Utilizing accelerometer data to configure an autonomous vehicle for a user

• US 9,989,645 B2
• Filed: 04/01/2016
• Issued: 06/05/2018
• Est. Priority Date: 04/01/2016
• Status: Active Grant

• Current Assignee: Uber Technologies, Inc.
• Original Assignee: Uber Technologies, Inc.
• Inventors: Donnelly, Richard
• Primary Examiner(s): Black, Thomas G
• Assistant Examiner(s): Smith-Stewart, Demetra R
• Application Number:
  US15/089,408
• Publication Number:
  US 20170284819A1
• Time in Patent Office: 795 Days
• Field of Search: None
• CPC Class Codes: B60N 2/02 the seat or part thereof being movable, e.g. adjustable adjustable arm-rests B60N2/75; adjustable head-rests B60N2/806
• CPC Class Codes: B60N 2/20 the back-rest being tiltable, e.g. to permit easy access B60N2/04, B60N2/22 , B60N2/3002 take precedence
• CPC Class Codes: B60R 16/037 for occupant comfort , e.g. for automatic adjustment of appliances according to personal settings, e.g. seats, mirrors, steering wheel
• CPC Class Codes: B60W 2540/00 Input parameters relating to occupants
• CPC Class Codes: B60W 40/08 related to drivers or passengers
• CPC Class Codes: G01S 19/13 Receivers
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083
• CPC Class Codes: G08G 1/20 Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles

Abstract

A system can analyze accelerometer data and location data from a mobile computing device to determine a set of user attributes for a user of the mobile computing device. In certain implementations, the set of user attributes can be utilized by a backend transport facilitation system to configure an autonomous vehicle'"'"'s seat for the user prior to being picked up for transport.

Claims

1. A transport facilitation system comprising:

one or more processors; and

one or more memory resources storing instructions that, when executed by the one or more processors, cause the transport facilitation system to;

receive a pick-up request from a mobile computing device of a requesting user, the pick-up request comprising a pick-up location;

based on the pick-up location, select an autonomous vehicle (AV) to service the pick-up request;

in response to receiving the pick-up request, receive and analyze accelerometer data and location data from the mobile computing device;

based on the accelerometer data and the location data, determine a set of user attributes of the requesting user;

based on the determined set of user attributes, determine a set of seat adjustments for a seat of the selected AV; and

transmit, to the selected AV, a set of configuration instructions based on the set of seat adjustments to cause the selected AV to configure the seat based on the set of user attributes for the requesting user prior to arriving at the pick-up location.

2. The transport facilitation system of claim 1, wherein the executed instructions cause the transport facilitation system to analyze the accelerometer data and the location data to (i) identify a stride length of the requesting user, and (ii) estimate a height of the requesting user based on the stride length.

3. The transport facilitation system of claim 2, wherein the executed instructions cause the transport facilitation system to analyze the accelerometer data and the location data to further determine a femur length of the user based on the stride length, and wherein the set of seat adjustments comprises a thigh extension adjustment based on the femur length of the user.

4. The transport facilitation system of claim 1, wherein the executed instructions further cause the transport facilitation system to analyze the accelerometer data and the location data to (i) determine a gait pattern of the requesting user, and (ii) estimate a body type of the requesting user based on the gait pattern.

5. The transport facilitation system of claim 4, wherein the set of seat adjustments comprises one of a relaxed setting or an upright setting based on the body type of the requesting user.

6. The transport facilitation system of claim 1, wherein the set of seat adjustments comprises adjustments for two or more of a backrest angle, a thigh extension length, a fore-and-aft position, a headrest angle, a headrest level, a lumbar setting, a seat depth, a seat height, an upper seat tilt angle, and a shoulder support setting.

7. The transport facilitation system of claim 1, wherein the executed instructions further cause the transport facilitation system to:

receive adjustment data from the selected AV, the adjustment data corresponding to subsequent set of seat adjustments made by the requesting user while en route to a drop-off location; and

generate and store a comfort profile for the requesting user based on the adjustment data.

8. The transport facilitation system of claim 1, wherein the executed instructions further cause the transport facilitation system to:

transmit, to the mobile computing device of the requesting user, a notification indicating a location of the configured seat within the AV prior to the AV arriving at the pick-up location.

9. A mobile computing device comprising:

a display screen;

a positioning system;

an inertial measurement unit;

one or more processors; and

one or more memory resources storing a designated application for a transportation service, wherein the designated application, when executed by the one or more processors, causes the mobile computing device to;

generate a user interface for the transportation service on the display screen;

receive user inputs via the user interface requesting transportation for a requesting user of the mobile computing device;

in response to the user inputs, transmit a pick-up request to a backend transport facilitation system to enable selection of an autonomous vehicle (AV) to service the pick-up request and rendezvous with the requesting user at a pick-up location;

analyze accelerometer data from the inertial measurement unit and location data from the positioning system;

based on the accelerometer data and the location data, determine a set of user attributes of the requesting user;

transmit, to the backend transport facilitation system, the set of user attributes to enable a seat of the AV to be automatically configured, prior to arriving at the pick-up location, for the requesting user.

10. The mobile computing device of claim 9, wherein execution of the designated application further causes the mobile computing device to analyze the accelerometer data and the location data to (i) identify a stride length of the requesting user, and (ii) estimate a height of the requesting user based on the stride length, the height being included in the set of user attributes.

11. The mobile computing device of claim 10, wherein execution of the designated application causes the mobile computing device to analyze the accelerometer data and the location data to further determine a femur length of the requesting user based on the stride length, the femur length being included in the set of user attributes.

12. A computer-implemented method of determining user attributes to configure an autonomous vehicle (AV) the method being performed by one or more processors and comprising:

analyzing accelerometer data from a mobile computing device of a user;

analyzing location data from the mobile computing device;

based on the accelerometer data and the location data, determining a set of physical user attributes for the user of the mobile computing device;

based on the determined set of user attributes, determining a set of seat adjustments for a seat of the AV; and

transmitting, to the AV, a set of configuration instructions based on the set of seat adjustments to cause the AV to configure the seat based on the set of user attributes for the user prior to arriving at a pick-up location to rendezvous with the user.

13. The method of claim 12, wherein analyzing the accelerometer data and the location data comprises determining a stride length of the user, and wherein the set of physical user attributes comprises an estimated height of the user based on the stride length.

14. The method of claim 13, wherein the set of physical user attributes comprises an estimated femur length of the user based on the stride length.

15. The method of claim 12, wherein analyzing the accelerometer data and the location data comprises determining a gait pattern of the requesting user, and wherein the set of physical user attributes comprises a body type of the user based on the gait pattern.

16. The method of claim 12, wherein the method is performed by a backend transport facilitation system that receives the accelerometer data and the location data from the mobile computing device in response to receiving a pick-up request from the mobile computing device.

17. The method of claim 16, wherein the pick-up request comprises the pick-up location, the method further comprising:

based on the pick-up location, selecting the AV to service the pick-up request.

18. The method of claim 17, wherein the set of seat adjustments comprises adjustments for two or more of a backrest angle, a thigh extension length, a fore-and-aft position, a headrest angle, a headrest level, a lumbar setting, a seat depth, a seat height, an upper seat tilt angle, and a shoulder support setting.

19. The method of claim 17, further comprising:

receiving adjustment data from the selected AV, the adjustment data corresponding to subsequent set of seat adjustments made by the user while en route to a drop-off location; and

generating and storing a comfort profile for the user based on the adjustment data.

20. The method of claim 12, further comprising:

transmitting, to the mobile computing device of the user, a notification indicating a location of the configured seat within the AV prior to the AV arriving at the pick-up location.