Abstract: An approach is provided for detecting lane departure events based on map data and probe data. The approach, for example, involves map-matching probe data to a lane of a road segment. The probe data is collected from one or more sensors of at least one vehicle and/or at least one user device that traversed the road segment. The approach also involves processing the probe data to detect at least one lane departure event. The approach further involves categorizing the at least one lane departure event as an intentional lane departure event or an unintentional lane departure event. The approach further involves creating a lane departure warning message for the road segment based on the at least one categorized lane departure event, and/or road segments associated with multiple lane departure warning messages within a certain time period. The approach further involves providing the lane departure warning message as an output.

Abstract: An approach is provided for traffic Signal Phase and Timing (SPaT) verification using sensor data and probe data. The approach involves, for instance, retrieving image data captured using a sensor of a vehicle traveling within proximity of a traffic light. The approach also involves processing the image data to identify at least one transition of the traffic light between one or more traffic light states. The approach further involves determining a transition time, a cycle time, or a combination thereof between the one or more traffic light states based on the identified at least one transition of the traffic light. The approach further involves performing a comparison of signal phase and timing (SPaT) data of the traffic light with the transition time, the cycle time, or a combination thereof and providing the comparison of the SPaT data as an output.

Abstract: An approach is provided for traffic data blending based on road segment travel time reliability during traffic prediction. The approach involves, for instance, retrieving real-time traffic information and/or historical traffic information for each road segment within a geographic area. The approach also involves aggregating traffic flow speed data in the real-time traffic information to compute traffic pattern data for each road segment. The traffic pattern data includes static speed data of each said road segment. The approach further involves aggregating traffic flow speed data in the historical traffic information to compute travel time reliability index metric(s) for each said road segment. The approach further involves determining, based on the travel time reliability index metric(s), to use the traffic pattern data, a mean, or a percentile of a road segment travel time distribution in the historical traffic information for traffic prediction associated with each said road segment.

Abstract: An approach is provided for determining road work zone travel time reliability based on vehicle sensor data. The approach involves, for instance, aggregating telematic data generated by vehicles traveling within a geographic area, to detect a road work zone and/or active time period(s) thereof. The approach also involves identifying a start location and an end location of the road work zone. The approach further involves identifying a starting time point when one of the vehicles approaching the start location and an end time point when the vehicle passes the end location. The approach further involves calculating a time difference between the start and end time points as a travel time through the road work zone. The approach further involves aggregating the vehicle travel times, to compute work zone travel time reliability index(es) for the road work zone. The approach further involves providing the travel time reliability index(es) as an output.

Abstract: Embodiments described herein may provide a method for aggregating probe data to detect a road work event and generating, from the road work event, a work zone map overlay to inform navigational systems and autonomous vehicles. Methods may include: receiving probe data from a plurality of probe apparatuses traveling within a road network; identifying, from the probe data, a road work event within the road network; determining, from the road work event and the probe data, a work zone; generating a map overlay including the work zone, where the map overlay is independent from map data of the road network; providing the map overlay to at least one vehicle for use in combination with the map data of the road network; and providing for at least one of navigational assistance or at least semi-autonomous vehicle control based on the map overlay of the map data of the road network.

Abstract: A method, apparatus and computer program product are provided to estimate the location of a vehicle based at least in part upon two or more road signs that are depicted by one or more images captured by one or more image capture devices onboard the vehicle. By relying at least in part upon the two or more road signs, the location of the vehicle may be refined or otherwise estimated with enhanced accuracy, such as in instances in which there is an inability to maintain a line-of-sight with the satellites of a satellite positioning system or otherwise in instances in which the location estimated based upon reliance on satellite or radio signals is considered insufficient. As a result, the vehicle may be navigated in a more informed and reliable manner and the relationship of the vehicle to other vehicles may be determined with greater confidence.

Abstract: A method, apparatus and computer program product are provided to estimate the location of a vehicle based at least in part upon two or more road signs that are depicted by one or more images captured by one or more image capture devices onboard the vehicle. By relying at least in part upon the two or more road signs, the location of the vehicle may be refined or otherwise estimated with enhanced accuracy, such as in instances in which there is an inability to maintain a line-of-sight with the satellites of a satellite positioning system or otherwise in instances in which the location estimated based upon reliance on satellite or radio signals is considered insufficient. As a result, the vehicle may be navigated in a more informed and reliable manner and the relationship of the vehicle to other vehicles may be determined with greater confidence.

Abstract: A system, a method, and a computer program product may be provided for generating traffic congestion estimation data of one or more lanes in a region. A system may include a memory configured to store computer program code and a processor configured to execute the computer program code to obtain image data associated with the region. The processor may be configured to determine a count of one or more first movable objects in one or lanes, based on image data, calculate a lane object static capacity of the one or more lanes, based on one or more map free flow or speed limit attributes associated with the one or more lanes and generate the traffic congestion estimation data based on count of first movable objects in the one or more lanes, the moving speed of movable objects crossing multiple image frames, the lane object static capacity of lanes.

Abstract: An approach is provided for detecting lane-level dangerous slowdown events based on probe data and/or sensor data. The approach, for example, involves splitting probe data, sensor data, or a combination thereof into at least one vehicle trajectory, wherein the data is collected from one or more vehicles traveling on a road segment. For each vehicle trajectory of the at least one vehicle trajectory, the approach also involves processing said each vehicle trajectory to detect a slowdown event based on a speed reduction greater than a threshold reduction. The approach further involves classifying a slowdown event type of the slowdown event based on a final driving location, a final driving speed, or a combination thereof of the at least one vehicle trajectory. The approach further involves providing the slowdown event, the slowdown event type, or a combination thereof as an output for the road segment.

