Abstract: Embodiments described herein may provide a method for generating a local hazard warning polygon and establishing a quality score thereof. Methods may include: receiving a plurality of probe data points from a plurality of probes within a mapped region, where each probe data point includes location information and weather condition information; generating, based on a plurality of probe data points indicating an adverse weather condition, a local hazard warning condition polygon including a plurality of local hazard warning condition vertices; receiving weather conditions at each of a plurality of map points within the mapped region; correlating each local hazard warning condition vertex with a respective map point within the mapped region; and establishing a quality score of the local hazard warning condition polygon based on a proportion of the local hazard warning condition vertices indicating an adverse weather condition agreeing with a weather condition at a respective correlated map point.

Abstract: A computer-implemented method for validating the existence of roadwork is provided. The method comprises, for example, retrieving information for at least one segment of a road captured by a plurality of vehicles. The information comprises at least two of lane marking data, speed funnel presence data, and traffic behavior change data. The method also comprises generating a confidence score based on analysis of the retrieved information. The method further comprises validating the existence of the roadwork on the at least one segment of the road based on the generated confidence score.

Abstract: System and methods are provided for predicting, reacting to, and avoiding loss of traction events, such as hydroplaning for autonomous vehicles. For example, the method predicts a risk of an area being subject to hydroplaning using real-time data and/or historical data. The method may store possible hydroplaning events in a geographic map along with a risk assessment. The method provides lane level hydroplaning risk predictions and avoidance mechanisms.

Abstract: Systems and methods for the detection and analysis of road markings and other road objects are described. A method for detection of road markings comprises identifying image data including lane markings associated with a road segment, defining a plurality of subsections for the road segment, identifying boundary recognition observations for the lane markings from the image data corresponding to the at least one of the plurality of subsections for the road segments, calculating one or more clusters for the boundary recognition observations according to color or intensity, and outputting a lane marking indicator indicating the color or the intensity, for the at least one of the plurality of subsections for the road segments, in response to the one or more clusters.

Abstract: System and methods are provided for generating answers to questions by drivers or passengers of autonomous vehicles in order to better understand the behaviors of other vehicles around them by being able to get contextual answers to behavioral queries. The system receives a user inquiry from a user of the vehicle, the user inquiry related to a behavior of another vehicle in the vicinity of the vehicle. The system analyzes sensor data acquired by the vehicle for a period of time preceding the inquiry and generates an answer to the inquiry based on contextual information of the inquiry, the analysis of the sensor data, and mapping information.

Abstract: A method, apparatus and computer program product are provided for vehicle localization via frequency audio features. In this regard, a frequency audio signature of audio data received from one or more audio sensors of a vehicle is determined. Location data associated with the vehicle is also determined. Based on the location data for the vehicle, at least a portion of an audio feature map is selected. The audio feature map stores frequency audio signatures associated with road noise in relation to respective locations. Furthermore, the frequency audio signature of the audio data is compared with the frequency audio signatures of the audio feature map. Based on the comparison between the frequency audio signature of the audio data and the frequency audio signatures of the audio feature map, a location of the vehicle is refined to generate updated location data for the vehicle.

Abstract: A system, a method, and a computer program product for generating updated map data are provided. The method comprises obtaining first sensor data associated with a plurality of first road signs within a geographic region, obtaining second sensor data associated with the geographic region, and determining a sign matching efficiency for the geographic region, based on the first sensor data and the second sensor data. The method further comprises generating the updated map data, based on the determined sign matching efficiency.

Abstract: A system, a method, and a computer program product are disclosed for identifying a link offset. The system may comprise a memory configured to store computer-executable instructions; and one or more processors configured to execute the instructions to: receive a first plurality of road object observations associated with at least one road object for a first link, wherein the first link is associated with a second link; determine a second plurality of road object observations from the first plurality of road object observations; determine an offset distance based on the second plurality of road object observations; and identify a road segment portion of the first link and a road segment portion of the second link as the link offset, based on the determined offset distance.

Abstract: A system, a method, and a computer program product are disclosed for identifying a road object. The system may comprise a memory configured to store computer-executable instructions; and one or more processors configured to execute the instructions to: receive a road object observation associated with the road object for a first link, wherein the first link is associated with at least one second link; determine a first heading data for the received road object observation; determine a matched location for the received road object observation on the at least one second link; determine a second heading data for the received road object observation, based on the determined matched location; and identify the road object based on the determined first heading data and the determined second heading data, wherein as a result of identifying, the identified road object is either determined as associated with the first link or is determined to be not associated with the first link.

Abstract: Embodiments described herein may provide a method for generating a local hazard warning boundary and at least one confidence band therein. Methods may include: receiving a plurality of probe data points from a plurality of probes within a region, where each probe data point includes location information and an indication of a hazardous condition; generating, based on the plurality of probe data points, a boundary within the region identifying an area within which the hazardous condition is determined to exist with at least a first degree of confidence; generating, based on the plurality of probe data points, a confidence band within the boundary within which the hazardous condition is determined to exist with a second degree of confidence; and providing for an indication of the boundary and the confidence band to at least one of an autonomous vehicle control or to a driver assistance system.

