JP2020144817A - Driving information processing device, driving information processing method, and program - Google Patents

Abstract

To allow for accurately determining a level of difficulty of a curve a vehicle is traveling on.SOLUTION: A driving information processing device is provided, comprising a proficiency level acquisition unit 2010 configured to acquire proficiency levels of drivers driving on a curve; and a difficulty level determination unit 2020 configured to determine the level of difficulty of the curve based on the proficiency levels acquired from multiple drivers. Such a configuration allows for accurately determining the level of difficulty of a curve a vehicle is traveling on.SELECTED DRAWING: Figure 1

Description

The present invention relates to a driving information processing device, a driving information processing method and a program.

Conventionally, for example, the following Patent Document 1 describes that advice according to the skill level of a driver is displayed on an alarm device.

Japanese Unexamined Patent Publication No. 2003-99897

The roads on which vehicles travel vary, and the difficulty for drivers varies. For example, when passing through a curve with a high degree of difficulty in driving, if the driver knows in advance that the curve has a high degree of difficulty, he / she can drive carefully. However, it is difficult to determine the difficulty level of the curve, and it is impossible for the driver to know the difficulty level of the curve in advance.

In addition, the difficulty level of the curve is relatively different depending on the driving skill of the driver. Although the technique described in Patent Document 1 is supposed to provide advice according to the skill level of the driver, regarding determining the difficulty level of the curve according to the driving skill of the driver. No consideration is given.

Therefore, the present invention has been made in view of the above problems, and an object of the present invention is a new and improved driving capable of accurately determining the difficulty level of a curve on which a vehicle travels. The purpose is to provide an information processing device, an operation information processing method, and a program.

In order to solve the above problems, according to a certain viewpoint of the present invention, a skill level acquisition unit that acquires a driving skill level of a driver traveling on a curve and a skill level acquired from a plurality of drivers are used. Provided is a driving information processing device including a difficulty level determination unit for determining the difficulty level of the curve.

Further, a skilled driver extraction unit that extracts a skilled driver based on the skill level acquired from a plurality of drivers is provided, and the difficulty level determination unit is based on the ratio of the skilled driver determined as an unskilled driver. , The difficulty level of the curve may be determined.

Further, information on the difficulty level of the curve may be transmitted to each vehicle.
Further, the skill level and the difficulty level may be associated with each other according to the level, and the curve having a higher difficulty level than the difficulty level corresponding to the skill level may be determined.

Further, it may be provided with a route selection unit that selects a route based on the skill level of the driver and the difficulty level of the curve.

Further, the route selection unit may select the route including the curve having a difficulty level higher than the difficulty level corresponding to the skill level.

Further, in order to solve the above problems, according to another viewpoint of the present invention, based on the step of acquiring the driving skill of the driver traveling on the curve and the skill obtained from the plurality of drivers. A driving information processing method is provided, which comprises a step of determining the difficulty level of the curve.

Further, in order to solve the above problems, according to another viewpoint of the present invention, a means for acquiring the driving skill of a driver traveling on a curve, based on the skill obtained from a plurality of drivers. A program for operating a computer is provided as a means for determining the difficulty level of the curve.

According to the present invention, it is possible to accurately determine the difficulty level of the curve on which the vehicle travels.

It is a schematic diagram which shows the structure of the vehicle system which concerns on one Embodiment of this invention. It is a flowchart which shows the process of determining whether a driver of a vehicle is an expert based on a curve traveling section, and transmitting the position of a curve and driver data to a server. It is a characteristic diagram which shows the steering angle for Z seconds before and after the timing when the yaw rate becomes the maximum value (peak value) in step S16. It is a characteristic diagram which shows the standard deviation of a skilled person and an unskilled person obtained from the distribution of the steering angular velocity in Z seconds. It is a flowchart which shows the process of determining the curve which the server 2000 should pay attention to driving. It is a schematic diagram which shows the extraction of the skilled driver A to C, and the extraction of the curve 3 in which each of the skilled driver A, the skilled driver B, the skilled driver C, ... Is determined to be an unskilled person. It is a flowchart which shows the process of determining the level of a driver. It is a flowchart which shows the process of the determination method of a curve level.

