Teaching material generating device and teaching material generating method

Abstract

To provide persons under education with educational videos with high educational effect.SOLUTION: A teaching material generation device comprises a selection unit and a generation unit. The generation unit selects a similar subject having attribute information similar to that of a driver. The generation unit generates a comparison video obtained by comparing a driving video of the driver and a driving video of the similar subject selected by the selection unit as a teaching material video for the driver.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a teaching material generation device. Place and a method for generating teaching materials. [Background technology]

[0002] Conventionally, images captured by an on-board camera when a vehicle brakes suddenly, turns sharply, etc. have been used as educational materials for safe driving. For example, a technology has been disclosed for such educational materials that combines images captured by multiple cameras installed in a driving school to allow a specific event to be recognized from each of the camera's viewpoints (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2015-219497 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the conventional technology has room for improvement in terms of providing educational video with high educational effectiveness to educational subjects.

[0005] The present invention has been made in view of the above, and aims to provide a teaching material generation device, a teaching material generation system, and a teaching material generation method that can provide teaching materials with high educational effectiveness to students. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the object, the teaching material generation device according to the present invention includes a selection unit and a generation unit. The selection unit selects a similar target person having attribute information similar to that of a training target driver. The generation unit generates a comparison video as a teaching material video for the driver by comparing a driving video of the driver with a driving video of the similar target person selected by the selection unit. [Effects of the Invention]

[0007] According to the present invention, educational video with high educational effect can be provided to the education target. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing an outline of a teaching material generation system. [Figure 2] FIG. 2 is a block diagram of the teaching material generation device. [Figure 3] FIG. 3 is a diagram showing an example of information stored in the video database. [Figure 4] FIG. 4 is a diagram showing an example of information stored in the driver database. [Figure 5] FIG. 5 is a diagram showing an example of information stored in the teaching material database. [Figure 6] FIG. 6 is a flowchart showing the processing procedure executed by the teaching material generation device. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, embodiments of a teaching material generation device, a teaching material generation system, and a teaching material generation method disclosed in the present application will be described in detail with reference to the accompanying drawings. Note that the present invention is not limited to the following embodiments.

[0010] First, an outline of a teaching material generation device, a teaching material generation system, and a teaching material generation method according to an embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an outline of a teaching material generation system.

[0011] The teaching material generation system S according to the embodiment is a system that generates a teaching material video related to traffic safety using driving videos collected from each vehicle, for example. The teaching material generation system S collects driving videos from, for example, transportation companies or commercial vehicles, and generates a teaching material video for in-house traffic safety education.

[0012] 1, for example, the teaching material generation system S includes a teaching material generation device 1, an in-vehicle device 50, and a terminal device 100. The teaching material generation system S also includes a video database and a driver database. The video database is a database that stores driving videos collected from each vehicle, and the driver database is a database that stores information about the driver of each vehicle.

[0013] The in-vehicle device 50 mounted on each vehicle is, for example, a drive recorder equipped with a communication function, and captures driving video while the vehicle is traveling. Here, the driving video is, for example, video of the area in front of the vehicle, but also includes video of the area around the vehicle and video of the interior of the vehicle (i.e., the driver) while traveling.

[0014] The terminal device 100 is a display device with a communication function that is owned by each driver. In the example shown in Fig. 1, the terminal device 100 is a smartphone, but the terminal device 100 may also be a notebook computer, a desktop computer, or the like.

[0015] Incidentally, there are some traffic safety initiatives that use dangerous footage, such as traffic violation footage and near miss footage, captured by dashcams installed in sales vehicles as part of in-house training at companies, as educational materials. However, simply using videos of traffic violations and near misses as educational materials does not necessarily improve each individual's awareness of safe driving. One of the reasons for this is that drivers are unable to empathize with the videos shown as educational materials and feel that the videos are something that does not concern them.

[0016] The teaching material generation device 1 according to the embodiment focuses on these points and generates teaching materials that are highly effective in educating drivers by focusing on generating teaching materials that are highly relatable. Furthermore, in order to enhance the educational effect, the teaching material generation device 1 according to the embodiment utilizes e-learning, for example, by making it possible for the teaching material video to be viewed on the terminal device 100 of each driver.

[0017] Specifically, as shown in Fig. 1, the teaching material generation device 1 first acquires driving videos from the in-vehicle devices 50 (step S1). As shown in Fig. 1, the teaching material generation device 1 has a video database, and registers driving videos acquired from each in-vehicle device 50 in the video database.

