Driving data display device, driving data display method, and program

Abstract

The system appropriately represents driving data that changes uniquely for each speed range. [Solution] The CPU 11 of the driving data display device 1 acquires race data 132 (speed information during the user's driving, and at least one driving parameter (driving data) correlated with the speed information), derives a linear regression line (for example, linear regression lines L1, L2, L3; see Figure 3) that shows the relationship between the speed information and the driving parameter (driving data) included in each predetermined speed range, and displays the slope of the linear regression line on the display unit 15 as an index indicating the speed dependence of the driving parameter (driving data).

Description

Technical Field

[0001] The present invention relates to a travel data display device, a travel data display method, and a program.

Background Art

[0002] Conventionally, a regression line is obtained from each scatter diagram based on speed data and other various travel data (running parameters such as pitch, stride, vertical movement, etc.), and the value of each travel data is converted into a value obtained by dividing it by the value on the regression line corresponding to the reference value of the speed data, thereby objectively evaluating the influence of each travel data on speed and the degree of influence on speed between each travel data. A method of expressing travel data has been disclosed (see Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the method disclosed in Patent Document 1 above, each travel data has not been evaluated for each speed range, and there is a problem that each travel data that changes uniquely for each speed range cannot be fully expressed.

[0005] The present invention has been made in view of such problems, and an object thereof is to suitably express travel data that changes uniquely for each speed range.

Means for Solving the Problems

[0006] To solve the above problems, the driving data display device according to the present invention comprises a display unit and a control unit, wherein the control unit acquires speed information of the user's driving and at least one driving parameter correlated with the speed information, derives a linear regression line showing the relationship between the speed information and the driving parameter included in each predetermined speed range, and displays the slope of the linear regression line on the display unit as an index indicating the speed dependence of the driving parameter. [Effects of the Invention]

[0007] According to the present invention, driving data that changes uniquely for each speed range can be suitably represented. [Brief explanation of the drawing]

[0008] [Figure 1] This block diagram shows the functional configuration of the driving data display device according to this embodiment. [Figure 2] This is a flowchart showing the process for displaying driving data. [Figure 3] This is a scatter plot showing the relationship between pitch data and velocity information. [Figure 4] This figure shows an example of a graph illustrating the time-dependent change in the slope of the first regression line (dependence on pitch velocity). [Figure 5] This figure shows an example of a graph where the horizontal axis represents distance (distance traveled) and the vertical axis represents the slope of the first regression line (dependence of pitch on speed). [Figure 6] This graph displays a linear regression line showing the relationship between vertical movement data and velocity information. [Figure 7] This graph displays a linear regression line showing the relationship between stride data and velocity information. [Figure 8] This graph displays a linear regression line showing the relationship between vertical movement data and velocity information. [Figure 9] This graph displays a linear regression line showing the relationship between pitch data and velocity information. [Figure 10]This figure shows an example of a graph where the horizontal axis represents distance (distance traveled) and the vertical axis represents the slope of the first regression line (dependence of stride on speed). [Figure 11] This figure shows an example of a graph with distance (running distance) on the horizontal axis and correlation coefficient (stride-velocity correlation) on the vertical axis. [Modes for carrying out the invention]

[0009] Embodiments of the present invention will be described in detail below with reference to the attached drawings. Note that the present invention is not limited to the illustrated examples. As shown in Figure 1, the driving data display device 1 comprises a CPU (Central Processing Unit) 11, a RAM (Random Access Memory) 12, a storage unit 13, an operation unit 14, a display unit 15, and a communication unit 16. Furthermore, each part of the driving data display device 1 is connected via a bus 17.

[0010] The CPU 11 controls each part of the driving data display device 1. The CPU 11 reads a specified program from among the system programs and application programs stored in the memory unit 13, loads it into the work area of ​​the RAM 12, and executes various processes according to the program. The RAM 12 is, for example, a volatile memory and has a work area for temporarily storing various programs and data read by the CPU 11. The memory unit 13 is, for example, composed of an HDD (Hard Disk Drive), SSD (Solid State Drive), etc., and is a memory unit that can write and read data and programs. The memory unit 13 also stores programs 131, race data 132, etc.

