Abstract: The disclosure provides a system, a method, and a computer program product for validation of sensor data. The system may be configured to receive sensor data associated with a hazard. The sensor data may include at least a first time of occurrence of the hazard. The system may be further configured to determine a second time of occurrence of the hazard based on a time-space diagram associated with one or more vehicles that passed through a location of the occurrence of the hazard. The system may further calculate a validation result for the received sensor data based on a comparison of the first time of occurrence and the second time of occurrence, and an associated first predefined threshold.

Abstract: An approach is provided for determining bicycle lane deviations for autonomous vehicle warning or operation. The approach, for example, involves retrieving probe data associated with a bicycle transportation mode. The approach also involves determining a plurality of probe points of the probe data that are map-matched outside of a bicycle lane. The approach further involves clustering the plurality of probe points into at least one location cluster. The approach further involves storing the one or more location clusters in a geographic database as respective one or more hazard areas where a plurality of bicycles deviates outside of the bicycle lane. By way of example, the approach can further involve using the at least one location cluster to perform at least one of providing a warning message or determining a driving parameter for an autonomous vehicle.

Abstract: A system, a method, and a computer program product may be provided for generating traffic congestion data for a road in a region. The system may include a memory configured to store computer executable instructions and a processor configured to execute the computer executable instructions to obtain probe data and map data. The processor may be further configured to generate traffic condition data for the road. The processor may be further configured to determine speed changes data associated with one or more vehicles. The processor may be further configured to calculate congestion length, time period, congestion speed for the one or more vehicles to reach a non-congestion state from a congestion state. The processor may be further configured to generate the traffic congestion data, based on the speed changes data, congestion length, a time period and congestion speed associated with the one or more vehicles on the road.

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 are described for the vehicle emission measurement. An example method may include receiving a plurality of images from a first vehicle traveling on a section of roadway, determining a quantity of surrounding vehicles from the plurality of images, determining a cropped image of at least one of the surrounding vehicles from the plurality of images, identifying a model of the at least one of the surrounding vehicles from the cropped image, and calculating an emission measurement factor for the section of roadway based on at least the quantity of surrounding vehicles for the at least one of the surrounding vehicles.

Abstract: A method and apparatus for calculating an estimated travel time and a method and apparatus for defining a model configured to estimate a travel time are provided. The method for estimating a travel time includes obtaining a movement pattern for a train, determining one or more predicted times when the train will be present at a train crossing where a road path and a train path intersect using the movement pattern, obtaining vehicle historical data including an average time for a vehicle to travel one or more road segments adjoining the train crossing, obtaining a start time, and calculating the travel time for the one or more road segments based on the vehicle historical data, the start time, and the predicted time when the train will be present at the train crossing.

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.

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: The disclosure provides a system, a method, and a computer program product for determining coverage of a vehicle. The system is configured to, for example, acquire sensor data and vehicle data from a user equipment. The sensor data is associated with a region including a plurality of roads. Further, the system is configured to determine a function class of each of the plurality of roads based on the sensor data. Further, the system is configured to determine a type of a vehicle associated with the user equipment, based on the vehicle data. The system is configured to further determine coverage data of the vehicle for each of the plurality of roads based on the function class of a respective road of the plurality of roads and the type of the vehicle. Further, a first notification associated with the coverage of the vehicle, is generated as output.

Abstract: The disclosure provides a system, a method, and a computer program product for updating map data. The system, for example, receives, from one or more user equipment, at least one road works observation. The at least one road works observation is associated with a road works object. Further, the system, determines a first lane and a second lane. Further, the first lane is associated with the at least one road works observation and the second lane is associated with the road works object. Further, the system determines traffic density associated with a region in vicinity of the road works object. Further, the system detects the road works zone based on the first lane, the second lane and the traffic density.

