CN112949015A - Modeling apparatus, assistance system, vehicle, method, and storage medium - Google Patents
Modeling apparatus, assistance system, vehicle, method, and storage medium Download PDFInfo
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Abstract
The invention provides a modeling apparatus for building a workload-to-awareness relationship model for a vehicle user, an assistance system for a vehicle, a corresponding vehicle, a method, a computer device and a computer-readable storage medium. The modeling apparatus includes: a first identity recognition unit configured to recognize identity information of the vehicle user; a first data acquisition and processing unit configured to acquire workload data and awareness data of the vehicle user during driving; a model building unit configured to train a relationship model between workload and consciousness level according to the workload data and the consciousness level data. The technical scheme of the invention can improve the driving safety.
Description
Technical Field
The present invention relates to the field of vehicle technology, and more particularly, to a modeling apparatus for building a workload-awareness relationship model for a vehicle user, an assistance system for a vehicle, a corresponding vehicle, a method, a computer device and a computer-readable storage medium.
Background
In the related art, the workload-consciousness degree curve can be used for determining the consciousness degree of a vehicle user in the driving process, and corresponding measures can be taken according to the consciousness degree to ensure the driving safety. However, since different vehicle users have different workload-awareness curves, how to provide a corresponding personalized workload-awareness curve for different vehicle users becomes a technical problem to be solved urgently.
Disclosure of Invention
In order to solve the technical problems, the invention provides a technical scheme capable of providing a corresponding personalized workload-consciousness degree relation model for different vehicle users, so that reminding is carried out in response to the user consciousness degree outside a preset range based on the relation model, and the aim of improving driving safety is fulfilled.
As a first aspect of the present invention, there is provided a modeling apparatus for building a workload-consciousness relationship model of a vehicle user, wherein the modeling apparatus comprises:
a first identity recognition unit configured to recognize identity information of the vehicle user;
a first data acquisition and processing unit configured to acquire workload data and awareness data of the vehicle user during driving;
a model building unit configured to train a relationship model between workload and consciousness level according to the workload data and the consciousness level data.
As a second aspect of the present invention, there is provided an assist system for a vehicle, comprising:
a second identification unit configured to identify identification information of the vehicle user;
a model retrieving unit configured to: in response to the identity information of the identified vehicle user, calling a workload and consciousness degree relation model of the vehicle user, wherein the workload and consciousness degree relation model is established by the modeling device;
the second data acquisition and processing unit is configured to acquire workload data of the vehicle user in the driving process and determine the consciousness degree of the vehicle user corresponding to the workload data according to the workload and consciousness degree relation model of the vehicle user;
a first judgment unit configured to judge whether the determined degree of consciousness of the vehicle user is outside a preset range;
a first execution unit configured to: and in response to the first judgment unit judging that the determined consciousness degree of the vehicle user is out of the preset range, sending a visual, auditory and/or tactile safety prompt and/or an automatic driving takeover request to the vehicle user.
As a third aspect of the present invention, there is provided an assist system for a vehicle, comprising:
the modeling apparatus according to the first aspect of the present invention is configured to build a workload-consciousness relationship model of a vehicle user, wherein the first data acquiring and processing unit included in the modeling apparatus is further configured to: responding to a workload and consciousness degree relation model which is established by the modeling device and aims at the vehicle user, acquiring workload data of the vehicle user in the driving process, and determining the consciousness degree of the vehicle user corresponding to the workload data according to the workload and consciousness degree relation model of the vehicle user;
a second determination unit configured to determine whether the determined degree of consciousness of the vehicle user is outside a preset range;
a second execution unit configured to: and responding to the second judgment unit to judge that the determined real-time awareness of the vehicle user is out of the preset range, and sending a visual, auditory and/or tactile safety prompt and/or an automatic driving takeover request to the vehicle user.
As a fourth aspect of the present invention, there is provided a vehicle including the modeling apparatus of the first aspect of the present invention and/or the assist system for a vehicle of the second aspect of the present invention, or including the assist system for a vehicle of the third aspect of the present invention.
As a fifth aspect of the present invention, there is provided a modeling method for building a workload-consciousness relationship model of a vehicle user, wherein the modeling method comprises:
identifying identity information of the vehicle user;
acquiring workload data and consciousness data of the vehicle user in the driving process;
and training a relation model between the workload and the consciousness degree according to the workload data and the consciousness degree data.
As a sixth aspect of the present invention, there is provided an assist method for a vehicle, comprising:
identifying identity information of a vehicle user;
in response to the identity information of the identified vehicle user, calling a workload and consciousness degree relation model of the vehicle user, wherein the workload and consciousness degree relation model is established by the modeling method of the fifth aspect of the invention;
acquiring the workload data of the vehicle user in the driving process, and determining the consciousness degree of the vehicle user corresponding to the workload data according to the workload and consciousness degree relation model of the vehicle user;
judging whether the determined consciousness degree of the vehicle user is out of a preset range or not;
in response to determining that the determined degree of consciousness of the vehicle user is outside of a preset range, issuing a visual, audible and/or tactile safety prompt and/or an automatic driving takeover request to the vehicle user.