[0011] Program 131 includes the various system programs and application programs described above, which are executed by the CPU 11. Race data 132 is a set of multiple types of running data (for example, data such as speed, pitch, stride, vertical oscillation, ground contact time, and hip rotation angle (pitch, yaw, roll) (running parameters)) that indicate user-specific running characteristics obtained when running a predetermined distance (for example, 10,000 meters). This running data is, for example, data acquired (measured) at regular intervals (distance interval or time interval) during a race. Race data 132 also includes average speed data when each user achieves their best record. In this invention, the method of acquiring the running data is not limited. Furthermore, the race is not limited to one in which multiple competitors run simultaneously, but may also be one in which a user runs alone, and may not be a so-called formal competition, but may also be a run during practice, etc. Furthermore, in the above example, the race was a 10,000-meter track and field race, but the race could also be a sprint or marathon, or even a non-track and field event such as a bicycle race, speed skating, or swimming. In this invention, these are collectively referred to as a race.

[0012] The operation unit 14 includes, for example, a key input unit such as a keyboard and a pointing device such as a mouse. The operation unit 14 also receives key input and position input and outputs the operation information to the CPU 11. The display unit 15 is composed of, for example, an LCD (Liquid Crystal Display) or an organic EL (Electro Luminescence) display. The display unit 15 also displays various screens according to the instructions of the display signals input from the CPU 11. The communication unit 16 is composed of a network card or the like and is connected to a communication network to communicate with devices on the communication network.

[0013] Next, with reference to Figure 2, the driving data display process performed by the driving data display device 1 will be explained. The driving data display process is executed by the CPU 11 working in cooperation with the program 131 (driving data display program) which is read from the storage unit 13 and appropriately loaded into the RAM 12.

[0014] As shown in Figure 2, first, the CPU 11 receives a request from the user via the operation unit 14 to specify the race data to be displayed from the race data 132 stored in the storage unit 13 (step S1). Here, in step S1, it is possible to specify a single race data, a portion of a race data that is limited to a certain running section or running time, or to specify multiple race data.

[0015] Next, the CPU 11 divides the race data specified in step S1 for each predetermined speed range (step S2). For example, as shown in FIG. 3, in a scatter diagram showing the relationship between pitch data (travel parameter), which is race data, and speed information, the pitch data is divided for each predetermined speed range. Here, in the scatter diagram, the horizontal axis is speed information and the vertical axis is pitch data (travel parameter). The black circles on the scatter diagram represent the pitch data corresponding to the measured speeds. The speed ranges are assumed to be divided into three regions: a low speed range (for example, less than 80 m / min), a medium speed range (for example, 80 m / min or more and less than 160 m / min), and a high speed range (for example, 160 m / min or more), but this is merely an example. For example, the speed ranges may be divided into two regions or four or more regions. Also, the speed ranges do not necessarily need to be divided at equal intervals and may be divided in consideration of the speed range in the user's travel, the race space, etc. Further, based on information (setting information) for setting speed ranges input in advance based on user operations via the operation unit 14, for example, each of a low speed range (for example, less than 50 m / min), a medium speed range (for example, 50 m / min or more and less than 150 m / min), and a high speed range (for example, 160 m / min or more) may be set, or the number of regions of the speed ranges (for example, three regions of a low speed range, a medium speed range, and a high speed range) may be set. Also, the speed ranges of each speed range may be set based on the speed information included in the race data specified in step S1 and each data correlated with the speed information. For example, the speed at the time when the stride falls below the first threshold is set as the lower limit of the medium speed range, and the speed at the time when the stride becomes equal to or more than the second threshold is set as the upper limit of the medium speed range. Note that in FIG. 3, pitch data is taken as an example and the pitch data is divided for each predetermined speed range, but in step S2, for each data (travel parameter correlated with speed information) such as stride, vertical movement, ground contact time, and waist rotation angle, which are race data, each of the data is divided for each predetermined speed range in the same manner as the pitch data.

[0016] Next, the CPU 11 derives a linear regression line based on the race data divided for each predetermined speed range in step S2 (step S3). For example, as shown in FIG. 3, a linear regression line L1 is derived based on the pitch data included in the low speed range by the above division. Also, a linear regression line L2 is derived based on the pitch data included in the medium speed range by the above division. Further, a linear regression line L3 is derived based on the pitch data included in the high speed range by the above division. Here, the slope of the derived linear regression line can be used as an index indicating the speed dependence of the pitch data. In FIG. 3, the linear regression lines L1, L2, and L3 are derived for each predetermined speed range using the pitch data as an example. However, in step S3, for each data such as stride, vertical movement, ground contact time, and waist rotation angle, which are race data, a linear regression line is derived for each predetermined speed range in the same manner as the pitch data.

[0017] Also, in step S3, the CPU 11 derives a correlation coefficient between the speed information and the race data for each predetermined speed range (low speed range, medium speed range, high speed range). Further, in step S3, based on the linear regression line derived for each predetermined speed range (low speed range, medium speed range, high speed range), the CPU 11 derives a standard deviation indicating the deviation of the race data from the linear regression line. Here, the derived correlation coefficient can be used as an index indicating the speed correlation of the corresponding race data. Also, the derived standard deviation can be used as an index indicating the stability of the corresponding race data. In step S3, the above correlation coefficient and standard deviation are derived for each of the data such as pitch, stride, vertical movement, ground contact time, and waist rotation angle, which are race data.