A preferred embodiment of the present invention will be described in detail below with reference to the accompanying drawings. In the present specification and the drawings, components having substantially the same functional configuration are designated by the same reference numerals, so that duplicate description will be omitted.

FIG. 1 is a schematic view showing a configuration of a vehicle system 1000 according to an embodiment of the present invention and its surroundings. The vehicle system 1000 is basically a system configured in a vehicle such as an automobile. As shown in FIG. 1, the vehicle system 1000 includes an external sensor 100, a vehicle sensor 200, a steering angle sensor 300, a control device 400, an in-vehicle display device 500, an external display device 600, a navigation device 700, a communication device 800, and a speaker 900. It is configured to have. The vehicle system 1000 is configured to be able to communicate with the external server 2000.

The vehicle exterior sensor 100 is composed of a stereo camera, a monocular camera, a millimeter wave radar, an infrared sensor, and the like, and measures the position and speed of a person or vehicle around the own vehicle. When the vehicle exterior sensor 100 is composed of a stereo camera, the stereo camera is configured to have a pair of left and right cameras having image pickup elements such as a CCD sensor and a CMOS sensor, and images the external environment outside the vehicle. The image information is sent to the control device 400. As an example, a stereo camera is composed of a color camera capable of acquiring color information and is installed on the upper part of the windshield of a vehicle.

The vehicle sensor 200 acquires information communicated by CAN (Control Area Network) in the vehicle, such as vehicle speed, acceleration, angular velocity, and yaw rate. In addition, these information can be acquired from various sensors. The steering angle sensor 300 is attached to the steering wheel and detects the steering angle of the steering wheel.

The control device 400 determines the driving skill of the driver of the vehicle and sends it to the server 2000. Therefore, the control device 400 has a skill level determination unit 402, a transmission processing unit 404, a driver authentication unit 406, and a display control unit 408. The skill level determination unit 402 determines the driving skill level of the driver of the vehicle. The transmission processing unit 404 performs a process for transmitting the driver's skill level determined by the skill level determination unit 402 to the server 2000 via the communication device 800. The driver authentication unit 406 authenticates the driver who drives the vehicle. An example of the authentication method is a method of authenticating the driver's face and fingerprint, and various methods can be used as the authentication method. Each component of the control device 400 can be configured by a circuit (hardware), a central processing unit such as a CPU, and a program (software) for functioning the central processing unit.

The in-vehicle display device 500 is, for example, a device that displays on a dash panel in the vehicle, around a meter, or the like. The vehicle exterior display device 600 is a device that displays toward the outside of the vehicle. The vehicle exterior display device 600 may be composed of a HUD (Head-up Display) device. A HUD (Head-up Display) device is a display device that directly displays information in a human visual field, and displays a real image or a virtual image on glass such as a windshield or a rear glass of an automobile.

The communication device 800 communicates with the server 2000 outside the vehicle and receives various information such as traffic jam information and road information. Further, as will be described later, the communication device 800 transmits the position of the curve and the driver data for which the skill level is determined to the server 2000. The navigation device 700 searches for a route from the current location to the destination based on the map information. Therefore, the navigation device 700 can acquire the current position of the vehicle by a global positioning system (GPS: Global Positioning System) or the like. In addition, the navigation device 700 remembers the route on which the vehicle has traveled to the current location.

The server 2000 acquires the skill level of the driver determined on the vehicle side and the information of the curve for which the skill level is determined, and determines the difficulty level of the curve. At this time, the server 2000 extracts the skilled driver based on the skill level acquired from the plurality of drivers, and determines the difficulty level of the curve based on the ratio of the skilled driver determined as an unskilled driver. Further, the server 2000 transmits information on the difficulty level of the curve to the vehicle side. Therefore, the server 2000 has a skill level acquisition unit 2010, a difficulty level determination unit 2020, a skill level driver extraction unit 2030, a route selection unit 2040, and a communication processing unit 2050.

