Systems and methods for controlling autonomous vehicles that provide a vehicle service to users

Patent metadata

Field	Value
Publication number	US-10528059-B2
Application number	US-201715662314-A
Country	US
Kind code	B2
Filing date	Jul 28, 2017
Priority date	May 24, 2017
Publication date	Jan 7, 2020
Grant date	Jan 7, 2020

Abstract

Systems and methods for controlling autonomous vehicles are provided. In one example embodiment, a computer implemented method includes obtaining data indicative of a location associated with a user to which an autonomous vehicle is to travel. The autonomous vehicle is to travel along a first vehicle route that leads to the location. The method includes obtaining traffic data associated with a geographic area that includes the location. The method includes determining an estimated traffic impact of the autonomous vehicle on the geographic area based at least in part on the traffic data. The method includes determining vehicle action(s) based at least in part on the estimated traffic impact and causing the autonomous vehicle to perform the vehicle action(s) that include at least one of stopping the autonomous vehicle at least partially in a travel way within a vicinity of the location or travelling along a second vehicle route.

First claim

What is claimed is:

1. A computer-implemented method of controlling autonomous vehicles, comprising:
obtaining, by a vehicle computing system that comprises one or more computing devices, data indicative of a location associated with a user to which an autonomous vehicle is to travel, wherein the autonomous vehicle is to travel along a first vehicle route that leads to the location associated with the user;
obtaining, by the computing system via one or more sensors of the autonomous vehicle, sensor data associated with a surrounding environment of the autonomous vehicle that is within a vicinity of the location associated with the user;
determining, by the computing system, a level of traffic associated with a geographic area that includes the location associated with the user based at least in part on the sensor data;
determining, by the vehicle computing system, an estimated traffic impact of the autonomous vehicle on the geographic area based at least in part on the level of traffic that is based at least in part on the sensor data, wherein the estimated traffic impact is indicative of an estimated impact of the autonomous vehicle on one or more objects within the surrounding environment of the autonomous vehicle in the event that the autonomous vehicle were to stop at least partially in a travel way within the vicinity of the location associated with the user;
determining, by the vehicle computing system, one or more vehicle actions based at least in part on the estimated traffic impact; and
causing, by the vehicle computing system, the autonomous vehicle to perform the one or more vehicle actions, wherein the one or more vehicle actions comprise at least one of stopping the autonomous vehicle at least partially in the travel way within the vicinity of the location associated with the user or travelling along a second vehicle route.

2. The computer-implemented method of claim 1 , further comprising:
obtaining, by the vehicle computing system, location data associated with a user device associated with the user;
determining, by the vehicle computing system, an estimated time of user arrival based at least in part on the location data associated with the user device; and
determining, by the vehicle computing system, the one or more vehicle actions also based at least in part on the estimated time of user arrival.

3. The computer-implemented method of claim 1 , wherein the vicinity of the location associated with the user is defined at least in part by a distance from the location associated with the user, and wherein the distance from the location associated with the user is based at least in part on an acceptable walking distance from the location associated with the user.

4. The computer-implemented method of claim 1 , wherein determining, by the vehicle computing system, the estimated traffic impact comprises:
comparing, by the vehicle computing system, the level of traffic to a traffic constraint.

5. The computer-implemented method of claim 4 , wherein the traffic constraint comprises a traffic threshold indicative of a threshold level of traffic.

6. The computer-implemented method of claim 4 , wherein the traffic constraint is determined at least in part on a machine-learned model.

7. The computer-implemented method of claim 1 , wherein the second vehicle route is at least partially different from the first vehicle route and wherein the second vehicle route includes a route that leads to the location associated with the user.

8. The computer-implemented method of claim 1 , wherein the autonomous vehicle stops at least partially in the travel way within the vicinity of the location associated with the user, the method further comprising:
providing, by the vehicle computing system to a user device associated with the user, a communication indicating that the autonomous vehicle is stopped, and
wherein in response to receiving the communication the user device displays a map user interface that indicates a vehicle location of the autonomous vehicle and a user route to the vehicle location of the autonomous vehicle.

9. The computer-implemented method of claim 1 , further comprising:
determining, by the vehicle computing system, that a parking location that is out of the travel way is unavailable for the autonomous vehicle.

10. A vehicle computing system onboard an autonomous vehicle, comprising:
one or more processors; and
one or more memory devices, the one or more memory devices storing instructions that when executed by the one or more processors cause the computing system to perform operations, the operations comprising:
obtaining data indicative of a location associated with a user, wherein the user is associated with a request for a vehicle service provided by the autonomous vehicle, and wherein the autonomous vehicle is to travel along a first vehicle route to arrive within a vicinity of the location associated with the user;
obtaining, via one or more sensors of the autonomous vehicle, sensor data associated with a surrounding environment of the autonomous vehicle that is within the vicinity of the location associated with the user;
determining a level of traffic associated with a geographic area that includes the location associated with the user based at least in part on the sensor data;
obtaining location data associated with a user device associated with the user;
determining an estimated traffic impact of the autonomous vehicle on the geographic area based at least in part on the level of traffic that is based at least in part on the sensor data and an estimated time of user arrival based at least in part on the location data associated with the user device,
wherein the estimated traffic impact is indicative of an estimated impact of the autonomous vehicle on one or more objects within the surrounding environment of the autonomous vehicle in the event that the autonomous vehicle were to stop at least partially in a travel way within the vicinity of the location associated with the user;
determining one or more vehicle actions based at least in part on at least one of the estimated traffic impact or the estimated time of user arrival; and
causing the autonomous vehicle to perform the one or more vehicle actions, wherein the one or more vehicle actions comprise at least one of stopping the autonomous vehicle at least partially in the travel way within the vicinity of the location associated with the user or travelling along a second vehicle route.

11. The computing system of claim 10 , wherein determining one or more vehicle actions based at least in part on at least one of the estimated traffic impact or the estimated time of user arrival comprises:
applying a first weighting factor to the estimated traffic impact and a second weighting factor to the estimated time of user arrival.

12. The computing system of claim 10 , wherein the autonomous vehicle stops at least partially in the travel way within the vicinity of the location associated with the user, and wherein the operations further comprise:
determining at least one of an updated estimated traffic impact or an updated estimated time of user arrival; and
causing the autonomous vehicle to travel along the second vehicle route based at least in part on at least one of the updated estimated traffic impact or the updated estimated time of user arrival.

13. The computing system of claim 10 , wherein the autonomous vehicle travels along the second vehicle route, and wherein the operations further comprise:
providing a communication to the user device associated with the user, wherein the communication indicates that the autonomous vehicle is travelling to return to

Assignees

• Uatc Llc

Inventors

• Donnelly Richard Brian
• Aitken Michael

Classifications

• G08G1/143

  inside the vehicles · CPC title

• G08G1/0112

  from the vehicle, e.g. floating car data [FCD] · CPC title

• G08G1/0145

  for active traffic flow control · CPC title

• G08G1/09623

  Systems involving the acquisition of information from passive traffic signs by means mounted on the vehicle (G08G1/0967 takes precedence) · CPC title

• B60R16/037

  for occupant comfort {, e.g. for automatic adjustment of appliances according to personal settings, e.g. seats, mirrors, steering wheel} · CPC title