[0018] Next, the teaching material generation device 1 refers to the driver database and selects similar drivers whose attribute information is similar to that of the driver to be trained (hereinafter simply referred to as the trainee) (step S2). Here, the attribute information includes, for example, driving attributes relating to the driving tendencies of each driver, such as the driving characteristics and personality of each driver, and area attributes relating to the route and area to be traveled.

[0019] Therefore, similarity of attributes with the trainee means similarity of information on either driving attributes or area attributes. Subsequently, the learning material generation device 1 generates learning material video It for the trainee (step S3).

[0020] 1, the teaching material video It is a comparison video obtained by comparing the driving video Im of the trainee with the driving video Io of a similar trainee. The teaching material generation device 1 also transmits the generated teaching material video It to the terminal device 100 of the trainee (step S4).

[0021] This allows the student to view the educational video on his / her own terminal device 100. That is, the student can view the educational video without being restricted by time or place.

[0022] 1, the driving video Im and the driving video Io each include, from the left side of the page, a video from a drive recorder, a video of the driver, and a bird's-eye view of the vehicle. The bird's-eye view image is generated, for example, based on vehicle position information, etc.

[0023] For example, when selecting a driver with similar driving tendencies as a similar subject, the training subject can compare his or her own driving with that of other drivers with similar confidence and driving tendencies. Here, "similar driving tendencies" refers to a match or similarity in some driving tendencies, such as infrequent braking, frequent sudden braking, frequent sudden acceleration, or frequent sudden steering, based on vehicle operation information. Furthermore, "similar personality" refers to a match or similarity in some personality, such as a tendency to panic based on analysis of usual driving, or a laid-back personality that tends to start driving at the last minute based on travel schedule information.

[0024] Furthermore, for example, when selecting a driver with similar area attributes as a similar subject, the trainee can compare his or her own driving with the driving of other drivers on the route he or she usually drives. Furthermore, similar area attributes mean, for example, that the driving areas are the same or within a certain distance.

[0025] In this way, the teaching material generation device 1 generates teaching material videos using driving videos of similar subjects who have similar attribute information to the training subject. This allows the training subject to use videos that are more familiar to them as teaching materials, which is expected to improve the effectiveness of education.

[0026] Therefore, the teaching material generation device 1 according to the embodiment can provide teaching material videos with high educational effectiveness to the education recipients.

[0027] Next, an example of the configuration of the teaching material generation device 1 according to the embodiment will be described with reference to Fig. 2. Fig. 2 is a block diagram of the teaching material generation device 1. As shown in Fig. 2, the teaching material generation device 1 includes a communication unit 10, a storage unit 20, and a control unit 30. The communication unit 10 is realized, for example, by a network interface card (NIC). The communication unit 10 is connected to a predetermined communication network so as to be able to perform two-way communication, and transmits and receives information to and from an in-vehicle device 50, a terminal device 100, etc.

[0028] The storage unit 20 is a storage unit configured with a storage device such as a non-volatile memory, a data flash, a hard disk drive, etc. As shown in Fig. 2, the storage unit 20 has a video database 21, a driver database 22, and a learning material database 23.

[0029] The video database 21 is a database that stores, for example, driving videos received from each in-vehicle device 50. Fig. 3 is a diagram showing an example of information stored in the video database 21. As shown in Fig. 3, for example, the video database 21 stores information on items such as "video ID," "shooting date / shooting area," "driver ID," and "video type" in association with one another.

[0030] The "video ID" is an identifier for identifying the driving video stored in the video database 21. The "shooting date and time / shooting area" is information about the shooting date and time and shooting area of ​​the corresponding driving video. The shooting area may be, for example, a city, town, village, prefecture, or any other arbitrary unit.

[0031] The "driver ID" is an identifier for identifying the driver at the time the corresponding driving video was captured. Note that if a specific driver drives each vehicle, the driver ID may be used as the vehicle ID.

[0032] "Video type" is information indicating the type of corresponding driving video. In the example of Fig. 3, "near miss" indicates driving video at the time of a near miss, and "exemplary" indicates driving video during exemplary driving. Note that the video type is not limited to the above example and may be other types.

[0033] Returning to the explanation of Fig. 2, the following will explain the driver database 22. The driver database 22 is a database that stores various information related to drivers. Fig. 4 is a diagram showing an example of information stored in the driver database.

[0034] 4, the driver database 22 stores information on items such as "driver ID," "driving attributes," and "area attributes" in association with each other. As described above, the "driver ID" is an identifier that identifies the driver.

[0035] "Driving attributes" indicate attributes related to the driver's driving, and include information such as personality, driving tendencies, and driving skills. "Area attributes" indicate attributes related to the driving area in which the corresponding driver drives. Area attributes include, for example, information about frequently driven routes and frequently driven regions.

