of travel through the toll plaza based on the traffic congestion. Methods may include: determining active toll lanes of all toll lanes at a toll plaza; obtaining probe data for each active toll lane at the toll plaza; determining lane-wise congestion for each active toll lane at the toll plaza; identifying a preferred lane of the active toll lanes; and providing for at least one of a navigational instruction or at least semi-autonomous vehicle control to enter or continue in the preferred lane.

Method, apparatus and computer program product for lane level toll plaza congestion modeling

A system, a method and a computer program product are provided to predict vehicle parking bunching in a geographic region. For example, the system is configured to obtain a plurality of contextual features and/or a plurality of sensor data related to parking information in the geographic region. The system is configured to predict a vehicle parking bunching based on a vehicle unparking threshold, a vehicle separation distance cluster threshold and/or unparking vehicle information. The system may also be configured to alert a vehicle of the vehicle parking bunching with a vehicle parking bunching notification.

System to predict vehicle parking bunching

An apparatus, method and computer program product are provided for predicting tire temperature levels. In one example, the apparatus receives input data indicating attributes of the target vehicle and attributes of target routes for the target vehicle. The apparatus causes a machine learning model to generate output data as a function of the input data, where the output data indicate a subset of the target routes of which the target vehicle can successfully traverse while using the at least one spare tire. The machine learning model is trained to generate the output data as a function of the input data based on training data, where the training data indicate events in which vehicles used spare tires to traverse routes. The training data indicate attributes of the vehicles and attributes of the routes.

Apparatus and methods for providing routes for vehicles using spare tires

An apparatus, method and computer program product are provided for determining a state of visibility for a road object. In one example, the apparatus receives temporal data, calculates an orientation of a light source with respect to a road object using the temporal data, and predicts a state of visibility for the road object based on the orientation of the light source. In another example, the apparatus determines an artificial light source associated with a road object, receives attribute data associated with the artificial light source, determines a state of the artificial light source using the attribute data, and predicts a state of visibility for the road object based on the state of the artificial light source.

Apparatus and methods for predicting a state of visibility for a road object based on a light source associated with the road object

A system, a method, and a computer program product for validating a road sign are provided. The method comprises determining a transition location associated with the road sign using map data. The transition location is at least one of a map region start location or a map region end location. The method further comprises determining road sign data associated with the road sign using a sensor data cluster. The method further comprises determining a validity of the road sign based on the road sign data and the transition location.

Method and system to validate road signs

System and methods are provided that allow users of shared vehicles to benefit from an enhanced user experience that seamlessly unlocks and/or provides access to features for autonomous vehicles by proactively computing an interest index based on detected contextual behavioral patterns of the pedestrians such as the trajectory a candidate passenger is walking given a locational context.

Providing access to an autonomous vehicle based on user's detected interest

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

A method, apparatus and computer program product are provided for controlling a functional road object. For example, at least one processor receives road sign attribute data indicating at least one attribute of a road sign and receives weather forecast data indicating a weather forecast of a location in which the road sign is disposed. The road sign includes at least one machinery for mitigating exposure to one or more weather conditions. The at least one processor identifies a state of visibility for the road sign using the road sign attribute data and the weather forecast data and generates a control signal for controlling the at least one machinery using the state of visibility.

Apparatus and method for controlling a functional road object

Embodiments described herein may provide a method for using vehicle sensor data to identify where road work exists within a road network. Methods may include: receiving probe data and sensor data from a plurality of probe apparatuses traveling along a sequence of road segments; identifying, from the sensor data, one or more indicators of a beginning of a road work area; identifying, from the sensor data, binary indicators of the presence of road work or a lack of presence of road work along the sequence of road segments; and determining, based on the one or more indicators of a beginning of a road work area and the binary indicators of the presence of road work or the lack of road work along the sequence of road segments, a probability of road work occurring along one or more road segments of the sequence of road segments.

Method, apparatus and computer program product for identifying road work within a road network

Growing community of inventors

Chicago, IL, United States of America

Leon Stenneth