Abstract: A method, a system, and a computer program product may be provided for generating indoor emergency route plan for an infrastructure. The method includes obtaining indoor map data of the infrastructure, where the indoor map data comprises one or more first exit routes to one or more exits in the infrastructure. The method further includes obtaining first location data associated with an indoor emergency event. The method further includes generating one or more second exit routes to the one or more exits, based on the first location data and the one or more first exit routes. The method further includes providing the one or more second exit routes to one or more subjects.

Abstract: Systems and methods include receiving probe data and sensor data from a mobile device, comparing conditions defined by the probe data and the sensor data to a requirement to enable a driver assistance feature for the mobile device, determining that the conditions fail to meet the requirement to enable the driver assistance feature based on the probe data and the sensor data, and outputting a navigation message to the mobile device providing for remote control of the mobile device when the conditions fail to meet the requirement to enable the driver assistance feature.

Abstract: Systems and methods for determining a cause of a change in driver assistance capability may be based on probe data generated by a mobile device or vehicle. The probe data is matched to a path segment. A cause of the change in driver assistance capability for the path segment is determined based on the probe data matched to the path segment. A geographic database record including the cause of the change in the driver assistance capability is output.

Abstract: A method, a system, and a computer program product are provided for predicting road closure in a region. The method comprises obtaining, probe data, such as sensor data, and map data, for the region. The method may include detecting a change in speed of a one or more vehicle on a road, based on the obtained probe data and the obtained map data for the region, wherein the change in speed is associated with a slowdown event associated with the one or more vehicles. The method may include identifying a vehicle event on the road based on the detected change in speed of the one or more vehicles, wherein the vehicle event is associated with a location corresponding to a matching trajectory of the one or more vehicles and predicting the road closure based on the identified vehicle event.

Abstract: An approach is provided for providing traffic based location referencing with offsets for road incident reporting. The approach, for example, involves determining a road incident that crosses at least one boundary between a first road segment and a second road segment. The approach also involves creating an aggregated road segment comprising a start location of the road incident in the first road segment to the boundary and from the boundary to an end location of the road incident in the second road segment or an end road segment. The approach further involves providing a report of the road incident that is referenced to a positive offset from the start location of the road incident to a beginning of the first road segment and/or a negative offset from the end location of the road incident to an end of the second road segment or the end road segment.

Abstract: Systems and methods for vehicle routing may be based on wireless network performance data. A vehicle route includes one or more path segments included in the route based on the wireless performance data. The vehicle route may be updated based on updated wireless performance data. Driving assistance features of a vehicle may be enabled by the wireless performance data, and different driving assistance features may be enabled or disabled on the vehicle route according to changes in wireless performance data. As the vehicle traverses the route, the driving assistance features may be enabled or disabled based on the wireless performance data for the path segment. The vehicle route may be updated to continue to enable a set of the driving assistance features.

Abstract: Systems and methods for vehicle routing may be based on wireless network performance data. A vehicle route includes one or more path segments included in the route based on the wireless performance data. The vehicle route may be updated based on updated wireless performance data. Driving assistance features of a vehicle may be enabled by the wireless performance data, and different driving assistance features may be enabled or disabled on the vehicle route according to changes in wireless performance data. As the vehicle traverses the route, the driving assistance features may be enabled or disabled based on the wireless performance data for the path segment. The vehicle route may be updated to continue to enable a set of the driving assistance features.

Abstract: A method, apparatus and computer program product for determining a road work event confidence are described herein. In the context of a method, the method may determine a road network speed profile corresponding with a road work event location. The method may determine, based at least in part on probe data corresponding with the road work event location, a probe speed profile. The method may determine the road work event confidence based at least in part on evaluation of the road network speed profile and the probe speed profile. Evaluation of the road network speed profile and the probe speed profile may comprise identifying a plurality of road segments corresponding with the road work event location and correlating road network speed profile characteristics and probe data characteristics for each respective road segment.

Abstract: A system, a method, and a computer program product may be provided for determining dynamic road capacity data of one or more lanes of a road segment in a region. A system may include a memory configured to store computer program code and a processor configured to execute the computer program code to obtain probe data, historical capacity dynamic pattern data and event data. The processor may be configured to calculate road capacity data of the lane. The processor may be configured to calculate a count of movable objects in the lane. The processor may be configured to determine a traffic condition of the lane. The processor may be configured to determine the dynamic road capacity data based on the road capacity data, the count of one or more movable objects, the historical capacity dynamic pattern data and the traffic condition of the at least one lane of the road segment.

Abstract: A method for providing alerts for a traffic slowdown includes receiving location data for at least a first vehicle of a plurality of vehicles, map matching the location data for at least the first vehicle to a road network, calculating an approaching speed for at least the first vehicle at a first time, calculating a final speed for at least the first vehicle at a second time, and generating a traffic slowdown message in response to the approaching speed and the final speed. The traffic slowdown message includes at least one characteristic of the traffic slowdown.

Abstract: An approach is provided for identifying and characterizing mobile work zones (e.g., roadway striping, pothole filling, tree trimming, etc.). The approach, for example, involves processing probe data at a lane level to determine at least one forward forming shockwave associated with a congestion front of a mobile roadwork zone on at least one lane. The approach also involves providing data indicating the mobile roadwork zone as an output. The approach further involves determining a propagation rate of the mobile roadwork zone. The approach further involves determining a congestion recovery speed, where the congestion is caused by the mobile roadwork zone.