CN115517639A - Method, device and equipment for calibrating trust of automatic driving system and vehicle - Google Patents

Method, device and equipment for calibrating trust of automatic driving system and vehicle Download PDF

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Publication number
CN115517639A
CN115517639A CN202211268640.1A CN202211268640A CN115517639A CN 115517639 A CN115517639 A CN 115517639A CN 202211268640 A CN202211268640 A CN 202211268640A CN 115517639 A CN115517639 A CN 115517639A
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China
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target
index
vehicle
user
trust
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周可远
李心怡
张海沫
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Guangdong Oppo Mobile Telecommunications Corp Ltd
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Guangdong Oppo Mobile Telecommunications Corp Ltd
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
    • A61B5/02055—Simultaneously evaluating both cardiovascular condition and temperature
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    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
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    • A61M21/02—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis for inducing sleep or relaxation, e.g. by direct nerve stimulation, hypnosis, analgesia
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    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/021—Measuring pressure in heart or blood vessels
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Abstract

The embodiment of the application discloses a method, a device, equipment and a vehicle for calibrating the trust of an automatic driving system, wherein the calibration method comprises the following steps: acquiring state information of a user in a vehicle, wherein the state information comprises behavior information and/or physiological information; determining a target trust degree index corresponding to the user according to the state information, wherein the target trust degree index is used for representing the trust degree of the user on an automatic driving system of the vehicle; and executing target operation for adjusting the trust degree according to the target trust degree index. By implementing the method, the trust degree of the user on the automatic driving system of the vehicle can be calibrated in time.

Description

Method, device and equipment for calibrating trust degree of automatic driving system and vehicle
Technical Field
The application relates to the technical field of automatic driving, in particular to a method, a device, equipment and a vehicle for calibrating the trust level of an automatic driving system.
Background
With the progress of the automatic Driving technology, the activities required by users to be put into car operation and road observation are gradually reduced, and more energy is put into Non-Driving-related behaviors (NDRT), such as watching movies, playing games, playing mobile phones, chatting, sleeping, and the like. This phenomenon is premised on the user having a suitable sense of trust in the vehicle's autopilot system.
Disclosure of Invention
The embodiment of the application provides a method, a device and equipment for calibrating the trust level of an automatic driving system and a vehicle, and the trust level of a user on the automatic driving system of the vehicle can be calibrated in time.
The embodiment of the application provides a method for calibrating the trust level of an automatic driving system in a first aspect, which comprises the following steps:
acquiring state information of a user in a vehicle, wherein the state information comprises behavior information and/or physiological information;
determining a target trust degree index corresponding to the user according to the state information, wherein the target trust degree index is used for representing the trust degree of the user on an automatic driving system of the vehicle;
and executing target operation for adjusting the trust degree according to the target trust degree index.
A second aspect of the embodiments of the present application provides a device for calibrating a confidence level of an automatic driving system, including:
the system comprises a state acquisition unit, a state acquisition unit and a state processing unit, wherein the state acquisition unit is used for acquiring state information of a user in a vehicle, and the state information comprises behavior information and/or physiological information;
the trust degree calculation unit is used for determining a target trust degree index corresponding to the user according to the state information, and the target trust degree index is used for representing the trust degree of the user on an automatic driving system of the vehicle;
and the credibility calibration unit is used for executing target operation for adjusting the credibility according to the target credibility index.
A third aspect of embodiments of the present application provides an electronic device, including:
a memory storing executable program code;
and a processor coupled to the memory;
the processor calls the executable program code stored in the memory, and when executed by the processor, the executable program code causes the processor to implement the method according to the first aspect of the embodiments of the present application.
A fourth aspect of the embodiments of the present application provides a vehicle including the electronic device according to the third aspect of the embodiments of the present application.
A fifth aspect of embodiments of the present application provides a computer-readable storage medium, on which executable program code is stored, and when the executable program code is executed by a processor, the method according to the first aspect of embodiments of the present application is implemented.
A sixth aspect of embodiments of the present application discloses a computer program product, which, when run on a computer, causes the computer to perform any one of the methods disclosed in the first aspect of embodiments of the present application.
A seventh aspect of the embodiments of the present application discloses an application publishing platform, where the application publishing platform is configured to publish a computer program product, where when the computer program product runs on a computer, the computer is caused to execute any one of the methods disclosed in the first aspect of the embodiments of the present application.
According to the technical scheme, the embodiment of the application has the following advantages:
in the embodiment of the application, the state information of a user in a vehicle is acquired, wherein the state information comprises behavior information and/or physiological information; determining a target trust degree index corresponding to the user according to the state information, wherein the target trust degree index is used for representing the trust degree of the user on an automatic driving system of the vehicle; and executing target operation for adjusting the trust degree according to the target trust degree index.
By implementing the method, the trust degree of the user on the automatic driving system of the vehicle can be determined in real time according to the state information of the user in the vehicle, and then the corresponding target operation is executed according to the trust degree, so that the aim of calibrating the trust degree of the user on the automatic driving system of the vehicle in real time is fulfilled.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings used in the description of the embodiments and the prior art will be briefly described below, and it is obvious that the drawings in the description below are only some embodiments of the present application, and other drawings can be obtained according to the drawings.
