Active vehicle performance tuning based on driver behavior

• US 10,259,468 B2
• Filed: 06/15/2017
• Issued: 04/16/2019
• Est. Priority Date: 06/15/2017
• Status: Active Grant

• Current Assignee: Hitachi, Ltd.
• Original Assignee: Hitachi, Ltd.
• Inventors: Avireddi, Prashanth, Chen, Heming
• Primary Examiner(s): Swarthout, Brent
• Application Number:
  US15/624,631
• Publication Number:
  US 20180362049A1
• Time in Patent Office: 670 Days
• Field of Search: None
• CPC Class Codes: B60W 2050/0075 Automatic parameter input, automatic initialising or calibrating means
• CPC Class Codes: B60W 2050/0088 Adaptive recalibration
• CPC Class Codes: B60W 2520/105 Longitudinal acceleration
• CPC Class Codes: B60W 2540/043 Identity of occupants
• CPC Class Codes: B60W 2540/10 Accelerator pedal position
• CPC Class Codes: B60W 2540/12 Brake pedal position
• CPC Class Codes: B60W 2540/16 Ratio selector position
• CPC Class Codes: B60W 2540/18 Steering angle
• CPC Class Codes: B60W 2540/30 Driving style
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2554/406 Traffic density
• CPC Class Codes: B60W 2554/80 Spatial relation or speed relative to objects
• CPC Class Codes: B60W 2556/10 Historical data
• CPC Class Codes: B60W 2556/45 External transmission of data to or from the vehicle
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 2556/55 using telemetry
• CPC Class Codes: B60W 2710/06 Combustion engines, Gas turbines
• CPC Class Codes: B60W 2710/10 Change speed gearings
• CPC Class Codes: B60W 2710/22 Suspension systems
• CPC Class Codes: B60W 30/182 Selecting between different operative modes, e.g. comfort and performance modes
• CPC Class Codes: B60W 40/09 : Driving style or behaviour
• CPC Class Codes: B60W 50/0097 : Predicting future conditions
• CPC Class Codes: B60W 50/082 : Selecting or switching between different modes of propelling
• CPC Class Codes: B60W 50/085 : Changing the parameters of the control units, e.g. changing limit values, working points by control input
• CPC Class Codes: G06F 16/437 : Administration of user profiles, e.g. generation, initialisation, adaptation, distribution

Abstract

The driver'"'"'s driving behavior will be recorded and a signature will be created either on vehicle or on a cloud data center. The driver signature can be accessed using secure authentication by any vehicle he will be driving. The data collection is a continuous process monitoring driving behavior of the driver. The guidelines from OEM are used to compare driver signature with ideal driving characteristics. Changes are pushed to the vehicle controller to modify controls of individual automotive components to adjust the efficiency of vehicle and improve the ride comfort for the driver. The changes to be made can be decided on a remote cloud system or on the vehicle.

Claims

1. A vehicle, comprising:

one or more sensors configured to provide sensor data;

a processor, configured to;

determine a driver signature for a vehicle corresponding to a driver of the vehicle, the driver signature configured to provide a prediction of one or more upcoming driver actions made to the vehicle;

while the vehicle is in operation, control functionality of the vehicle in response to the prediction from the driver signature, wherein different functionality of the vehicle is controlled based on different predicted upcoming drive actions from the driver signature;

wherein, to determine the driver signature for the vehicle corresponding to the driver of the vehicle, the processor is configured to, for the driver having an associated driver signature, select the driver signature from a plurality of driver signatures based on the sensor data of the vehicle received while the vehicle is in operation, wherein each of the plurality of driver signatures is associated with a corresponding driver, wherein the each of the plurality of driver signatures is generated from historical driver data of the corresponding driver.

2. The vehicle of claim 1, wherein the one or more upcoming driving actions comprises at least one of:

braking, acceleration, lane changing, turning and cruising.

3. The vehicle of claim 1, wherein the processor is further configured to, for the driver not having an associated driver signature from the plurality of signatures:

construct the driver signature for the driver from a machine learning process, the machine learning process configured to;

process as input, historical sensor information associated with the driver; and

generate the driver signature to be configured to process sensor information of the vehicle as input to determine the upcoming driver actions as output.

4. The vehicle of claim 1, wherein the processor is configured to control the functionality of the vehicle in response to the prediction from the driver signature of the one or more upcoming driver actions made to the vehicle while the vehicle is in operation through control of parameters for at least one of vehicle suspension and transmission, shock absorbers, and engine control system.