As a seventh aspect of the present invention, there is provided an assist method for a vehicle, comprising:
establishing a relation model between the workload and the consciousness degree of a vehicle user by the modeling method of the fifth aspect of the invention;
responding to the established relation model of the workload and the consciousness degree aiming at the vehicle user, acquiring the workload data of the vehicle user in the driving process, and determining the consciousness degree of the vehicle user corresponding to the workload data according to the relation model of the workload and the consciousness degree of the vehicle user;
judging whether the determined consciousness degree of the vehicle user is out of a preset range or not;
in response to determining that the determined real-time awareness of the vehicle user is outside of a preset range, issuing a visual, audible, and/or tactile safety prompt and/or an automatic driving takeover request to the vehicle user.
As an eighth aspect of the present invention, there is provided a computer-readable storage medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the modeling method of the fifth aspect of the present invention, the assisting method of the sixth aspect of the present invention, or the assisting method of the seventh aspect of the present invention.
As a ninth aspect of the present invention, there is provided a computer apparatus comprising a memory storing a computer program and a processor, wherein the processor implements the modeling method of the fifth aspect of the present invention, the assisting method of the sixth aspect of the present invention, or the assisting method of the seventh aspect of the present invention when executing the computer program.
The invention has the beneficial technical effects that:
by utilizing the technical scheme of the invention, the modeling device can acquire the operation related information and the driving performance of the vehicle user in the driving process, then the workload data and the consciousness degree data can be obtained according to the operation related information and the driving performance, and then the relation model between the workload and the consciousness degree corresponding to the vehicle user is obtained according to the workload data and the consciousness degree data. Namely, the relation model between the workload and the consciousness degree is obtained by aiming at a certain vehicle user through real-time training, so that the driving state of the vehicle user can be objectively and accurately reflected, and the relation model has higher pertinence. Further, the auxiliary system may obtain real-time workload data of a certain vehicle user and a relationship model between the workload and the awareness, so as to determine a real-time awareness of the vehicle user corresponding to the real-time workload data, and send a corresponding prompt and/or request to the vehicle user in response to the obtained real-time awareness being outside a preset range (i.e., a safety awareness range), so as to ensure driving safety.
Drawings
Non-limiting and non-exhaustive embodiments of the present invention are described by way of example with reference to the following drawings, in which:
FIG. 1 is a schematic diagram illustrating a modeling apparatus for modeling workload versus awareness relationships of a vehicle user, according to an embodiment of a first aspect of the present invention;
FIG. 2 is a schematic diagram illustrating an assistance system for a vehicle according to one embodiment of a second aspect of the present invention;
FIG. 3 is a schematic diagram illustrating an assistance system for a vehicle according to one embodiment of a third aspect of the present invention;
FIG. 4 is a flow diagram illustrating a modeling method for modeling a workload-to-awareness relationship model for a vehicle user, according to an embodiment of a fifth aspect of the present invention;
fig. 5 is a flowchart illustrating an assist method for a vehicle according to an embodiment of a sixth aspect of the invention;
fig. 6 is a flowchart showing an assist method for a vehicle according to one embodiment of the seventh aspect of the invention.
Detailed Description
In order to make the above and other features and advantages of the present invention more apparent, the present invention is further described below with reference to the accompanying drawings. It is understood that the specific embodiments described herein are for purposes of illustration only and are not intended to be limiting.
As a first aspect of the present invention, a modeling apparatus for modeling a workload-consciousness relationship model of a vehicle user is provided. Fig. 1 schematically shows a modeling apparatus 100 for modeling a workload-to-awareness relationship model of a vehicle user according to an embodiment of a first aspect of the present invention.
The modeling apparatus 100 includes a first identity identification unit 110, a first data acquisition and processing unit 120, and a model building unit 130, and the units are communicatively coupled. The modeling apparatus 100 may be disposed on the vehicle side, or may also be disposed on the server side — for example, on a server that may be in communication with the vehicle.
The first identification unit 110 may be configured to identify identity information of a vehicle user.
As can be appreciated, the first identification unit 100 may obtain identity information of a vehicle user when and/or after entering the vehicle by means of sensors mounted on said vehicle. The sensors may include a camera, a fingerprint sensor, an iris scan device, a retina scan device, and an audio collector or any other suitable sensor, or a suitable combination thereof.
In one embodiment, the first identity recognizing unit 100 recognizes the identity information of the vehicle user by:
I. biometric identification is performed on the vehicle user.
The biometric identification technology is an identification technology which carries out identity verification by depending on the body characteristics of a human body, has the characteristics of no loss, no forgetting, uniqueness, invariance, good anti-counterfeiting performance and convenient use, and is widely applied to entrance guard, attendance, finance, public safety and terminal electronic equipment. Commonly used biometric identification includes eight categories, namely face identification, fingerprint identification, eye print identification, iris identification, retina identification, voice print identification. These techniques have become mature and are not described in detail herein.
