Road network optimization based on vehicle telematics information
Methods, systems and apparatus, including computer programs encoded on computer storage media for determining asset efficiency. Unmanned Aerial Vehicles (UAVs) may be used to obtain aerial images of locations, property or structures. The aerial images may be geo-rectified, and a ortho-mosaic, digital surface model, or a point cloud may be created. In the context of an operation where mobile assets are used, such as construction or earth moving equipment, location-based event information may be obtained. The location-based event information may be used to determine road segment conditions or road topology where problematic road conditions likely exist.
1. An apparatus comprising:
a computer readable storage media; and
program instructions stored on the computer readable storage media which, when executed by a processing system, direct the processing system to:
obtain aerial images representing real-world locations;
generate one or more segments based on the aerial images;
obtain historical event information for one or more vehicles that have traversed the one or more segments;
determine from the historical event information whether the one or more vehicles traversed the one or more segments in accordance with traversal criteria; and
in response to determining that at a first subset of the one or more vehicles did not traverse the one or more segments in accordance with the traversal criteria:
generate instructions for at least a second subset of the one or more vehicles to obtain updated sensor data associated with a segment of the one or more segments,
transmit the instructions to each vehicle of the second subset of the one or more vehicles,
receive the updated sensor data, and
update a portion of a road network based on the updated sensor data.
2. The apparatus of claim 1 , wherein to generate the one or more segments based on the aerial images comprises to:
generate the road network based on the aerial images; and
divide the road network into the one or more segments.
3. The apparatus of claim 2 , wherein the one or more segments comprise one or more road segments.
4. The apparatus of claim 3 , wherein
the updated sensor data includes at least one of digital images or LIDAR data.
5. The apparatus of claim 1 , wherein the program instructions, when executed by the processing system, direct the processing system to:
train a visual classifier with a data set of images of the actual physical road conditions;
receive a different set of images from the data set of images, wherein the different set of images depict a portion of a road associated with the road network; and
identify, with the visual classifier, a type of road condition found in the different set of images, wherein the type of road condition is at least one of pot holes, wash boarding, ruts, ditches, alligator cracking, block cracking, transverse cracking, edge cracks, joint reflection cracks, slippage cracks, depressions, shoving, upheaval, raveling, water pooling, snow, large rocks, obstacles, erosion, plant overgrowth, foliage overgrowth, uneven surfaces, or protrusions.
6. The apparatus of claim 1 , wherein the program instructions, when executed by the processing system, direct the processing system to:
determine the traversal criteria for each of the one or more segments as a predefined traversal time based on a type of vehicle, wherein each type of vehicle has a particular traversal time for each of the one or more segments.
7. The apparatus of claim 1 , wherein the program instructions, when executed by the processing system, direct the processing system to:
obtain operational data from the one or more vehicles, the operational data corresponding to the historical event information and comprising at least one of geospatial positions, time, or event data.
8. The apparatus of claim 1 , wherein the program instructions, when executed by the processing system, direct the processing system to:
present, via a user interface, the one or more segments.
9. The apparatus of claim 8 , wherein the program instructions, when executed by the processing system, direct the processing system to:
responsive to determining that the one or more vehicles traversed the one or more segments in accordance with the traversal criteria, display, via the user interface, the one or more segments in a first configuration.
10. The apparatus of claim 8 , wherein the program instructions, when executed by the processing system, direct the processing system to:
responsive to determining that the one or more vehicles traversed the one or more segments not in accordance with the traversal criteria, display, via the user interface, the one or more segments in a second configuration.
11. The apparatus of claim 8 , wherein the program instructions, when executed by the processing system, direct the processing system to:
responsive to determining that a first set of the one or more vehicles traversed the one or more segments in accordance with to the traversal criteria and that a second set of the one or more vehicles traversed the one or more segments not in accordance with the traversal criteria, display, via the user interface, the first set in a first configuration and the second set in a second configuration.
12. The apparatus of claim 1 , wherein the historical event information includes a unique identifier for each vehicle of the one or more vehicles.
13. The apparatus of claim 1 , wherein the historical event information for a vehicle of the one or more vehicles includes at least one of a time of an event, geo-spatial location of the event, duration of the event, speed of the vehicle, fuel consumption of the vehicle, gear position of the vehicle, brake application, vehicle load information, shock absorber data, acceleration data, or deceleration data.
14. The apparatus of claim 1 , wherein the program instructions, when executed by the processing system, direct the processing system to:
determine the traversal criteria based on a road geometry for a particular segment of the one or more segments, wherein the road geometry is based on at least one of cross-falls, center line, superelevation, road width, grade, radius, switch backs, 2-ways, n-ways, or rimpull curves.
15. The apparatus of claim 1 , wherein the program instructions, when executed by the processing system, direct the processing system to:
generate a flight plan for an unmanned aerial vehicle based on at least one of an inspection area associated with the one or more segments or a location of a condition associated with the one or more segments; and
provide the flight plan to the unmanned aerial vehicle or to a ground control station operable to control the unmanned aerial vehicle to perform the flight plan.
16. A system comprising:
a road network vehicle optimization interface module configured to:
obtain aerial images representing real-world locations,
generate one or more road segments based on the aerial images,
obtain historical event information for one or more vehicles that have traversed the one or more road segments,
determine that the one or more vehicles traversed the one or more road segments at a range or value in accordance with a traversal criterion based on the historical event information; and
in response to the determination:
generate instructions for at least some of the one or more vehicles to obtain updated sensor data associated with a segment of the one or more road segments,
transmit the instructions to the at least some of the one or more vehicles, receive the updated sensor data, and
update a portion of a road network based on the updated sensor data; and
an asset efficiency user interface module configured to display the one or more road segments.
17. The system of claim 16 , wherein the road network vehicle optimization interface module is further configured to:
determine the traversal criterion for each of the one or more road segments as a predefined traversal time based on a type of vehicle, wherein each type of vehicle has a particular traversal time for each of the one or more road segments.
18. The system of claim 16 , wherein the road network vehicle optimization interface module is further configured to:
generate a flight plan for an unmanned aerial vehicle based on the one or more road segments; and
provide the flight plan to the unmanned aerial vehicle or to a ground control station operable to control the unmanned aerial vehicle to perform the flight plan.
19. A method comprising:
generating one or more segments based on aerial images obtained from an unmanned aerial vehicle;
obtaining historical information for one or more vehicles that have traversed the one or more segments; and
determining from the historical information that at least some of the one or more vehicles did not traverse at least one of the one or more segments in accordance with traversal criteria; and
in response to determining from the historical information that the at least some of the one or more vehicles did not traverse the at least one of the one or more segments in accordance with the traversal criterion:
generating a flight plan for the unmanned aerial vehicle based on the one or more segments, and
providing the flight plan to the unmanned aerial vehicle to perform the flight plan.
20. The method of claim 19 , comprising:
generating, in response to the determining from the historical information, instructions for the one or more vehicles to obtain sensor data describing actual physical road conditions associated with a segment of the one or more segments;
transmitting the instructions to the one or more vehicles;
receiving the sensor data obtained from the one or more vehicles; and
updating a portion of a road network based on the sensor data.