Abstract: 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.

Abstract: A system is disclosed for generating speed limit data. The system may include a memory configured to store computer executable instructions and one or more processor configured to execute the instructions to receive sign data relating to one or more traffic entities. The sign data comprises at least one of: a set of speed values, a set of transportation mode values, and one or more entity parameters associated with the corresponding one or more traffic entities. The processors are further configured to generate matching data based on a matching between the set of speed values and the set of transportation mode values, based on the one or more entity parameters. The processors are further configured to generate speed limit data based at least on: the matching data, the sign data and a predefined condition associated with transportation mode.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Embodiments described herein may provide a method for using map data to alter criteria for the identification of road work in locations where false positives are more likely. Methods may include: receiving probe data from a plurality of probe apparatuses traveling within a road network; determining, from the probe data captured at a first location, an indication of road work; determining a type of map area of the first location; applying a suppression method to the probe data captured at the first location in response to the type of map area of the first location corresponding to an area having a relatively high false positive rate of indications of road work; and determining, based on the suppression method to the probe data captured at the first location, the presence or absence of road work occurring at the first location.

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: An apparatus, method and computer program product are provided for determining a newly established vehicle-related rule within an area. In one example, the apparatus receives sensor data indicating attributes of an area for a first period. The attributes indicate a number of vehicle-related tickets issued within the area, a parking orientation of each vehicle within the area, or a combination thereof. The apparatus compares the sensor data to historical data associated with the area. The historical data indicate the attributes of the area for one or more second periods preceding the first period. Based on comparison of the sensor data and the historical data, the apparatus determines a likelihood of a vehicle-related rule established for the area, where the vehicle-related rule did not exist during the one or more second periods. The apparatus causes a notification indicating the likelihood at a user interface.

Abstract: The disclosure provides a method, a system, and a computer program product for updating map data. The method comprises obtaining vehicle sensor data associated with first spatial data and first temporal data related to one or more hazard-based event. The method may further include obtaining image data associated with second spatial data and second temporal data related to one or more hazard-based event. The method may further include combining the first spatial data with the second spatial data based on a match between the first spatial data and the second spatial data and between the first temporal data and the second temporal data respectively. The method may further include updating the map data based on the combining.

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: An approach is provided for suppressing false positive reports of detectable road events. For example, the approach involves receiving a detection of a roadwork zone and a time-to-live period associated with the roadwork zone. The approach also involves receiving a subsequent observation of the roadwork zone. The subsequent observation is generated based on sensor data captured by at least one sensor associated with at least one vehicle traveling within proximity of the roadwork zone. The approach further involves classifying the subsequent observation as a false positive observation based on determining that the subsequent observation is created after the time-to-live period. The approach further involves initiating a blacklisting of the roadwork zone as a false positive roadwork zone based on the false positive observation. The approach further involves providing the blacklisting as an output.

Abstract: 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.

Abstract: A method, apparatus, and computer program product are provided for using visual analysis of a road surface to identify markings indicative of road surface anomalies. Methods may include, for example: receiving data from an image sensor associated with a vehicle traveling along a road segment; identifying, within the data, a visual indication of a road surface anomaly, where the visual indication is a result of the road surface anomaly; and cause at least one of: an indication of the road surface anomaly to be provided to a user of the vehicle; a vehicle operational setting to be changed responsive to the road surface anomaly; or a map update to be generated to include the road surface anomaly within a map database.

Abstract: 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.

Abstract: A system, a method and a computer program product are provided to determine a left turn decision for a user or autonomous vehicle attempting to turn at an intersection of a road. For example, the system obtains contextual features and/or sensor data related to the intersection of the road. An optimal location on the road is determined for the user or autonomous vehicle to position the vehicle to make the left turn decision, based on the contextual features and/or the sensor data. A left turn risk factor is determined based on the location on the road for the user or autonomous vehicle to position the vehicle to make a left turn. An alert is presented to the user or autonomous vehicle regarding the left turn risk factor with a left turn advisory message.

Abstract: The disclosure provides a system, a method, and a computer program product for detecting active road work zones. The system obtains first sensor data associated with a detection of a road work zone, using a first sensor type and obtains second sensor data associated with presence of at least one individual in the road work zone, using a second sensor type. Further, the system determines a confidence level associated with the detection of the road work zone based on fusing of the first sensor data and the second sensor data. The system classifies the detected road work zone as at least one of the active road work zone or a non-active road work zone, based on the confidence level. The system updates map data associated with a map of a region based on the classification.