JP7269037B2 - Driving information processing device, driving information processing method and program - Google Patents

Description

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

2. Description of the Related Art Conventionally, for example, Japanese Patent Application Laid-Open No. 2002-200002 describes displaying advice according to a driver's skill level on an alarm device.

JP-A-2003-99897

There are various roads on which vehicles travel, and there are various degrees of difficulty for drivers. For example, when passing through a curve that is difficult to drive, if the driver knows in advance that the curve is difficult, he or she can drive carefully. However, it is difficult to determine the degree of difficulty of a curve, and it is impossible for a driver to know the degree of difficulty of a curve in advance.

Also, the degree of difficulty of a curve is relatively different depending on the driving skill of the driver. Although the technique described in Patent Literature 1 assumes that advice is provided according to the skill level of the driver, the difficulty level of the curve is determined according to the driving skill level of the driver. nothing to consider.

SUMMARY OF THE INVENTION Accordingly, the present invention has been made in view of the above problems, and an object of the present invention is to provide a new and improved driving system capable of accurately determining the degree of difficulty of a curve on which a vehicle travels. An object of the present invention is to provide an information processing device, a driving information processing method, and a program.

In order to solve the above problems, according to one aspect of the present invention, a skill acquisition unit acquires the driving skill of a driver traveling on a curve; a skilled driver extracting unit for extracting, as a skilled driver, a driver determined to be a skilled driver on a predetermined ratio or more of curves out of a plurality of curves; and extracting the skill level obtained from the plurality of drivers and the skilled driver a difficulty level determination unit that determines the difficulty level of the curve based on the result , wherein the difficulty level determination unit determines the number of skilled drivers determined as unskilled drivers with respect to the total number of skilled drivers on individual curves. A driving information processing device is provided that determines the degree of difficulty of the curve based on the ratio of the numbers .

Moreover, the information regarding the degree of difficulty of the curve may be transmitted to each vehicle.
Further, the skill level and the difficulty level may be associated 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, a route selection unit may be provided for selecting 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.

In order to solve the above problems, according to another aspect of the present invention, a computer obtains a driving skill level of a driver traveling on a curve; a step of extracting, as skilled drivers, drivers determined to be skilled drivers on a predetermined ratio or more of curves among a plurality of curves, and extracting said skill levels obtained from said plurality of drivers and said skilled drivers , and, based on the results , determining the difficulty of the curve, wherein the step of determining the difficulty of the curve includes determining the skilled drivers determined as unskilled relative to the total number of skilled drivers at each curve. A driving information processing method is provided, characterized in that the degree of difficulty of the curve is determined based on the ratio of the number of drivers .

Further, in order to solve the above problems, according to another aspect of the present invention, means for acquiring the driving skill level of a driver traveling on a curve, based on the skill levels acquired from a plurality of drivers, Means for extracting a driver judged to be a skilled driver on a predetermined ratio or more of curves out of a plurality of curves as a skilled driver, the skill level obtained from the plurality of drivers, and based on the extraction result of the skilled driver , The computer functions as means for determining the degree of difficulty of the curve, and the means for determining the degree of difficulty of the curve determines the number of skilled drivers determined as unskilled drivers with respect to the total number of skilled drivers on each curve. A program is provided for determining the difficulty of the curve based on a percentage .

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

1 is a schematic diagram showing the configuration of a vehicle system according to one embodiment of the present invention; FIG. 4 is a flow chart showing the process of determining whether the driver of the vehicle is a skilled driver based on the curve travel section, and transmitting the curve position and driver data to the server. FIG. 10 is a characteristic diagram showing the steering angle for Z seconds before and after the timing at which the yaw rate reaches the maximum value (peak value) in step S16; FIG. 5 is a characteristic diagram showing the standard deviation of a skilled driver and a non-skilled driver obtained from the distribution of steering angular velocities for Z seconds. 4 is a flow chart showing a process of determining a curve that requires caution in driving by the server 2000. FIG. FIG. 10 is a schematic diagram showing extraction of skilled drivers A to C and extraction of curve 3 where each of skilled driver A, skilled driver B, skilled driver C, . It is a flowchart which shows the process which determines the level of a driver. 4 is a flow chart showing the processing of a curve level determination method;

Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. In the present specification and drawings, constituent elements having substantially the same functional configuration are denoted by the same reference numerals, thereby omitting redundant description.

