Methods and devices for determining personality traits

Abstract

A method and apparatus for determining personality traits, belonging to the field of information processing, are disclosed. The method includes: acquiring driving characteristic information of a first vehicle and behavioral characteristic information of the driver of the first vehicle during the driving process, wherein the behavioral characteristic information includes at least one of action characteristic information and voice characteristic information, and the driving characteristic information is used to characterize the driving status of the first vehicle; determining the driver's personality characteristic information based on the behavioral characteristic information and the driving characteristic information, wherein the personality characteristic information is used to characterize the driver's personality traits; and generating a personality characteristic report of the driver based on the personality characteristic information. This application can reduce the time required to determine the driver's personality traits and improve the efficiency of determining the driver's personality traits.

Description

Technical Field

[0001] This application relates to the field of information processing, and in particular to a method and apparatus for determining personality traits. Background Technology

[0002] Personality traits refer to the characteristics of an individual's behavior in social adaptation to people, things, and themselves. In the automotive industry, understanding user personality traits plays a crucial role in the manufacturing of automobiles. For example, understanding user personality traits allows for the creation of more personalized automobiles, or the improvement of vehicle functionality based on user personality traits.

[0003] Currently, user personality traits are typically determined through questionnaires. Specifically, users fill out questionnaires, and staff analyze these questionnaires to determine the user's personality traits.

[0004] However, the process of analyzing questionnaires by staff is usually time-consuming, which leads to a lengthy and inefficient process of determining users' personality traits. Summary of the Invention

[0005] This application provides a method and apparatus for determining personality traits, which can reduce the time required to determine a driver's personality traits and improve the efficiency of determining a driver's personality traits. The technical solution of this application is as follows.

[0006] Firstly, a method for determining personality traits is provided, the method comprising:

[0007] The driving characteristic information of the first vehicle and the behavioral characteristic information of the driver of the first vehicle during the driving process are obtained. The behavioral characteristic information includes at least one of action characteristic information and voice characteristic information. The driving characteristic information is used to characterize the driving status of the first vehicle.

[0008] The driver's personality characteristics are determined based on the behavioral characteristic information and the driving characteristic information, and the personality characteristic information is used to characterize the driver's personality characteristics;

[0009] A personality trait report of the driver is generated based on the personality trait information.

[0010] Optionally, determining the driver's personality characteristic information based on the behavioral characteristic information and the driving characteristic information includes: determining the driver's personality characteristic information based on the behavioral characteristic information, the driving characteristic information, and a personality characteristic model, wherein the personality characteristic model is used to determine the personality characteristic information based on the behavioral characteristic information and the driving characteristic information.

[0011] Optionally, the method further includes:

[0012] Obtain a training dataset, which includes multiple training data sets, each of which includes behavioral feature information, driving feature information, and personality feature information;

[0013] The personality trait model is obtained by training the model based on the training dataset.

[0014] Optionally, generating the driver's personality characteristic report based on the personality characteristic information includes:

[0015] Based on the personality trait information and the first mapping relationship, the explanatory information of the personality trait information is determined, wherein the first mapping relationship includes the mapping relationship between the personality trait information and the explanatory information;

[0016] The personality trait report is generated based on the personality trait information and the explanatory information.

[0017] Optionally, the driving characteristic information of the first vehicle is obtained, including:

[0018] The driving data of the first vehicle at multiple times is obtained, and the driving data at each of the multiple times is used to characterize the driving status of the first vehicle at each time.

[0019] Based on the driving data at the multiple times, at least one driving time period and at least one driving distance corresponding to the at least one driving time period are determined. Each driving distance in the at least one driving distance is the driving distance of the first vehicle in the corresponding driving time period. The multiple times include the start time and the end time of each driving time period in the at least one driving time period. Different driving time periods in the at least one driving time period do not overlap.

[0020] The driving characteristic information of the first vehicle is determined based on the at least one driving distance, the at least one driving period, and the driving data at the multiple times.

[0021] Optionally, the at least one driving time period can be multiple driving time periods, and the at least one driving distance can be multiple driving distances corresponding one-to-one with the multiple driving time periods.

[0022] The step of determining the driving characteristic information of the first vehicle based on the at least one driving distance, the at least one driving time period, and the driving data at the multiple times includes:

[0023] A target driving time period is determined from the at least one driving time period, wherein the target driving time period is longer than a preset driving time and / or the driving distance corresponding to the target driving time period is longer than a preset driving distance;

[0024] The driving characteristic information of the first vehicle is determined based on the target driving time period, the driving distance corresponding to the target driving time period, and the driving data at the multiple times.

[0025] Optionally, the driving data includes at least one of the following: ignition status information, fuel level, engine speed, accelerator pedal opening, brake pedal opening, longitudinal acceleration, lateral acceleration, global positioning system (GPS) direction, driving speed, antilock brake system (ABS) alarm status information, and cumulative travel.

[0026] The driving characteristic information includes at least one of the following: average driving speed, maximum driving speed, fuel consumption, number of rapid accelerations, number of rapid decelerations, number of sharp turns, number of speeding incidents, number of ABS alarms, maximum braking force, start-up time, and number of quick starts.

[0027] Optionally, the action feature information includes at least one of head sway amplitude, eye opening and closing distance, and mouth opening and closing distance, to obtain behavioral feature information of the driver of the first vehicle during the process of driving the first vehicle, including:

[0028] Acquire the driver's driving image, which is an image of the driver captured by a camera while the driver is driving the first vehicle;

[0029] Determine at least one of the following based on the driver's driving image: the driver's head sway amplitude, the driver's eye opening and closing distance, and the driver's mouth opening and closing distance.

[0030] Optionally, the speech feature information is information about the driver's speech signal, and the speech feature information includes at least one of the following: pitch, intensity, formants, effective speech length, speech rate, and number of pauses.

[0031] Secondly, a personality trait determination device is provided, the device comprising:

[0032] The first acquisition module is used to acquire driving characteristic information of the first vehicle and behavioral characteristic information of the driver of the first vehicle during the driving process of the first vehicle. The behavioral characteristic information includes at least one of action characteristic information and voice characteristic information. The driving characteristic information is used to characterize the driving status of the first vehicle.

[0033] The determination module is used to determine the driver's personality characteristic information based on the behavioral characteristic information and the driving characteristic information, wherein the personality characteristic information is used to characterize the driver's personality characteristics;

[0034] The generation module is used to generate a personality characteristic report of the driver based on the personality characteristic information.

[0035] Optionally, the determining module is configured to: determine the driver's personality characteristic information based on the behavioral characteristic information, the driving characteristic information, and the personality characteristic model, wherein the personality characteristic model is used to determine the personality characteristic information based on the behavioral characteristic information and the driving characteristic information.

[0036] Optionally, the device further includes:

[0037] The second acquisition module is used to acquire a training dataset, which includes multiple training data sets, each of which includes behavioral feature information, driving feature information, and personality feature information.

[0038] The training module is used to train the model based on the training dataset to obtain the personality feature model.

[0039] Optionally, the generation module is used for:

[0040] Based on the personality trait information and the first mapping relationship, the explanatory information of the personality trait information is determined, wherein the first mapping relationship includes the mapping relationship between the personality trait information and the explanatory information;

[0041] The personality trait report is generated based on the personality trait information and the explanatory information.

[0042] Optionally, the first acquisition module is used for:

[0043] The driving data of the first vehicle at multiple times is obtained, and the driving data at each of the multiple times is used to characterize the driving status of the first vehicle at each time.

[0044] Based on the driving data at the multiple times, at least one driving time period and at least one driving distance corresponding to the at least one driving time period are determined. Each driving distance in the at least one driving distance is the driving distance of the first vehicle in the corresponding driving time period. The multiple times include the start time and the end time of each driving time period in the at least one driving time period. Different driving time periods in the at least one driving time period do not overlap.

[0045] The driving characteristic information of the first vehicle is determined based on the at least one driving distance, the at least one driving period, and the driving data at the multiple times.

[0046] Optionally, the at least one driving time period can be multiple driving time periods, and the at least one driving distance can be multiple driving distances corresponding one-to-one with the multiple driving time periods. The first acquisition module is used for:

[0047] A target driving time period is determined from the at least one driving time period, wherein the target driving time period is longer than a preset driving time and / or the driving distance corresponding to the target driving time period is longer than a preset driving distance;

[0048] The driving characteristic information of the first vehicle is determined based on the target driving time period, the driving distance corresponding to the target driving time period, and the driving data at the multiple times.

