Method and system for risk based driving mode switching in hybrid driving

• US 10,710,590 B2
• Filed: 12/19/2017
• Issued: 07/14/2020
• Est. Priority Date: 12/19/2017
• Status: Active Grant

• Current Assignee: PlusAI, Inc.
• Original Assignee: PlusAI Corp.
• Inventors: Zheng, Hao, Daly, Jr., Timothy Patrick, Liu, David Wanqian
• Primary Examiner(s): Beaulieu, Yonel
• Application Number:
  US15/846,817
• Publication Number:
  US 20190184997A1
• Time in Patent Office: 938 Days
• CPC Class Codes: B60W 2040/0818 Inactivity or incapacity of driver
• CPC Class Codes: B60W 2050/0029 Mathematical model of the driver
• CPC Class Codes: B60W 2050/007 Switching between manual and automatic parameter input, and vice versa
• CPC Class Codes: B60W 2540/045 Occupant permissions
• CPC Class Codes: B60W 2552/00 Input parameters relating to infrastructure
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2555/20 Ambient conditions, e.g. wind or rain
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 2710/20 Steering 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 50/14 Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: B60W 60/0051 from occupants to vehicle
• CPC Class Codes: B60W 60/0053 from vehicle to occupant
• CPC Class Codes: B60W 60/0059 Estimation of the risk associated with autonomous or manual driving, e.g. situation too complex, sensor failure or driver incapacity
• CPC Class Codes: B60W 60/007 Emergency override Handing over between remote control and on-board control or handing over between remote control arrangements G05D1/227
• CPC Class Codes: G05D 1/0011 associated with a remote control arrangement
• 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

Abstract

The present teaching relates to method, system, and medium, for operating a vehicle. The method includes the steps of receiving Real-time data related to the vehicle are received. A current mode of operation of the vehicle is determined. A first risk associated with the current mode of operation of the vehicle is evaluated based on the real-time data in accordance with a risk model. If the first risk satisfies a first criterion, a second risk associated with switching the current mode to a different mode of operation of the vehicle is determined. The vehicle is switched from the current mode to the different mode if the second risk satisfies a second criterion.

Claims

1. A method, implemented on a machine having at least one processor, storage, and a communication platform capable of connecting to a network for operating a vehicle, the method comprising:

receiving real-time data related to the vehicle;

determining a current mode of operation of the vehicle;

evaluating a first risk associated with the current mode of operation of the vehicle based on the real-time data in accordance with a risk model;

determining, in response to the first risk satisfying a first criterion, a second risk associated with switching the current mode to a different mode of operation of the vehicle; and

switching, in response to the second risk satisfying a second criterion, the vehicle from the current mode to the different mode.

2. The method of claim 1, wherein the first risk is indicative of a first level of danger if the vehicle continues to be operated in the current mode, and the second risk is indicative of a second level of danger by switching from the current mode to the different mode.

3. The method of claim 1, further comprising:

receiving sensor data related to a driver of the vehicle; and

determining a state of the driver based on the sensor data in accordance with a driver detection model.

4. The method of claim 3, wherein the current mode of operation of the vehicle is a manual mode, and the first risk is evaluated based on the determined state of the driver.

5. The method of claim 3, wherein the first criterion corresponds to the first risk exceeding a first level associated with the current mode of operation of the vehicle, and the second criterion corresponds to the second risk not exceeding a second level associated with the different mode of operation of the vehicle.

6. The method of claim 1, wherein the real-time data related to the vehicle includes intrinsic capability of the vehicle and extrinsic capability of the vehicle, the intrinsic capability of the vehicle including information relevant to operational capability of the vehicle, and the extrinsic capability of the vehicle including information relevant to an external environment of the vehicle.

7. The method of claim 1, wherein

the current mode of operation of the vehicle is an autonomous mode and the different mode of operation of the vehicle is a manual mode;

and

the second risk is evaluated based on the determined state of the driver.

8. A machine readable medium having information stored thereon for operating a vehicle, wherein the information, when read by the machine, causes the machine to perform the following:

receiving real-time data related to the vehicle;

determining a current mode of operation of the vehicle;

evaluating a first risk associated with the current mode of operation of the vehicle based on the real-time data in accordance with a risk model;

determining, in response to the first risk satisfying a first criterion, a second risk associated with switching the current mode to a different mode of operation of the vehicle; and

switching, in response to the second risk satisfying a second criterion, the vehicle from the current mode to the different mode.

9. The medium of claim 8, wherein the first risk is indicative of a first level of danger if the vehicle continues to be operated in the current mode, and the second risk is indicative of a second level of danger by switching from the current mode to the different mode.

10. The medium of claim 8, wherein the information, when read by the machine further causes the machine to perform:

receiving sensor data related to a driver of the vehicle; and

determining a state of the driver based on the sensor data in accordance with a driver detection model.

11. The medium of claim 10, wherein the current mode of operation of the vehicle is a manual mode, and the first risk is evaluated based on the determined state of the driver.

12. The medium of claim 10, wherein the first criterion corresponds to the first risk exceeding a first level associated with the current mode of operation of the vehicle, and the second criterion corresponds to the second risk not exceeding a second level associated with the different mode of operation of the vehicle.

13. The medium of claim 8, wherein the real-time data related to the vehicle includes intrinsic capability of the vehicle and extrinsic capability of the vehicle, the intrinsic capability of the vehicle including information relevant to operational capability of the vehicle, and the extrinsic capability of the vehicle including information relevant to an external environment of the vehicle.

14. The medium of claim 8, wherein

the current mode of operation of the vehicle is an autonomous mode and the different mode of operation of the vehicle is a manual mode;

and

the second risk is evaluated based on the determined state of the driver.

15. A system for operating a vehicle comprising:

a current risk evaluator implemented by a processor and configured to;

receive real-time data related to the vehicle;

determine a current mode of operation of the vehicle; and

evaluate a first risk associated with the current mode of operation of the vehicle based on the real-time data in accordance with a risk model;

a switch risk determiner implemented by the processor and configured to determine, in response to the first risk satisfying a first criterion, a second risk associated with switching the current mode to a different mode of operation of the vehicle; and

a switch executor implemented by the processor and configured to switch, in response to the second risk satisfying a second criterion, the vehicle from the current mode to the different mode.

16. The system of claim 15, wherein the first risk is indicative of a first level of danger if the vehicle continues to be operated in the current mode, and the second risk is indicative of a second level of danger by switching from the current mode to the different mode.

17. The system of claim 15, wherein the current risk evaluator is further configured to:

receive sensor data related to a driver of the vehicle; and

determine a state of the driver based on the sensor data in accordance with a driver detection model.

18. The system of claim 17, wherein the current mode of operation of the vehicle is a manual mode, and the first risk is evaluated based on the determined state of the driver.

19. The system of claim 17, wherein the first criterion corresponds to the first risk exceeding a first level associated with the current mode of operation of the vehicle, and the second criterion corresponds to the second risk not exceeding a second level associated with the different mode of operation of the vehicle.

20. The system of claim 15, wherein the real-time data related to the vehicle includes intrinsic capability of the vehicle and extrinsic capability of the vehicle, the intrinsic capability of the vehicle including information relevant to operational capability of the vehicle, and the extrinsic capability of the vehicle including information relevant to an external environment of the vehicle.