Method and system for driving mode switching based on self-aware capability parameters in hybrid driving
The present teaching relates to method, system, and medium, for switching a mode of a vehicle. Real-time data related to the vehicle are received, which include intrinsic/extrinsic capability parameters, based on which a set of tasks to switch from a current mode to a different mode is determined. A first duration of time required for the switch is determined based on a first risk evaluated with respect to the current mode and the real-time data. A task duration time needed by a driver to complete the task is estimated for each of the set of tasks. A second risk for the switching is estimated based on the required first duration of time and a total task duration times needed to complete the set of tasks. The switch is carried out when the second risk satisfying a criterion.
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, wherein the real-time data include intrinsic capability parameters and extrinsic capability parameters;
determining, based on the real-time data, a set of tasks to be performed to switch the vehicle from a current mode to a different mode in accordance with a task model;
determining, based on a first risk evaluated with respect to the current mode and the real-time data, a first duration of time required to switch from the current mode to the different mode;
estimating, for each task of the set of tasks, a task duration time needed by a driver present in the vehicle to complete the task;
estimating a second risk of switching from the current mode to the different mode based on the required first duration of time and a total duration of time needed to complete the set of tasks determined based on the task duration times; 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 intrinsic capability parameters specify conditions internal to the vehicle that limit the operational capability of the vehicle, the extrinsic capability parameters specify 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 task of the set of tasks is estimated based on a state of the driver observed.
4. The method of claim 3 , wherein the task duration time for each task of the set of tasks is further estimated based on
a generic response-time profile, characterizing a length of time required by human drivers to complete the task; and
a driver profile for the driver indicative of the task duration time needed by the driver to complete the task.
5. The method of claim 3 , 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.
6. 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.
7. 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 task of the set of tasks.
8. The medium of claim 1 , wherein the data, when read by the machine, further cause 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 task of the set of tasks.
9. 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, wherein the real-time data include intrinsic capability parameters and extrinsic capability parameters;
determining, based on the real-time data, a set of tasks to be performed to switch the vehicle from a current mode to a different mode in accordance with a task model;
determining, based on a first risk evaluated with respect to the current mode and the real-time data, a first duration of time required to switch from the current mode to the different mode;
estimating, for each task of the set of tasks, a task duration time needed by a driver present in the vehicle to complete the task;
estimating a second risk of switching from the current mode to the different mode based on the required first duration of time and a total duration of time needed to complete the set of tasks determined based on the task duration times; and
switching, in response to the second risk satisfying a criterion, from the current mode of the vehicle to the different mode.
10. The medium of claim 9 , wherein the intrinsic capability parameters specify conditions internal to the vehicle that limit the operational capability of the vehicle, the extrinsic capability parameters specify conditions external to the vehicle that limit the operational capability of the vehicle.
11. The medium of claim 9 , wherein the task duration time for each task of the set of tasks is estimated based on a state of the driver observed.
12. The medium of claim 11 , wherein the task duration time for each task of the set of tasks is further estimated based on
a generic response-time profile, characterizing a length of time required by human drivers to complete the task; and
a driver profile for the driver indicative of the task duration time needed by the driver to complete the task.
13. The medium of claim 11 , 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.
14. The medium of claim 9 , 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.
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, wherein the real-time data include intrinsic capability parameters and extrinsic capability parameters, and
determine, based on the real-time data, a set of tasks to be performed to switch the vehicle from a current mode to a different mode in accordance with a task model;
a response time estimator configured to:
determine, based on a first risk evaluated with respect to the current mode and the real-time data, a first duration of time required to switch from the current mode to the different mode, and
estimate, for each task of the set of tasks, a task duration time needed by a driver present in the vehicle 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 required first duration of time and a total duration of time to complete the set of tasks determined based on the task duration times; and
a switch executor configured to switch, in response to the second risk satisfying a criterion, the vehicle from the current mode to the different mode.
16. The system of claim 15 , wherein the intrinsic capability parameters specify conditions internal to the vehicle that limit the operational capability of the vehicle, the extrinsic capability parameters specify 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 task of the set of tasks is estimated based on a state of the driver observed.
18. The system of claim 17 , wherein the task duration time for each task of the set of tasks is further estimated based on
a generic response-time profile, characterizing a length of time required by human drivers to complete the task; and
a driver profile for the driver indicative of the task duration time needed by the driver to complete the task.
19. The system of claim 17 , 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.
20. 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.
21. 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 task of the set of tasks.