[0049] Optionally, the driving data includes at least one of the following: ignition status information, fuel level, engine speed, accelerator pedal opening, brake pedal opening, longitudinal acceleration, lateral acceleration, GPS direction, driving speed, ABS alarm status information, and cumulative mileage.

[0050] The driving characteristic information includes at least one of the following: average driving speed, maximum driving speed, fuel consumption, number of rapid accelerations, number of rapid decelerations, number of sharp turns, number of speeding incidents, number of ABS alarms, maximum braking force, start-up time, and number of quick starts.

[0051] Optionally, the motion feature information includes at least one of head sway amplitude, eye opening and closing distance, and mouth opening and closing distance, wherein the first acquisition module is used to:

[0052] Acquire the driver's driving image, which is an image of the driver captured by a camera while the driver is driving the first vehicle;

[0053] Determine at least one of the following based on the driver's driving image: the driver's head sway amplitude, the driver's eye opening and closing distance, and the driver's mouth opening and closing distance.

[0054] Optionally, the speech feature information is information about the driver's speech signal, and the speech feature information includes at least one of the following: pitch, intensity, formants, effective speech length, speech rate, and number of pauses.

[0055] Thirdly, a device for determining personality traits is provided, including a memory and a processor;

[0056] The memory is used to store computer programs;

[0057] The processor is used to execute a computer program stored in the memory so that the personality trait determination device performs the personality trait determination method provided by the first aspect or any optional implementation thereof.

[0058] Fourthly, a vehicle is provided, including a personality characteristic determination device as provided in the second aspect or any alternative implementation of the second aspect, or including a personality characteristic determination device as provided in the third aspect.

[0059] Fifthly, a computer-readable storage medium is provided, wherein a computer program is stored therein, and when executed, the computer program implements the personality trait determination method provided by the first aspect or any alternative method of the first aspect described above.

[0060] In a sixth aspect, a computer program product is provided, the computer program product comprising a program or code, which, when executed, implements the personality trait determination method provided as described in the first aspect or any alternative method of the first aspect.

[0061] The beneficial effects of the technical solution provided in this application are:

[0062] This application provides a method and apparatus for determining personality traits. The method is executed by the personality trait determination apparatus. After acquiring driving characteristic information of a first vehicle and behavioral characteristic information of the driver of the first vehicle during driving, the personality trait determination apparatus determines the driver's personality trait information based on the driver's behavioral characteristic information and the driving characteristic information of the first vehicle, and generates a personality trait report for the driver based on this information. Compared to manually analyzing questionnaires to determine the driver's personality traits, this application uses a personality trait determination apparatus to determine the driver's personality traits based on the driving characteristic information of the first vehicle and the driver's behavioral characteristic information during driving, which reduces the time required for determining the driver's personality traits and improves the efficiency of the process. Attached Figure Description

[0063] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0064] Figure 1 This is a flowchart of a method for determining personality traits provided in an embodiment of this application;

[0065] Figure 2 This is a schematic diagram of a first vehicle provided in an embodiment of this application;

[0066] Figure 3This is a schematic diagram of a personality trait determination method provided in an embodiment of this application;

[0067] Figure 4 This is a schematic diagram of another method for determining personality traits provided in an embodiment of this application;

[0068] Figure 5 This is a schematic diagram of a personality trait determination device provided in an embodiment of this application;

[0069] Figure 6 This is a schematic diagram of another personality trait determination device provided in an embodiment of this application.

[0070] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. Detailed Implementation

[0071] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0072] Personality traits refer to an individual's behavioral characteristics in social adaptation, including their interactions with others, situations, and themselves. According to the Big Five personality theory, a complete personality trait comprises five dimensions: openness, agreeableness, conscientiousness, neuroticism, and extraversion. In the automotive industry, understanding user personality traits plays a crucial role in the manufacturing of automobiles. For example, understanding user personality traits allows for the creation of more personalized automotive products, or the improvement of vehicle functionality based on user personality characteristics.

[0073] Currently, user personality traits are typically determined through questionnaires, which can be written or spoken. Users can complete the questionnaire by filling in text or by voice input, and staff determine the user's personality traits by analyzing the completed questionnaire.

[0074] However, questionnaire completion is inherently subjective, which can lead to significant discrepancies between the personality traits identified through the questionnaire and the user's actual personality traits. Furthermore, the process of analyzing questionnaires is typically time-consuming, resulting in a lengthy and inefficient process for determining user personality traits.

[0075] This application provides a method and apparatus for determining personality traits. The method is executed by the personality trait determination apparatus. After acquiring driving characteristic information of a first vehicle and behavioral characteristic information of the driver of the first vehicle during driving, the personality trait determination apparatus determines the driver's personality trait information based on the driver's behavioral characteristic information and the driving characteristic information of the first vehicle, and generates a personality trait report for the driver based on the driver's personality trait information. Compared to manually analyzing questionnaires to determine the driver's personality traits, this application embodiment uses a personality trait determination apparatus to determine the driver's personality traits based on the driving characteristic information of the first vehicle and the behavioral characteristic information of the driver of the first vehicle during driving, which can reduce the time spent in determining the driver's personality traits and improve the efficiency of determining the driver's personality traits.

[0076] The following describes an embodiment of the personality trait determination method of this application.

[0077] Please refer to Figure 1 The diagram illustrates a flowchart of a personality trait determination method provided in an embodiment of this application. This personality trait determination method is executed by a personality trait determination device. See also... Figure 1 The method for determining this personality trait includes the following steps S101 to S103.

[0078] S101. Obtain driving characteristic information of the first vehicle and behavioral characteristic information of the driver of the first vehicle during the driving process of the first vehicle, wherein the behavioral characteristic information includes at least one of action characteristic information and voice characteristic information, and the driving characteristic information is used to characterize the driving status of the first vehicle.

[0079] The behavioral characteristic information of the driver of the first vehicle during the driving process is used to characterize the driver's behavior during the driving process. The driving characteristic information of the first vehicle is used to characterize the driving status of the first vehicle during the driving process. In this embodiment of the application, the driver's action characteristic information includes at least one of head sway amplitude, eye opening and closing distance, and mouth opening and closing distance. The eye opening and closing distance includes at least one of left eye opening and closing distance and right eye opening and closing distance. The left eye opening and closing distance refers to the distance between the midpoint of the upper eyelid and the midpoint of the lower eyelid of the left eye. The right eye opening and closing distance refers to the distance between the midpoint of the upper eyelid and the midpoint of the lower eyelid of the right eye. The mouth opening and closing distance includes at least one of vertical mouth opening and closing distance and horizontal mouth opening and closing distance. The vertical mouth opening and closing distance refers to the distance between the midpoint of the upper lip and the midpoint of the lower lip, and the horizontal mouth opening and closing distance refers to the distance between the left corner of the mouth and the right corner of the mouth. The driving characteristic information of the first vehicle includes at least one of the following: average driving speed, maximum driving speed, fuel consumption, number of rapid accelerations, number of rapid decelerations, number of sharp turns, number of speedings, number of antilock brake system (ABS) warnings, maximum braking force, start-up time, and number of quick starts.

[0080] In an optional embodiment, the personality characteristic determination device obtains the driving characteristic information of the first vehicle and the behavioral characteristic information of the driver of the first vehicle during the driving process from its storage space. The driving characteristic information of the first vehicle and the behavioral characteristic information of the driver of the first vehicle stored in the storage space are obtained and stored in advance during the driving process of the driver of the first vehicle. Alternatively, the personality characteristic determination device obtains the driving characteristic information of the first vehicle and the behavioral characteristic information of the driver during the driving process of the first vehicle. This embodiment of the application does not limit this.

[0081] In an optional embodiment, the personality characteristic determination device acquires driving data of the first vehicle at multiple moments during the driver's operation. Based on the driving data at these multiple moments, the device determines at least one driving time period and at least one driving distance corresponding to each driving time period. The device also determines driving characteristic information of the first vehicle based on the at least one driving distance, the at least one driving time period, and the driving data at the multiple moments. The duration between adjacent moments is less than a preset duration, for example, 10 seconds. The driving data at each moment represents the driving status of the first vehicle at that moment. Each driving distance is the distance traveled by the first vehicle within its corresponding driving time period. The multiple moments include the start time and end time of each driving time period, and different driving time periods do not overlap. For example, for any two driving time periods, the start time of one driving time period may be after the end time of the other, or the start time of one driving time period may be the same as the end time of the other.

[0082] In an optional embodiment, the personality characteristic determination device obtains the driving data of the first vehicle at multiple times through the first vehicle's telematics-box (T-box).

