Abstract: An apparatus, method and computer program product are provided for providing autonomous vehicle navigation at intersections. In one example, the apparatus identifies an intersection associated with at least two road signs having the same sign type and facing the same direction. The apparatus updates map data to include a datapoint that provides a representation of a single road sign at the intersection instead of the at least two road signs, thereby enabling an autonomous vehicle relying on the map data to traverse the intersection to adhere to the single road sign in lieu of the at least two road signs.

Abstract: Systems and methods for selecting an autonomous vehicle software application are provided. For example, a method for selecting an autonomous vehicle software application includes receiving information corresponding to a vehicle trip in a given vehicle. The method also includes determining one or more elements corresponding to at least one of the vehicle trip and the given vehicle. The method also includes based on the determined one or more elements, selecting an autonomous vehicle software application for operation of the given vehicle.

Abstract: Systems and methods for optimizing the notification of a modification to a route are provided. For example, a method of optimizing the notification of a modification to a route includes analyzing mobility data of an individual at a first location. The method also includes receiving at least one modification to a level of autonomous driving corresponding to one or more road segments between the first location and a second location. The method also includes, based on the at least one modification to the level of autonomous driving corresponding to the one or more road segments, determining one or more changes to at least one route between the first location and the second location. The method also includes providing a notification to the individual that includes information about the one or more changes to the at least one route between the first location and the second location.

Abstract: An approach is provided for computing an estimated time of arrival via a route based on a degraded state of a vehicle after an accident and/or malfunction. The approach involves receiving, by one or more processors, data indicating an operational status of a vehicle. The approach also involves processing, by the one or more processors, the data to determine a degraded operational state of the vehicle. The approach further involves computing, by the one or more processors, an estimated time of arrival, a route, or a combination thereof of the vehicle based on the degraded operational state.

Abstract: An interface and headgear assembly includes a headgear assembly. The headgear assembly has a first strap configured to connect to the interface. A crown strap can be adjusted along a length of the first strap. In some configurations, the crown strap has a first portion and a second portion that are adjustably connected. The crown strap can be removably connected to the first strap using bridge regions of the first portion and the second portion.

Abstract: A method, apparatus, and user interface for left turn indicator detection comprising obtaining image data of at least one navigable link, determining a left turn indicator based on the obtained image data, wherein the left turn indicator includes data from at least one driver profile, and associating the determined left turn indicator with one or more navigable links to update a map layer of a geographic database.

Abstract: A method, apparatus, and user interface for determining appointment attendance probability comprising obtaining an indication of least a first location and second location of an end user; wherein the first location and second location are obtained at a predefined time interval, obtaining end user driving profile data, obtaining end user appointment data, determining appointment attendance probability based, at least in part, on the obtained first location, second location, end user appointment data, and end user driving profile data, and updating at least one database with the determined appointment attendance probability.

Abstract: A method, apparatus, and user interface for road debris detection comprising, in some embodiments, obtaining image data of at least one navigable link and/or road debris, determining a road debris indicator based on the obtained image data, wherein the road debris indicator includes road debris classification data, and associating the determined road debris indicator with one or more navigable links to update a map layer of a geographic database.

Abstract: A method, apparatus and computer program product are provided to predict a map object based at least in part on audio data. With respect to predicting a map object, audio data created by a vehicle while driving over a road surface is obtained. The audio data includes one or more audio amplitude features, one or more audio frequency features or a combination of audio amplitude features and audio frequency features. The audio data including the one or more audio amplitude features is provided to a machine learning model and the map object that created the audio data while the vehicle interacted therewith is predicted utilizing the machine learning model. A method, apparatus and computer program product are also provided for training the machine learning model to predict the map object based at least in part on audio data.

Abstract: An apparatus, method and computer program product are provided for predicting events in which drivers fail to see curbs while the drivers are maneuvering vehicles. In one example, the apparatus receives vehicle attribute data associated with a first vehicle, map data indicating one or more attributes of a road portion including a first curb, and sensor data indicating an orientation of a first driver within the first vehicle. The apparatus causes a machine learning model to render an output as a function of the vehicle attribute data, the map data, and the sensor data. The output indicates a likelihood of which the first driver will not be able to see the first curb at the road portion when the first driver is maneuvering the first vehicle. The machine learning model is trained to predict the output based on historical data indicating events in which second drivers maneuvered second vehicles to encounter the first curb or one or more second curbs.