Fig. 1 is a schematic diagram of an application scenario disclosed in an embodiment of the present application;
FIG. 2 is a flowchart illustration of a method for calibrating confidence in an autopilot system as disclosed in an embodiment of the present application;
FIG. 3 is a flowchart illustration of another method for calibrating confidence in an autopilot system as disclosed in an embodiment of the present application;
FIG. 4 is a diagram of an exemplary architecture of a confidence calibration apparatus for an autopilot system according to an embodiment of the present disclosure;
fig. 5 is a structural diagram of an electronic device disclosed in an embodiment of the present application.
Detailed Description
The embodiment of the application provides a method, a device and equipment for calibrating the trust level of an automatic driving system and a vehicle, and the trust level of a user on the automatic driving system of the vehicle can be calibrated in time.
For a person skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, and not all embodiments. The embodiments in the present application shall fall within the protection scope of the present application.
The technical scheme disclosed by the embodiment of the application is applied to the automatic driving vehicle, and the automatic driving vehicle can comprise but is not limited to a two-wheel vehicle, a three-wheel vehicle, a four-wheel vehicle, a hybrid vehicle or other driving energy source driving vehicles with automatic driving capability. When the autonomous vehicle executes the autonomous Driving agent, a user in the vehicle may perform a Non-Driving-related action (NDRT) in the vehicle, or may monitor the vehicle at any time. The user in the vehicle may be a driver, an operator, a supervisor of the autonomous vehicle, or may be a general passenger.
Fig. 1 is a schematic view of an application scenario disclosed in an embodiment of the present application. The application scenario diagram shown in fig. 1 includes a vehicle 10. With the advancement of the automatic driving technology, the activities of the user in the vehicle 10 involved in car maneuvering and road observation gradually decrease, and more energy is put into the NDRT, such as watching movies, playing games, playing mobile phones, chatting, sleeping, and the like. The premise of this phenomenon is that the user has a suitable trust level for the automatic driving system of the vehicle 10, and therefore, how to calibrate the trust level of the user for the automatic driving system of the vehicle becomes a technical problem that needs to be solved urgently in the industry.
In the prior art, a method for calibrating the trust level of a user on an automatic driving system of a vehicle generally includes obtaining a report of the trust level of the automatic driving system of the vehicle, which is reported by the user in the vehicle 10 in a period of time, measuring according to the obtained report, and calibrating according to a measurement result, which is poor in real-time performance.
In the technical scheme disclosed in the embodiment of the application, the trust level of the user on the automatic driving system of the vehicle 10 can be determined in real time according to the state information of the user in the vehicle 10, and then the corresponding target operation is executed according to the trust level, so that the purpose of calibrating the trust level of the user on the automatic driving system of the vehicle 10 in real time is achieved.
Referring to fig. 2, fig. 2 is a flowchart illustrating a method for calibrating confidence level of an automatic driving system according to an embodiment of the present disclosure. The calibration method as shown in fig. 2 may comprise the steps of:
201. status information of a user in a vehicle is obtained, the status information including behavioral information and/or physiological information.
In the embodiment of the application, the state information of the user in the vehicle can be acquired through the sensor system of the vehicle. Among others, the sensor system may include, but is not limited to, the following devices: gaze detectors, cameras, microphones, wearable devices, and other physiological signal measuring devices, and the like. Wherein, gazing detector and camera can be used for acquireing user's in the vehicle action information, and wearing equipment and other physiological signal measuring equipment can be used for acquireing user's in the vehicle physiological information.
In some embodiments, the behavioral information may include at least one of: posture information, expression information, eye movement information, and the like. The physiological information may include at least one of: electrocardio, heart rate, pressure, skin temperature, blood oxygen saturation, blood pressure, respiratory rate, skin electricity, myoelectricity, electroencephalogram and the like.
202. And determining a target trust degree index corresponding to the user according to the state information, wherein the target trust degree index is used for representing the trust degree of the user on the automatic driving system of the vehicle.
Under the condition that one user is in the vehicle, the target trust degree index represents the trust degree of the user on the automatic driving system of the vehicle, and the target trust degree index can be obtained according to the state information of the user. In the case that there are a plurality of users in the vehicle, the target trust index may represent the overall trust level of the plurality of users on the automatic driving system of the vehicle, and the target trust index may be obtained according to the state information of each user.
The target trust index may be proportional to the trust degree, and the greater the target trust index is, the higher the trust degree of the user on the automatic driving system of the vehicle is.
203. And executing target operation for adjusting the trust degree according to the target trust degree index.
In some embodiments, performing a target operation for adjusting the trust level according to the target trust level index may include:
when the target trust degree index is smaller than a first index threshold value, executing a first operation for improving the trust degree; and/or the presence of a gas in the gas,
and when the target confidence index is larger than the second index threshold value, executing a second operation for reducing the confidence level.
By implementing the method, when the target confidence index is smaller than the first index threshold, the first operation for improving the confidence degree is executed, and when the target confidence index is larger than the second index threshold, the second operation for reducing the confidence degree is executed, so that the user can keep proper confidence degree for the automatic driving system of the vehicle, the user can effectively benefit from the automatic driving system, proper driving alertness can be kept, and the occurrence probability of accidents is reduced.
In some embodiments, performing a target operation for adjusting a trust level according to the target confidence index may include: and executing target operation for adjusting the trust degree through the vehicle-mounted equipment of the vehicle according to the target trust degree index.