For face recognition, for example, after a certain vehicle user enters a driving seat, a camera installed in front of the vehicle may be used to capture a facial image of the vehicle user and send the facial image to the first identity recognition unit 110, and the first identity recognition unit 100 may compare the received facial image of the vehicle user in a preset identity information database, so as to determine the identity of the vehicle user. For eye print recognition, iris recognition, retina recognition, similarly, the face image of the vehicle user may be taken by the camera first, and then the identity of the vehicle user may be determined by the first identity recognition unit 100.
For fingerprint recognition, for example, a fingerprint sensor may be disposed at a door handle position or a steering wheel of a vehicle to collect a fingerprint of a vehicle user, and the first identity recognition unit 110 may compare the fingerprint collected by the fingerprint sensor in a preset identity information database, so as to determine the identity of the vehicle user.
For voiceprint recognition, for example, an audio collector may be installed in the vehicle to collect the sound of the vehicle user, and the first identity recognition unit 110 may compare the voiceprint collected by the audio collector in a preset identity information database, so as to determine the identity of the vehicle user.
II. And logging in through the account number of the vehicle user for identification.
For example, the vehicle user logs in the vehicle system of the vehicle by inputting an account password, and the first identity recognition unit 110 may retrieve the registration information of the account at the server according to the account password, thereby determining the identity of the vehicle user.
The first data acquisition and processing unit 120 may be configured to acquire workload data and awareness data of the vehicle user during driving.
In one embodiment, the first data acquisition and processing unit 120 may be further configured to: and acquiring and quantifying operation related information of the vehicle user in the driving process, and taking a quantification result as the workload data, wherein the operation related information comprises vehicle driving operation related information, vehicle-mounted system operation related information and personal behavior related information.
Here, the operation-related information may be operation-related information of a user of the vehicle during driving. Wherein, the vehicle driving operation can be, for example, controlling a steering wheel, controlling a clutch pedal, and/or controlling an accelerator pedal/an accelerator pedal, etc.; the in-vehicle system operation may be, for example, using/operating an in-vehicle entertainment system; the personal behavior may be, for example, making and receiving calls, eating, drinking, picking up items, etc. The quantification may be, for example, a statistic/measure of the above-mentioned operation of the vehicle user during driving, and the workload data may be, for example, the frequency of use of the accelerator pedal/gas pedal of the vehicle user, the number of uses of the in-vehicle infotainment system, and/or the duration and/or number of calls received. It will be appreciated that the operations given above are for exemplary purposes only, and that any other workload-related operations may be considered.
As can be appreciated, the first data acquisition and processing unit 120 may acquire information related to the operation of the user of the vehicle during driving via suitable sensors mounted on the vehicle and/or via a central control system of the vehicle. For example, the first data acquiring and processing unit 120 may capture an image of a vehicle user at a driving position by means of a camera, and then analyze the image to obtain operation-related information of the vehicle user, such as eating and/or the number of times, duration, etc. of making and receiving calls. Wherein the image may be, for example, a real-time surveillance video image. Alternatively, the first data acquisition and processing unit 120 may also be configured to be operatively connected to a central control system of the vehicle, whereby operation-related information of the vehicle user, such as the direction and magnitude of rotation of the steering wheel, the frequency of use of the accelerator pedal/gas pedal, the number of times of use of the infotainment system, etc., is acquired in real time by the central control system.
In another embodiment, the first data acquisition and processing unit 120 is further configured to: the method includes the steps of obtaining and quantifying the driving performance of the vehicle user, calculating an average value as a quantification result of a reference driving performance of the vehicle user based on the quantification result of the driving performance, and calculating a difference value between the quantification result of the current driving performance of the vehicle user and the quantification result of the reference driving performance of the vehicle user as current awareness data of the vehicle user, wherein the quantification result of the driving performance and the quantification result of the current driving performance include data on reaction time and/or safety awareness of the vehicle user, but are not limited thereto.
As can be appreciated, the first data acquisition and processing unit 120 may acquire and quantify the driving performance of the vehicle user via the vehicle's central control system and sensors mounted on the vehicle. The sensors described herein may include cameras, lidar, millimeter-wave radar, ultrasonic sensors, or any other suitable sensor, or any suitable combination thereof. For example, a vehicle driven by a vehicle user is taken as a current vehicle, and a vehicle traveling ahead of the current vehicle is taken as a preceding vehicle, and a camera or a lidar mounted on the current vehicle can detect a traveling state of the preceding vehicle. The central control system of the present vehicle may detect or sense an operation performed by a vehicle user in response to a change in the driving state of the preceding vehicle by means of other suitable sensors — for example, when the preceding vehicle is braked, the present vehicle is also braked. The central control system of the current vehicle can call a timing unit to start timing from the moment when the front vehicle brake is detected until the vehicle user is detected to step on the brake, and the calculated time can be used as the reaction time of the vehicle user.