[0083] In optional embodiments, the driving data of the first vehicle includes at least one of the following: ignition status information, fuel balance, engine speed, accelerator pedal opening, brake pedal opening, longitudinal acceleration, lateral acceleration, Global Positioning System (GPS) direction, driving speed, ABS alarm status information, and accumulated mileage. The ignition status information of the first vehicle at any given time is used to indicate whether the first vehicle is in an ignition state or an off state at that time. For example, the ignition status information is either first status information or second status information. The first status information is used to indicate that the first vehicle is in an ignition state (including the state of ignition in progress and the state of already ignited), and the second status information is used to indicate that the first vehicle is in an off state. The fuel balance of the first vehicle at any given time is the remaining fuel quantity of the first vehicle at that time, or the fuel balance of the first vehicle at any given time is the percentage of the remaining fuel quantity of the first vehicle at that time. The longitudinal acceleration of the first vehicle at any given time is the acceleration of the first vehicle in the same direction as its driving direction at that time. The lateral acceleration of the first vehicle at any given time is the acceleration of the first vehicle in the direction perpendicular to its driving direction at that time. The GPS orientation of the first vehicle at any given time is the angle between the vehicle's direction of travel at that time and the X-axis of the GPS coordinate system, or the GPS orientation of the first vehicle at any given time is the angle between the vehicle's direction of travel at that time and the Y-axis of the GPS coordinate system, where the GPS coordinates are the coordinates used by the GPS system. The ABS alarm status information of the first vehicle at any given time indicates whether the ABS of the first vehicle has issued an alarm at that time. The cumulative mileage of the first vehicle at any given time is the distance traveled by the first vehicle within the time period formed by that time and the initial time, where the initial time can be the time when the first vehicle first traveled.

[0084] In an optional embodiment, the driving data of the first vehicle includes ignition status information and cumulative mileage. The personality characteristic determination device determines at least one driving period and at least one driving distance corresponding to the at least one driving period based on the ignition status information at the plurality of times and the cumulative mileage at the plurality of times. In a specific embodiment, the personality characteristic determination device determines at least one time when the ignition status information is first status information (e.g., the at least one time is referred to as the ignition status time) and at least one time when the ignition status information is second status information (e.g., the at least one time is referred to as the shutdown status time) among the plurality of times. The personality characteristic determination device determines the ignition status time adjacent to and following a shutdown status time among the at least one ignition status times as a start time, and determines the first shutdown status time after the start time as an end time. The personality characteristic determination device determines the time period between the start time and the end time as a driving period. The personality characteristic determination device determines the driving distance corresponding to the driving period based on the cumulative mileage at the start time and the cumulative mileage at the end time of the driving period. Specifically, the personality trait determination device determines the driving distance corresponding to the driving period as the difference between the driving distance at the end of the driving period and the driving distance at the beginning of the driving period. For example, if time 1 is the end time, time 2 is the beginning time, time 3 is the beginning time, time 4 is the beginning time, time 5 is the end time, and time 6 is the end time, the personality trait determination device determines the time period between time 2 and time 5 as a driving period, and determines the driving distance corresponding to the driving period as the difference between the cumulative distance traveled at time 5 and the cumulative distance traveled at time 2.

[0085] In an optional embodiment, the driving characteristic information of the first vehicle includes average driving speed. After the personality characteristic determination device determines at least one driving time period and at least one driving distance corresponding to the at least one driving time period based on the driving data at the plurality of time points, the personality characteristic determination device determines the average driving speed of the first vehicle in each driving time period based on the duration of each driving time period and the driving distance corresponding to each driving time period. The personality characteristic determination device can determine at least one average driving speed corresponding to the at least one driving time period, and the average driving speed corresponding to each driving time period in the at least one driving time period is the average driving speed of the first vehicle in each driving time period. In a specific embodiment, the personality characteristic determination device determines the ratio of the driving distance corresponding to each driving time period to the duration of each driving time period as the average driving speed of the first vehicle in each driving time period.

[0086] In an optional embodiment, the driving characteristic information of the first vehicle includes its maximum driving speed. After the personality characteristic determination device determines at least one average driving speed corresponding to the at least one driving time period, the personality characteristic determination device determines the maximum value among the at least one average driving speed as the maximum driving speed of the first vehicle.

[0087] In an optional embodiment, the driving data of the first vehicle includes the remaining fuel level, and the driving characteristic information of the first vehicle includes fuel consumption. The personality characteristic determination device determines the fuel consumption for each driving period based on the remaining fuel level at the start and end of each driving period within the at least one driving period. The personality characteristic determination device then determines the fuel consumption of the first vehicle based on the fuel consumption for the at least one driving period. For example, for each driving period within the at least one driving period: if the remaining fuel level at the multiple times obtained by the personality characteristic determination device is a specific remaining fuel level value, the personality characteristic determination device determines the difference between the remaining fuel level at the start and end of the driving period as the fuel consumption for that driving period; if the remaining fuel level at the multiple times obtained by the personality characteristic determination device is a percentage of the remaining fuel level, the personality characteristic determination device determines the fuel consumption for that driving period by multiplying the difference between the remaining fuel level at the start and end of the driving period by the fuel tank capacity of the first vehicle. The personality trait determination device determines the sum of fuel consumption during at least one driving period as the fuel consumption of the first vehicle.

[0088] In an optional embodiment, the driving data of the first vehicle includes engine speed, accelerator pedal opening, and brake pedal opening, and the driving characteristic information of the first vehicle includes the number of rapid accelerations. The personality characteristic determination device determines the number of rapid accelerations of the first vehicle based on the engine speed, brake pedal opening, and accelerator pedal opening of the first vehicle at multiple times. In a specific embodiment, the personality characteristic determination device determines the number of rapid acceleration moments among the multiple times based on the engine speed, brake pedal opening, and accelerator pedal opening of the first vehicle at multiple times, and the personality determination device determines the number of rapid acceleration moments among the multiple times as the number of rapid accelerations of the first vehicle. In one embodiment, for each of the plurality of moments: the personality characteristic determination device determines whether the engine speed of the first vehicle at that moment is within a preset speed range; if the engine speed of the first vehicle at that moment is not within the preset speed range, the personality characteristic determination device determines whether the brake pedal opening of the first vehicle at that moment is 0; if the brake pedal opening of the first vehicle at that moment is 0, the personality characteristic determination device determines whether the accelerator pedal opening of the first vehicle at that moment is greater than a preset accelerator pedal opening; if the accelerator pedal opening of the first vehicle at that moment is greater than the preset accelerator pedal opening, the personality characteristic determination device determines that moment is a rapid acceleration moment; if the engine speed of the first vehicle at that moment is within the preset speed range, or if the brake pedal opening of the first vehicle at that moment is not 0, or if the accelerator pedal opening of the first vehicle at that moment is not greater than the preset accelerator pedal opening, the personality characteristic determination device determines that moment is not a rapid acceleration moment. For example, when the driver does not press the accelerator pedal, the opening of the accelerator pedal is 0, and when the driver fully presses the accelerator pedal, the opening of the accelerator pedal is 100%. The preset accelerator pedal opening can be 30%, but this application embodiment does not limit it.

[0089] In an optional embodiment, the driving data of the first vehicle includes longitudinal acceleration, accelerator pedal opening, and brake pedal opening, and the driving characteristic information of the first vehicle includes the number of sudden decelerations. The personality characteristic determination device determines the number of sudden decelerations of the first vehicle based on the longitudinal acceleration, brake pedal opening, and accelerator pedal opening of the first vehicle at the multiple moments. In a specific embodiment, the personality characteristic determination device determines the number of sudden deceleration moments among the multiple moments based on the longitudinal acceleration, brake pedal opening, and accelerator pedal opening of the first vehicle at the multiple moments, and the personality determination device determines the number of sudden deceleration moments among the multiple moments as the number of sudden decelerations of the first vehicle. In one embodiment, for each of the plurality of moments: the personality characteristic determination device determines whether the longitudinal acceleration of the first vehicle at that moment is within a preset longitudinal acceleration range; if the longitudinal acceleration of the first vehicle at that moment is not within the preset longitudinal acceleration range, the personality characteristic determination device determines whether the brake pedal opening of the first vehicle at that moment is 0; if the brake pedal opening of the first vehicle at that moment is not 0, the personality characteristic determination device determines whether the accelerator pedal opening of the first vehicle at that moment is 0; if the accelerator pedal opening of the first vehicle at that moment is 0, the personality characteristic determination device determines that moment is a rapid deceleration moment; if the longitudinal acceleration of the first vehicle at that moment is within a preset longitudinal acceleration range, or if the brake pedal opening of the first vehicle at that moment is 0, or if the accelerator pedal opening of the first vehicle at that moment is not 0, the personality characteristic determination device determines that moment is not a rapid deceleration moment.