The proficiency level acquisition unit 2010 acquires the proficiency level of driving of the driver traveling on the curve, which is transmitted from the vehicle system 1000 side. The difficulty level determination unit 2020 determines the difficulty level of the curve based on the skill level acquired from the plurality of drivers. Further, the difficulty level determination unit 2020 determines the difficulty level of the curve based on the ratio of the skilled driver determined as an unskilled person. Further, the difficulty level determination unit 2020 associates the skill level with the difficulty level of the curve corresponding to the skill level according to the level, and determines a curve having a higher difficulty level than the difficulty level corresponding to the skill level. .. This makes it possible to warn before a difficult curve or select a route to avoid a difficult curve, depending on the driver's skill level. The skilled driver extraction unit 2030 extracts a skilled driver based on the skill level acquired from the plurality of drivers. The route selection unit 2040 selects a route including a curve having a difficulty level higher than the difficulty level corresponding to the skill level, based on the skill level of an arbitrary driver and the difficulty level of the curve. The communication processing unit 2050 performs a process of transmitting information on the difficulty level of the curve to each vehicle. Each component of the server 2000 can be configured by a circuit (hardware) or a central processing unit such as a CPU and a program (software) for operating the central processing unit.

FIG. 2 is a flowchart showing a process of determining whether the driver of the vehicle is an expert based on the curve traveling section and transmitting the position of the curve and the driver data to the server 2000. More specifically, in the process of FIG. 2, a difficult curve is mapped and notified, and a process of determining a curve in which a skilled person frequently becomes unskilled is performed. The process of FIG. 2 is mainly performed by the control device 400 at predetermined intervals, and is mainly performed by the skill level determination unit 402. The curve may be a single curve, or a plurality of curves may be averaged.

First, in step S10, it is determined whether or not the vehicle has traveled on a curve based on the yaw rate of the vehicle detected by the in-vehicle sensor 200. Specifically, in step S10, when the yaw rate is larger than the first threshold value X1 and smaller than the second threshold value X2, it is determined that the vehicle has traveled on the curve. If the vehicle has traveled on the curve, the process proceeds to step S12, and if the vehicle has not traveled on the curve, the process ends.

In step S12, it is determined whether or not the time t1 in which the vehicle is traveling on the curve continues for a certain period of time. Specifically, in step S12, it is determined whether or not the time t1 in which the vehicle is traveling on the curve exceeds the threshold value Y, and the time t1 in which the vehicle is traveling on the curve exceeds the threshold value Y. If so, it is determined that the time t1 in which the vehicle is traveling on the curve has continued for a certain period of time, and the process proceeds to step S16.

In step S16, based on the yaw rate of the vehicle detected by the in-vehicle sensor 200, the steering angle for Z seconds before and after the timing when the yaw rate reaches the maximum value (peak value) in the time t1 when the vehicle is traveling on the curve is set. get. In the next step S18, the steering angular velocity α or the steering angular acceleration β in Z seconds is calculated. In the next step S20, the standard deviation σ of the steering angular velocity α or the steering angular acceleration β is calculated.

In the next step S22, it is determined whether or not the value of the standard deviation σ is larger than the predetermined threshold value T, and if the standard deviation σ is larger than the predetermined threshold value T, the process proceeds to step S24. When the process proceeds to step S24, it is considered that the steering is unstable because the variation in the steering angular velocity α or the steering angular acceleration β is relatively large. Therefore, in step S24, it is determined that the driver of the vehicle is an unskilled person. After step S24, the process proceeds to step S28, and the position information of the curve determined by the driver to be an unskilled person and the information about the driver (driver data) are transmitted to the server 2000. After step S28, the process ends. The information about the driver is information for identifying the driver, such as the name of the driver, and can be obtained by, for example, being authenticated by the driver authentication unit 406.