Wherein, the vehicle-mounted equipment can comprise at least one of the following: vehicle-mounted screen, loudspeaker, vibration actuator, odor generator, cockpit lighting controller and the like
In some embodiments, performing the first operation may include at least one of:
outputting weather information through a vehicle-mounted screen and/or a loudspeaker;
outputting food recommendation information through a vehicle-mounted screen and/or a loudspeaker;
outputting the scenic spot recommendation information through a vehicle-mounted screen and/or a loudspeaker;
playing the relaxing music through a loudspeaker;
displaying interesting visual advertisements through a vehicle-mounted screen;
controlling the cabin light to be in a mild atmosphere mode;
the odor generator is controlled to emit refreshing fragrance.
In some embodiments, performing the second operation may include at least one of:
outputting vehicle state information through a vehicle-mounted screen and/or a loudspeaker; wherein the vehicle state information may include at least one of: vehicle travel speed, vehicle current location, driving mode, etc.;
outputting vehicle surrounding environment information through a vehicle-mounted screen and/or a loudspeaker; wherein the vehicle surrounding environment information may include at least one of: other vehicles, pedestrians, traffic lights, traffic signs, etc. near the vehicle;
outputting vehicle decision information and the like through a vehicle-mounted screen and/or a loudspeaker; wherein the vehicle decision information may include at least one of: acceleration, deceleration, emergency stop, lane change, etc.;
controlling the cabin light to be in a strong atmosphere mode;
controlling the scent generator to emit an inspiring scent;
and controlling the vibration actuator to vibrate greatly.
By implementing the method, the information for adjusting the trust degree is not limited to vision, but also can comprise touch, hearing and smell, and the calibration mode is richer.
By implementing the method, the trust degree of the user on the automatic driving system of the vehicle can be determined in real time according to the state information of the user in the vehicle, and the corresponding target operation is executed according to the trust degree, so that the aim of calibrating the trust degree of the user on the automatic driving system of the vehicle in real time is fulfilled.
Referring to fig. 3, fig. 3 is a flowchart illustrating another method for calibrating the confidence level of the automatic driving system according to an embodiment of the disclosure. The calibration method as shown in fig. 3 may comprise the steps of:
301. status information of a user in a vehicle is obtained, the status information including behavioral information and/or physiological information.
For the related content of the status information, please refer to the following description of step 201 shown in fig. 2, which is not repeated herein.
302. And determining a target trust degree index corresponding to the user according to the state information, wherein the target trust degree index is used for representing the trust degree of the user on the automatic driving system of the vehicle.
In some embodiments, the current driving scene information of the vehicle can be further identified according to the environmental information around the vehicle.
Further, determining a target trust index corresponding to the user according to the state information may include: and determining a target trust degree index corresponding to the user according to the state information and the current driving scene information of the vehicle.
In some embodiments, the number of users in the vehicle is multiple, and determining the target confidence index corresponding to the user according to the state information may include: determining a trust index corresponding to each user according to the state information of each user in the vehicle; and taking the minimum trust index in the trust indexes corresponding to each user as a target trust index corresponding to the user in the vehicle.
In some embodiments, the status information includes behavioral information and physiological information, the in-vehicle user includes a first user; determining a trust index corresponding to the first user according to the state information of the first user may include: determining a first trust index according to the behavior information of the first user; determining a second confidence index according to the physiological information of the first user; and determining the trust index corresponding to the first user according to the first trust index and the second trust index.
In some embodiments, determining the first confidence index based on the behavioral information of the first user may include: and determining a first confidence index according to the behavior information of the first user and the current driving scene information of the vehicle.
In some embodiments, the behavior information includes posture information, expression information, and eye movement information, and the determining the first confidence index according to the behavior information of the first user and the current driving scene information of the vehicle may include, but is not limited to, the following:
the method comprises the steps that 1, a first sub-trust index, a second sub-trust index and a third sub-trust index are determined according to posture information, expression information and eye movement information of a first user respectively; respectively adjusting the first sub-trust index, the second sub-trust index and the third sub-trust index according to the current driving scene information of the vehicle; and determining a first confidence index according to the adjusted first sub-confidence index, the adjusted second sub-confidence index and the adjusted third sub-confidence index.
In some embodiments, determining the first sub-confidence index from the gesture information of the first user may include: determining the posture ease level of the first user according to the posture information of the first user; taking the trust index corresponding to the gesture looseness level of the first user in the first trust index table as a first sub-trust index; wherein the gesture ease level represents the easier the gesture of the first user, the higher the corresponding confidence index.
In some embodiments, adjusting the first sub-confidence index according to the current driving scenario information of the vehicle may include: when the current driving scene information of the vehicle indicates that the vehicle is in a complex driving scene, adjusting a first sub-trust index by using a first coefficient; and when the current driving scene information of the vehicle indicates that the vehicle is in a simple driving scene, adjusting the first sub-confidence index by using a second coefficient.
In some embodiments, the first factor is greater than 1 and the second factor is less than 1.
For example, the complex driving scenes include driving scenes with complex road conditions and driving scenes with large pedestrian volume. The simple driving scenes comprise driving scenes with simple road conditions and driving scenes with small pedestrian volume.
