Method for calculating nominal vehicle paths for lanes within a geographic region
View Patent ↗One variation of a method for calculating nominal paths for lanes within a geographic region includes: serving a digital frame of a road segment to an annotation portal; at the annotation portal, receiving insertion of a lane marker label, for a lane marker represented in the digital frame, over the digital frame; calculating a nominal path over the road segment and defining a virtual simulator environment for the road segment based on the lane marker label; during a simulation, traversing the virtual road vehicle along the nominal path within the virtual simulator environment and scanning the virtual simulator environment for collisions between the virtual road vehicle and virtual objects within the virtual simulator environment; and, in response to absence of a collision between the virtual road vehicle and virtual objects in the virtual simulator environment, updating a navigation map for the road segment with the nominal path.
1. A method for navigation within a geographic region comprising:
obtaining a digital frame of a road segment;
identifying a lane marker represented in the digital frame;
generating a nominal path over the road segment based on the lane marker;
characterizing motion of a representative vehicle traversing the nominal path according to a physics model of a road vehicle; and
updating a navigation map for the road segment based on the nominal path in response to the motion of the representative vehicle traversing the nominal path falling within motion limitations assigned to autonomous vehicles, navigation of at least one particular autonomous vehicle based on the navigation map.
2. The method of claim 1 , wherein at least one of the nominal path or a label corresponding to the lane marker is adjusted in response to the motion of the representative vehicle traversing the nominal path deviating from the motion limitations assigned to the autonomous vehicles.
3. The method of claim 1 , wherein the motion of the representative vehicle traversing the nominal path is characterized by characterizing lateral accelerations of the representative vehicle traversing the nominal path according to the physics model.
4. The method of claim 1 , wherein the nominal path is adjusted in response to lateral accelerations of the representative vehicle traversing the nominal path exceeding a threshold lateral acceleration.
5. The method of claim 4 , wherein the threshold lateral acceleration is assigned to the autonomous vehicles.
6. The method of claim 1 , wherein the at least one particular autonomous vehicle includes a fleet of autonomous vehicles, each autonomous vehicle in the fleet of autonomous vehicles navigating along a route including the road segment.
7. The method of claim 1 , wherein the nominal path is generated based on a center defined between the lane marker and a second lane marker.
8. The method of claim 7 , wherein the lane marker and the second lane marker are at least one of adjacent or offset.
9. The method of claim 1 , wherein the digital frame is created based on sensor data.
10. The method of claim 1 , wherein the sensor data includes a three-dimensional point cloud.
11. One or more tangible non-transitory computer-readable storage media storing computer-executable instructions for performing a computer process on a computing system, the computer process comprising:
obtaining a digital frame of a road segment;
identifying a lane marker represented in the digital frame;
generating a nominal path over the road segment based on the lane marker;
characterizing motion of a representative vehicle traversing the nominal path according to a physics model of a road vehicle; and
updating a navigation map for the road segment based on the nominal path in response to the motion of the representative vehicle traversing the nominal path falling within motion limitations assigned to autonomous vehicles, navigation of at least one particular autonomous vehicle based on the navigation map.
12. The one or more tangible non-transitory computer-readable storage media of claim 11 , wherein at least one of the nominal path or a label corresponding to the lane marker is adjusted in response to the motion of the representative vehicle traversing the nominal path deviating from the motion limitations assigned to the autonomous vehicles.
13. The one or more tangible non-transitory computer-readable storage media of claim 11 , wherein the motion of the representative vehicle traversing the nominal path is characterized by characterizing lateral accelerations of the representative vehicle traversing the nominal path according to the physics model.
14. The one or more tangible non-transitory computer-readable storage media of claim 11 , wherein the nominal path is adjusted in response to lateral accelerations of the representative vehicle traversing the nominal path exceeding a threshold lateral acceleration.
15. The one or more tangible non-transitory computer-readable storage media of claim 14 , wherein the threshold lateral acceleration is assigned to the autonomous vehicles.
16. The one or more tangible non-transitory computer-readable storage media of claim 11 , wherein the at least one particular autonomous vehicle includes a fleet of autonomous vehicles, each autonomous vehicle in the fleet of autonomous vehicles navigating along a route including the road segment.
17. The one or more tangible non-transitory computer-readable storage media of claim 11 , wherein the nominal path is generated based on a center defined between the lane marker and a second lane marker.
18. The one or more tangible non-transitory computer-readable storage media of claim 17 , wherein the lane marker and the second lane marker are at least one of adjacent or offset.
19. The one or more tangible non-transitory computer-readable storage media of claim 11 , wherein the digital frame is created based on sensor data.
20. The one or more tangible non-transitory computer-readable storage media of claim 11 , wherein the sensor data includes a three-dimensional point cloud.