[0018] Next, the CPU 11 stores the data related to the slope, correlation coefficient, and standard deviation of the linear regression line derived in step S3 in the storage unit 13 (step S4). Subsequently, the CPU 11 displays the slope (speed dependence), correlation coefficient (speed correlation), and standard deviation (stability) of the linear regression line derived in step S3 on the display unit 15 via the operation unit 14 based on user operation (step S5). Then, the CPU 11 terminates the driving data display processing. Note that in step S5, when displaying the slope (speed dependence) of the linear regression line on the display unit 15, as shown in Figure 4, the display unit 15 may display a graph showing the change in the slope (speed dependence) of the linear regression line over time by using past data related to the slope of the linear regression line stored in the storage unit 13. Alternatively, as shown in Figure 5, the display unit 15 may display a graph with distance (driving distance) on the horizontal axis and the slope (speed dependence) of the linear regression line on the vertical axis. Note that the graph shown in Figure 5 may also be a graph where the horizontal axis represents travel time.

[0019] As described above, the CPU 11 of the driving data display device 1 acquires race data 132 (speed information during the user's driving, and at least one driving parameter (driving data) correlated with said speed information), derives a linear regression line (for example, linear regression lines L1, L2, L3; see Figure 3) that shows the relationship between the speed information and driving parameters (driving data) included in each predetermined speed range, and displays the slope of the linear regression line on the display unit 15 as an index indicating the speed dependence of the driving parameters (driving data). Therefore, the driving data display device 1 can suitably represent driving data that changes uniquely for each predetermined speed range by displaying the slope of the linear regression line for each predetermined speed range.

[0020] For example, as shown in Figure 6, when the display unit 15 displays linear regression lines L1A, L2A, and L3A, which show the relationship between speed information and running parameters (vertical motion) included in each predetermined speed range (low speed range, medium speed range, and high speed range), it can be seen from the slopes of the linear regression lines L1A and L2A that vertical motion decreases as the speed increases in the low speed and medium speed ranges. On the other hand, in the high speed range, it can be seen from the slope of the linear regression line L3A that vertical motion increases as the speed increases. From this phenomenon, it can be inferred that the stride is being artificially lengthened in the high speed range. Here, as shown in Figure 7, by displaying the linear regression lines L1A, L2A, and L3A, which show the relationship between speed information and running parameters (stride) included in each predetermined speed range (low speed range, medium speed range, and high speed range), on the display unit 15, it becomes possible to prove that the stride is being lengthened in the high speed range from the slope of the linear regression line L3B in the high speed range.

[0021] Furthermore, as shown in Figure 8, when the display unit 15 displays linear regression lines L1C, L2C, and L3C, which show the relationship between speed information and driving parameters (vertical motion) included in each predetermined speed range (low speed range, medium speed range, and high speed range), it can be seen from the slopes of the linear regression lines L2C and L3C that vertical motion decreases as the speed increases in the medium speed range and high speed range. On the other hand, in the low speed range, it can be seen from the slope of the linear regression line L1C that vertical motion increases as the speed increases. From this phenomenon, it can be inferred that in the low speed range, the vehicle is unable to reduce speed effectively and bounces upward, that is, it reduces speed by directing its force upward. In this case, the force exerted does not decrease even when the speed is reduced, so it can be said that physical strength is wasted. Here, as shown in Figure 9, by displaying linear regression lines L1D, L2D, and L3D, which show the relationship between speed information and driving parameters (pitch) included in each predetermined speed range (low speed range, medium speed range, and high speed range), on the display unit 15, it becomes possible to prove from the slope of the linear regression line L1D in the low speed range that in the low speed range, the speed is adjusted by changing the direction of the force without changing the pitch to a general extent.