Abstract: An apparatus, method and computer program product are provided for predicting events in which drivers fail to see curbs while the drivers are maneuvering vehicles. In one example, the apparatus receives vehicle attribute data associated with a first vehicle, map data indicating one or more attributes of a road portion including a first curb, and sensor data indicating an orientation of a first driver within the first vehicle. The apparatus causes a machine learning model to render an output as a function of the vehicle attribute data, the map data, and the sensor data. The output indicates a likelihood of which the first driver will not be able to see the first curb at the road portion when the first driver is maneuvering the first vehicle. The machine learning model is trained to predict the output based on historical data indicating events in which second drivers maneuvered second vehicles to encounter the first curb or one or more second curbs.

Abstract: An approach is provided for determining a lane marking confusion index based on lane confusion event detections. The approach, for example, involves detecting, by at least one processor, a number of instances of a lane confusion event associated with a location in a road network. The lane confusion event indicates presence of temporary lane markings in addition to standard lane markings at the location. The approach also involves determining, by the at least on processor, a lane marking confusion index for the location based on the detected number of instances of the lane confusion event in association with the location. The approach further involves storing, by the at least one processor, the lane marking confusion index as a map attribute of the location in a geographic database.

Abstract: An apparatus, method and computer program product are provided for predicting road locations that are likely to induce tire pressure changes. In one example, the apparatus receives historical data of an event in which a first vehicle is impacted by a first tire pressure change at a first road segment. The historical data indicates point-of-interest (POI) information associated with the first road segment. The apparatus trains a prediction model using the historical data. The prediction model is configured to determine a likelihood in which a second road segment induces a second tire pressure change for a second vehicle based on POI information associated with the second road segment.

Abstract: A method, system, and computer readable storage medium are provided for predicting behavior of a vehicle. More specifically, image data of the vehicle is obtained by generating class prediction data for the vehicle and then identifying one or more related points of interest. The method, system, and computer readable storage medium then predict the behavior of the vehicle based upon the one or more points of interest and the class prediction data.

Abstract: A method, apparatus, and computer program product are provided for encoding audio events as geo-referenced audio events for use in location establishment. Methods may include: receiving first audio data from a first sensor; establishing a baseline frequency profile; identifying, within the first audio data, a first audio event, where the first audio event satisfies at least one predefined criteria relative to the baseline frequency profile; identify a location corresponding to the first audio event; encoding the first audio event in a database to correspond to the location; receiving second audio data from a second sensor; identifying, within the second audio data, a second audio event; correlating the second audio event with the first audio event; and providing the location in response to the second audio data. The at least one criteria may include a statistically significant change in a prominent frequency in the audio data.

Abstract: An apparatus, method and computer program product are provided for providing adaptive vehicle parking assistance. In one example, the apparatus receives sensor data indicating a user's interaction associated with a vehicle parking assistance feature. The vehicle parking assistance feature is a feature in which a vehicle causes a notification on a user interface in response to an object abutting or overlapping a virtual zone surrounding the vehicle. The apparatus determines a level of the user's familiarity on using the vehicle parking assistance feature based on the sensor data, and the apparatus adjusts a size of the virtual zone based on the level.

Abstract: An apparatus, method and computer program product are provided for providing trailer sway detection. In one example, the apparatus receives sensor data and determines a pitch angle of a trailer based on the sensor data. The apparatus further determines a confidence of trailer sway occurring based on the pitch angle and in response to the confidence exceeding a threshold, the apparatus generates a warning signal indicating a potential trailer sway.

Abstract: A method, system, and computer readable storage medium are provided for predicting behavior of a vehicle. More specifically, image data of the vehicle is obtained by generating class prediction data for the vehicle and then identifying one or more related points of interest. The method, system, and computer readable storage medium then predict the behavior of the vehicle based upon the one or more points of interest and the class prediction data.

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 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.