Systems and methods for navigating lane merges and lane splits
Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a system includes a processing device programmed to receive a plurality of images representative of an environment of the host vehicle. The environment includes a road on which the host vehicle is traveling. The at least one processing device is further programmed to analyze the images to identify a target vehicle traveling in a lane of the road different from a lane in which the host vehicle is traveling; analyze the images to identify a lane mark associated with the lane in which the target vehicle is traveling; detect lane mark characteristics of the identified lane mark; use the detected lane mark characteristics to determine a type of the identified lane mark; determine a characteristic of the target vehicle; and determine a navigational action for the host vehicle based on the determined lane mark type and the determined characteristic of the target vehicle.
1. A system for navigating a host vehicle, the system comprising:
at least one processing device comprising circuitry and a memory, wherein the memory includes instructions that when executed by the circuitry cause the at least one processing device to:
receive a plurality of images acquired by an image capture device, the plurality of images being representative of an environment of the host vehicle;
analyze at least one of the plurality of images to identify at least one lane mark associated with a lane in which a target vehicle is traveling;
determine at least one characteristic of the target vehicle based on at least one of the plurality of images, wherein the at least one determined characteristic of the target vehicle includes a detected motion of the target vehicle relative to the at least one identified lane mark; and
determine a navigational action for the host vehicle based on the determined characteristic of the target vehicle.
2. The system of claim 1 , wherein the at least one identified lane mark includes a merge lane.
3. The system of claim 1 , wherein the instructions when executed by the circuitry further cause the at least one processing device to detect a distance of the at least one identified lane mark to a reference point.
4. The system of claim 3 , wherein the reference point includes at least one other lane mark of the road.
5. The system of claim 1 , wherein the instructions when executed by the circuitry further cause the at least one processing device to detect an intersection of the at least one identified lane mark with at least one other lane mark of the road.
6. The system of claim 1 , wherein the instructions when executed by the circuitry further cause the at least one processing device to detect a change in lateral distances between the at least one identified lane mark and at least one other lane mark of the road.
7. The system of claim 1 , wherein determining at least one characteristic of the target vehicle includes analyzing at least one of the plurality of images.
8. The system of claim 1 , wherein the at least one determined characteristic of the target vehicle includes a position of the target vehicle on the road forward of the host vehicle.
9. The system of claim 1 , wherein the at least one determined characteristic of the target vehicle includes a velocity of the target vehicle relative to the host vehicle.
10. The system of claim 1 , wherein the at least one determined characteristic of the target vehicle includes a predicted trajectory of the target vehicle.
11. The system of claim 1 , wherein the determined navigation action for the host vehicle includes changing a rate of acceleration.
12. The system of claim 1 , wherein the determined navigation action for the host vehicle includes a steering action of the host vehicle.
13. The system of claim 1 , wherein the instructions when executed by the circuitry further cause the at least one processing device to predict a navigational action of the target vehicle based on a determined lane mark type.
14. The system of claim 13 , wherein the predicted navigational action of the target vehicle includes a lane merge.
15. The system of claim 1 , wherein the at least one identified lane mark includes a split lane.
16. The system of claim 1 , wherein the instructions when executed by the circuitry further cause the at least one processing device to detect a distance of the at least one identified lane mark to a reference point.
17. The system of claim 16 , wherein the reference point includes at least one other lane mark of the road.
18. The system of claim 1 , wherein the instructions when executed by the circuitry further cause the at least one processing device to detect a split of the at least identified lane mark into another lane mark.
19. A method for navigating a host vehicle, the method comprising:
receiving a plurality of images acquired by an image capture device, the plurality of images being representative of an environment of the host vehicle;
analyzing at least one of the plurality of images to identify at least one lane mark associated with a lane in which a target vehicle is traveling;
determining at least one characteristic of the target vehicle based on at least one of the plurality of images, wherein the at least one determined characteristic of the target vehicle includes a detected motion of the target vehicle relative to the at least one identified lane mark; and
determining a navigational action for the host vehicle based on the determined characteristic of the target vehicle.
20. The method of claim 19 , wherein the at least one identified lane mark includes a merge lane.
21. The method of claim 19 , wherein the instructions when executed by the circuitry further cause the at least one processing device to detect a distance of the at least one identified lane mark to a reference point.
22. The method of claim 21 , wherein the reference point includes at least one other lane mark of the road.
23. The method of claim 19 , further comprising detecting an intersection of the at least one identified lane mark with at least one other lane mark of the road.
24. The method of claim 19 , further comprising detecting a change in lateral distances between the at least one identified lane mark and at least one other lane mark of the road.
25. The method of claim 19 , wherein determining at least one characteristic of the target vehicle includes analyzing at least one of the plurality of images.
26. The method of claim 19 , wherein the at least one determined characteristic of the target vehicle includes a position of the target vehicle on the road forward of the host vehicle.
27. The method of claim 19 , wherein the at least one determined characteristic of the target vehicle includes a velocity of the target vehicle relative to the host vehicle.
28. The method of claim 19 , wherein the at least one determined characteristic of the target vehicle includes a predicted trajectory of the target vehicle.
29. The method of claim 19 , wherein the determined navigation action for the host vehicle includes changing a rate of acceleration.
30. The method of claim 19 , wherein the determined navigation action for the host vehicle includes a steering action of the host vehicle.
31. The method of claim 19 , further comprising predicting a navigational action of the target vehicle based on a determined lane mark type.
32. The method of claim 31 , wherein the predicted navigational action of the target vehicle includes a lane merge.
33. The method of claim 19 , wherein the at least one identified lane mark includes a split lane.
34. The method of claim 19 , further comprising detecting a distance of the at least one identified lane mark to a reference point.
35. The method of claim 34 , wherein the reference point includes at least one other lane mark of the road.
36. The method of claim 19 , further comprising detecting a split of the at least identified lane mark into another lane mark.
37. A non-transitory computer-readable medium storing instructions executable by at least processor to perform a method for navigating a host vehicle, the method comprising:
receiving a plurality of images acquired by an image capture device, the plurality of images being representative of an environment of the host vehicle;
analyze at least one of the plurality of images to identify at least one lane mark associated with a lane in which a target vehicle is traveling;
determine at least one characteristic of the target vehicle based on at least one of the plurality of images, wherein the at least one determined characteristic of the target vehicle includes a detected motion of the target vehicle relative to the at least one identified lane mark; and
determine a navigational action for the host vehicle based on the determined at least one characteristic of the target vehicle.