[0090] In an optional embodiment, the driving data of the first vehicle includes lateral acceleration, GPS direction, and driving speed, and the driving characteristic information of the first vehicle includes the number of sharp turns. The personality characteristic determination device determines the number of sharp turns of the first vehicle based on the GPS direction, driving speed, and lateral acceleration of the first vehicle at multiple times. In a specific embodiment, the personality characteristic determination device determines the number of sharp turn moments among the multiple times based on the GPS direction, driving speed, and lateral acceleration of the first vehicle at multiple times, and the personality determination device determines the number of sharp turn moments among the multiple times as the number of sharp turns of the first vehicle. In one embodiment, for each of the plurality of moments: the personality characteristic determination device determines whether the difference between the GPS direction of the first vehicle at that moment and the GPS direction of the first vehicle at the next moment is greater than a preset GPS direction difference; if the difference between the GPS direction of the first vehicle at that moment and the GPS direction of the first vehicle at the next moment is greater than the preset GPS direction difference, the personality characteristic determination device determines whether the driving speed of the first vehicle at that moment is greater than a preset driving speed; if the driving speed of the first vehicle at that moment is greater than the preset speed, the personality characteristic determination device determines whether the lateral acceleration of the first vehicle at that moment is within a preset lateral acceleration range; if the lateral acceleration of the first vehicle at that moment is within the preset lateral acceleration range, the personality characteristic determination device determines that moment is a sharp turn moment; if the difference between the GPS direction of the first vehicle at that moment and the GPS direction of the first vehicle at the next moment is less than or equal to the preset GPS direction difference, or if the driving speed of the first vehicle at that moment is less than or equal to the preset speed, or if the lateral acceleration of the first vehicle at that moment is not within the preset lateral acceleration range, the personality characteristic determination device determines that moment is not a sharp turn moment. For example, the preset GPS orientation difference can be 70 degrees, and the preset driving speed can be 15 kilometers per hour (km / h).

[0091] In an optional embodiment, the driving characteristic information of the first vehicle includes the number of speeding violations. After the personality characteristic determination device determines at least one average driving speed corresponding to the at least one driving time period, the personality characteristic determination device determines the number of times the at least one average driving speed exceeds a preset average speed, and the personality characteristic determination device determines the number of times the at least one average driving speed exceeds the preset average speed as the number of speeding violations by the first vehicle. For example, the preset average speed may be 60 km / h.

[0092] In an optional embodiment, the driving data of the first vehicle includes ABS alarm status information, and the driving characteristic information of the first vehicle includes the number of ABS alarms. The personality characteristic determination device determines the number of ABS alarms of the first vehicle based on the ABS alarm status information of the first vehicle at multiple times. In a specific embodiment, the personality characteristic determination device determines the number of alarm times among the multiple times based on the ABS alarm status information of the first vehicle at multiple times, and the personality characteristic determination device determines the number of alarm times among the multiple times as the number of ABS alarms of the first vehicle. In one embodiment, for each of the multiple times: the personality characteristic determination device determines whether the ABS of the first vehicle has issued an alarm at that time based on the ABS alarm status information of the first vehicle at that time, that is, determines whether the ABS alarm status information of the first vehicle at that time indicates that the ABS of the first vehicle has issued an alarm at that time; if the ABS of the first vehicle has issued an alarm at that time, the personality characteristic determination device determines that time is an alarm time; if the ABS of the first vehicle has not issued an alarm at that time, the personality characteristic determination device determines that time is not an alarm time.

[0093] In an optional embodiment, the driving data of the first vehicle includes longitudinal acceleration, and the driving characteristic information of the first vehicle includes maximum braking force. The personality characteristic determination device determines the maximum braking force of the first vehicle based on the longitudinal acceleration of the first vehicle at each of the multiple moments. In a specific embodiment, the personality characteristic determination device determines the braking force of the first vehicle at each of the multiple moments based on the longitudinal acceleration of the first vehicle at each moment. The personality characteristic determination device can obtain multiple braking forces corresponding to the multiple moments, and the braking force corresponding to each of the multiple moments is the braking force of the first vehicle at that moment. The personality characteristic determination device determines the maximum braking force among the multiple braking forces as the maximum braking force of the first vehicle. In one embodiment, for each of the multiple moments, the personality characteristic determination device determines the braking force of the first vehicle at that moment as the product of the longitudinal acceleration of the first vehicle at that moment and the mass of the first vehicle.

[0094] In an optional embodiment, the driving data of the first vehicle includes driving speed, and the driving characteristic information of the first vehicle includes start-up time. The personality characteristic determination device determines the start-up time of the first vehicle based on the driving speed of the first vehicle at multiple moments. In a specific embodiment, the personality characteristic determination device determines the start-up time of each of the at least one driving time period, and the average of the start-up times of the at least one driving time period is determined as the start-up time of the first vehicle. In one embodiment, for each of the at least one driving time period: the personality characteristic determination device determines that among the multiple moments included in each driving time period, the moment when the driving speed is 0 is the first moment, the moment when the driving speed is a preset start-up speed is the second moment, and the personality characteristic determination device determines the difference between the second moment and the first moment as the start-up time of the driving time period. For example, the preset start-up speed may be 20 km / h.

[0095] In an optional embodiment, the driving data of the first vehicle includes driving speed, accelerator pedal opening, longitudinal acceleration, and engine speed, and the driving characteristic information of the first vehicle includes the number of quick starts. The personality characteristic determination device determines the number of quick starts of the first vehicle based on the driving speed, accelerator pedal opening, longitudinal acceleration, and engine speed of the first vehicle at multiple moments. In a specific embodiment, the personality characteristic determination device determines the number of quick start moments among the multiple moments based on the driving speed, accelerator pedal opening, longitudinal acceleration, and engine speed of the first vehicle at multiple moments, and the personality determination device determines the number of quick start moments among the multiple moments as the number of quick starts of the first vehicle. In one embodiment, for each of the plurality of moments: the personality characteristic determination device determines whether the speed of the first vehicle at that moment is less than a first speed; if the speed of the first vehicle at that moment is less than the first speed, the personality characteristic determination device determines whether the accelerator pedal opening of the first vehicle at the next moment is 0; if the accelerator pedal opening of the first vehicle at the next moment is not 0, the personality characteristic determination device determines whether the longitudinal acceleration of the first vehicle at the next moment is greater than a preset longitudinal acceleration; if the longitudinal acceleration of the first vehicle at the next moment is greater than the preset longitudinal acceleration, the personality characteristic determination device determines the engine speed of the first vehicle at that moment and the next moment... The device determines whether the difference between the engine speeds of the first vehicle at a given moment and the engine speed at the next moment is greater than a preset speed difference. If the difference is greater than the preset speed difference, the personality characteristic determination device determines that moment is a fast start moment. If the speed of the first vehicle at that moment is greater than or equal to a first speed, or the accelerator pedal opening of the first vehicle at the next moment is 0, or the difference between the engine speeds of the first vehicle at that moment and the engine speed at the next moment is less than the preset speed difference, the personality characteristic determination device determines that moment is not a fast start moment. For example, the first speed can be 10 km / h, and the preset longitudinal acceleration can be 0.1 m / s². 2 The preset speed difference can be 2000 revolutions per minute (r / min).

[0096] In an optional embodiment, the at least one driving time period is multiple driving time periods, and the at least one driving distance is multiple driving distances corresponding one-to-one with the multiple driving time periods. The personality characteristic determination device determines the driving characteristic information of the first vehicle based on the at least one driving distance, the at least one driving time period, and the driving data at the multiple times, including: the personality characteristic determination device determining a target driving time period from the at least one driving time period; and the personality characteristic determination device determining the driving characteristic information of the first vehicle based on the target driving time period, the driving distance corresponding to the target driving time period, and the driving data at the multiple times. Wherein, the driving duration of the target driving time period is greater than a preset driving duration and / or the driving distance corresponding to the target driving time period is greater than a preset driving distance, and the number of target driving time periods can be one or more.

[0097] In a specific embodiment, for each of the at least one driving time period: the personality characteristic determination device determines whether the driving duration (i.e., the length of the driving time period) of the driving time period is greater than a preset driving duration, and determines whether the driving distance corresponding to the driving time period is greater than a preset driving distance. If the driving duration of the driving time period is greater than the preset driving duration and / or the driving distance corresponding to the driving time period is greater than the preset driving distance, the personality characteristic determination device determines the driving time period as a target driving time period. If the driving duration of the driving time period is not greater than the preset driving duration and the driving distance corresponding to the driving time period is not greater than the preset driving distance, the personality characteristic determination device does not determine the driving time period as a target driving time period.