Abstract: Systems and methods are described for the vehicle emission measurement. An example method may include receiving a plurality of images from a first vehicle traveling on a section of roadway, determining a quantity of surrounding vehicles from the plurality of images, determining a cropped image of at least one of the surrounding vehicles from the plurality of images, identifying a model of the at least one of the surrounding vehicles from the cropped image, and calculating an emission measurement factor for the section of roadway based on at least the quantity of surrounding vehicles for the at least one of the surrounding vehicles.

Abstract: Embodiments described herein relate to anonymizing sensor data through the use of map data. Methods include: receiving sensor data defining a trajectory; map-matching the sensor data using a map-matching algorithm to a plurality of road segments of a map database to generate a sequence of map-matched sensor data elements; determining a first value representing anonymization associated with a start of the trajectory; determining a second value representing anonymization associated with an end of the trajectory; determining first map-matched sensor data elements at the start of the trajectory to be redacted based on the first value; determining second map-matched sensor data elements at the end of the trajectory to be redacted based on the second value; and transmitting sensor data associated with elements in the sequence of map-matched sensor data elements between the first map-matched sensor data elements and the second map-matched sensor data elements.

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: The disclosure provides a method, a system, and a computer program product for predicting traffic information for at least one map tile area. The method comprises obtaining probe data and map attribute data for each of a plurality of road segments in the at least one map tile area. The method may include generating current traffic condition data for each of the plurality of road segments in the at least one map tile area based on the obtained probe data and the obtained map attribute data. The method may further include obtaining historical traffic pattern data associated with each of the plurality of road segments in the at least one map tile area.

Abstract: 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.

Abstract: An approach is provided for probe vehicle analysis across travel zones. The approach involves, for example, determining probe data, sensor data, or a combination thereof collected from a plurality of sensors of a plurality of probe vehicles traveling in a geographic area of interest. The approach also involves for each probe vehicle of the plurality of probe vehicles, determining a vehicle attribute and a vehicle path for each probe vehicle from the probe data, the sensor data, or a combination thereof, and determining a start travel zone and an end travel zone of the vehicle path for each probe vehicle. The approach further involves processing the vehicle path for each probe vehicle to determine trip data crossing travel zones based on the start travel zone and the end travel zone. The approach further involves providing the trip data as an output based on the vehicle attribute.

Abstract: Embodiments described herein may provide a method for establishing traffic patterns in an efficient manner. Methods include: receiving historical probe data associated with a road segment; generating traffic pattern data and short-term traffic pattern data for a plurality of periods of time for the road segment, where the traffic pattern data includes traffic patterns that are consistent with historical traffic patterns during a first period of time, and where short-term traffic pattern data includes traffic patterns that fluctuate relative to historical traffic patterns during a second period of time; receiving real-time probe data associated with the road segment during the first period of time and the second period of time; generating traffic data for the road segment using historical traffic pattern data for the first period of time; and generating real-time traffic data for the road segment using the real-time probe data received during the second period of time.

Abstract: An approach is provided for zone-to-zone trip reliability. The approach involves, for example, determining probe data collected from a plurality of sensors of a plurality of probe vehicles traveling in a geographic area of interest. The approach also involves processing the probe data to determine a plurality of vehicle trips. The approach further involves clustering the plurality of vehicle trips into one or more zone-to-zone trip categories based on the origin zones and destination zones of the plurality of vehicle trips. The approach further involves, for each zone-to-zone trip category of the one or more zone-to-zone trip categories, computing a zone-to-zone trip category reliability metric based on the plurality of vehicle trips clustered into each zone-to-zone trip category. The approach further involves providing the zone-to-zone trip category reliability metric for each zone-to-zone trip category as an output.

Abstract: System and methods for detecting and obtaining lane level insight in unplanned incidents. Probe-based vehicles and lane-level insight using a lane-level map-matcher are used to acquire information. This information is aggregated and used to differentiate lane activity in terms of traffic and safe navigation. With the identification of probes per-lane and probe speeds per-lane, sudden reductions in probe speeds may be obtained at a lane-based level. This is used to verify or detect lane-level incident or hazard warnings and consequently alert a driver to safer navigation paths ahead of time, for example alerting the driver to maneuver to a different lane or to take an alternative route.

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.