In some embodiments, determining a gesture ease level for the first user based on the gesture information for the first user may include: the gesture information of the first user is processed through a first level classifier to obtain a gesture ease level of the first user. The first-level classifier can be obtained by pre-training with a plurality of sample posture information.
Illustratively, when the posture information of the first user indicates that the first user is sitting upright, holding an article and the action amplitude is small, determining the ease level of the first user as a first level;
determining the posture ease level of the first user to be a second level when the posture information of the first user indicates that the first user is sitting upright and grasping an article;
determining the posture ease level of the first user to be a third level when the posture information of the first user indicates the sitting position end of the first user;
when the posture information of the first user indicates that the first user sluggish to lie, determining that the posture ease level of the first user is a fourth level;
when the posture information of the first user indicates that the first user sluggish to lie and the action amplitude is large, determining that the posture looseness grade of the first user is a fifth grade;
it should be noted that the gestures of the first user are increasingly relaxed from the first level to the fifth level.
In some embodiments, determining the second sub-trust index according to the expression information of the first user may include: determining the expression emotion level of the first user according to the expression information of the first user; taking the trust index corresponding to the expression emotion level of the first user in the second trust index table as a second sub-trust index; wherein the more positive the expression emotion rating characterizes the emotion of the first user, the higher the corresponding confidence index.
For the manner of adjusting the second sub-confidence index, reference may be made to the manner of adjusting the first sub-confidence index, which is not described herein again.
In some embodiments, the expression information may include facial expression data of the first user, and determining the expressive emotion level of the first user from the expression information of the first user may include: inputting the facial expression data of the first user into the second hierarchical classifier to obtain the expression emotion level of the first user. Wherein the second-level classifier may be pre-trained using a plurality of sample facial expression data.
In some embodiments, the eye movement information may include a gaze duration ratio, which may be derived from the gaze duration for the own NDRT task (movie watching, cell phone playing, reading, game playing, etc.) divided by a specified duration, or may be derived from the gaze duration for the in-vehicle display system divided by a specified duration, or may be derived from the gaze duration for the environment outside the vehicle (pedestrian, vehicle, road, surrounding trees divided by a specified duration.
Further, determining the third sub-confidence index according to the eye movement information may include: and searching a third sub-trust index corresponding to the watching duration from the third trust index table.
The confidence degree represented by the third sub-confidence degree index is stronger when the watching time length is obtained by dividing the watching time length of the NDRT task (watching a movie, playing a mobile phone, reading, playing a game and the like) by a specified time length, or when the watching time length is obtained by dividing the watching time length of the environment outside the vehicle (pedestrians, vehicles, roads, surrounding trees) by the specified time length.
For the manner of adjusting the third sub-confidence index, reference may be made to the manner of adjusting the first sub-confidence index, which is not described herein again.
In some embodiments, determining the first confidence index according to the adjusted first sub-confidence index, the second sub-confidence index and the third sub-confidence index may include, but is not limited to, the following:
taking the maximum trust index in the adjusted first sub-trust index, the adjusted second sub-trust index and the adjusted third sub-trust index as a first trust index;
alternatively, the first and second liquid crystal display panels may be,
taking the average value of the adjusted first sub-trust index, the adjusted second sub-trust index and the adjusted third sub-trust index as a first trust index;
alternatively, the first and second electrodes may be,
and taking the minimum trust index in the adjusted first sub-trust index, the adjusted second sub-trust index and the adjusted third sub-trust index as the first trust index.
Mode 2, determining a first sub-trust index, a second sub-trust index and a third sub-trust index according to the posture information, the expression information and the eye movement information of the first user respectively; determining a third confidence index according to the first sub-confidence index, the second sub-confidence index and the third sub-confidence index; and adjusting the third trust index according to the current driving scene information of the vehicle to obtain the first trust index.
For the calculation manner of the first sub-trust index, the second sub-trust index, and the third sub-trust index, reference may be made to the above description, and details are not repeated here.
In some embodiments, determining the third confidence index according to the first sub confidence index, the second sub confidence index and the third sub confidence index may include, but is not limited to, the following:
taking the maximum trust index in the first sub-trust index, the second sub-trust index and the third sub-trust index as a third trust index;
alternatively, the first and second liquid crystal display panels may be,
taking the average value of the first sub-trust index, the second sub-trust index and the third sub-trust index as a third trust index;
alternatively, the first and second liquid crystal display panels may be,
and taking the trust index with the minimum first sub-trust index, the minimum second sub-trust index and the minimum third sub-trust index as a third trust index.
For the adjustment manner of the third confidence index, reference may be made to the manner of adjusting the first sub-confidence index, which is not described herein again.
In some embodiments, the determining the second confidence index according to the physiological information of the first user may specifically include: processing the physiological information of the first user through a fourth level classifier to obtain a physiological emotion level of the first user; the fourth-level classifier can be obtained by pre-training a plurality of sample physiological information; and taking the confidence index matched with the physiological emotion level of the first user in the fourth confidence index table as the second confidence index. Wherein the more intense the physiological emotion level characterizes the emotion of the first user, the stronger the confidence represented by the corresponding second confidence index.