[0098] like Figure 2 As shown, Figure 2 A schematic diagram of a first vehicle is provided. The first vehicle includes a camera, a microphone, a battery, a personality characteristic determination device, an indicator light, and a switch. The personality characteristic determination device includes a processor and a memory. The camera is used to acquire driving images of the driver, specifically images of the driver while driving the first vehicle. The microphone is used to acquire the driver's voice signal. The battery supplies power to the camera, microphone, personality characteristic determination device, indicator light, and switch. The switch controls the on / off state of the personality characteristic determination device. The indicator light indicates the on / off state of the personality characteristic determination device.

[0099] In this embodiment, the driver's action characteristic information includes at least one of head sway amplitude, eye opening and closing distance, and mouth opening and closing distance. The personality characteristic determination device acquires behavioral characteristic information of the driver of the first vehicle during the driving process, including: acquiring driving images of the driver; determining at least one of the driver's head sway amplitude, eye opening and closing distance, and mouth opening and closing distance based on the driving images. In an optional embodiment, the personality characteristic determination device acquires multiple driving images of the driver; inputs the multiple driving images into a facial feature model; after recognizing the multiple driving images, the facial feature model marks feature points on the multiple driving images to obtain multiple feature images corresponding to each of the multiple driving images, each feature image including at least one marked feature point; the facial feature model outputs the multiple feature images. The personality characteristic determination device determines at least one of the driver's head sway amplitude, eye opening and closing distance, and mouth opening and closing distance based on the multiple feature images. The driver's driving image can be an image of the driver captured by a camera, or an image of the driver extracted from a video captured by a camera.

[0100] In an optional embodiment, the multiple driving images correspond one-to-one with the multiple feature images. The multiple driving images are acquired at different times. The personality feature determination device sorts the multiple feature images according to their acquisition times to obtain an image sequence. The personality feature device determines each pair of adjacent feature images in the image sequence as a feature image set to obtain at least one feature image set. The personality feature device determines the head sway amplitude based on each feature image set in the at least one feature image set to obtain the head sway amplitude corresponding to each feature image set. The personality feature device performs feature operations on the head sway amplitude corresponding to the at least one feature image set, and determines the feature value obtained from the feature operations as the driver's head sway amplitude. For example, the feature operations include average operation, maximum operation, minimum operation, variance operation, or median operation, and the feature value includes average, maximum, minimum, variance, or median. In a specific embodiment, the feature point of the feature image includes the center point of the driver's face. The two feature images in each feature image set of the at least one feature image set include a first image and a second image. The first image can be ordered before or after the second image. For each feature image set in the at least one feature image set: the personality feature determining device determines the two-dimensional coordinates of the center point of the driver's face in the first image and the two-dimensional coordinates of the center point of the driver's face in the second image; the personality feature determining device converts the two-dimensional coordinates of the center point of the driver's face in the first image and the two-dimensional coordinates of the center point of the driver's face in the second image into three-dimensional coordinates respectively; the personality feature determining device determines the line segment between the three-dimensional coordinates of the center point of the driver's face in the first image and the three-dimensional coordinates of the center point of the driver's face in the second image as a first line segment; the personality feature determining device determines the angle between the first line segment and the X-axis as the amplitude of the driver's head movement in the X-axis direction; the personality feature determining device determines the angle between the first line segment and the Y-axis as the amplitude of the driver's head movement in the Y-axis direction; the personality feature determining device determines the angle between the first line segment and the Z-axis as the amplitude of the driver's head movement in the Z-axis direction. Wherein, the X-axis, Y-axis, and Z-axis are the three coordinate axes of the three-dimensional coordinate system. For example, the personality trait determination device uses a perspective-n-point (PnP) algorithm to convert the two-dimensional coordinates of the center point of the driver's face into three-dimensional coordinates.

[0101] In an optional embodiment, the driver's eye opening distance includes at least one of the driver's left eye opening distance and the driver's right eye opening distance. The personality feature determination device determines the driver's left eye opening distance based on the driver's left eye opening distance in the multiple feature images, and determines the driver's right eye opening distance based on the driver's right eye opening distance in the multiple feature images. For example, the personality feature determination device performs feature calculations on the driver's left eye opening distance corresponding to the multiple feature images, and determines the feature value obtained from the feature calculations as the driver's left eye opening distance. The personality feature determination device also performs feature calculations on the driver's right eye opening distance in the multiple feature images, and determines the feature value obtained from the feature calculations as the driver's right eye opening distance. For example, the feature calculations include average calculation, maximum value calculation, minimum value calculation, variance calculation, or median value calculation, and the feature value includes average, maximum, minimum, variance, or median value. In a specific embodiment, the feature points of the feature image include the midpoint of the upper eyelid of the driver's left eye, the midpoint of the lower eyelid of the driver's left eye, the midpoint of the upper eyelid of the driver's right eye, and the midpoint of the lower eyelid of the driver's right eye.

[0102] For each of the multiple feature images: the personality feature determination device determines the driver's left eye opening distance in the feature image based on the midpoint of the driver's left upper eyelid and the midpoint of the driver's left lower eyelid; the personality feature determination device determines the driver's right eye opening distance in the feature image based on the midpoint of the driver's right upper eyelid and the midpoint of the driver's right lower eyelid. The personality feature determination device determines the distance between the midpoint of the left upper eyelid and the midpoint of the left lower eyelid, and determines this distance as the driver's left eye opening distance in the feature image. The personality feature determination device determines the distance between the midpoint of the right upper eyelid and the midpoint of the right lower eyelid, and determines this distance as the driver's right eye opening distance in the feature image.

[0103] In an optional embodiment, the driver's mouth opening distance includes at least one of the driver's vertical mouth opening distance and the driver's horizontal mouth opening distance. The personality feature determination device determines the driver's vertical mouth opening distance based on the vertical mouth opening distance of the multiple feature images, and the personality feature determination device determines the driver's horizontal mouth opening distance based on the horizontal mouth opening distance of the multiple feature images. For example, the personality feature device performs feature calculations on the driver's vertical mouth opening distance of the multiple feature images, and determines the feature value obtained from the feature calculations as the driver's vertical mouth opening distance. The personality feature device performs feature calculations on the driver's horizontal mouth opening distance of the multiple feature images, and determines the feature value obtained from the feature calculations as the driver's horizontal mouth opening distance. For example, the feature calculations include average value calculation, maximum value calculation, minimum value calculation, variance calculation, or median value calculation, and the feature value includes average value, maximum value, minimum value, variance, or median value. In a specific embodiment, the feature points of the feature image include the midpoint of the driver's upper lip, the midpoint of the driver's lower lip, the left corner of the driver's mouth, and the right corner of the driver's mouth.

[0104] For each of the multiple feature images: the personality feature determination device determines the vertical opening distance of the driver's mouth in the feature image based on the midpoint of the driver's upper lip and the midpoint of the driver's lower lip; the personality feature determination device determines the horizontal opening distance of the driver's mouth in the feature image based on the left corner and the right corner of the driver's mouth. The personality feature determination device determines the distance between the midpoint of the upper lip and the midpoint of the lower lip, and determines the vertical opening distance of the driver's mouth in the feature image based on the distance between the left corner and the right corner of the mouth. The personality feature determination device determines the distance between the left corner and the right corner of the mouth, and determines the horizontal opening distance of the driver's mouth in the feature image based on the distance between the left corner and the right corner of the mouth.

[0105] In a specific embodiment, the personality feature determination device can determine the distance between two points based on their coordinates, or it can determine the distance between two points based on their pixel counts. For example, the personality feature determination device can determine the distance between the midpoints of the upper and lower eyelids of the left eye based on the coordinates of the midpoints of the upper and lower eyelids of the left eye, or it can determine the number of pixels between the midpoint pixels of the upper and lower eyelids of the left eye as the distance between the midpoints of the upper and lower eyelids of the left eye.

[0106] The driver's voice feature information refers to the driver's voice signal information, which includes at least one of pitch, intensity, formants, effective speech length, speech rate, and number of pauses. After acquiring the driver's voice signal via a microphone, the personality feature determination device inputs the voice signal into speech science software. The speech science software analyzes the driver's voice signal to obtain the driver's voice feature information and outputs it. The personality feature determination device acquires the driver's voice feature information output by the speech science software. The speech science software can be Praat speech science software (primarily used for analyzing digitized voice signals).

[0107] S102. Determine the driver's personality characteristics based on the driver's behavioral characteristics information and the driving characteristics information of the first vehicle. The personality characteristics information is used to characterize the driver's personality characteristics.

