Cognitive load routing metric for vehicle guidance

• US 10,627,248 B2
• Filed: 09/21/2017
• Issued: 04/21/2020
• Est. Priority Date: 09/21/2016
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: Han, Byron B., Carlson, Jamie P., Gough, Robert J.
• Primary Examiner(s): Badii, Behrang
• Assistant Examiner(s): Abd El Latif, Hossam M
• Application Number:
  US15/711,691
• Publication Number:
  US 20180080785A1
• Time in Patent Office: 943 Days
• Field of Search: 701 25
• CPC Class Codes: B60W 2540/22 Psychological state; Stress level or workload
• CPC Class Codes: B60W 50/0098 Details of control systems ensuring comfort, safety or stability not otherwise provided for
• CPC Class Codes: G01C 21/3453 Special cost functions, i.e. other than distance or default speed limit of road segments
• CPC Class Codes: G01C 21/3461 Preferred or disfavoured areas, e.g. dangerous zones, toll or emission zones, intersections, manoeuvre types, segments such as motorways, toll roads, ferries
• CPC Class Codes: G01C 21/3484 Personalized, e.g. from learned user behaviour or user-defined profiles
• CPC Class Codes: G01C 21/3492 employing speed data or traffic data, e.g. real-time or historical traffic control systems for road vehicles involving transmission of navigation instructions to the vehicle G08G1/0968
• CPC Class Codes: G01C 21/3676 Overview of the route on the road map
• 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: G05D 1/0276 using signals provided by a source external to the vehicle involving a plurality of vehicles G05D1/0287; automatically controlling vehicle speed responsive to externally generated signals B60K31/0058
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/096827 where the route is computed onboard
• CPC Class Codes: G08G 1/096833 where different aspects are considered when computing the route
• CPC Class Codes: G08G 1/096855 where the output is provided in a suitable form to the driver details on I/O arrangements for onboard navigation computers G01C21/36

Abstract

A method for routing a vehicle includes receiving a current location for the vehicle and a destination location for the vehicle and identifying candidate navigation routes extending between the current location and the destination location. The method also includes determining a cognitive load parameter for each candidate navigation route and determining a cost value for a cost function for each candidate navigation route. Each cost value is based on the cognitive load parameter for the respective candidate navigation route. The method also includes selecting the navigation route from the candidate navigation routes based on the cost values for the candidate navigation routes.

Claims

1. A method for selecting a navigation route for a vehicle, comprising:

receiving, by a processor, a current location for the vehicle and a destination location for the vehicle;

identifying, by the processor, candidate navigation routes extending between the current location and the destination location;

determining, by the processor, a distance parameter, a speed parameter, and a cognitive load parameter for each candidate navigation route;

determining, by the processor, a cost value for each candidate navigation route by applying weights to the distance parameter, to the speed parameter, and to the cognitive load parameter of each candidate navigation route, wherein the weights are based on biometric information related to a passenger reaction to a previously selected candidate navigation route; and

selecting, by the processor, the navigation route from the candidate navigation routes based on the cost values for the candidate navigation routes.

2. The method of claim 1, wherein determining the cost value for each candidate navigation route includes determining a cost function for each candidate navigation route, each cost function based on summing the weighted parameters for the respective candidate navigation routes.

3. The method of claim 1, wherein selecting the navigation route includes selecting the candidate navigation route having the highest weight applied to the cognitive load parameter.

4. The method of claim 1, wherein selecting the navigation route includes selecting the candidate navigation route having the lowest cost value.

5. The method of claim 1, wherein selecting the navigation route includes selecting the candidate navigation route having a mid-level cost value within a predetermined range of cost values, wherein the predetermined range of cost values extends between the lowest cost value for the candidate navigation routes and the highest cost value for the candidate navigation routes.

6. The method of claim 1, further comprising:

sending, by the processor, a command to one or more vehicle systems to automatically move the vehicle along the navigation route.

7. The method of claim 1, further comprising:

sending, by the processor for display on a vehicle interface to a passenger of the vehicle, a representation of the navigation route to support guidance along the navigation route.

8. The method of claim 1, wherein the cognitive load parameter is based on at least one of passenger information, infrastructure information, traffic information, or environment information.

9. The method of claim 1, wherein the passenger reaction includes at least one of stress, relaxation, happiness, irritation, or aggravation as indicated by the biometric information.

10. The method of claim 8, wherein the cognitive load parameter is based on infrastructure information including at least one of construction information or resource information.

11. The method of claim 8, wherein the cognitive load parameter is based on traffic information including at least one of pedestrian information, density information, speed information, or incident information.

12. The method of claim 8, wherein the cognitive load parameter is based on environment information including at least one of weather information, scenic information, or security information.

13. A system for selecting a navigation route, comprising:

a controller apparatus configured to perform operations comprising;

receiving a current location for a vehicle and a destination location for the vehicle;

identifying candidate navigation routes extending between the current location and the destination location;

determining a distance parameter and a cognitive load parameter for each candidate navigation route;

determining a cost value for each candidate navigation route by applying weights to the distance parameter and the cognitive load parameter of each candidate navigation route, wherein the weights are based on biometric information related to a passenger reaction to a previously selected candidate navigation route; and

selecting the navigation route from the candidate navigation routes based on the cost values for the candidate navigation routes.

14. The system of claim 13, comprising vehicle systems configured to actuate movement of the vehicle, and wherein the operations further comprise:

sending a command to one or more of the vehicle systems to automatically move the vehicle along the navigation route.

15. The system of claim 13, wherein the cognitive load parameter is based on at least one of passenger information, infrastructure information, traffic information, or environment information.

16. The system of claim 13, wherein the passenger reaction includes at least one of stress, relaxation, happiness, irritation, or aggravation as indicated by the biometric information.

17. The system of claim 15, wherein the cognitive load parameter is based on infrastructure information including at least one of construction information or resource information.

18. The system of claim 15, wherein the cognitive load parameter is based on traffic information including at least one of pedestrian information, density information, speed information, or incident information.

19. The system of claim 15, wherein the cognitive load parameter is based on environment information including at least one of weather information, scenic information, or security information.

20. A non-transitory computer-readable storage medium including program instructions executable by one or more processors that, when executed, cause the one or more processors to perform operations, the operations comprising:

receiving a current location for a vehicle and a destination location for the vehicle;

identifying candidate navigation routes extending between the current location and the destination location;

determining a speed parameter and a cognitive load parameter for each candidate navigation route;

determining a cost value for each candidate navigation route by applying weights to the speed parameter and the cognitive load parameter of each candidate navigation route, wherein the weights are based on biometric information related to a passenger reaction to a previously selected candidate navigation route; and

selecting the navigation route from the candidate navigation routes based on the cost values for the candidate navigation routes.