Passenger classification-based autonomous vehicle routing

• US 10,152,053 B1
• Filed: 07/06/2018
• Issued: 12/11/2018
• Est. Priority Date: 07/06/2017
• Status: Active Grant

• Current Assignee: Cubic Corporation
• Original Assignee: Cubic Corporation
• Inventors: Smith, Gavin, Reymann, Steffen
• Primary Examiner(s): Patel, Shardul D
• Application Number:
  US16/029,218
• Time in Patent Office: 158 Days
• Field of Search: 701 23, 701 25, 701 28, 340435
• CPC Class Codes: G01C 21/3438 Rendez-vous, i.e. searching a destination where several users can meet, and the routes to this destination for these users; Ride sharing, i.e. searching a route such that at least two users can share a vehicle for at least part of the route
• CPC Class Codes: G01C 21/3453 Special cost functions, i.e. other than distance or default speed limit of road segments
• CPC Class Codes: G05D 1/0027 involving a plurality of vehicles, e.g. fleet or convoy travelling fleet control of land vehicles from a control room G05D1/0297; traffic control systems for road vehicles G08G1/00; for marine craft G08G3/00; for aircraft G08G5/00
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G06Q 10/02 Reservations, e.g. for tickets, services or events
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083

Abstract

An autonomous vehicle (AV) fleet management system includes a communications interface, one or more processors, and a memory that stores instructions that cause the processors to receive, a request for a ride using an AV from a wireless communication device of a user. The request may include a pick-up location of the user. The instructions also cause the processors to identify demographic information related to the user, determine a vulnerability score and a priority of the user based at least in part on the demographic information, and receive location information from a plurality of AVs in a fleet of AVs. The instructions further cause the processors to identify a particular AV from the fleet of AVs based at least in part on the vulnerability score, the priority, the pick-up location of the user, and the location of the particular AV and cause the particular AV to pick-up the user.

Claims

1. An autonomous vehicle (AV) fleet management system, comprising:

a communications interface that is in communication with a fleet of AVs;

one or more processors; and

a memory configured to store instructions thereon that, when executed, cause the one or more processors to;

receive, using the communications interface, a request for a ride using an AV from a wireless communication device of a user, the request comprising a pick-up location of the user;

identify demographic information related to the user;

determine a vulnerability score and a priority of the user based at least in part on the demographic information;

receive, using the communications interface, location information from a plurality of AVs in a fleet of AVs;

identify a particular AV from the fleet of AVs based at least in part on the vulnerability score, the priority, the pick-up location of the user, and the location of the particular AV; and

cause the particular AV to pick-up the user.

2. The autonomous vehicle (AV) fleet management system of claim 1, wherein the memory further comprises instructions that, when executed, cause the one or more processors to:

identify any current and identified future riders that are scheduled for each of the plurality of AVs whose rides overlap with the user; and

determine demographic information associated with the any current and identified future riders, and wherein the particular AV is identified from the fleet of AVs based at least in part on the demographic information associated with the any current and identified future riders.

3. The autonomous vehicle (AV) fleet management system of claim 1, wherein the memory further comprises instructions that, when executed, cause the one or more processors to:

determine whether any additional people are within a predetermined threshold distance of the pick-up location;

receiving demographic information about the additional people and wherein identifying the particular AV is further based on the demographic information about the additional people.

4. The autonomous vehicle (AV) fleet management system of claim 1, wherein the memory further comprises instructions that, when executed, cause the one or more processors to:

identify any current and identified future riders that are scheduled that are scheduled to overlap with the user for the particular AV;

determine demographic information for each of the current and identified future riders;

determine that at least one of the current and identified future riders should not share the particular AV with the user; and

issue a command to a different AV from the fleet of AVs to pick-up the user or at least one of the identified future riders based on the determination that at least one of the current and identified future riders should not share the particular AV with the user.

5. The autonomous vehicle (AV) fleet management system of claim 4, wherein the memory further comprises instructions that, when executed, cause the one or more processors to:

communicate a notification the user that the different AV has been dispatched, wherein the notification comprises an estimated pick-up time for the different AV.

6. The autonomous vehicle (AV) fleet management system of claim 4, wherein the memory further comprises instructions that, when executed, cause the one or more processors to:

receive a video feed from an interior of the particular AV; and

analyzing the video feed, wherein determining that at least one of the current and identified future riders should not share the particular AV with the user is based on the analysis of the video feed.

7. The autonomous vehicle (AV) fleet management system of claim 1, wherein the memory further comprises instructions that, when executed, cause the one or more processors to:

communicate a notification to the wireless communications device of the user that the particular AV has been sent to pick the user up.