In some embodiments, the determining the second confidence index according to the physiological information of the first user may specifically include: processing the physiological information of the first user through a fourth level classifier to obtain a physiological emotion level of the first user; the fourth-level classifier can be obtained by pre-training a plurality of sample physiological information; obtaining a confidence index matched with the physiological emotion grade of the first user in a fourth confidence index table; and adjusting the confidence index matched with the physiological emotion grade of the first user according to the current driving scene information of the vehicle to obtain a second confidence index.
In some embodiments, determining the trust index corresponding to the first user according to the first trust index and the second trust index may include, but is not limited to, the following:
taking the maximum trust index in the first trust index and the second trust index as the trust index corresponding to the first user;
alternatively, the first and second liquid crystal display panels may be,
taking the average value of the first trust index and the second trust index as the trust index corresponding to the first user;
alternatively, the first and second electrodes may be,
and taking the minimum trust index in the first trust index and the second trust index as the trust index corresponding to the first user.
303. And identifying a target reminding mode corresponding to the target user.
When the number of users in the vehicle is 1, the target user is the user; when the user in the vehicle includes a plurality of users, the target user is a user with the lowest degree of trust in the automatic driving system of the vehicle among the plurality of users.
In some embodiments, the targeted alert mode includes at least one of: a visual alert mode, an auditory alert mode, a tactile alert mode, and an olfactory alert mode.
In some embodiments, identifying a target alert mode corresponding to a target user may include: and identifying a target reminding mode corresponding to the target user according to the behavior information of the target user.
In some embodiments, identifying a target reminding mode corresponding to a target user according to behavior information of the target user may include:
when the behavior information of the target user indicates that the target user sits and opens eyes, determining that the target reminding mode is a visual reminding mode;
when the behavior information of the target user indicates that the target user closes the eyes, the fixation point of the eyes of the target user is positioned outside the vehicle window or the target user lies flat, determining that the target reminding mode is at least one of the following modes: an auditory alert mode, a tactile alert mode, and an olfactory alert mode;
when the behavior information of the target user indicates that the target user wears the earphone, determining that the target reminding mode is at least one of the following modes: a visual reminding mode, a tactile reminding mode and an olfactory reminding mode;
304. and determining the vehicle-mounted equipment matched with the target reminding mode from at least one vehicle-mounted equipment of the vehicle.
The reminding mode corresponding to the vehicle-mounted screen is a visual reminding mode, the reminding mode corresponding to the loudspeaker is an auditory reminding mode, the reminding mode corresponding to the vibrator is a tactile reminding mode, and the reminding mode corresponding to the odor generator is an olfactory reminding mode.
305. And executing target operation for adjusting the trust degree through the vehicle-mounted equipment matched with the target reminding mode according to the target trust degree index.
In some embodiments, the number of the target reminding mode matched vehicle-mounted devices is one or more.
When a plurality of vehicle-mounted devices matched with the target reminding mode are provided, according to the target trust degree index, the vehicle-mounted device matched with the target reminding mode executes a target operation for adjusting the trust degree, which can include but is not limited to the following modes:
the method comprises the following steps that 1, vehicle-mounted equipment with the highest priority is used as target equipment in the vehicle-mounted equipment matched with the target reminding mode; and executing target operation for adjusting the trust degree through the target equipment according to the target trust degree index.
In some embodiments, performing, by the target device, the target operation for adjusting the trust level according to the target trust level index may include: when the target trust degree index is smaller than a first index threshold value, executing a first operation for improving the trust degree through the target equipment; and/or performing, by the target device, a second operation for reducing the trust level when the target trust level index is greater than the second index threshold.
The method 2 includes the steps that when the target trust degree index is smaller than a first index threshold value, a driving experience index of a target user is obtained, and the driving experience index is used for representing the driving proficiency of the target user; taking the vehicle-mounted equipment corresponding to the driving experience index in the vehicle-mounted equipment matched with the target reminding mode as target equipment; the lower the driving experience index is, the less visual interference of the corresponding vehicle-mounted equipment to the target user is; by the target device, a first operation for increasing the degree of trust is performed.
In some embodiments, a plurality of index ranges may be preset, and each index range corresponds to a different vehicle-mounted device. The vehicle-mounted equipment corresponding to the driving experience index comprises: and the vehicle-mounted equipment corresponds to the index range in which the driving experience index of the target user is positioned.
Illustratively, 4 index ranges are preset, including a first index range, a second index range, a third index range and a fourth index range. Wherein the first index range represents a level of driving proficiency that is less than the level of driving proficiency represented by the second index range, the second index range represents a level of driving proficiency that is less than the level of driving proficiency represented by the third index range, and the third index range represents a level of driving proficiency that is less than the level of driving proficiency represented by the fourth index range. The vehicle-mounted equipment corresponding to the first index range is an odor generator, the vehicle-mounted equipment corresponding to the second index range is a vibration actuator, the vehicle-mounted equipment corresponding to the third index range is a loudspeaker, and the vehicle-mounted equipment corresponding to the fourth index range is a vehicle-mounted screen.
By implementing the method, when a user with less driving experience has no trust feeling on the vehicle, the mode of not increasing the workload is preferentially selected as much as possible for calibration, and the calibration mode is more suitable for the requirements of the user.