It should be noted that the driving performance of the vehicle user may also be a real-time driving performance, and may be obtained synchronously with the operation related information of the vehicle user during driving, that is, the real-time synchronous obtaining of the workload data and awareness data of the vehicle user during driving is realized. The driving performance of the vehicle user can be accumulated continuously, and the more the driving performance is accumulated, the more accurate the result obtained by the calculated average value is, so that the quantitative result of the reference driving performance can be optimized.
In one embodiment, the first data acquiring and processing unit 120 may start to calculate the awareness data in response to acquiring the first set of driving performance of the vehicle user, so as to provide immediate feedback to the vehicle user and improve user experience.
In a preferred embodiment, the first data acquisition and processing unit 120 may be further configured to: and taking the driving performance of the vehicle user acquired after the preset time threshold value as the current driving performance. As can be appreciated, the calculation of the awareness data may be resumed after a predetermined time threshold of the first set of driving performances of the vehicle user is obtained, before which the awareness data is not calculated for the moment. In the preset time threshold, the accumulated driving performance of the vehicle user is only used for calculating the quantitative result of the reference driving performance, the quantitative result of the reference driving performance can tend to be stable after the preset time threshold, and further, the current awareness data of the vehicle user is calculated based on the quantitative result of the reference driving performance which tends to be stable and the current driving performance of the vehicle user (the real-time driving performance obtained after the preset time threshold), so that the accuracy of calculating the awareness data is improved.
The predetermined time threshold is not limited in the present invention, and may be, for example, 1 minute, 5 minutes, 10 minutes, or may be adjusted according to the actual situation of the user.
The model building unit 130 may be configured to train a relationship model between workload and degree of consciousness from the workload data and the degree of consciousness data.
In one embodiment, the model building unit 130 may be further configured to: and performing regression analysis by using the workload data as abscissa data and the consciousness data as ordinate data to obtain a fitting curve representing the relationship between the workload and the consciousness of the vehicle user. The present invention is not limited to the specific implementation of regression analysis and curve fitting, and may be adjusted according to actual situations or needs, so as to select a suitable implementation for execution.
In one embodiment, the modeling apparatus 100 may further include a storage unit, and the storage unit may be configured to store a relationship model between the workload and the consciousness degree, which is trained by the model establishing unit 130, and identity information of a corresponding vehicle user. The storage unit may be a whole or a part of the modeling apparatus 100, or may be a part of a server for providing data storage services that is communicable with the modeling apparatus 100.
As a second aspect of the present invention, an assistance system for a vehicle is provided. Fig. 2 schematically shows an assistance system 200 for a vehicle according to an embodiment of the second aspect of the invention.
The assistance system 200 includes a second identification unit 210, a model retrieving unit 220, a second data acquiring and processing unit 230, a first determining unit 240, and a first executing unit 250, and each unit is communicatively coupled to each other. The assistance system 200 may be provided on the vehicle side.
The second identification unit 210 may be configured to identify identification information of the vehicle user.
Here, the second identity recognizing unit 210 is additionally configured for the auxiliary system 200, and may have the same function as the first identity recognizing unit 110 in the modeling apparatus 100, that is, the extension of the first identity recognizing unit 110 described above is also applicable to the second identity recognizing unit 210, and for the sake of simplicity, the description is omitted here.
The model retrieving unit 220 is configured to: in response to the identity information of the identified vehicle user, a workload and consciousness degree relation model of the vehicle user is retrieved, wherein the workload and consciousness degree relation model is established by the modeling apparatus 100 according to the first aspect of the present invention.
For example, the workload-consciousness relationship model of the vehicle user established by the modeling apparatus 100 may be stored in a separate storage unit or a suitable server, and at the same time, the identity information of the vehicle user (the identity information is identified by the first identity identifying unit 110) may be stored correspondingly. The model retrieving unit 220 may retrieve the identification information of the vehicle user identified by the second identification unit 210 from the storage unit or the server, and if the identification information is matched with the identification information stored in the storage unit or the server, that is, the identification information indicates the same vehicle user, the corresponding workload and consciousness degree relationship model of the vehicle user may be retrieved.
The second data acquiring and processing unit 230 may be configured to acquire workload data of the vehicle user during driving, and determine the awareness of the vehicle user corresponding to the workload data according to the workload and awareness relationship model of the vehicle user. Here, the second data acquisition and processing unit 230 may acquire and quantify the operation-related information of the vehicle user during driving in real time, with the quantified result as the workload data. The workload-consciousness relational model may be, for example, a two-dimensional coordinate plane curve in which the workload data is the coordinate data of the X-axis and the consciousness is the coordinate data of the Y-axis. Based on the curve, a functional relationship y ═ f (X) between the awareness and the workload can be determined, so that the workload data obtained by the second data acquisition and processing unit 230 is input into the functional relationship as a value of an independent variable X (coordinate data of an X-axis), and the awareness of the vehicle user corresponding to the workload data can be determined.
