Smart car method for autonomous navigation by creating a 3D model based on outputs of the camera and sensor; accessing a high definition map database and generating a trip with travel segments from origin to destination; detecting a freeway entrance or an exit lane based on a road marking using a camera and a sensor; if the travel segment passes the freeway entrance or exit, then follow the current lane without exiting; and otherwise following the freeway entrance or exit.
1. A method for autonomous navigation, comprising:
generating one or more trip travel segments from origin to destination;
creating a 3D model based on outputs of the camera and sensor;
accessing a high definition map database and confirming the 3D model with the with travel segments;
detecting a freeway entrance, an exit lane, or a highway divider structure based on a road marking using a camera and a sensor;
guided by the 3D model and determining if the travel segment passes the freeway entrance or exit, then follow the current lane without exiting; and otherwise following the freeway entrance or exit.
2. The method of claim 1 , wherein the marking indicates a yield line, comprising detecting a row of solid isosceles triangles with a black arrow indicating a travel direction.
3. The method of claim 1 , comprising detecting a Yield Marking.
4. The method of claim 1 , comprising detecting a Work Zone Pavement Marking.
5. The method of claim 1 , comprising detecting an Intersection Marking.
6. The method of claim 1 , comprising detecting a Two-Way Traffic Marking.
7. The method of claim 1 , comprising detecting a Freeway Entrance and Exit Marking.
8. The method of claim 1 , comprising detecting a High occupancy vehicle (HOV) Lane Marking.
9. The method of claim 1 , comprising detecting periodic depressions on a side of the road.
10. The method of claim 1 , comprising detecting a side rail on a side of the road.
11. The method of claim 1 , comprising detecting reflective panels on a side of the road.
12. The method of claim 1 , comprising detecting periodic street signs on a side of the road.
13. The method of claim 1 , comprising detecting a curvature on a side of the road.
14. The method of claim 1 , comprising detecting an incoming vehicle.
15. The method of claim 1 , comprising detecting a neighboring vehicle.
16. The method of claim 1 , comprising detecting road reflectors, raised pavement markers, or cat's eyes on a side of the road.
17. The method of claim 1 , comprising detecting rumble strips on a side of the road.
18. The method of claim 1 , comprising detecting a parking area, a pedestrian on a sidewalk, a bike parking structure or a marking.
19. The method of claim 1 , comprising applying a neural network to detect the freeway entrance, exit lane or highway divider structure.
20. A vehicle, comprising:
one or more cameras and sensors;
a processor coupled to the one or more cameras and sensors; and
code executable by the processor for:
creating a 3D model based on outputs of the camera and sensor;
accessing a high definition map database and generating a trip with travel segments from origin to destination;
detecting a freeway entrance, an exit lane, or a highway divider structure based on a road marking using the camera;
guided by the 3D model and determining if the travel segment passes the freeway entrance or exit, then follow the current lane without exiting; and otherwise following the freeway entrance or exit,
wherein the vehicle operates without requiring input from a positioning system.