Abstract: A method, apparatus and computer program product are provided for managing autonomous vehicles. In this regard, vehicle context data associated with an indication of a change in an autonomous level for a vehicle traveling along a road segment is determined. Furthermore, the vehicle is assigned to a queue of vehicles traveling along the road segment in response to a determination that the vehicle context data corresponds to particular vehicle context data associated with the queue of vehicles. An indication of the queue of vehicles may also be provided to the vehicle to facilitate navigation of the vehicle.

Abstract: A method, apparatus and computer program product are provided for predicting autonomous transition regions using historical information. In this regard, historical autonomous transition data is accessed. The historical autonomous transition data is associated with vehicles that transition from respective autonomous levels while traveling along one or more road segments associated with a first geographic area. Furthermore, one or more features of the historical autonomous transition data associated with the first geographic area is identified. A machine learning model is then trained based on the one or more features associated with the first geographic area.

Abstract: A method, apparatus and computer program product are provided for identifying and providing dynamic solutions for improvement of autonomous transition regions. In the context of a method, the method receives autonomous transition data associated with at least one autonomous transition region from at least one autonomous vehicle, and based at least on the autonomous transition data, determines one or more dynamic solutions for autonomous transitions within the at least one autonomous transition region. The method also generates a recommendation comprising at least indications of the one or more dynamic solutions and causes transmission of the recommendation to at least one external source.

Abstract: A method, apparatus and computer program product are provided for improving user experiences for autonomous driving. In context of a method, the method determines one or more autonomous transition region parameters for a respective autonomous transition region along a route. The method also, based on the one or more autonomous transition region parameters, determines whether an action is to be performed by a vehicle in accordance with user preference data associated with a user. The method also causes the vehicle to perform the action in accordance with a determination that the action is to be performed by the vehicle.

Abstract: A method, apparatus and computer program product are provided for generating an automated driving capability map index. In this regard, autonomous level data and location data thereof associated with a vehicle traveling along a road segment is received. The autonomous level data is identified based on a change in an autonomous level for the vehicle. Furthermore, based on the location data, the autonomous level data is aggregated with other autonomous level data for one or more other vehicles associated with the road segment to generate aggregated autonomous level data for the road segment. The aggregated autonomous level data is also encoded in a database to facilitate an autonomous level prediction for vehicles associated with the road segment.

Abstract: A method, apparatus and computer program product are provided for generating recommendations of autonomous vehicles that satisfy a personalized autonomous transition tolerance. In context of a method, the method receives a route request associated with a user and determines a personalized vehicle recommendation of one or more autonomous vehicles for the user based upon historical data associated with the user regarding prior vehicle selections including historical data relating to an autonomous transition tolerance to changes in autonomy level of a vehicle during traversal of a route. The method also causes transmission of the personalized vehicle recommendation to a user device associated with the user.

Abstract: A method, apparatus and computer program product are provided for generating a transition variability index related to autonomous driving. In this regard, a first transition variability index is calculated. The first transition variability index is indicative of a first degree of variability in relation to transition of vehicles from respective autonomous levels while traveling proximate a first spatial reference point. Furthermore, a second transition variability index is generated. The second transition variability index is indicative of a second degree of variability in relation to transition of vehicles from respective autonomous levels while traveling along proximate a second spatial reference point. Updating of transition data associated with one of the first and second spatial reference points relative to another one of the first and second spatial reference points is then prioritized based on a comparison between the first transition variability index and the second transition variability index.

Abstract: A method, apparatus and computer program product are provided to facilitate autonomous vehicle selection based on the vehicle's ability to navigate autonomous transition regions along a particular route comprising at least one autonomous transition region. In context of a method, the method receives a route request comprising an origin location and a destination location and determines, based at least on the route request, one or more candidate routes. For a respective candidate route, the method analyzes the respective candidate route based upon one or more autonomous transition region parameters, and causes transmission of information relating to the respective candidate route based upon the analyzing of the respective candidate route and the one or more autonomous transition region parameters associated therewith.

Abstract: A method, a system, and a computer program for identification of at least one road work extension in a geographical location are provided. The method includes, for example, the process of building and accessing a map for the geographic location curated with the marking of one or more road work zones corresponding to the at least one road work extensions. To calculate road work extension, the method includes obtaining a plurality of lane markings on a road work link and determine a start and an end offset of at least one link using obtained lane marking observations. Further, the method includes generating the road work extension data comprising co-ordinates of each of the start position and the end position of the road work extension, based on the determined link start offset and the link end offset.

Abstract: A method, apparatus, and computer program product are provided for identifying the reliability of objects within a mapped region for localization and facilitating autonomous control of a vehicle. Methods may include: receiving an indication of an event having event data; assigning at least one object at a location of the event an impact score based on an estimated impact of the event; and providing an indication of a reduction in autonomous vehicle capability in response to the impact score failing to satisfy a predetermined value. The impact score may include a probability that the corresponding object is reliable for localization or autonomous vehicle control. Methods may include providing the indication of a reduction in autonomous vehicle capability to at least one device associated with a vehicle in response to the at least one device associated with the vehicle having a travel path including the at least one road link.