On the other hand, if the value of the standard deviation σ is equal to or less than the predetermined threshold value T in step S22, the process proceeds to step S26. When the process proceeds to step S26, it is considered that the steering is stable because the variation in the steering angular velocity α or the steering angular acceleration β is relatively small. Therefore, in step S26, it is determined that the driver of the vehicle is an expert. After step S26, the process proceeds to step S29, and the position information of the curve determined by the driver to be an expert and the information about the driver are transmitted to the server 2000. After step S28, the process ends.

FIG. 3A is a characteristic diagram showing a steering angle for Z seconds before and after the timing at which the yaw rate reaches the maximum value (peak value) in step S16. Further, FIG. 3B is a characteristic diagram showing a standard deviation between a skilled person and an unskilled person, which is obtained from the distribution of the steering angular velocity in Z seconds. As shown in FIG. 4B, the expert has a narrower distribution of steering angular velocity and a larger standard deviation value than the unskilled.

The skill level determination unit 402 may determine the skill level of a driver whose skill level is known in advance based on the result of authentication by the driver certification unit 406. For example, when a driver A determined to be an unskilled person in the past drives a vehicle, if the driver authentication unit 410 authenticates the driver A, the driver A is used without performing the process shown in FIG. It can be judged as an unskilled person.

Further, as a method for determining the skill level of the driver, a method other than the method shown in FIG. 2 may be used. For example, the smoothness of acceleration / deceleration may be evaluated from the standard deviation of the accelerator opening degree change rate to determine the driver's skill level. Further, the wobbling in a straight line may be evaluated based on a traveling locus obtained from GPS, white line detection, or the like to determine the driver's skill level. In addition to the traveling locus, the frequency analysis result of the steering angular velocity, the time (or the number of times) that the absolute value of the steering angular velocity exceeds a predetermined value, the standard deviation of the yaw rate, the number of lane departures, etc. can be evaluated by the threshold value. good. Further, the driver's skill level may be evaluated by evaluating how to take the distance between vehicles from the standard deviation of the collision margin time.

According to the process of FIG. 2, for each curve, it is possible to collect data indicating whether the driver is a skilled driver or an unskilled driver. On the server 2000 side, the curve to be noted for driving is determined based on the data obtained in this way. FIG. 4 is a flowchart showing a process of determining a curve in which the server 2000 should pay attention to operation.

First, in step S30, the skilled driver extraction unit 2030 extracts a driver determined to be a skilled driver with a number of curves of M% or more. The value of M is, for example, 60 (%). The upper part of FIG. 5 shows the skilled drivers A to C determined to be skilled in the number of curves of 60% or more in step S30. Skilled drivers A to C are judged to be skilled in three or more of the five curves.

In the next step S32, the skilled driver extracted in step S30 extracts the curve determined as an unskilled person. The lower part of FIG. 5 shows how each of the skilled driver A, the skilled driver B, the skilled driver C, ... Extracts the curve 3 determined to be an unskilled person. The skilled driver A, the skilled driver B, and the skilled driver C are judged to be skilled in a curve of 60% or more, but the skilled driver is judged to be a non-skilled driver in the curves 2 and 3. Therefore, curves 2 and 3 are difficult curves even for skilled drivers A to C, and are extracted as curves to be noted.

In the next step S34, the unskilled determination ratio in the curve extracted in step S32 is calculated. The unskilled determination ratio for an individual curve is the ratio of the number of skilled drivers determined to be unskilled on that curve to the total number of skilled drivers. In the example shown in the lower part of FIG. 5, out of the four skilled drivers, three skilled drivers are determined to be unskilled on the curve 3. Therefore, the unskilled rate on curve 3 is 3/4 = 0.75 = 75%. Similarly, with respect to curve 2, one of the four skilled drivers is determined to be unskilled on curve 2. Therefore, the unskilled rate on curve 2 is 1/4 = 0.25 = 25%.