5. The vehicle of claim 1, wherein, to determine the driver signature for the vehicle, the processor is configured to:

process a driver identifier associated with the driver, and;

obtain the driver signature associated with the driver identifier.

6. An apparatus, communicatively coupled to one or more vehicles, the apparatus comprising:

a network interface configured to facilitate communications to the one or more vehicles; and

a processor, configured to;

process sensor data from each of the one or more vehicles;

determine a driver signature for a vehicle from the one or more vehicles corresponding to a driver of the vehicle, the driver signature configured to provide a prediction of one or more upcoming driver actions made to the vehicle from the one or more vehicles, wherein different functionality of the vehicle is controlled based on different predicted upcoming drive actions from the driver signature; and

while the vehicle is in operation, provide the driver signature for the vehicle from the one or more vehicles;

wherein, to determine the driver signature for the vehicle, the processor is configured to, for the driver having an associated driver signature, select the driver signature from a plurality of driver signatures based on sensor data of the vehicle received while the vehicle is in operation, wherein each of the plurality of driver signatures is associated with a corresponding driver, wherein the each of the plurality of driver signatures is generated from historical driver data of the corresponding driver.

7. The apparatus of claim 6, wherein the one or more upcoming driving actions comprises at least one of:

braking, acceleration, lane changing, turning and cruising.

8. The apparatus of claim 6, wherein the processor is further configured to, for the driver not having an associated driver signature from the plurality of signatures:

construct the driver signature from a machine learning process for the driver, the machine learning process configured to;

process as input, historical sensor information associated with the driver; and

generate the driver signature to be configured to process sensor information of the vehicle from the one or more vehicles as input to determine the upcoming driver actions as output.

9. The apparatus of claim 6, wherein the processor is configured to control the functionality of the vehicle in response to the prediction from the driver signature of the one or more upcoming driver actions made to the vehicle while the vehicle is in operation through control of parameters for at least one of vehicle suspension and transmission, shock absorbers, and engine control system.

10. The apparatus of claim 6, wherein to determine the driver signature for the vehicle from the one or more vehicles, the processor is configured to:

process a driver identifier associated with the driver of the vehicle from the one or more vehicles, and;

obtain the driver signature associated with the driver identifier.

11. A system, comprising:

one or more vehicles configured to provide sensor data; and

an apparatus, communicatively coupled to one or more vehicles, the apparatus comprising;

a network interface configured to facilitate communications to the one or more vehicles; and

a processor, configured to;

process the provided sensor data from each of the one or more vehicles;

determine a driver signature for a vehicle from the one or more vehicles corresponding to a driver of the vehicle, the driver signature configured to provide a prediction of one or more upcoming driver actions made to the vehicle from the one or more vehicle; and

while the vehicle from the one or more vehicles is in operation, provide the driver signature to the vehicle from the one or more vehicles, wherein different functionality of the vehicle is controlled based on different predicted upcoming drive actions from the driver signature;

wherein, to determine the driver signature for the vehicle, the processor is configured to, for the driver of the vehicle having an associated driver signature, select the driver signature from a plurality of driver signatures based on sensor data of the vehicle received while the vehicle is in operation, wherein each of the plurality of driver signatures is associated with a corresponding driver, wherein the each of the plurality of driver signatures is generated from historical driver data of the corresponding driver.

12. The system of claim 11, wherein the one or more upcoming driving actions comprises at least one of:

braking, acceleration, lane changing, turning and cruising.

13. The system of claim 11, wherein the processor is further configured to, for the driver not having an associated driver signature from the plurality of signatures:

construct the driver signature for the driver from a machine learning process, the machine learning process configured to;

process as input, historical trip information associated with the driver and historical sensor information associated with the driver;

generate the driver signature to be configured to process sensor information of the vehicle as input to determine the upcoming driver actions as output.

14. The system of claim 11, wherein the processor is configured to control the functionality of the vehicle in response to the prediction from the driver signature of the one or more upcoming driver actions made to the vehicle while the vehicle is in operation through control of parameters for at least one of vehicle suspension and transmission, shock absorbers, and engine control system.

15. The system of claim 11, wherein to determine the driver signature for the vehicle from the one or more vehicles, the processor is configured to:

process a driver identifier associated with the driver of the vehicle from the one or more vehicles, and;

obtain the driver signature associated with the driver identifier.

16. The system of claim 11, wherein each of the one or more vehicles configured to construct the driver signature for the driver from a machine learning process, the machine learning process configured to:

process as input, historical trip information associated with the driver and historical sensor information associated with the driver;

generate the driver signature to be configured to process sensor information of the vehicle as input to determine the upcoming driver actions as output.