Classifying routes of travel

Patent metadata

Field	Value
Publication number	US-9733097-B2
Application number	US-201414530290-A
Country	US
Kind code	B2
Filing date	Oct 31, 2014
Priority date	Oct 31, 2014
Publication date	Aug 15, 2017
Grant date	Aug 15, 2017

Abstract

The disclosure includes a method that includes assigning a classification to a travel route followed by a first client device based on data associated with when the first client device followed the travel route. The method may further include recommending the travel route to a second client device based on a request from the second client device for a desired travel route with the classification.

First claim

What is claimed is:

1. A method, comprising:
estimating an attitude of an operator of a first client device towards a travel route based on data collected by the first client device while the first client device was following the travel route and operated by the operator, wherein the travel route includes a plurality of scenes and the data describes one or more emotional states of the operator while the first client device and the operator were present at the plurality of scenes such that each of the one or more emotional states are responsive to at least one of the scenes included in the plurality of scenes;
assigning, by a processor, a classification to the travel route based on the attitude of the operator towards the travel route, wherein the classification describes the travel route consistent with the one or more emotional states of the operator responsive to the at least one of the scenes included in the plurality of scenes;
generating a map that includes a plurality of travel routes and their assigned classifications, wherein the plurality of travel routes includes the travel route followed by the first client device and its assigned classification and the map visually depicts the plurality of scenes and the one or more emotional states of the operator while the first client device and the operator were present at the plurality of scenes; and
recommending the travel route to a second client device based on a request from the second client device for a desired travel route with the classification, wherein recommending the travel route includes selecting the travel route from the map based on the classification wherein the second client device is an onboard computer of a vehicle that is configured to provide the recommended travel route to an operator of the vehicle.

2. The method of claim 1 , further comprising verifying the one or more emotional states based on user data from a user interface of the first client device.

3. The method of claim 1 , wherein the data includes sensor data collected by one or more sensors of a second vehicle which is communicatively coupled to the first client device.

4. The method of claim 1 , wherein the first client device is a first onboard computer of a first vehicle and the second client device is a second onboard computer of a second vehicle.

5. The method of claim 1 , wherein the estimation of the emotional state of the operator is based on one or more of an image of the operator and a biological metric of the operator.

6. The method of claim 1 , wherein the data further includes images of the plurality of scenes along the travel route followed by the first client device.

7. The method of claim 6 , wherein the images are captured by one or more sensors of a second vehicle with which the first client device is associated, wherein the second vehicle is different than the first client device.

8. The method of claim 6 , wherein the images are retrieved from one or more social media collections associated with the first client device.

9. The method of claim 6 , wherein the map includes the images of the plurality of scenes.

10. The method of claim 1 , further comprising:
receiving time synchronicity data associated with when the first client device followed the travel route; and
receiving weather data about the travel route that corresponds to the time synchronicity data, wherein the travel route followed by the first client device is classified based on the weather data.

11. A system comprising:
one or more processors; and
a memory communicatively coupled to the one or more processors, the memory storing instructions that when executed cause the system to:
assign a classification to a travel route followed by a first client device based on data associated with when the first client device followed the travel route while operated by an operator, wherein the travel route includes a plurality of scenes, the data describes an emotional reaction of the operator to the plurality of scenes and the classification describes the travel route based on the emotional reaction;
generate a map that includes a plurality of travel routes and their assigned classifications as aggregated from a plurality of client devices, wherein the plurality includes the travel route followed by the first client device and its assigned classification and the map visually depicts the plurality of scenes and the emotional reaction; and
recommend the travel route followed by a first client device to a second client device based on a request from the second client device for a desired travel route with the classification, wherein recommending the travel route includes selecting the travel route from the map based on the classification wherein the second client device is an onboard computer of a vehicle that is configured to provide the recommended travel route to an operator of the vehicle.

12. The system of claim 11 , wherein the instructions further cause the system to verify the classification of the travel route based on user data from a user interface.

13. The system of claim 11 , wherein the data is based on one or more sensors of a second vehicle of which the first client device is associated, wherein the second vehicle is different than the first client device.

14. The system of claim 11 , wherein the data includes sensor data collected by one or more sensors of a second vehicle with which the first client device is associated, wherein the second vehicle is different than the first client device.

15. The system of claim 11 wherein the data includes an indication of an emotional state of the operator.

16. The system of claim 15 , wherein the indication of the emotional state of the operator is based on one or more of an image of the operator and a biological metric of the operator.

17. The system of claim 11 , wherein the data includes images of scenes along the travel route followed by the first client device.

18. The system of claim 17 , wherein the images are captured by one or more sensors of a vehicle with which the first client device is associated.

19. The system of claim 17 , wherein the images are retrieved from one or more social media collections associated with the first client device.

20. The system of claim 18 , wherein the instructions further cause the system to:
receive time synchronicity data associated with when the first client device followed the travel route; and
receive weather data about the travel route that corresponds to the time synchronicity data, wherein the travel route followed by the first client device is classified based on the weather data.

21. The system of claim 11 , wherein the instructions further cause the system to provide the map to the second client device.

22. A non-transitory computer-readable medium having computer instructions stored thereon that are executable by a processing device to perform or control performance of operations comprising:
receive sensor data that includes travel route data of a first client device associated with a vehicle and operator data of an operator of the vehicle as the first client device follows a travel route;
determine, based on the operator data, an emotional state of the operator while the operator follows the travel route;
correlate the travel route data with the emotional state of the operator;
assign a classification to the travel route based on correlation of the travel route data and the emotional state of the operator; and
generating a map that includes a plurality of

Assignees

• Toyota Motor Co Ltd
• Denso Corp

Inventors

• Sisbot Emrah Akin
• Yalla Veera Ganesh
• Martinson Eric
• Nomoto Hirokazu
• Hasegawa Takuya

Classifications

• G06F18/24

  Classification techniques · CPC title

• G06F17/30268

  Physics · mapped topic

• G06K9/00711

  Physics · mapped topic

• G01C21/3453

  Special cost functions, i.e. other than distance or default speed limit of road segments · CPC title

• G06K9/00302

  Physics · mapped topic