[0108] The driver's personality trait information includes at least one of the following: openness, agreeableness, conscientiousness, neuroticism, and extraversion. The openness information indicates the driver's degree of openness; the agreeableness information indicates the driver's degree of agreeableness; the conscientiousness information indicates the driver's degree of conscientiousness; the neuroticism information indicates the driver's degree of neuroticism; and the extraversion information indicates the driver's degree of extraversion.

[0109] In an optional embodiment, the personality characteristic determination device determines the driver's personality characteristic information based on the driver's behavioral characteristic information, the driving characteristic information of the first vehicle, and a personality characteristic model. The personality characteristic model is used to determine the personality characteristic information based on the behavioral characteristic information and the driving characteristic information.

[0110] In a specific embodiment, the personality trait determination device inputs the driver's behavioral characteristic information and the driving characteristic information of the first vehicle into a personality trait model. The personality trait model analyzes the driver's behavioral characteristic information and the driving characteristic information of the first vehicle to obtain the driver's personality trait information and outputs the driver's personality trait information. The personality trait determination device acquires the driver's personality trait information output by the personality trait model. In one embodiment, the driver's personality trait information output by the personality trait model includes the driver's openness score, the driver's agreeableness score, the driver's conscientiousness score, the driver's neuroticism score, and the driver's extraversion score. If the driver's openness score is greater than a preset openness score, the personality trait determination device determines that the driver has high openness; if the driver's openness score is not greater than the preset openness score, the personality trait determination device determines that the driver has low openness. If the driver's agreeableness score is greater than a preset agreeableness score, the personality trait determination device determines that the driver's agreeableness is high; if the driver's agreeableness score is not greater than the preset agreeableness score, the personality trait determination device determines that the driver's agreeableness is low. If the driver's conscientiousness score is greater than a preset conscientiousness score, the personality trait determination device determines that the driver's conscientiousness is high; if the driver's conscientiousness score is not greater than the preset conscientiousness score, the personality trait determination device determines that the driver's conscientiousness is low. If the driver's neuroticism score is greater than a preset neuroticism score, the personality trait determination device determines that the driver's neuroticism is high; if the driver's neuroticism score is not greater than the preset neuroticism score, the personality trait determination device determines that the driver's neuroticism is low. If the driver's extraversion score is greater than a preset extraversion score, the personality trait determination device determines that the driver's extraversion is high; if the driver's extraversion score is not greater than the preset extraversion score, the personality trait determination device determines that the driver's extraversion is low.

[0111] In an optional embodiment, before determining the driver's personality characteristic information based on the driver's behavioral characteristic information, the driving characteristic information of the first vehicle, and the personality characteristic model, the personality characteristic determination device acquires the personality characteristic model. For example, the personality characteristic determination device acquires the pre-trained personality characteristic model, or the personality characteristic determination device trains the personality characteristic model.

[0112] This application embodiment uses the training of the personality feature model by the personality feature determination device as an example. In an optional embodiment, the personality feature determination device acquires a training dataset, which includes multiple training data points, each of which includes behavioral feature information, driving feature information, and personality feature information; the personality feature determination device trains the model based on the training dataset to obtain the personality feature model.

[0113] In an optional embodiment, the personality characteristic determination device acquires behavioral characteristic information, driving characteristic information, and personality characteristic information for each of the multiple testers. The device then uses this information as a training data point, and the set of multiple training data points for each tester is defined as a training dataset. In a specific embodiment, the device acquires the personality characteristic information of each tester input by a staff member; it acquires images and audio recordings of each tester driving a vehicle, and determines the behavioral characteristic information of each tester based on these images and audio recordings; it acquires the driving data of the vehicle during the driving process, and determines the driving characteristic information of the vehicle based on this driving data. Alternatively, the staff member can determine the personality characteristic information of the testers through a questionnaire, such as the Big Five personality disorder questionnaire, and analyze the questionnaires completed by the multiple testers to determine their personality characteristic information.

[0114] In an optional embodiment, for each piece of training data in the training dataset: the personality feature determination device inputs the behavioral feature information and driving feature information from the training data into an initial model, causing the initial model to analyze the behavioral feature information and driving feature information to obtain the corresponding personality feature information, and output the corresponding personality feature information; the personality feature determination device adjusts the model parameters of the initial model based on the difference between the personality feature information output by the initial model and the personality feature information in the training data; the personality feature determination device inputs the behavioral feature information and driving feature information from the training data into the adjustment... The model with adjusted parameters is used to analyze the behavioral and driving characteristics again to obtain the corresponding personality characteristics, and outputs the corresponding personality characteristics. The personality characteristic determination device then adjusts the model parameters again based on the difference between the behavioral and driving characteristics output by the adjusted model and the personality characteristics in the training data, and performs another analysis. The personality characteristic determination device repeats the process of inputting behavioral and driving characteristics to adjust model parameters to train the model until a termination condition is met. The model obtained when the termination condition is met is determined as the trained personality characteristic model. The process from inputting behavioral and driving characteristics from the training data to adjusting model parameters constitutes one iteration. The termination condition includes at least one of the following: the difference between the personality characteristics output by the personality characteristic model and the personality characteristics in the training data is less than a preset difference; the number of training iterations (i.e., the number of iterations during training) reaches a preset number; or the personality characteristics obtained by the personality characteristic model from analyzing the same behavioral and driving characteristics in the training data multiple times show little change.

[0115] In optional embodiments, the personality characteristic determination device may also use a random forest classification algorithm or a support vector machine (SVM) classification algorithm to train the model based on the training dataset to obtain the personality characteristic model. This application embodiment does not limit this.

[0116] S103. Generate a personality characteristic report of the driver based on the driver's personality characteristic information.

[0117] The personality trait determination device determines the corresponding explanatory information for the driver's personality trait information based on the driver's personality trait information and a first mapping relationship. The device then generates a personality trait report based on the personality trait information and the explanatory information. The explanatory information is used to interpret the meaning of the personality trait information, and the first mapping relationship includes the mapping relationship between the personality trait information and the explanatory information.

[0118] In an optional embodiment, the first mapping relationship includes multiple personality characteristic information and corresponding explanatory information. In the first mapping relationship, one personality characteristic information corresponds to one explanatory information. The personality characteristic determination device searches the first mapping relationship based on the driver's personality characteristic information to determine the explanatory information corresponding to the driver's personality characteristic information in the first mapping relationship.

[0119] In one example, the first mapping relationship is shown in Table 1 below:

[0120] Table 1

[0121] Personality trait information Explanation information Open information A Explanation of Information 1 Open information B Explanation of Information 2 Pleasantness Information A Explanation of Information 3 Pleasantness Information B Explanation of Information 4 Due diligence information A Explanation of information 5 Due diligence information B Explanation of Information 6 Neurotic Information A Explanation of Information 7 Neurotic Information B Explanation Message 8 Outward information A Explanation of Information 9 Outward information B Explanation Message 10 ...... ......

[0122] For example, the driver's personality characteristic information includes open information B. The personality characteristic determination device searches for the first mapping relationship shown in Table 1 based on "open information B" and determines that the explanatory information corresponding to the personality characteristic information is "explanatory information 2".

[0123] In optional embodiments, such as Figure 3 As shown, Figure 3 This is a schematic diagram of a personality trait determination method provided in an embodiment of this application. During the driving of the first vehicle, the personality trait determination device acquires the driver's motion characteristic information through a camera, the driver's voice characteristic information through a microphone, and the first vehicle's driving characteristic information through a T-box. The personality trait determination device inputs the driver's motion characteristic information, the driver's voice characteristic information, and the first vehicle's driving characteristic information into a personality trait model to determine the driver's personality trait information. The personality trait determination device generates a personality trait report for the driver based on the driver's personality trait information. In a specific embodiment, such as... Figure 4 As shown, Figure 4This is a schematic diagram of another personality trait determination method provided in this application embodiment. The personality trait determination device acquires driver motion data via a camera and determines the driver's motion characteristic information based on the motion data. The device also acquires driver voice data via a microphone and determines the driver's voice characteristic information based on the voice data. Furthermore, the device acquires driving data of a first vehicle via a T-box and determines the first vehicle's driving characteristic information based on the driving data. Finally, the device inputs the driver's motion characteristic information, the driver's voice characteristic information, and the first vehicle's driving characteristic information into a personality trait model to determine the driver's personality trait information and generates a personality trait report based on this information.

