Activity recommendation based on a real-time mapping between activity characteristics and autonomous vehicle dynamics

Patent metadata

Field	Value
Publication number	US-10996074-B2
Application number	US-201816202599-A
Country	US
Kind code	B2
Filing date	Nov 28, 2018
Priority date	Nov 28, 2018
Publication date	May 4, 2021
Grant date	May 4, 2021

Abstract

An approach for recommending an activity during travel. The approach includes receiving a request for a travel destination and a desired arrival time. Furthermore, the approach determines a route to the travel destination and retrieves external data based on the route. Based on the retrieved data and the route, the approach calculates and outputs an initial activity list. And the approach measures vehicle dynamics based on one or more motion sensors and updates and outputs the activity list based on the vehicle dynamics.

First claim

What is claimed is:

1. A method for recommending an activity during travel by an autonomous vehicle, the method comprising: receiving a request for a travel destination and a desired arrival time for a traveler on an autonomous vehicle;
determining a route to the travel destination; retrieving external data based on the route; calculating and outputting an initial activity list based on the external data, energy consumption rate of the autonomous vehicle as required by each individual activity as part of the initial activity list, habit and propensity of the traveler and the route, wherein the initial activity list consists of jogging, rowing and running; measuring vehicle dynamics based on one or more motion sensors of an autonomous vehicle; and updating the initial activity list and outputting an updated initial activity list based on the vehicle dynamics, energy consumption rate of the autonomous vehicle as required by each individual activity as part of the updated initial activity list and changing road conditions.

2. The method of claim 1 , wherein determining the route to the travel destination further comprises:
retrieving one or more routes to the travel destination; and
selecting one route from the one or more routes based on the desired arrival time.

3. The method of claim 1 , wherein retrieving external data further comprises of weather-related, traffic related and road conditions.

4. The method of claim 1 , wherein calculating and outputting the initial activity list further comprises:
determining the initial activity list based on one or more susceptibility factors, the external data and the desired arrival time; and
outputting the initial activity list to one or more users.

5. The method of claim 4 , wherein the one or more susceptibility factors further comprises of α, β and γ wherein are α, β and γ are the one or more susceptibility factors for the activity list associated movements along X, Y and Z axes, respectively.

6. The method of claim 1 , wherein measuring the vehicle dynamics further comprises:
retrieving data from one or more sensors wherein the one or more sensors are capable of detecting forces along x, y and z axis of the vehicle.

7. The method of claim 1 , wherein updating the initial activity list and outputting the updated initial activity list based on the vehicle dynamics further comprises:
determining the initial activity list based on one or more susceptibility factors, the external data, the desired arrival time and the vehicle dynamics; and
outputting the updated initial activity list to one or more users.

8. The method of claim 1 , wherein the one or more sensors further comprises of radio frequency-based proximity sensors, sound-based proximity sensors, accelerometers, camera and GPS.

9. The method of claim 1 , further comprising:
measuring a cognitive state of one or more users; and
updating the initial activity list and outputting the updated initial activity list based on the cognitive state of the one or more users.

10. The method of claim 9 , wherein the cognitive state of the user further comprises of happy, sad, sleepy, angry and tired.

11. A computer system for recommending an activity during travel by an autonomous vehicle, the computer system comprising: one or more computer processors; one or more computer readable storage devices; and program instructions stored on the one or more computer readable storage devices for execution by at least one of the one or more computer processors, the stored program instructions comprising: program instructions to receive a request for a travel destination and a desired arrival time for a traveler on an autonomous vehicle; program instructions to determine a route to the travel destination;
program instructions to retrieve external data based on the route; program instructions to calculate and output an initial activity list based on the external data, energy consumption rate of the autonomous vehicle as required by each individual activity as part of the initial activity list, habit and propensity of the traveler and the route, wherein the initial activity list consists of jogging, rowing and running;
program instructions to measure vehicle dynamics based on one or more motion sensors of an autonomous vehicle; and program instructions to update the initial activity list and output the updated initial activity list based on the vehicle dynamics, energy consumption rate of the autonomous vehicle as required by each individual activity as part of the updated initial activity list and changing road conditions.

12. The computer system of claim 11 , wherein determining the route to the travel destination further comprises:
program instructions to retrieve one or more routes to the travel destination; and
program instructions to select one route from the one or more routes based on the desired arrival time.

13. The computer system of claim 11 , wherein retrieving external data further comprises of weather-related, traffic related and road conditions.

14. The computer system of claim 11 , wherein calculating and outputting the initial activity list further comprises:
program instructions to determine the initial activity list based on one or more susceptibility factors, the external data and the desired arrival time; and
program instructions to output the initial activity list to one or more users.

15. The computer system of claim 14 , wherein the one or more susceptibility factors further comprises of α, β and γ wherein are α, β and γ are the one or more susceptibility factors for the activity list associated movements along X, Y and Z axes, respectively.

16. The computer system of claim 11 , wherein measuring the vehicle dynamics further comprises:
program instructions to retrieve data from one or more sensors wherein the one or more sensors are capable of detecting forces along x, y and z axis of the vehicle.

17. The computer system of claim 11 , wherein updating the initial activity list and outputting the updated initial activity list based on the vehicle dynamics further comprises:
program instructions to determine the initial activity list based on one or more susceptibility factors, the external data, the desired arrival time and the vehicle dynamics; and
program instructions to output the initial activity list to one or more users.

18. The computer system of claim 11 , wherein the one or more sensors further comprises of radio frequency-based proximity sensors, sound-based proximity sensors, accelerometers, camera and GPS.

19. The computer system of claim 11 , further comprising:
program instructions to measure a cognitive state of one or more users; and
program instructions to update the initial activity list and output the updated initial activity list based on the cognitive state of the one or more users.

20. The computer system of claim 19 , wherein the cognitive state of the user further comprises of happy, sad, sleepy, angry and tired.

Assignees

• IBM

Inventors

• Pandey Diwesh
• Ghosh Shiladitya
• Reddy Shashidhar
• Joseph Arun
• Haridass Anand

Classifications

• A61B5/0022

  Monitoring a patient using a global network, e.g. telephone networks, internet · CPC title

• G01C21/3697 Primary

  Output of additional, non-guidance related information, e.g. low fuel level (G01C21/3679 takes precedence) · CPC title

• G06N5/04

  Inference or reasoning models · CPC title

• A61B5/165

  Evaluating the state of mind, e.g. depression, anxiety · CPC title

• A61B2503/22

  Motor vehicles operators, e.g. drivers, pilots, captains · CPC title