The following further explains the above steps with reference to a scene example:
example 1: when a user in a vehicle pays attention to vehicle external information for a long time and the body posture is tense, the user is judged to have low confidence to an automatic driving system of the vehicle and needs to be calibrated. In order to calibrate the user's sense of trust in the vehicle's autopilot system, the presence of pedestrians is highlighted on the in-vehicle map display system that the user is interested in, or the textual explanation information that the vehicle stops waiting can also be prompted to the user through voice, thereby enabling the user to be more comfortable and attentive to the current NDRT.
Example 2: the user is excessively immersed in the NDRT task, the time of visual fixation staying on the non-navigation information accounts for a relatively long time, the vehicle condition is not concerned, the driving scene is relatively complex, and the fact that the user has high confidence in an automatic driving system of the vehicle is judged to need to be calibrated. In order to calibrate the confidence of a user on the automatic driving system of the vehicle, the user is prompted to pay attention to environmental information around the driving of the vehicle, decision information of the driving of the vehicle and the like through voice and cabin vibration.
Example 3: in the vehicle driving process, the sleeping time of a user is too long, the user does not pay attention to vehicle information for a long time, the driving scene is simple, and the fact that the user has high confidence in an automatic driving system of the vehicle is judged to need to be calibrated. In order to calibrate the trust sense of a user on the automatic driving system of the vehicle, the voice broadcast is carried out at regular time by playing music or the smell is emitted to improve the atmosphere in the vehicle, so that the user can keep a certain waking state and slightly know the condition of the vehicle.
By implementing the method, the trust degree of the user on the automatic driving system of the vehicle can be determined in real time according to the state information of the user in the vehicle, and the corresponding target operation is executed according to the trust degree, so that the aim of calibrating the trust degree of the user on the automatic driving system of the vehicle in real time is fulfilled. Furthermore, the vehicle-mounted equipment matched with the target reminding mode can be determined from the vehicle-mounted equipment, and target operation for adjusting the trust degree is executed through the vehicle-mounted equipment matched with the target reminding mode, so that the vehicle-mounted equipment can be quickly perceived by a user in a vehicle, and the requirements of the user can be met.
Referring to fig. 4, fig. 4 is a schematic diagram of a structure of a device for calibrating confidence level of an automatic driving system according to an embodiment of the present application. The calibration apparatus shown in fig. 4 may include a state acquiring unit 401, a confidence calculating unit 402, and a confidence calibrating unit 403; wherein:
a state obtaining unit 401, configured to obtain state information of a user in a vehicle, where the state information includes behavior information and/or physiological information;
the confidence calculation unit 402 is used for determining a target confidence index corresponding to the user according to the state information, wherein the target confidence index is used for representing the confidence degree of the user on the automatic driving system of the vehicle;
a confidence calibration unit 403, configured to execute a target operation for adjusting the confidence level according to the target confidence index.
In some embodiments, the number of the users in the vehicle is multiple, and the manner that the confidence calculating unit 402 is configured to determine the target confidence index corresponding to the user according to the state information may specifically include: a confidence calculation unit 402, configured to determine a confidence index corresponding to each user according to state information of each user in the vehicle; and taking the minimum trust index in the trust indexes corresponding to each user as a target trust index corresponding to the user in the vehicle.
In some embodiments, the status information includes behavioral information and physiological information, the in-vehicle user includes a first user; the manner in which the confidence calculation unit 402 is configured to determine the confidence index corresponding to the first user according to the state information of the first user may specifically include: a confidence calculation unit 402, configured to determine a first confidence index according to behavior information of the first user, where the behavior information includes at least one of: posture information, expression information and eye movement information; and determining a second confidence index based on physiological information of the first user, the physiological information including at least one of: electrocardio, heart rate, pressure, skin temperature, blood oxygen saturation, blood pressure, respiratory rate, skin electricity, myoelectricity and electroencephalogram; and determining the trust index corresponding to the first user according to the first trust index and the second trust index.
In some embodiments, the manner that the confidence calculating unit 402 is configured to determine the target confidence index corresponding to the user according to the state information may specifically include: and the confidence calculation unit 402 is configured to determine a target confidence index corresponding to the user according to the state information and the current driving scene information of the vehicle.
In some embodiments, the manner in which the confidence calibration unit 403 is configured to execute the target operation for adjusting the confidence level according to the target confidence index may specifically include: a confidence calibration unit 403, configured to identify a target reminding mode corresponding to a target user; determining the vehicle-mounted equipment matched with the target reminding mode from at least one vehicle-mounted equipment of the vehicle; and executing target operation for adjusting the trust degree through the vehicle-mounted equipment matched with the target reminding mode according to the target trust degree index.
In some embodiments, when the number of users in the vehicle is 1, the target user is the user; when the user in the vehicle includes a plurality of users, the target user is a user with the lowest degree of trust in the automatic driving system of the vehicle among the plurality of users.
In some embodiments, the number of the vehicle-mounted devices matched with the target reminding mode is multiple, and the manner that the trust degree calibration unit 403 is used for executing the target operation for adjusting the trust degree through the vehicle-mounted device matched with the target reminding mode according to the target trust degree index may specifically include: a confidence calibration unit 403, configured to use a vehicle-mounted device with the highest priority as a target device in the vehicle-mounted devices matched with the target reminding pattern; and executing target operation for adjusting the trust degree through the target equipment according to the target trust degree index.