[0124] In one embodiment, the personality trait determination device includes a display screen on which the driver's personality trait report is displayed, and the user obtains the driver's personality trait report through the display screen. In another embodiment, the personality trait determination device includes a memory on which the driver's personality trait report is stored, and the user obtains the driver's personality trait report through the memory. In yet another embodiment, the personality trait determination device is communicatively connected to a printer, and the personality trait determination device sends the driver's personality trait determination report to the printer, and the user prints out the driver's personality trait report by operating the printer.

[0125] In summary, the personality trait determination method provided in this application involves a personality trait determination device acquiring driving characteristic information of a first vehicle and behavioral characteristic information of the driver of the first vehicle during driving. Based on the driver's behavioral characteristic information and the driving characteristic information of the first vehicle, the device determines the driver's personality trait information and generates a personality trait report based on this information. Compared to manually analyzing questionnaires to determine a driver's personality trait, this application uses a personality trait determination device to determine the driver's personality trait based on the driving characteristic information of the first vehicle and the driver's behavioral characteristic information during driving, which reduces the time required for determining the driver's personality trait and improves the efficiency of the process.

[0126] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0127] Please refer to Figure 5 The diagram illustrates a personality trait determination device 500 provided in an embodiment of this application. The personality trait determination device 500 is used to perform... Figure 1The embodiment shown provides a method for determining personality traits. For example... Figure 5 As shown, the personality trait determination 500 includes, but is not limited to, the first acquisition module 501, the determination module 502, and the generation module 503.

[0128] The first acquisition module 501 is used to acquire driving characteristic information of the first vehicle and behavioral characteristic information of the driver of the first vehicle during the driving process of the first vehicle. The behavioral characteristic information includes at least one of action characteristic information and voice characteristic information. The driving characteristic information is used to characterize the driving status of the first vehicle.

[0129] The determination module 502 is used to determine the driver's personality characteristic information based on behavioral characteristic information and driving characteristic information. The personality characteristic information is used to characterize the driver's personality characteristics.

[0130] The generation module 503 is used to generate a personality characteristic report of the driver based on the personality characteristic information.

[0131] Optionally, the determining module 502 is used to: determine the driver's personality characteristic information based on the behavioral characteristic information, the driving characteristic information, and the personality characteristic model, wherein the personality characteristic model is used to determine the personality characteristic information based on the behavioral characteristic information and the driving characteristic information.

[0132] Optionally, the personality trait determination device 500 also includes:

[0133] The second acquisition module 504 is used to acquire a training dataset, which includes multiple training data, each of which includes behavioral feature information, driving feature information and personality feature information.

[0134] Training module 505 is used to train the model based on the training dataset to obtain the personality feature model.

[0135] Optionally, the generation module 503 is used for:

[0136] Based on the personality trait information and the first mapping relationship, the explanatory information of the personality trait information is determined, wherein the first mapping relationship includes the mapping relationship between the personality trait information and the explanatory information;

[0137] The personality trait report is generated based on the personality trait information and the explanatory information.

[0138] Optionally, the first acquisition module 501 is used for:

[0139] The driving data of the first vehicle at multiple times is obtained, and the driving data at each of the multiple times is used to characterize the driving status of the first vehicle at each time.

[0140] Based on the driving data at multiple times, at least one driving time period and at least one driving distance corresponding to the at least one driving time period are determined. Each of the at least one driving distances is the driving distance of the first vehicle within the corresponding driving time period. The multiple times include the start time and the end time of each of the at least one driving time periods. Different driving time periods in the at least one driving time period do not overlap.

[0141] Based on the at least one driving distance, the at least one driving time period, and the driving data at the multiple times, the driving characteristic information of the first vehicle is determined.

[0142] Optionally, the at least one driving time period can be multiple driving time periods, and the at least one driving distance can be multiple driving distances corresponding one-to-one with the multiple driving time periods. The first acquisition module 501 is used for:

[0143] A target driving time period is determined from the at least one driving time period, wherein the target driving time period is longer than a preset driving time and / or the driving distance corresponding to the target driving time period is longer than a preset driving distance;

[0144] Based on the target travel time period, the travel distance corresponding to the target travel time period, and the travel data at multiple times, the travel characteristic information of the first vehicle is determined.

[0145] Optionally, the driving data includes at least one of the following: ignition status information, fuel level, engine speed, accelerator pedal opening, brake pedal opening, longitudinal acceleration, lateral acceleration, GPS direction, driving speed, ABS warning status information, and cumulative mileage.

[0146] Driving characteristic information includes at least one of the following: average driving speed, maximum driving speed, fuel consumption, number of rapid accelerations, number of rapid decelerations, number of sharp turns, number of speeding incidents, number of ABS warnings, maximum braking force, start-up time, and number of quick starts.

[0147] Optionally, the motion feature information includes at least one of head sway amplitude, eye opening and closing distance, and mouth opening and closing distance. The first acquisition module 501 is used for:

[0148] Acquire the driver's driving image, which is an image of the driver captured by a camera while the driver is driving the first vehicle;

[0149] Determine at least one of the following based on the driver's driving image: the driver's head sway amplitude, the driver's eye opening distance, and the driver's mouth opening distance.

[0150] Optionally, the speech feature information is information about the driver's speech signal, and the speech feature information includes at least one of the following: pitch, intensity, formants, effective speech length, speech rate, and number of pauses.

[0151] In summary, the technical solution provided in this application involves a personality characteristic determination device that, after acquiring the driving characteristic information of a first vehicle and the behavioral characteristic information of the driver of the first vehicle during the driving process, determines the driver's personality characteristic information based on the driver's behavioral characteristic information and the driving characteristic information of the first vehicle, and generates a personality characteristic report for the driver based on the driver's personality characteristic information. Compared to manually analyzing questionnaires to determine the driver's personality characteristics, this application uses a personality characteristic determination device to determine the driver's personality characteristics based on the driving characteristic information of the first vehicle and the behavioral characteristic information of the driver of the first vehicle during the driving process, which can reduce the time spent in determining the driver's personality characteristics and improve the efficiency of determining the driver's personality characteristics.

[0152] This application provides a personality trait determination device, including a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program stored in the memory so that the personality trait determination device performs the personality trait determination method as provided in the above embodiments.

[0153] The device for determining these personality traits can be a vehicle or a computer device.

[0154] As an example, please refer to Figure 6 The diagram illustrates a personality trait determination device 600 provided in an embodiment of this application. Typically, the personality trait determination device 600 includes a processor 601 and a memory 602.

[0155] Processor 601 may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. Processor 601 may be implemented using at least one hardware form selected from digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). Processor 601 may include, but is not limited to, a central processing unit (CPU). In some embodiments, processor 601 may integrate a graphics processing unit (GPU), which is responsible for rendering and drawing the content to be displayed on the screen. Processor 601 may also include an artificial intelligence (AI) processor to handle computational operations related to machine learning.

[0156] The memory 602 may include one or more computer-readable storage media, which may be non-transitory. The memory 602 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 602 are used to store at least one instruction, which is executed by the processor 601 to implement the personality characteristic determination method provided in the embodiments of this application.

[0157] In some embodiments, the personality characteristic determination device 600 may also optionally include: a peripheral device interface 603 and at least one peripheral device. The processor 601, memory 602, and peripheral device interface 603 can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface 603 via a bus, signal line, or circuit board. The peripheral device may include at least one of: a radio frequency circuit 604, a touch display screen 605, a camera 606, an audio circuit 607, a positioning component 608, and a power supply 609.

[0158] Peripheral interface 603 can be used to connect at least one input / output (I / O) related peripheral device to processor 601 and memory 602. In some embodiments, processor 601, memory 602 and peripheral interface 603 are integrated on the same chip or circuit board; in some embodiments, any one or two of processor 601, memory 602 and peripheral interface 603 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0159] The radio frequency (RF) circuit 604 is used to receive and transmit radio frequency (RF) signals, also known as electromagnetic signals. The RF circuit 604 communicates with communication networks and other communication devices via electromagnetic signals. The RF circuit 604 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electrical signals. Optionally, the RF circuit 604 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, etc. The RF circuit 604 can communicate with other devices through at least one wireless communication protocol. This wireless communication protocol includes, but is not limited to: the World Wide Web, metropolitan area networks, intranets, various generations of mobile communication networks (2G, 3G, 4G, and 5G), and wireless local area networks; the embodiments of this application do not limit this to specific protocols.

[0160] Display screen 605 is used to display a user interface (UI). The UI may include graphics, text, icons, video, and any combination thereof. When display screen 605 is a touch display screen, it also has the ability to collect touch signals on or above its surface. These touch signals can be input as control signals to processor 601 for processing. In this case, display screen 605 can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, display screen 605 may be a flexible display screen. Furthermore, display screen 605 may be configured as a non-rectangular, irregular shape, i.e., a non-rectangular screen. Display screen 605 may be a liquid crystal display (LCD), an organic light-emitting diode (OLED) display screen, etc.