8. An autonomous vehicle (AV) fleet management system, comprising:

a communications interface that is in communication with a fleet of AVs;

one or more processors; and

a memory configured to store instructions thereon that, when executed, cause the one or more processors to;

receive a plurality of requests for rides using an AV, wherein each of the plurality of requests is provided by a wireless communication device of one of a plurality of users, each request comprising a pick-up location of the a particular one of the plurality of users that is associated with the request;

identify demographic information related to each of the plurality of users;

determine a vulnerability score and a priority for each of the plurality of users based at least in part on the demographic information of each of the particular users;

receive location information from a plurality of AVs in a fleet of AVs;

identify a particular AV from the fleet of AVs for each of the plurality of users based at least in part on the vulnerability score, the priority, the pick-up location of each of the plurality of users, and the location of each of the plurality of AVs, wherein users having higher priorities are assigned an AV from the plurality of AVs with earlier pick-up times than users with lower priorities; and

cause each particular AV to pick-up at least one of the plurality of users.

9. The autonomous vehicle (AV) fleet management system of claim 8, wherein the memory further comprises instructions that, when executed, cause the one or more processors to:

receive crime data for an area associated with the pick-up location for each of the plurality of users, wherein the vulnerability score and the priority for each of the plurality of users is based in part on the crime data.

10. The autonomous vehicle (AV) fleet management system of claim 8, wherein:

at least one AV from the plurality of AVs picks up multiple of the plurality of users during a single trip.

11. The autonomous vehicle (AV) fleet management system of claim 8, wherein the memory further comprises instructions that, when executed, cause the one or more processors to:

receive weather data in an area associated with the pick-up location for each of the plurality of users, wherein the vulnerability score and the priority for each of the plurality of users is based in part on the weather data.

12. The autonomous vehicle (AV) fleet management system of claim 8, wherein the memory further comprises instructions that, when executed, cause the one or more processors to:

alter a route of at least one of the plurality of AVs to accommodate vehicle requirements of a particular one of the plurality of users.

13. The autonomous vehicle (AV) fleet management system of claim 8, wherein the memory further comprises instructions that, when executed, cause the one or more processors to:

determine that a particular one of the plurality of users had additional members in a ride party;

identify demographic information associated with the additional members;

store the demographic information in a profile associated with the particular one of the plurality of users; and

use the stored demographic information in a future identification of a particular AV from the fleet of AVs.

14. The autonomous vehicle (AV) fleet management system of claim 13, wherein:

determining that the particular one of the plurality of users had additional members in a ride party is based on video analytics of an interior of the particular one of the plurality of AVs associated with the particular one of the plurality of users.

15. A method for controlling a fleet of autonomous vehicles (AVs), comprising:

receiving a plurality of requests for rides using an AV, wherein each of the plurality of requests is provided by a wireless communication device of one of a plurality of users, each request comprising a pick-up location of a particular one of the plurality of users that is associated with the request;

identifying demographic information related to each of the plurality of users;

determining a vulnerability score and a priority for each of the plurality of users based at least in part on the demographic information of each of the particular users;

receiving location information from a plurality of AVs in a fleet of AVs;

identifying a particular AV from the fleet of AVs for each of the plurality of users based at least in part on the vulnerability score, the priority, the pick-up location of each of the plurality of users, and the location of each of the plurality of AVs, wherein users having higher priorities are assigned an AV from the plurality of AVs with earlier pick-up times than users with lower priorities; and

causing each particular AV to pick-up at least one of the plurality of users.

16. The method for controlling a fleet of autonomous vehicles (AVs) of claim 15, further comprising:

receiving user accessibility requirements associated with at least one of the plurality of users;

wherein identifying the particular AV for the at least one of the plurality of users is based on the accessibility data, and wherein the particular AV for the at least one of the plurality of users has accessibility resources that match the accessibility requirements associated with the at least one of the plurality of users.

17. The method for controlling a fleet of autonomous vehicles (AVs) of claim 15, further comprising:

determining whether any additional people are within a predetermined threshold distance of the pick-up location for at least one of the plurality of users;

receiving demographic information about the additional people and wherein identifying each particular AV is further based on the demographic information about the additional people.

18. The method for controlling a fleet of autonomous vehicles (AVs) of claim 17, wherein:

determining whether any additional people are within a predetermined threshold distance of the pick-up location comprises;

receiving a video feed from one or more of a camera from one or more AVs of the fleet of AVS or a camera located proximate to the pick-up location; and

analyzing the video to determine one or more of demographic information of the additional people, a mood of the additional people, and a level of aggressiveness of the additional people; and

the priority for the at least one of the plurality of users is determined based at least in part on the demographic information of the additional people, a mood of the additional people, and a level of aggressiveness of the additional people.

19. The method for controlling a fleet of autonomous vehicles (AVs) of claim 15, further comprising:

after causing a particular AV to pick-up a particular one of the passengers, determining that the particular AV does not meet the requirements of the particular one of the users; and

cause a different AV of the plurality of AVs to pick-up the particular one of the users.

20. The method for controlling a fleet of autonomous vehicles (AVs) of claim 19, wherein:

the determination that the particular AV does not meet the requirements of the particular one of the users is based on one or more of the pick-up location, a time of day of the request, a crime rate associated with the pick-up location;

weather data for the pick-up location, demographic information associated with current and future identified users of the particular AV, or demographic information associated with additional people proximate to the pick-up location.