[0036] Returning to the explanation of Fig. 2, the teaching material database 23 will now be described. The teaching material database 23 is a database that stores information related to teaching material videos generated for each training target. Fig. 5 is a diagram showing an example of information stored in the teaching material database 23. As shown in Fig. 5, the teaching material database 23 stores information on items such as "driver ID," "teaching material content," "evaluation," and "characteristics" in association with one another.

[0037] "Driver ID" is an identifier for identifying a driver, and is used here to identify the training recipient. "Learning material content" indicates the content of the training material video provided to the corresponding training recipient. The training material content stores, for example, information about similar subjects (described later) and information about the display format (how the comparison video) provided as the training video.

[0038] "Evaluation" refers to the student's evaluation of the provided educational material content. The evaluation here refers to, for example, the student's evaluation of the educational material video after viewing the educational material video, but it may also be an evaluation of the educational material video by the educational material generation system S based on the degree of improvement in the student's driving before and after viewing the educational material video.

[0039] "Features" indicates the characteristics of educational video that have a high (or low) educational effect for each educational target. In other words, information about characteristics, such as what kind of similar target should be selected for a specific educational target and how the comparison video should be presented to increase the educational effect, is stored in the feature item. Note that the features are derived, for example, by machine learning using the content and evaluation of the educational material.

[0040] Returning to the explanation of Fig. 2, the control unit 30 will now be described. The control unit 30 includes an acquisition unit 31, an evaluation unit 32, a selection unit 33, a generation unit 34, and a distribution unit 35, and includes a computer and various circuits having, for example, a CPU (Central Processing Unit), ROM (Read Only Memory), RAM (Random Access Memory), a hard disk drive, input / output ports, etc.

[0041] The CPU of the computer functions as the acquisition unit 31, evaluation unit 32, selection unit 33, generation unit 34, and distribution unit 35 of the control unit 30, for example, by reading and executing a program stored in the ROM.

[0042] In addition, at least some or all of the acquisition unit 31, evaluation unit 32, selection unit 33, generation unit 34 and distribution unit 35 of the control unit 30 can be configured using hardware such as an ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate Array).

[0043] The acquisition unit 31 acquires various types of information from each in-vehicle device 50 and the terminal device 100 via the communication unit 10. For example, the acquisition unit 31 acquires driving video and various types of information linked to the driving video from each in-vehicle device 50. The various types of information here include position information, speed information, steering angle information, braking information, etc.

[0044] For example, the acquisition unit 31 may acquire only dangerous footage from each in-vehicle device 50, such as near-miss footage, which is driving footage linked to sudden steering angles, sudden braking, etc., or accident footage, which is footage of an actual accident.

[0045] Furthermore, the acquisition unit 31 acquires, for example, evaluation information on the educational video provided from the terminal device 100. For example, in the educational material generation system S, when an educational material video is provided, a message such as "Was this educational material useful?" is displayed, and an evaluation is received from the education recipient, and the acquisition unit 31 acquires information related to the received evaluation as evaluation information.

[0046] The evaluation unit 32 evaluates the attribute information of each driver. For example, the evaluation unit 32 evaluates the driving attributes of each driver based on driving video and various information linked to the driving video. The evaluation unit 32 also evaluates area attributes based on information related to the driving location, for example. The evaluation unit 32 also writes the evaluation results of the attribute information into the driver database 22.

[0047] The selection unit 33 selects a similar target person whose attribute information is similar to that of the training target person. For example, the selection unit 33 refers to the driver database 22 and selects a similar target person whose attribute information is at least partially similar to or matches that of the training target person.

[0048] In this case, the selection unit 33 may refer to the educational material database 23 and, for example, preferentially select similar subjects who tend to have a high educational effect on the education target. Furthermore, for example, when selecting similar subjects with similar area attributes, the selection unit 33 may preferentially select similar subjects who tend to drive more recklessly than the education target or similar subjects who tend to drive more safely. This is because, for example, in educational material videos, similar subjects who tend to drive more recklessly will be bad examples, and comparison subjects who tend to drive more safely will be good examples.

[0049] Furthermore, when the selection unit 33 selects the similar target person, the selection unit 33 associates information about the training target person with information about the similar target person and passes the information to the generation unit 34.

[0050] The generation unit 34 generates, as a teaching material video for the training target, a comparison video obtained by comparing the driving video of the training target with the driving video of the similar target selected by the selection unit 33. Specifically, for example, the generation unit 34 refers to the video database 21 and extracts the driving video of the training target and the driving video of the similar target.

