METHOD AND SYSTEM FOR RISK CONTROL IN SWITCHING DRIVING MODE

• US 20190187700A1
• Filed: 12/19/2017
• Published: 06/20/2019
• 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
• Granted Patent: US 10,620,627 B2
• Time in Patent Office: Days
• CPC Class Codes: B60W 2040/0872 Driver physiology
• CPC Class Codes: B60W 2050/0072 Controller asks driver to take over
• CPC Class Codes: B60W 2050/0095 Automatic control mode change
• CPC Class Codes: B60W 2520/10 Longitudinal speed
• CPC Class Codes: B60W 2540/22 Psychological state; Stress level or workload
• CPC Class Codes: B60W 2540/221 Physiology, e.g. weight, heartbeat, health or special needs
• CPC Class Codes: B60W 2540/223 Posture, e.g. hand, foot, or seat position, turned or inclined
• CPC Class Codes: B60W 2540/229 Attention level, e.g. attentive to driving, reading or sleeping
• CPC Class Codes: B60W 2540/26 Incapacity
• CPC Class Codes: B60W 2552/53 Road markings, e.g. lane marker or crosswalk
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 40/08 related to drivers or passengers
• CPC Class Codes: B60W 50/082 Selecting or switching between different modes of propelling
• CPC Class Codes: B60W 50/14 Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: B60W 60/0057 Estimation of the time available or required for the handover
• 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: G05D 1/0061 for transition from automatic pilot to manual pilot and vice versa
• CPC Class Codes: G06F 9/4881 Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
• CPC Class Codes: G06F 9/4887 involving deadlines, e.g. rate based, periodic

Abstract

The present teaching relates to method, system, and medium, for switching a mode of a vehicle. Real-time data related to the vehicle and a state of a driver are received and used to determine a set of tasks to be performed to switch the vehicle from a current mode to a different mode based on a task model. A first duration of time required to switch is determined based on a first risk associated with the current mode. A task duration time needed to complete each task is estimated. A second risk associated with the switching is determined based on the first duration as required and a total duration of time determined based on the task duration time needed to complete the set of tasks. The vehicle mode is switched if the second risk satisfying a 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 switching a vehicle from a current mode to a different mode, the method comprising:

receiving real-time data related to the vehicle and a state of a driver in the vehicle;

determining, based on the real-time data, a set of tasks to be performed to switch the vehicle from the current mode to the different mode in accordance with a task model;

determining, based on a first risk associated with the current mode, a first duration of time required to switch from the current mode to the different mode;

estimating, for each of the set of tasks, a task duration time needed to complete the task;

estimating a second risk of switching from the current mode to the different mode based on the first duration of time as required and a total duration of time determined based on the task duration time needed to complete the set of tasks; and

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

2. The method of claim 1, wherein the real-time data includes intrinsic capability parameters and extrinsic capability parameters, the intrinsic capability parameters specifying conditions internal to the vehicle that limit the operational capability of the vehicle, the extrinsic capability parameters specifying conditions external to the vehicle that limit the operational capability of the vehicle.

3. The method of claim 1, wherein the task duration time for each of the set of tasks is estimated based on the state of the driver and/or a driver profile.

4. The method of claim 3, wherein the task duration time for each of the set of tasks is further estimated based on a response-time profile, which includes information corresponding to time required by human drivers to complete the task, and the driver profile is indicative of the task duration time needed by the driver to complete the task.

5. The method of claim 1, wherein the criterion corresponds to the total duration of time needed to complete the set of tasks being less than or equal to the first duration of time.

6. The method of claim 1, further comprising:

generating, prior to the switching, a switch warning instruction in response to the second risk satisfying the criterion, based on the set of tasks to be performed and the task duration time needed to complete each of the set of tasks.

7. The method of claim 1, wherein the state of the driver

is estimated based on information obtained from a plurality of sensors disposed in the vehicle;

and

includes at least one of a pose of the driver, a functional state of the driver, a health state of the driver, and a mental state of the driver.

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

receiving real-time data related to the vehicle and a state of a driver in the vehicle;

determining, based on the real-time data, a set of tasks to be performed to switch the vehicle from the current mode to the different mode in accordance with a task model;

determining, based on a first risk associated with the current mode, a first duration of time required to switch from the current mode to the different mode;

estimating, for each of the set of tasks, a task duration time needed to complete the task;

estimating a second risk of switching from the current mode to the different mode based on the first duration of time as required and a total duration of time determined based on the task duration time needed to complete the set of tasks; and

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

9. The medium of claim 8, wherein the real-time data includes intrinsic capability parameters and extrinsic capability parameters, the intrinsic capability parameters specifying conditions internal to the vehicle that limit the operational capability of the vehicle, the extrinsic capability parameters specifying conditions external to the vehicle that limit the operational capability of the vehicle.

10. The medium of claim 8, wherein the task duration time for each of the set of tasks is estimated based on the state of the driver and/or a driver profile.

11. The medium of claim 10, wherein the task duration time for each of the set of tasks is further estimated based on a response-time profile, which includes information corresponding to time required by human drivers to complete the task, and the driver profile is indicative of the task duration time needed by the driver to complete the task.

12. The medium of claim 8, wherein the criterion corresponds to the total duration of time needed to complete the set of tasks being less than or equal to the first duration of time.

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

generating, prior to the switching, a switch warning instruction in response to the second risk satisfying the criterion, based on the set of tasks to be performed and the task duration time needed to complete each of the set of tasks.

14. The medium of claim 8, wherein the state of the driver

is estimated based on information obtained from a plurality of sensors disposed in the vehicle;

and

includes at least one of a pose of the driver, a functional state of the driver, a health state of the driver, and a mental state of the driver.

15. A system for switching a vehicle from a current mode to a different mode, the system comprising:

a switch task estimator configured to;

receive real-time data related to the vehicle and a state of a driver in the vehicle; and

determine, based on the real-time data, a set of tasks to be performed to switch the vehicle from the current mode to the different mode in accordance with a task model;

a response time estimator configured to;

determine, based on a first risk associated with the current mode, a first duration of time required to switch from the current mode to the different mode; and

estimate, for each of the set of tasks, a task duration time needed to complete the task;

a switching risk estimator configured to;

estimate a second risk of switching from the current mode to the different mode based on the first duration of time as required and a total duration of time determined based on the task duration time needed to complete the set of tasks; and

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

16. The system of claim 15, wherein the real-time data includes intrinsic capability parameters and extrinsic capability parameters, the intrinsic capability parameters specifying conditions internal to the vehicle that limit the operational capability of the vehicle, the extrinsic capability parameters specifying conditions external to the vehicle that limit the operational capability of the vehicle.

17. The system of claim 15, wherein the task duration time for each of the set of tasks is estimated based on the state of the driver and/or a driver profile.

18. The system of claim 17, wherein the task duration time for each of the set of tasks is further estimated based on a response-time profile, which includes information corresponding to time required by human drivers to complete the task, and the driver profile is indicative of the task duration time needed by the driver to complete the task.

19. The system of claim 15, wherein the criterion corresponds to the total duration of time needed to complete the set of tasks being less than or equal to the first duration of time.

20. The system of claim 15, further comprising a warning instruction generator configured to:

generate, prior to the switching, a switch warning instruction in response to the second risk satisfying the criterion, based on the set of tasks to be performed and the task duration time needed to complete each of the set of tasks.