In the next step S36, the difficulty determination unit 2020 determines whether or not the unskilled determination ratio calculated in step S34 is N% or more with respect to the curve extracted in step S32, and the unskilled determination ratio is N% or more. In the case, the process proceeds to step S38. On the other hand, if the unskilled determination ratio is less than N%, the process is terminated.

The value of N is 70% as an example. In this case, since the unskilled determination ratio on the curve 3 is 75%, the process proceeds to step S38, and the curve 3 is registered in the server 2000 as a difficult curve to be noted.

In step S36, the unskilled ratio was determined based on one threshold value, and the difficulty level of the curve was determined in two stages. However, the unskilled determination ratio was determined based on a plurality of different threshold values. The difficulty level may be divided into three or more levels.

In the next step S40, the communication processing unit 2050 transmits the information of the curve 3 registered in step S38 to each vehicle. In each vehicle, information indicating that the curve 3 is a difficult curve to be careful of is displayed on the in-vehicle display device 500. The display on the in-vehicle display device 500 is performed under the control of the display control unit 408. In the next step S42, when the vehicle travels on the curve 3, the driver is alerted by changing the display color of the in-vehicle display device 500 or notifying the voice by the speaker 900.

In the process of FIG. 4, the curve to be noted was determined based on the driver extracted as the skilled driver, but the ratio of the driver who was simply determined to be skilled and the unskilled driver were also used using the judgment results other than the skilled driver. The difficulty level of the curve may be determined based on the ratio determined to be a person. For example, in a certain curve, when 20% of the drivers are judged to be skilled and 80% are judged to be unskilled, the curve can be judged as a curve to be noted. ..

Next, a process in which the driver selects a route that is slightly more difficult than his / her driving level will be described based on FIGS. 6 and 7. The processing of FIGS. 6 and 7 is mainly performed by the route selection unit 2040. FIG. 6 is a flowchart showing a process of determining the level of the driver. According to this process, the driving of the driver can be improved, and the driving pleasure can be provided.

First, in step S50, the ratio of skilled and unskilled determination results (skilled ratio J) in each curve is calculated for the driver whose level is to be determined. The skill ratio is the ratio of the number of curves judged to be skilled to the total number of curves judged to be skilled or unskilled. In the next step S52, it is determined whether or not 33> skill ratio J ≧ 0, and if 33> skill ratio J ≧ 0, the process proceeds to step S54. In step S54, the driver level is determined to be level 1. After step S54, the process proceeds to step S56, and the route selection unit 2040 selects a route including the curve of the unskilled determination ratio level 2. The information of the selected route is transmitted to the driver whose level is to be determined by the processing of the communication processing unit 2050. After step S56, the process ends.

If 33> skill ratio J ≧ 0 in step S52, the process proceeds to step S58. In step S58, it is determined whether or not 66> skill ratio J ≧ 33, and if 66> skill ratio J ≧ 33, the process proceeds to step S60. In step S60, the driver level is determined to be level 2. After step S60, the process proceeds to step S62, and a route including the curve of the unskilled determination ratio level 3 is selected. After step S62, the process ends.

If 66> skill ratio J ≧ 33 in step S58, the process proceeds to step S64. In step S64, it is determined whether or not 100 ≧ skill ratio J ≧ 66, and if 100 ≧ skill ratio J ≧ 66, the process proceeds to step S66. In step S66, the driver level is determined to be level 3. After step S66, the process proceeds to step S68, and a route including the curve of the unskilled determination ratio level 4 is selected. After step S62, the process ends.