The first determination unit 240 may be configured to determine whether the determined degree of consciousness of the vehicle user is outside a preset range. Here, the preset range of the degree of consciousness in the present invention is not particularly limited, and may be set, for example, based on an empirical value.
The first execution unit 250 may be configured to: in response to the first judgment unit 240 judging that the determined degree of consciousness of the vehicle user is outside the preset range, a visual, auditory and/or tactile prompt and/or an automatic driving takeover request is issued to the vehicle user.
For example, the vehicle user may be ensured to drive safely by displaying a warning sign and/or text in the field of view of the vehicle user, or by outputting audio warning information through an on-vehicle audio device, or by prompting the vehicle user that the current consciousness level is lower than a safety threshold value through seat vibration or the like. Or, the vehicle is an automatic driving vehicle, and when the real-time awareness of the vehicle user is outside the preset range, the first execution unit 240 may display an automatic driving takeover request for switching the vehicle application to the automatic driving mode in a field of view of the vehicle user, or may prompt the vehicle user through the vehicle-mounted audio device to request the automatic driving takeover request for switching the vehicle application to the automatic driving mode. Optionally, the seat may also be vibrated to enhance the notification to the vehicle user.
As a third aspect of the present invention, an assistance system for a vehicle is provided. Fig. 3 schematically shows an assistance system 300 for a vehicle according to an embodiment of the third aspect of the invention. It is noted that the assistance system 300 is essentially one system that combines model building and model application.
The assistance system 300 comprises the modelling means 100 according to the first aspect of the present invention for directly establishing a workload-consciousness relationship model for a vehicle user. It is to be appreciated that the first data acquisition and processing unit 120 included in the modeling apparatus 100 may be further configured to: the method comprises the steps of responding to a workload and consciousness degree relation model established by the modeling device 100 and aiming at the vehicle user, obtaining workload data of the vehicle user in the driving process, and determining the consciousness degree of the vehicle user corresponding to the workload data according to the workload and consciousness degree relation model of the vehicle user.
The assistance system 300 further comprises a second determination unit 310 and a second execution unit 320, and the units are communicatively coupled to each other and to the modeling apparatus 100.
The second determination unit 310 may be configured to determine whether the determined degree of consciousness of the vehicle user is outside a preset range.
The second execution unit 320 may be configured to: and responding to the second judgment unit to judge that the determined real-time awareness of the vehicle user is out of the preset range, and sending a visual, auditory and/or tactile safety prompt and/or an automatic driving takeover request to the vehicle user.
The extensions of the second aspect regarding the first determining unit 240 and the first executing unit 250 are also applicable to the second determining unit 310 and the second executing unit 320, respectively, and for the sake of simplicity, the descriptions thereof are omitted here.
It should be noted here that, while the auxiliary system 200 according to the second aspect and the auxiliary system 300 according to the third aspect are operating, the modeling apparatus 100 may also be operated continuously and synchronously. For example, the modeling apparatus 100 may continuously obtain the real-time driving performance of the user for optimizing the reference driving performance of the vehicle user, so as to improve the accuracy of the current awareness data of the vehicle user, and further optimize the relationship model between the workload and the awareness trained based on the awareness data. The assistance system 200,300 may obtain the latest relationship model in real time, and may thereby improve the accuracy of the determined awareness of the vehicle user.
As a fourth aspect of the invention, a vehicle is provided, wherein the vehicle comprises a modelling arrangement according to the first aspect of the invention and/or an assistance system according to the second aspect of the invention, or comprises an assistance system according to the third aspect of the invention. The vehicle can be an automatic driving vehicle or a human driving vehicle.
As a fifth aspect of the invention, a modeling method for modeling a workload-consciousness relationship model of a vehicle user is provided. Fig. 4 schematically illustrates a modeling method 400 for building a workload-to-awareness relationship model of a vehicle user, which may be implemented using the modeling apparatus 100 of the first aspect of the invention as described above, according to an embodiment of the fifth aspect of the invention.
As shown in fig. 4, the modeling method includes:
s410: identifying identity information of the vehicle user;
s420: acquiring workload data and consciousness data of the vehicle user in the driving process;
s430: and training a relation model between the workload and the consciousness degree according to the workload data and the consciousness degree data.
In one embodiment, the obtaining workload data of the vehicle user during driving comprises: and acquiring and quantifying operation related information of the vehicle user in the driving process, and taking a quantification result as the workload data, wherein the operation related information comprises vehicle driving operation related information, vehicle-mounted system operation related information and personal behavior related information.