[0051] For example, the generation unit 34 extracts driving footage to be used in the educational video from the driving footage of the training target person on that day, and generates the educational video by combining the extracted driving footage with driving footage of a similar target person filmed on a given date and time. For example, the generation unit 34 may generate the educational video by using dangerous driving footage as the driving footage of the similar target person. This, for example, can provide the training target person with a memorable educational video, giving them an opportunity to improve their own driving habits. Furthermore, using the driving footage of the training target person on that day allows them to reflect on their own driving while their memory is still fresh, thereby improving the effectiveness of the education. As a more specific example, if both the training target person and the similar target person have impatient or angry personalities, the generation unit 34 generates an educational video for the training target person that includes dangerous footage of the similar target person causing an accident. In this case, the training target person can be made to feel that if they do not improve their driving habits, they will have an accident like the one in the educational video.

[0052] Furthermore, when generating the educational video, the generating unit 34 may generate the educational video in which the focus points to be focused on by the trainee are highlighted. In this case, for example, if the difference between the trainee's own driving speed and the driving speed of a similar trainee should be emphasized, a speedometer or speed display may be superimposed. For example, if the timing of braking should be emphasized, a brake meter may be superimposed.

[0053] In this way, by using highlighting, it is possible to help the training recipient properly recognize the points they should pay attention to, i.e., the differences between their own driving and that of similar subjects, which is expected to further improve the effectiveness of the education.

[0054] The distribution unit 35 distributes the educational video generated by the generation unit 34 to the terminal device 100 of the student. Note that distribution here refers to making the educational video accessible to the student. Therefore, distribution also includes, for example, distributing a URL indicating the location of the educational video to the terminal device 100 or pasting the educational video on the student's membership page.

[0055] Next, a processing procedure executed by the teaching material generation device 1 according to the embodiment will be described with reference to Fig. 6. Fig. 6 is a flowchart showing the processing procedure executed by the teaching material generation device 1. The processing procedure shown below is executed by the control unit 30 at a predetermined cycle.

[0056] 6, the teaching material generation device 1 first selects a similar subject whose attribute information is similar to that of the education target (step S101). Next, the teaching material generation device 1 generates a teaching material video based on the selected similar subject (step S102) and distributes the generated teaching material video (step S103).

[0057] Thereafter, the teaching material generation device 1 acquires feedback information for the teaching material video (step S104), and updates the teaching material database 23 based on the acquired feed information (step S105), and then ends the process.

[0058] As described above, the teaching material generation device 1 according to the embodiment includes the selection unit 33 and the generation unit 34. The selection unit 33 selects a similar subject who has attribute information similar to that of the driver. The generation unit 34 generates a comparison video as a teaching material video for the driver by comparing a driving video of the driver with a driving video of the similar subject selected by the selection unit 33. Therefore, the teaching material generation device 1 according to the embodiment can provide a teaching material video with a high educational effect to the training target.

[0059] In the above-described embodiment, for example, if the driving video is used as is as a teaching material, there is a risk of violating the privacy of similar subjects or people appearing in the driving video. Therefore, predetermined image processing may be performed on the driving video. For example, as image processing, privacy can be protected by converting people and cars appearing in the driving video into illustrations or abstracting them.

[0060] Further advantages and modifications will readily occur to those skilled in the art. Therefore, the invention in its broader aspects is not limited to the specific details and representative embodiments shown and described above. Accordingly, various modifications may be made without departing from the spirit or scope of the general inventive concept as defined by the appended claims and their equivalents. [Explanation of symbols]

[0061] 1 Teaching material generation device 31 Acquisition Department 32 Evaluation Section 33 Selection section 34 Generation part 35 Distribution Department 50 Onboard equipment

Claims

1. a control unit that generates a comparison video as a learning video by comparing a driving video of the driver with a dangerous video of a driving of a similar subject having attribute information similar to that of the driver; Teaching material generation device.

2. The attribute information includes information on driving attributes related to driving tendencies or information on area attributes related to driving areas. The teaching material generating device according to claim 1.

3. The control unit generating the educational video in which the gaze points that the driver should gaze at are highlighted; The teaching material generating device according to claim 1.

4. The control unit On the day when the driver drives, the educational video is created and distributed to the terminal device held by the driver. The teaching material generating device according to claim 1.

5. The control unit On the day when the driver drives, the educational video is created and the educational video is made accessible from a terminal device owned by the driver. The teaching material generating device according to claim 1.

6. A computer-implemented teaching material generation method, Select similar targets with similar attribute information to the driver, Extracting dangerous driving images of the similar subject; generating a comparison video as a learning material video by comparing a driving video of the driver with a dangerous video of the driving of the similar subject; How to generate teaching materials.

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