FIG. 1 is a schematic diagram showing a vehicle system 1000 according to one embodiment of the present invention and its peripheral configuration. A 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 exterior sensor 100, a vehicle sensor 200, a steering angle sensor 300, a control device 400, an interior display device 500, an exterior display device 600, a navigation device 700, a communication device 800, and a speaker 900. It is configured with Vehicle system 1000 is configured to communicate with external server 2000 .

The vehicle exterior sensor 100 is composed of a stereo camera, a monocular camera, a millimeter wave radar, an infrared sensor, etc., and measures the positions and velocities of people and vehicles around the vehicle. When the vehicle exterior sensor 100 is composed of a stereo camera, the stereo camera includes a pair of left and right cameras having imaging elements such as CCD sensors, CMOS sensors, etc., and images the external environment outside the vehicle. Image information is sent to the control device 400 . As an example, the stereo camera is composed of a color camera capable of acquiring color information, and is installed above the windshield of the vehicle.

The vehicle sensor 200 acquires information such as vehicle speed, acceleration, angular velocity, and yaw rate, which is communicated via CAN (Controller Area Network) in the vehicle. 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.

Control device 400 determines the driving skill level of the driver of the vehicle and sends it to 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 processing for transmitting the skill level of the driver determined by the skill level determination unit 402 to the server 2000 via the communication device 800 . A driver authentication unit 406 authenticates a driver who drives a vehicle. As an example of the authentication method, there is a method of authenticating the driver's face and fingerprints, but various methods can be used as the authentication method. Each component of the control device 400 can be configured by a circuit (hardware) or a central processing unit such as a CPU and a program (software) for making this function.

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

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

The server 2000 acquires the skill level of the driver determined on the vehicle side and information on the curve for which the skill level was determined, and determines the degree of difficulty of the curve. At this time, the server 2000 extracts skilled drivers based on the skill levels obtained from the plurality of drivers, and determines the degree of difficulty of the curve based on the rate at which the skilled drivers are determined to be unskilled drivers. Server 2000 also transmits information about the degree of difficulty of the curve to the vehicle. Therefore, the server 2000 has a skill acquisition unit 2010 , a difficulty level determination unit 2020 , a skilled driver extraction unit 2030 , a route selection unit 2040 and a communication processing unit 2050 .

Skill level acquisition unit 2010 acquires the driving skill level of the driver traveling on a curve, transmitted from vehicle system 1000 . The difficulty level determination unit 2020 determines the difficulty level of a curve based on the skill levels obtained from a plurality of drivers. In addition, the difficulty level determination unit 2020 determines the difficulty level of the curve based on the rate at which skilled drivers are determined to be unskilled drivers. 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 with a higher difficulty level than the difficulty level corresponding to the skill level. . As a result, depending on the driver's proficiency level, it is possible to issue a warning in advance of difficult curves or select a route that avoids difficult curves. Skilled driver extraction unit 2030 extracts a skilled driver based on the skill levels obtained from a plurality of drivers. The route selection unit 2040 selects a route including curves with a difficulty level higher than the difficulty level corresponding to the skill level of an arbitrary driver based on the skill level of the driver and the difficulty level of the curves. The communication processing unit 2050 performs processing for transmitting information regarding the degree of difficulty 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 making this function.

FIG. 2 is a flow chart showing the process of determining whether the vehicle driver is a skilled driver based on the curve traveling section and transmitting the curve position and driver data to the server 2000 . More specifically, the process of FIG. 2 maps and notifies difficult curves, and performs processing for determining curves that frequently result in unskilled people in a skilled state. The processing in FIG. 2 is mainly performed by the control device 400 at predetermined intervals, and is mainly performed by the skill level determination unit 402 . Note that the curve may be a single curve, or an average of a plurality of curves.