In one embodiment, the acquiring awareness data of the vehicle user during driving includes: the method comprises the steps of obtaining and quantifying the driving performance of a vehicle user, calculating an average value as a quantification result of a reference driving performance of the vehicle user based on the quantification result of the driving performance, and calculating a difference value between the quantification result of the current driving performance of the vehicle user and the quantification result of the reference driving performance of the vehicle user as current awareness data of the vehicle user, wherein the quantification result of the driving performance and the quantification result of the current driving performance comprise data of reaction time and/or safety awareness of the vehicle user.
In one embodiment, the acquiring awareness data of the vehicle user during driving further comprises: and taking the driving performance of the vehicle user acquired after the preset time threshold value as the current driving performance.
In one embodiment, said training a relational model between workload and consciousness based on said workload data and said consciousness data comprises: and performing regression analysis by using the workload data as abscissa data and the consciousness data as ordinate data to obtain a fitting curve representing the relationship between the workload and the consciousness of the vehicle user.
In one embodiment, the identity information of the vehicle user is identified by: performing biometric recognition, such as face recognition, fingerprint recognition, eye print recognition, iris recognition, retina recognition, or voice print recognition, on the vehicle user; and/or logging in through the account number of the vehicle user for identification.
As a sixth aspect of the invention, an assist method for a vehicle is provided. Fig. 5 schematically shows an assistance method 500 for a vehicle according to an embodiment of a sixth aspect of the invention, which may be implemented with the assistance system 200 of the second aspect of the invention as described above.
As shown in fig. 5, the auxiliary method includes:
s510: identifying identity information of a vehicle user;
s520: in response to the identity information of the identified vehicle user, calling a workload and consciousness degree relation model of the vehicle user, wherein the workload and consciousness degree relation model is established by the modeling method of the fifth aspect of the invention;
s530: acquiring the workload data of the vehicle user in the driving process, and determining the consciousness degree of the vehicle user corresponding to the workload data according to the workload and consciousness degree relation model of the vehicle user;
s540: judging whether the determined consciousness degree of the vehicle user is out of a preset range or not;
s550: in response to determining that the determined degree of consciousness of the vehicle user is outside of a preset range, issuing a visual, audible and/or tactile safety prompt and/or an automatic driving takeover request to the vehicle user.
As a seventh aspect of the present invention, an assist method for a vehicle is provided. Fig. 6 schematically shows an assistance method 600 for a vehicle according to an embodiment of a seventh aspect of the invention, which may be implemented with the assistance system 300 of the third aspect of the invention as described above.
As shown in fig. 6, the auxiliary method includes:
s610: establishing a relation model between the workload and the consciousness degree of a vehicle user by the modeling method of the fifth aspect of the invention;
s620: responding to the established relation model of the workload and the consciousness degree aiming at the vehicle user, acquiring the workload data of the vehicle user in the driving process, and determining the consciousness degree of the vehicle user corresponding to the workload data according to the relation model of the workload and the consciousness degree of the vehicle user;
s630: judging whether the determined consciousness degree of the vehicle user is out of a preset range or not;
s640: in response to determining that the determined real-time awareness of the vehicle user is outside of a preset range, issuing a visual, audible, and/or tactile safety prompt and/or an automatic driving takeover request to the vehicle user.
It is to be understood that the specific features described herein in relation to the modeling apparatus of the aforementioned first aspect may also be similarly applied to the modeling method of the fifth aspect for similar extensions, the specific features described herein in relation to the auxiliary system of the aforementioned second aspect may also be similarly applied to the auxiliary method of the sixth aspect for similar extensions, and the specific features described herein in relation to the auxiliary system of the aforementioned third aspect may also be similarly applied to the auxiliary method of the seventh aspect for similar extensions. For the sake of simplicity, it is not described in detail.
It should be understood that the various elements of the modeling apparatus 100, the assistance system 200, and the assistance system 300 of the present invention may be implemented in whole or in part by software, hardware, firmware, or a combination thereof. The units may be embedded in a processor of the computer device in a hardware or firmware form or independent of the processor, or may be stored in a memory of the computer device in a software form for being called by the processor to execute operations of the units. Each of the units may be implemented as a separate component or module, or two or more units may be implemented as a single component or module.
It will be understood by those of ordinary skill in the art that the schematic diagram of the modeling apparatus 100 shown in fig. 1, the schematic diagram of the assistance system 200 shown in fig. 2, and the schematic diagram of the assistance system 300 shown in fig. 3 are merely exemplary illustrative block diagrams of partial structures associated with aspects of the present invention and do not constitute a limitation of a computer device, processor, or computer program embodying aspects of the present invention. A particular computer device, processor or computer program may include more or fewer components or modules than shown in the figures, or may combine or split certain components or modules, or may have a different arrangement of components or modules.
As an eighth aspect of the invention, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the method of the fifth, sixth or seventh aspect of the invention. In one embodiment, the computer program is distributed across a plurality of computer devices or processors coupled by a network such that the computer program is stored, accessed, and executed by one or more computer devices or processors in a distributed fashion. A single method step/operation, or two or more method steps/operations, may be performed by a single computer device or processor or by two or more computer devices or processors. One or more method steps/operations may be performed by one or more computer devices or processors, and one or more other method steps/operations may be performed by one or more other computer devices or processors. One or more computer devices or processors may perform a single method step/operation, or perform two or more method steps/operations.