[0161] The camera component 606 is used to capture images or videos.

[0162] The audio circuit 607 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, converting them into electrical signals that are input to the processor 601 for processing, or to the radio frequency circuit 604 for voice communication. For stereo sound acquisition or noise reduction purposes, multiple microphones may be used, positioned in different parts of the vehicle. The microphone can also be an array microphone or an omnidirectional microphone. The speaker is used to convert the electrical signals from the processor 601 or the radio frequency circuit 604 into sound waves. The speaker can be a traditional film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can convert electrical signals not only into audible sound waves but also into inaudible sound waves for purposes such as distance measurement.

[0163] The positioning component 608 is used to locate the geographic location of the personality characteristic determination device 600 in order to enable navigation or location-based services (LBS). The positioning component 608 can be a positioning component based on the global positioning system (GPS), BeiDou system, or Galileo system.

[0164] Power supply 609 provides power to the various components in personality trait determination device 600. Power supply 609 can be alternating current, direct current, a disposable battery, or a rechargeable battery. When power supply 609 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery that is charged via a wired connection, while a wireless rechargeable battery is a battery that is charged via a wireless coil.

[0165] In some embodiments, the personality characteristic determination device 600 further includes one or more sensors 610. The one or more sensors 610 include, but are not limited to: a fingerprint sensor 611, an optical sensor 612, a proximity sensor 613, a brake pedal sensor 614, and an accelerator pedal sensor 615.

[0166] The fingerprint sensor 611 is used to collect the user's fingerprint. The processor 601 identifies the user's identity based on the fingerprint collected by the fingerprint sensor 611, or the fingerprint sensor 611 identifies the user's identity based on the collected fingerprint. When the user's identity is identified as trusted, the processor 601 authorizes the user to perform relevant sensitive operations, including unlocking the screen, viewing encrypted information, downloading software, making payments, and changing settings.

[0167] The optical sensor 612 is used to collect ambient light intensity. In one embodiment, the processor 601 can control the display brightness of the touch screen 605 based on the ambient light intensity collected by the optical sensor 612. Specifically, when the ambient light intensity is high, the display brightness of the touch screen 605 is increased; when the ambient light intensity is low, the display brightness of the touch screen 605 is decreased. In another embodiment, the processor 601 can also dynamically adjust the shooting parameters of the camera assembly 606 based on the ambient light intensity collected by the optical sensor 612.

[0168] The proximity sensor 613, also known as a distance sensor, is typically installed on the front panel of the display screen 606 of the personality characteristic determination device 600. The proximity sensor 613 is used to detect the distance between the user and the display screen 605. In one embodiment, when the proximity sensor 614 detects that the distance between the user and the display screen 606 is gradually decreasing, the processor 601 controls the touch display screen 605 to switch from a screen-on state to a screen-off state; when the proximity sensor 616 detects that the distance between the user and the display screen 605 is gradually increasing, the processor 601 controls the touch display screen 605 to switch from a screen-off state to a screen-on state.

[0169] When the personality characteristic determination device 600 is a vehicle, the personality characteristic determination device 600 also includes a brake pedal sensor 614 and an accelerator pedal sensor 615. The brake pedal sensor 614 is used to collect the opening of the vehicle's brake pedal, and the accelerator pedal sensor 615 is used to collect the opening of the vehicle's accelerator pedal.

[0170] Those skilled in the art will understand that Figure 6 The structure shown does not constitute a limitation on the personality characteristic determination device 600. The personality characteristic determination device 600 may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0171] This application provides a vehicle that includes the personality characteristic determination device 500 or personality characteristic determination device 600 provided in the above embodiments.

[0172] This application provides a computer-readable storage medium storing a computer program that, when executed (e.g., by a personality trait determination device, one or more processors, etc.), implements all or part of the steps of the personality trait determination method provided in the above embodiments.

[0173] This application provides a computer program product, which includes a program or code. When the program or code is executed (e.g., by a personality trait determination device, one or more processors, etc.), it implements all or part of the steps of the personality trait determination method provided in the above embodiments.

[0174] It should be understood that the term "at least one" in this application refers to one or more, and "multiple" refers to two or more. The term "and / or" in this application is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Furthermore, for clarity, the terms "first," "second," and "third" are used in this application to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first," "second," and "third" do not limit the quantity or order of execution.

[0175] The method embodiments and device embodiments provided in this application can be referenced interchangeably, and this application does not limit them. The order of operations in the method embodiments provided in this application can be appropriately adjusted, and operations can be added or removed as needed. Any variations that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of this application, and therefore will not be elaborated further.

[0176] In the corresponding embodiments provided in this application, it should be understood that the disclosed devices, etc., can be implemented by other configurations. For example, the device embodiments described above are merely illustrative. For instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0177] The modules described as separate components may or may not be physically separate, and the components described as modules may or may not be physical modules. Some or all of the modules can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0178] The above description is merely an exemplary embodiment of this application, but the scope of protection of this application is not limited thereto. Any equivalent modifications or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for determining personality traits, characterized in that, The method includes: The driving data of the first vehicle at multiple times is obtained, and the driving data at each of the multiple times is used to characterize the driving status of the first vehicle at each time. Based on the driving data at the multiple times, at least one driving time period and at least one driving distance corresponding to the at least one driving time period are determined. Each driving distance in the at least one driving distance is the driving distance of the first vehicle in the corresponding driving time period. The multiple times include the start time and the end time of each driving time period in the at least one driving time period. Different driving time periods in the at least one driving time period do not overlap. Based on the at least one driving distance, the at least one driving period, and the driving data at the multiple times, the driving characteristic information of the first vehicle is determined, and the driving characteristic information is used to characterize the driving status of the first vehicle. The behavioral feature information of the driver of the first vehicle during the process of driving the first vehicle is obtained, and the behavioral feature information includes at least one of action feature information and voice feature information; The driver's personality characteristics are determined based on the behavioral characteristic information, the driving characteristic information, and the personality characteristic model, wherein the personality characteristic model is used to determine the personality characteristics based on the behavioral characteristic information and the driving characteristic information, and the personality characteristic information is used to characterize the driver's personality characteristics. Based on the personality trait information and the first mapping relationship, the explanatory information of the personality trait information is determined, wherein the first mapping relationship includes the mapping relationship between the personality trait information and the explanatory information; A personality trait report of the driver is generated based on the personality trait information and the explanatory information.

2. The method according to claim 1, characterized in that, The method further includes: Obtain a training dataset, which includes multiple training data sets, each of which includes behavioral feature information, driving feature information, and personality feature information; The personality trait model is obtained by training the model based on the training dataset.

3. A device for determining personality traits, characterized in that, The device includes: The first acquisition module is used to acquire driving data of the first vehicle at multiple times, wherein the driving data at each of the multiple times is used to characterize the driving status of the first vehicle at each time. The first acquisition module is used to determine at least one driving time period and at least one driving distance corresponding to the at least one driving time period based on the driving data at the plurality of times. Each driving distance in the at least one driving distance is the driving distance of the first vehicle in the corresponding driving time period. The plurality of times includes the start time and the end time of each driving time period in the at least one driving time period. Different driving time periods in the at least one driving time period do not overlap. The first acquisition module is used to determine the driving characteristic information of the first vehicle based on the at least one driving distance, the at least one driving time period, and the driving data at the multiple times, wherein the driving characteristic information is used to characterize the driving status of the first vehicle. The first acquisition module is used to acquire behavioral feature information of the driver of the first vehicle during the process of driving the first vehicle, and the behavioral feature information includes at least one of action feature information and voice feature information. The determination module is used to determine the driver's personality characteristic information based on the behavioral characteristic information, the driving characteristic information, and the personality characteristic model, wherein the personality characteristic model is used to determine the personality characteristic information based on the behavioral characteristic information and the driving characteristic information, and the personality characteristic information is used to characterize the driver's personality characteristics; A generation module is used to determine interpretation information of the personality feature information based on the personality feature information and a first mapping relationship, wherein the first mapping relationship includes a mapping relationship between the personality feature information and the interpretation information; The generation module is used to generate a personality characteristic report of the driver based on the personality characteristic information and the interpretation information.

4. The apparatus according to claim 3, characterized in that, The device further includes: The second acquisition module is used to acquire a training dataset, which includes multiple training data sets, each of which includes behavioral feature information, driving feature information, and personality feature information. The training module is used to train the model based on the training dataset to obtain the personality feature model.

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