Here, it is assumed that the driver level 1 corresponds to the unskilled determination level 1, the driver level 2 corresponds to the unskilled determination level 2, and the driver level 3 corresponds to the unskilled determination level 3. Then, when the driver's level and the unskilled determination level match, it is possible to drive a curve according to the skill of the driver. Based on such a premise, in the process of FIG. 6, a route including a curve of the unskilled determination ratio level one step higher than the driver level is selected. Therefore, by selecting a route that is slightly more difficult than the driver's driving level, the driver's driving can be improved and the driving pleasure can be provided.

FIG. 7 is a flowchart showing the process of the curve level determination method, and shows the process of determining the unskilled determination ratio level described above. The processing of step S70, step S72, and step S74 is performed in the same manner as in step S30, step S32, and step S34 of FIG. In the next step S76, it is determined whether or not the unskilled determination ratio H calculated in step S74 is 0%, and if the unskilled determination ratio H is 0, the process proceeds to step S78. In step S78, the unskilled determination ratio level is determined to be "1". After step S78, the process ends.

If the unskilled determination ratio H is not 0% in step S76, the process proceeds to step S80, and it is determined whether or not the unskilled determination ratio H calculated in step S74 is 33> unskilled ratio H ≧ 0, and 33> If the unskilled ratio H ≧ 0, the process proceeds to step S82. In step S82, the unskilled determination ratio level is determined to be “2”. After step S82, the process ends.

If 33> unskilled ratio H ≧ 0 in step S80, the process proceeds to step S84. In step S84, it is determined whether or not 66> unskilled ratio H ≧ 33, and if 66> unskilled ratio H ≧ 33, the process proceeds to step S86. In step S86, the unskilled determination ratio level is determined to be “3”. After step S86, the process ends.

If 66> unskilled ratio H ≧ 33 in step S84, the process proceeds to step S89. In step S89, it is determined whether or not 100 ≧ unskilled ratio H ≧ 66, and if 100 ≧ unskilled ratio H ≧ 66, the process proceeds to step S89. In step S89, the unskilled determination ratio level is determined to be “4”. After step S89, the process ends.

Although the preferred embodiments of the present invention have been described in detail with reference to the accompanying drawings, the present invention is not limited to such examples. It is clear that a person having ordinary knowledge in the field of technology to which the present invention belongs can come up with various modifications or modifications within the scope of the technical ideas described in the claims. , These are also naturally understood to belong to the technical scope of the present invention.

2000 Server 2010 Skill level acquisition unit 2020 Difficulty level judgment unit 2030 Skilled driver extraction unit 2040 Route selection unit

Claims (8)

The proficiency acquisition unit that acquires the driving proficiency of the driver while driving on a curve,
A difficulty level determination unit that determines the difficulty level of the curve based on the skill level acquired from a plurality of drivers, and
A driving information processing device characterized by being equipped with. A skilled driver extraction unit that extracts a skilled driver based on the skill level acquired from a plurality of drivers is provided.
The driving information processing device according to claim 1, wherein the difficulty level determination unit determines the difficulty level of the curve based on the ratio of the skilled driver determined as an unskilled person. The driving information processing device according to claim 1 or 2, wherein information on the difficulty level of the curve is transmitted to each vehicle. The skill level and the difficulty level are associated with each other according to the level.
The driving information processing apparatus according to claim 1 or 2, wherein the curve having a difficulty level higher than the difficulty level corresponding to the skill level is determined. The driving information processing apparatus according to any one of claims 1 to 3, further comprising a route selection unit that selects a route based on the skill level of the driver and the difficulty level of the curve. The skill level and the difficulty level are associated with each other according to the level.
The driving information processing device according to claim 5, wherein the route selection unit selects the route including the curve having a difficulty level higher than the difficulty level corresponding to the skill level. Steps to acquire the driving skill of the driver while driving on a curve, and
A step of determining the difficulty level of the curve based on the skill level acquired from a plurality of drivers, and
A driving information processing method characterized by being provided with. A means of acquiring driving proficiency of a driver traveling on a curve,
A means for determining the difficulty level of the curve based on the skill level acquired from a plurality of drivers.
A program to make your computer work as.

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