[0022] Furthermore, the CPU 11 derives a correlation coefficient between the speed information included in each predetermined speed range and the running parameters, and displays this correlation coefficient on the display unit 15 as an indicator showing the speed correlation of the running parameters (running data). Therefore, the running data display device 1 can more favorably represent running data that changes uniquely for each predetermined speed range by displaying the above correlation coefficient for each predetermined speed range. As a result, for example, even if the slope of the linear regression line displayed on the display unit 15 is the same, the user can appropriately consider the results according to the magnitude of the correlation coefficient. Also, as shown in Figure 10, when a graph with distance (running distance) on the horizontal axis and the slope of the linear regression line (speed dependence of stride) on the vertical axis is displayed on the display unit 15, it can be seen that the speed dependence of stride increases in the latter half of the run. This suggests that the stride length is being used to compensate for the decrease in speed due to fatigue. In other words, it suggests that the running form becomes inconsistent in the latter half of the run. Here, as shown in Figure 11, by displaying a graph on the display unit 15 with distance (running distance) on the horizontal axis and stride-velocity correlation on the vertical axis, it becomes possible to prove that the running form becomes disordered and inconsistent in the latter half of the run, as the stride-velocity correlation decreases in the latter half of the run.

[0023] Furthermore, the CPU 11 derives a standard deviation indicating the deviation of the driving parameters (driving data) from the linear regression line derived for each predetermined speed range, and displays this standard deviation on the display unit 15 as an indicator of the stability of the driving parameters (driving data). Therefore, the driving data display device 1 can suitably represent driving data that changes uniquely for each predetermined speed range by displaying the standard deviation for each predetermined speed range.

[0024] The above description of the embodiment is merely an example of the driving data display device, driving data display method, and program according to the present invention, and is not limited thereto. For example, in the above embodiment, as shown in Figure 4, a graph showing the change over time of the slope (speed dependence) of the first regression line can be displayed on the display unit 15, or as shown in Figure 5, a graph with distance (driving distance) on the horizontal axis and the slope (speed dependence) of the first regression line on the vertical axis can be displayed on the display unit 15. In addition, data from other users can be overlaid on the graph to allow comparison of data between users.

[0025] Furthermore, in the above embodiment, the content of running advice (information useful for improving running performance) may be determined based on the slope of the linear regression line derived for each predetermined speed range (low speed range, medium speed range, high speed range), and the advice may be displayed on the display unit 15.

[0026] Furthermore, it goes without saying that the detailed configuration and detailed operation of each component of the driving data display device 1 in the above embodiment can be appropriately modified without departing from the spirit of the present invention. [Explanation of Symbols]

[0027] 1 Driving data display device, 11 CPU (control unit), 15 Display unit, L1 Primary regression line, L2 Primary regression line, L3 Primary regression line

Claims

1. Display unit and It comprises a control unit and, The control unit, The system obtains the user's speed information during driving and at least one driving parameter correlated with said speed information. For each predetermined speed range, a linear regression line is derived that shows the relationship between the speed information included in that speed range and the driving parameters. The slope of the aforementioned linear regression line is displayed on the display unit as an indicator showing the speed dependence of the aforementioned driving parameters. A driving data display device characterized by the following features.

2. The control unit, For each predetermined speed range, the correlation coefficient between the speed information included in that speed range and the driving parameters is derived. The correlation coefficient is displayed on the display unit as an indicator showing the speed correlation of the driving parameters. The driving data display device according to feature 1.

3. The control unit further, Based on the linear regression lines derived for each predetermined speed range, the standard deviation showing the deviation of the driving parameters from the linear regression line is derived. The standard deviation is displayed on the display unit as an indicator of the stability of the driving parameters. The driving data display device according to feature 1.

4. The control unit, Based on the speed range of the user's driving indicated by the speed information, each of the speed ranges is determined. The driving data display device according to feature 1.

5. The control unit acquires speed range setting information input by the user and determines each of the speed ranges based on the setting information. The driving data display device according to feature 1.

6. The control unit determines the speed range for each of the speed ranges based on the speed information and the at least one driving parameter. The driving data display device according to feature 1.

7. The control unit, Based on the slope of the linear regression line derived in each of the aforementioned speed ranges, the content of the driving advice is determined, and the advice is provided to the user. The driving data display device according to feature 1.

8. A method for displaying driving data, which is performed by the computer of a driving data display device, An acquisition step of acquiring speed information during a user's driving and at least one driving parameter correlated with said speed information, A derivation step of deriving a linear regression line showing the relationship between the speed information included in a given speed range and the driving parameters for each predetermined speed range, A display control step that causes the slope of the aforementioned linear regression line to be displayed on the display unit as an indicator showing the speed dependence of the aforementioned driving parameters, A method for displaying driving data, characterized by including the following:

9. The computer of the driving data display device, A means for acquiring speed information of a user during driving and at least one driving parameter correlated with said speed information. Derivation means for deriving a linear regression line showing the relationship between the speed information included in a given speed range and the driving parameters for each predetermined speed range, Display control means for displaying the slope of the aforementioned linear regression line on a display unit as an indicator showing the speed dependence of the aforementioned driving parameters, A program characterized by being designed to function as such.

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