In some embodiments, the number of the vehicle-mounted devices matched with the target reminding mode is multiple, and the manner that the trust degree calibration unit 403 is used for executing the target operation for adjusting the trust degree through the vehicle-mounted device matched with the target reminding mode according to the target trust degree index may specifically include: when the target trust degree index is smaller than a first index threshold value, acquiring a driving experience index of the target user, wherein the driving experience index is used for representing the driving proficiency of the target user; and taking the vehicle-mounted equipment corresponding to the driving experience index in the vehicle-mounted equipment matched with the target reminding mode as target equipment; the lower the driving experience index is, the less the visual interference of the corresponding vehicle-mounted equipment to the target user is; and executing, by the target device, a first operation for increasing the degree of trust.
In some embodiments, the targeted alert mode includes at least one of: a visual alert mode, an auditory alert mode, a tactile alert mode, and an olfactory alert mode.
In some embodiments, the manner that the confidence calibration unit 403 is configured to execute the target operation for adjusting the confidence level according to the target confidence index may specifically include: a confidence calibration unit 403, configured to execute a first operation for increasing a confidence level when the target confidence index is smaller than a first index threshold; and/or, when the target confidence index is larger than the second index threshold, executing a second operation for reducing the confidence level.
Referring to fig. 5, fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure. The electronic device as shown in fig. 5 may comprise a memory 501 in which executable program code is stored, and a processor 502 coupled to the memory.
In the embodiment of the present application, the processor 502 further has the following functions:
acquiring state information of a user in a vehicle, wherein the state information comprises behavior information and/or physiological information;
determining a target trust degree index corresponding to the user according to the state information, wherein the target trust degree index is used for representing the trust degree of the user on an automatic driving system of the vehicle;
and executing target operation for adjusting the trust degree according to the target trust degree index.
In the embodiment of the present application, the number of users in the vehicle is multiple, and the processor 502 further has the following functions:
determining a corresponding trust index of each user according to the state information of each user in the vehicle;
and taking the minimum trust index in the trust indexes corresponding to each user as a target trust index corresponding to the user in the vehicle.
In the embodiment of the application, the state information comprises behavior information and physiological information, and the user in the vehicle comprises a first user; the processor 502 also has the following functions:
determining a first confidence index according to behavior information of the first user, wherein the behavior information comprises at least one of the following: posture information, expression information and eye movement information;
determining a second confidence index based on physiological information of the first user, the physiological information including at least one of: electrocardio, heart rate, pressure, skin temperature, blood oxygen saturation, blood pressure, respiratory rate, skin electricity, myoelectricity and electroencephalogram;
and determining the trust index corresponding to the first user according to the first trust index and the second trust index.
In the embodiment of the present application, the processor 502 further has the following functions:
and determining a target trust index corresponding to the user according to the state information and the current driving scene information of the vehicle.
In the embodiment of the present application, the processor 502 further has the following functions:
identifying a target reminding mode corresponding to a target user;
determining the vehicle-mounted equipment matched with the target reminding mode from at least one vehicle-mounted equipment of the vehicle;
and executing target operation for adjusting the trust degree through the vehicle-mounted equipment matched with the target reminding mode according to the target trust degree index.
In the embodiment of the application, when the number of users in a vehicle is 1, a target user is the user; when the user in the vehicle includes a plurality of users, the target user is a user of the plurality of users who has the least degree of trust in the automatic driving system of the vehicle.
In this embodiment of the application, there are a plurality of vehicle-mounted devices matched with the target reminding mode, and the processor 502 further has the following functions:
using the vehicle-mounted equipment with the highest priority in the vehicle-mounted equipment matched with the target reminding mode as target equipment;
and executing target operation for adjusting the trust degree through the target equipment according to the target trust degree index.
In this embodiment of the application, there are a plurality of vehicle-mounted devices matched with the target reminding mode, and the processor 502 further has the following functions:
when the target trust degree index is smaller than a first index threshold value, obtaining a driving experience index of a target user, wherein the driving experience index is used for representing the driving proficiency of the target user;
taking the vehicle-mounted equipment corresponding to the driving experience index in the vehicle-mounted equipment matched with the target reminding mode as target equipment; the lower the driving experience index is, the less the visual interference of the corresponding vehicle-mounted equipment to the target user is;
by the target device, a first operation for increasing the degree of trust is performed.
In an embodiment of the present application, the target reminding mode includes at least one of the following: a visual alert mode, an auditory alert mode, a tactile alert mode, and an olfactory alert mode.
In the embodiment of the present application, the processor 502 further has the following functions:
when the target trust degree index is smaller than a first index threshold value, executing a first operation for improving the trust degree; and/or the presence of a gas in the gas,
and when the target confidence index is larger than the second index threshold value, executing a second operation for reducing the confidence level.
The embodiment of the application discloses a vehicle, and the vehicle comprises the electronic equipment in the embodiment.
The embodiment of the application discloses a computer-readable storage medium, which stores a computer program, wherein when the computer program is executed by a processor, the processor is enabled to realize part or all of the steps executed by the electronic device in the embodiment.
The embodiment of the application discloses a computer program product, which enables a computer to execute part or all of the steps executed by the electronic equipment in the embodiment when the computer program product runs on the computer.
The embodiment of the application discloses an application publishing platform, which is used for publishing a computer program product, wherein when the computer program product runs on a computer, the computer is enabled to execute part or all of the steps executed by the electronic device in the embodiment.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product.