As a ninth aspect of the invention, there is provided a computer device comprising a memory and a processor, the memory having stored thereon computer instructions executable by the processor, the computer instructions, when executed by the processor, instructing the processor to perform the steps of the modeling method of the fifth aspect of the invention, the auxiliary method of the sixth aspect of the invention or the auxiliary method of the seventh aspect of the invention. The computer device may broadly be a server, a vehicle mounted terminal, or any other electronic device having the necessary computing and/or processing capabilities. In one embodiment, the computer device may include a processor, memory, a network interface, a communication interface, etc., connected by a system bus. The processor of the computer device may be used to provide the necessary computing, processing and/or control capabilities. The memory of the computer device may include non-volatile storage media and internal memory. An operating system, a computer program, and the like may be stored in or on the non-volatile storage medium. The internal memory may provide an environment for the operating system and the computer programs in the non-volatile storage medium to run. The network interface and the communication interface of the computer device may be used to connect and communicate with an external device through a network. Which computer program, when being executed by a processor, carries out the steps of the modeling method or the auxiliary method of the invention.
It will be understood by those skilled in the art that all or part of the steps of the modeling method and the assistance method of the present invention can be instructed to be performed by relevant hardware such as a computer device or a processor through a computer program, which can be stored in a non-transitory computer readable storage medium, and which when executed performs the steps of the modeling method and the assistance method of the present invention. Any reference herein to memory, storage, databases, or other media may include non-volatile and/or volatile memory, as appropriate. Examples of non-volatile memory include read-only memory (ROM), programmable ROM (prom), electrically programmable ROM (eprom), electrically erasable programmable ROM (eeprom), flash memory, magnetic tape, floppy disk, magneto-optical data storage device, hard disk, solid state disk, and the like. Examples of volatile memory include Random Access Memory (RAM), external cache memory, and the like.
The respective technical features described above may be arbitrarily combined. Although not all possible combinations of features are described, any combination of features should be considered to be covered by the present specification as long as there is no contradiction between such combinations.
While the present invention has been described in connection with the embodiments, it is to be understood by those skilled in the art that the foregoing description and drawings are merely illustrative and not restrictive of the broad invention, and that this invention not be limited to the disclosed embodiments. Various modifications and variations are possible without departing from the spirit of the invention.
Claims (12)
1. A modeling apparatus for modeling workload versus awareness relationship of a vehicle user, wherein the modeling apparatus comprises:
a first identity recognition unit configured to recognize identity information of the vehicle user;
a first data acquisition and processing unit configured to acquire workload data and awareness data of the vehicle user during driving;
a model building unit configured to train a relationship model between a workload and an awareness according to the workload data and the awareness data;
preferably, the first identity recognition unit is further configured to recognize the identity information of the vehicle user by:
performing biometric recognition, such as face recognition, fingerprint recognition, eye print recognition, iris recognition, retina recognition, or voice print recognition, on the vehicle user; and/or
And logging in through the account number of the vehicle user for identification.
2. The modeling apparatus of claim 1, wherein the first data acquisition and processing unit is further configured to:
acquiring and quantifying operation related information of the vehicle user in the driving process, and taking a quantification result as the workload data, wherein the operation related information comprises vehicle driving operation related information, vehicle-mounted system operation related information and personal behavior related information;
preferably, the first data acquisition and processing unit is further configured to:
the driving performance of the vehicle user is acquired and quantified,
calculating an average value as a result of quantifying a reference driving performance of the vehicle user based on the result of quantifying the driving performance,
calculating a difference between the result of quantifying the current driving performance of the vehicle user and the result of quantifying the reference driving performance of the vehicle user as current awareness data of the vehicle user,
wherein the quantification of the driving performance and the quantification of the current driving performance comprise data on reaction times and/or safety awareness aspects of the vehicle user;
further preferably, the first data acquisition and processing unit is further configured to: and taking the driving performance of the vehicle user acquired after the preset time threshold value as the current driving performance.
3. The modeling apparatus of claim 1 or 2, wherein the model building unit is further configured to:
and performing regression analysis by using the workload data as abscissa data and the consciousness data as ordinate data to obtain a fitting curve representing the relationship between the workload and the consciousness of the vehicle user.
4. An assistance system for a vehicle, comprising:
a second identification unit configured to identify identification information of the vehicle user;
a model retrieving unit configured to: in response to the identity information of the identified vehicle user, calling a workload and consciousness degree relation model of the vehicle user, wherein the workload and consciousness degree relation model is established by the modeling device of any one of claims 1-3;
the second data acquisition and processing unit is configured to acquire workload data of the vehicle user in the driving process and determine the consciousness degree of the vehicle user corresponding to the workload data according to the workload and consciousness degree relation model of the vehicle user;
a first judgment unit configured to judge whether the determined degree of consciousness of the vehicle user is outside a preset range;
a first execution unit configured to: and in response to the first judgment unit judging that the determined consciousness degree of the vehicle user is out of the preset range, sending a visual, auditory and/or tactile safety prompt and/or an automatic driving takeover request to the vehicle user.
