Method for influencing entities at a roadway intersection
One variation of a method for influencing entities proximal a road surface includes, at an autonomous vehicle: over a first period of time, detecting a pedestrian proximal a road surface; predicting an initial path of the pedestrian an initial confidence score for the initial path of the pedestrian based on and motion of the pedestrian during the first period of time; in response to the initial confidence score falling below a threshold confidence, replaying an audio track audible to the pedestrian and calculating a revised path of the pedestrian and a revised confidence score for the revised path based on motion of the pedestrian following replay of the audio track; and autonomously navigating across the road surface according to a planned route in response to the revised path of the pedestrian falling outside of the planned route and the revised confidence score exceeding the threshold confidence.
1. A system comprising:
at least one sensor of an autonomous vehicle, the at least one sensor configured to capture scan data of a field of view as the autonomous vehicle navigates autonomously along a travel path;
at least one processor configured to track a person proximal to the travel path of the autonomous vehicle and generate a prediction of a trajectory of the person; and
at least one output device of the autonomous vehicle configured to present a prompt to the pedestrian, the prompt presented to direct a movement of the person based on the prediction of the trajectory of the person, at least one action of the autonomous vehicle being autonomously executed based on the movement of the person.
2. The system of claim 1 , wherein the at least one output device includes a speaker presenting the prompt as an audio prompt.
3. The system of claim 2 , wherein the audio prompt is presented along an audio vector determined by tracking the trajectory of the person.
4. The system of claim 1 , wherein the trajectory of the person is determined based on at least one of: direction of motion of the person; speed of motion of the person; change in motion of the person; spatial location of the person relative to the travel path; or direction of gaze of the person.
5. The system of claim 1 , wherein the person is a pedestrian, a bicyclist, a motorcyclist, a driver of another vehicle, or riding a scooter.
6. The system of claim 1 , wherein the trajectory of the person is determined based on a confidence score.
7. The system of claim 6 , wherein the travel path includes an intersection and the confidence score is inversely proportional to a time elapsed since a right of way to enter the intersection transitioned to the autonomous vehicle.
8. One or more non-transitory computer-readable data storage media comprising instructions that, when executed by at least one computing unit of a computing system, cause the computing system to perform operations comprising:
tracking a person proximal to a travel path of an autonomous vehicle;
generating a prediction of a trajectory of the person;
directing a movement of the person based on the prediction of the trajectory of the person, the movement of the person directed by generating a prompt for presentation to the person; and
executing at least one action of the autonomous vehicle autonomously based on the movement of the person.
9. The one or more non-transitory computer-readable data storage media of claim 8 , wherein the prompt is an audio prompt.
10. The one or more non-transitory computer-readable data storage media of claim 9 , wherein the audio prompt is presented along an audio vector determined by tracking the trajectory of the person.
11. The one or more non-transitory computer-readable data storage media of claim 8 , wherein the trajectory of the person is determined based on at least one of: direction of motion of the person; speed of motion of the person; change in motion of the person; spatial location of the person relative to the travel path; or direction of gaze of the person.
12. The one or more non-transitory computer-readable data storage media of claim 8 , wherein the person is a pedestrian, a bicyclist, a motorcyclist, a driver of another vehicle, or riding a scooter.
13. The one or more non-transitory computer-readable data storage media of claim 8 , wherein the trajectory of the person is determined based on a confidence score.
14. The one or more non-transitory computer-readable data storage media of claim 13 , wherein the travel path includes an intersection and the confidence score is inversely proportional to a time elapsed since a right of way to enter the intersection transitioned to the autonomous vehicle.
15. A method comprising:
tracking a person proximal to a travel path of an autonomous vehicle;
generating a prediction of a trajectory of the person;
directing a movement of the person based on the prediction of the trajectory of the person, the movement of the person directed by presenting a prompt to the person; and
executing at least one action of the autonomous vehicle autonomously based on the movement of the person.
16. The method of claim 15 , wherein the travel path includes an intersection and the movement of the person is directed based on a time elapsed since a right of way to enter the intersection transitioned to the autonomous vehicle.
17. The method of claim 15 , wherein the trajectory of the person is determined based on at least one of: direction of motion of the person; speed of motion of the person; change in motion of the person; spatial location of the person relative to the travel path; or direction of gaze of the person.
18. The method of claim 15 , wherein the person is a pedestrian, a bicyclist, a motorcyclist, a driver of another vehicle, or riding a scooter.
19. The method of claim 15 , wherein the prompt is an audio prompt.
20. The method of claim 19 , wherein the audio prompt is presented along an audio vector determined by tracking the trajectory of the person.