The computer program product includes one or more computer instructions. The procedures or functions according to the embodiments of the present application are all or partially generated when the computer program instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, e.g., the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. Computer-readable storage media can be any available media that a computer can store or a data storage device, such as a server, data center, etc., that includes one or more available media. The usable medium may be a magnetic medium (e.g., floppy Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), among others.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a separate product, may be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application, which are essential or part of the technical solutions contributing to the prior art, or all or part of the technical solutions, may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.

Claims (13)

1. A method for calibrating the confidence level of an automatic driving system is characterized by comprising the following steps:
acquiring state information of a user in a vehicle, wherein the state information comprises behavior information and/or physiological information;
determining a target trust degree index corresponding to the user according to the state information, wherein the target trust degree index is used for representing the trust degree of the user on an automatic driving system of the vehicle;
and executing target operation for adjusting the trust degree according to the target trust degree index.
2. The method of claim 1, wherein the number of users in the vehicle is multiple, and determining the target confidence index corresponding to the user according to the status information comprises:
determining a corresponding trust index of each user according to the state information of each user in the vehicle;
and taking the minimum trust index in the trust indexes corresponding to each user as a target trust index corresponding to the user in the vehicle.
3. The method of claim 2, wherein the status information includes the behavioral information and the physiological information, the in-vehicle user includes a first user; determining a trust index corresponding to the first user according to the state information of the first user, including:
determining a first confidence index according to the behavior information of the first user, the behavior information including at least one of: posture information, expression information and eye movement information;
determining a second confidence index based on the physiological information of the first user, the physiological information including at least one of: electrocardio, heart rate, pressure, skin temperature, blood oxygen saturation, blood pressure, respiratory rate, skin electricity, myoelectricity and electroencephalogram;
and determining the trust index corresponding to the first user according to the first trust index and the second trust index.
4. The method according to claim 1, wherein the determining the target confidence index corresponding to the user according to the status information comprises:
and determining a target trust index corresponding to the user according to the state information and the current driving scene information of the vehicle.
5. The method of claim 1, wherein performing the target operation for adjusting the confidence level according to the target confidence index comprises:
identifying a target reminding mode corresponding to a target user;
determining the vehicle-mounted device matched with the target reminding mode from at least one vehicle-mounted device of the vehicle;
and executing target operation for adjusting the trust degree through the vehicle-mounted equipment matched with the target reminding mode according to the target trust degree index.
6. The method of claim 5, wherein the target user is the user when the number of users in the vehicle is 1; when the user in the vehicle includes a plurality of users, the target user is a user of the plurality of users who has the lowest degree of trust in an automatic driving system of the vehicle.
7. The method according to claim 5, wherein the number of the target reminding mode-matched vehicle-mounted devices is multiple, and the performing of the target operation for adjusting the trust degree through the target reminding mode-matched vehicle-mounted device according to the target trust degree index comprises:
using the vehicle-mounted equipment with the highest priority in the vehicle-mounted equipment matched with the target reminding mode as target equipment;
and executing target operation for adjusting the trust degree through the target equipment according to the target trust degree index.
8. The method according to claim 5 and 5, wherein the number of the target reminding mode matching vehicle-mounted devices is multiple, and the target operation for adjusting the trust degree is executed through the target reminding mode matching vehicle-mounted device according to the target trust degree index, and comprises the following steps:
when the target confidence index is smaller than a first index threshold value, acquiring a driving experience index of the target user, wherein the driving experience index is used for representing the driving proficiency of the target user;
taking the vehicle-mounted equipment corresponding to the driving experience index in the vehicle-mounted equipment matched with the target reminding mode as target equipment; the lower the driving experience index is, the less visual interference of the corresponding vehicle-mounted equipment to the target user is;
executing, by the target device, a first operation for increasing the degree of trust.
9. The method of any of claims 5-8, wherein the target alert mode comprises at least one of: a visual alert mode, an auditory alert mode, a tactile alert mode, and an olfactory alert mode.
10. The method of claim 1, wherein performing the target operation for adjusting the confidence level according to the target confidence index comprises:
when the target trust degree index is smaller than a first index threshold value, executing a first operation for improving the trust degree; and/or the presence of a gas in the atmosphere,
and when the target trust degree index is larger than a second index threshold value, executing a second operation for reducing the trust degree.
11. An apparatus for calibrating a level of trust of an autonomous driving system, comprising:
the system comprises a state acquisition unit, a state acquisition unit and a state processing unit, wherein the state acquisition unit is used for acquiring state information of a user in a vehicle, and the state information comprises behavior information and/or physiological information;
the trust degree calculation unit is used for determining a target trust degree index corresponding to the user according to the state information, and the target trust degree index is used for representing the trust degree of the user on an automatic driving system of the vehicle;
and the credibility calibration unit is used for executing target operation for adjusting the credibility according to the target credibility index.
12. An electronic device, comprising:
a memory storing executable program code;
and a processor coupled to the memory;
the processor calls the executable program code stored in the memory, which when executed by the processor causes the processor to implement the method of any of claims 1-10.
13. A vehicle comprising the electronic device of claim 12.
CN202211268640.1A 2022-10-17 2022-10-17 Method, device and equipment for calibrating trust of automatic driving system and vehicle Pending CN115517639A (en)

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