5. An assistance system for a vehicle, comprising:
a modelling apparatus as claimed in any of claims 1 to 3, for use in establishing a workload-to-awareness relationship model for a user of a vehicle, wherein the first data acquisition and processing unit comprised by the modelling apparatus is further configured to: establishing a relation model of the workload and the consciousness degree aiming at the vehicle user in response to the modeling device, acquiring the workload data of the vehicle user in the driving process, and determining the consciousness degree of the vehicle user corresponding to the workload data according to the relation model of the workload and the consciousness degree of the vehicle user;
a second determination unit configured to determine whether the determined degree of consciousness of the vehicle user is outside a preset range;
a second execution unit configured to: and responding to the second judgment unit to judge that the determined real-time awareness of the vehicle user is out of the preset range, and sending a visual, auditory and/or tactile safety prompt and/or an automatic driving takeover request to the vehicle user.
6. A vehicle, wherein the vehicle comprises a modelling arrangement according to any of claims 1-3 and/or an assistance system according to claim 4, or comprises an assistance system according to claim 5.
7. A modeling method for building a workload-to-awareness relationship model for a vehicle user, wherein the modeling method comprises:
identifying identity information of the vehicle user;
acquiring workload data and consciousness data of the vehicle user in the driving process;
training a relation model between the workload and the consciousness degree according to the workload data and the consciousness degree data;
preferably, the identity information of the vehicle user is identified by:
performing biometric recognition, such as face recognition, fingerprint recognition, eye print recognition, iris recognition, retina recognition, or voice print recognition, on the vehicle user; and/or
And logging in through the account number of the vehicle user for identification.
8. The modeling method of claim 7, wherein said obtaining workload data of the vehicle user during driving comprises:
acquiring and quantifying operation related information of the vehicle user in the driving process, and taking a quantification result as the workload data, wherein the operation related information comprises vehicle driving operation related information, vehicle-mounted system operation related information and personal behavior related information;
preferably, the acquiring consciousness data of the vehicle user during driving comprises:
the driving performance of the vehicle user is acquired and quantified,
calculating an average value as a result of quantifying a reference driving performance of the vehicle user based on the result of quantifying the driving performance,
calculating a difference between the result of quantifying the current driving performance of the vehicle user and the result of quantifying the reference driving performance of the vehicle user as current awareness data of the vehicle user,
wherein the quantification of the driving performance and the quantification of the current driving performance comprise data on reaction times and/or safety awareness aspects of the vehicle user;
further preferably, the acquiring consciousness data of the vehicle user during driving further comprises:
and taking the driving performance of the vehicle user acquired after the preset time threshold value as the current driving performance.
9. A modeling method according to claim 7 or 8, wherein said training a relational model between workload and consciousness from said workload data and said consciousness data comprises:
and performing regression analysis by using the workload data as abscissa data and the consciousness data as ordinate data to obtain a fitting curve representing the relationship between the workload and the consciousness of the vehicle user.
10. An assistance method for a vehicle, comprising:
identifying identity information of a vehicle user;
in response to the identity information of the identified vehicle user, calling a workload and consciousness degree relation model of the vehicle user, wherein the workload and consciousness degree relation model is established by the modeling method of any one of claims 7-9;
acquiring the workload data of the vehicle user in the driving process, and determining the consciousness degree of the vehicle user corresponding to the workload data according to the workload and consciousness degree relation model of the vehicle user;
judging whether the determined consciousness degree of the vehicle user is out of a preset range or not;
in response to determining that the determined degree of consciousness of the vehicle user is outside of a preset range, issuing a visual, audible and/or tactile safety prompt and/or an automatic driving takeover request to the vehicle user.
11. An assistance method for a vehicle, comprising:
establishing a workload and consciousness degree relation model of a vehicle user through the modeling method of any one of claims 7-9;
responding to the established relation model of the workload and the consciousness degree aiming at the vehicle user, acquiring the workload data of the vehicle user in the driving process, and determining the consciousness degree of the vehicle user corresponding to the workload data according to the relation model of the workload and the consciousness degree of the vehicle user;
judging whether the determined consciousness degree of the vehicle user is out of a preset range or not;
in response to determining that the determined real-time awareness of the vehicle user is outside of a preset range, issuing a visual, audible, and/or tactile safety prompt and/or an automatic driving takeover request to the vehicle user.
12. A computer-readable storage medium, on which a computer program is stored, wherein the computer program realizes the method of any of claims 7-9 or 10 or 11 when executed by a processor.
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