First, in step S10, based on the yaw rate of the vehicle detected by the in-vehicle sensor 200, it is determined whether or not the vehicle has traveled a curve. Specifically, in step S10, if the yaw rate is greater than the first threshold value X1 and less than the second threshold value X2, it is determined that the vehicle has traveled a 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 during which the vehicle is traveling on the curve has continued for a certain period of time. Specifically, in step S12, it is determined whether or not the time t1 during which the vehicle is traveling on the curve exceeds the threshold Y, and the time t1 during which the vehicle is traveling on the curve exceeds the threshold Y. If so, it is determined that the time t1 during 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 at which the yaw rate reaches the maximum value (peak value) during the time t1 during which the vehicle is traveling on a curve is determined. get. In the next step S18, the steering angular velocity α or the steering angular acceleration β for 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 greater than a predetermined threshold value T, and if the standard deviation σ is greater than the predetermined threshold value T, the process proceeds to step S24. If the process proceeds to step S24, it is considered that the steering is unstable because the steering angular velocity α or the steering angular acceleration β has a relatively large variation. Therefore, in step S24, it is determined that the driver of the vehicle is an unskilled person. After step S<b>24 , the process proceeds to step S<b>28 to transmit to server 2000 the position information of the curve where the driver is determined to be an unskilled driver and the information on the driver (driver data). After step S28, the process ends. The information about the driver is information for specifying the driver, such as the name of the driver, and can be obtained by authentication by the driver authentication unit 406, for example.

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 steering angular velocity α or the steering angular acceleration β has a relatively small variation. Therefore, in step S26, it is determined that the driver of the vehicle is an expert. After step S<b>26 , the process proceeds to step S<b>29 to transmit to server 2000 the positional information of the curve where the driver is determined to be a skilled driver and the information about the driver. After step S28, the process ends.

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

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 authentication unit 406 . For example, when driver A, who has been determined to be an unskilled driver in the past, drives a vehicle, and driver A is authenticated by driver authentication unit 410, driver A can be recognized without performing the processing shown in FIG. It can be judged as an unskilled person.

Also, as a method of determining the skill level of a 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 rate of change in accelerator opening to determine the skill level of the driver. Further, the driver's proficiency level may be determined by evaluating the swaying in a straight line based on the travel locus obtained from GPS, white line detection, or the like. In addition to the driving trajectory, the frequency analysis results of the steering angular velocity, the time (or number of times) when 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 with thresholds. good. Furthermore, the distance between vehicles may be evaluated from the standard deviation of the time to collision, and the skill level of the driver may be evaluated.

According to the process of FIG. 2, it is possible to collect data indicating whether an individual driver is judged to be a skilled driver or an unskilled driver for each curve. On the server 2000 side, based on the data obtained in this way, a curve that requires careful driving is determined. FIG. 4 is a flow chart showing the process of server 2000 determining a curve to which attention should be paid when driving.

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

In the next step S32, the skilled driver extracted in step S30 extracts a curve determined as an unskilled driver. The lower part of FIG. 5 shows how the expert driver A, the expert driver B, the expert driver C, . Skilled Driver A, Skilled Driver B, and Skilled Driver C are judged to be skilled drivers on curves of 60% or more, but for Curves 2 and 3, the skilled driver is judged to be unskilled. For this reason, curves 2 and 3 are difficult curves even for experienced drivers A to C, and are extracted as curves that require caution.

In the next step S34, the unskilled determination ratio for the curve extracted in step S32 is calculated. The unskilled determination ratio for each 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 , three skilled drivers out of four skilled drivers are determined to be unskilled at curve 3 . Therefore, the unskilled percentage for curve 3 is 3/4=0.75=75%. Similarly, for curve 2, one of the four skilled drivers is determined to be unskilled at curve 2. Therefore, the unskilled percentage for curve 2 is 1/4=0.25=25%.

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

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

In step S36, the unskilled percentage is determined based on one threshold value, and the difficulty level of the curve is determined in two stages. You may divide a difficulty level into three or more steps.

In the next step S40, the communication processing unit 2050 transmits the information of curve 3 registered in step S38 to each vehicle. In each vehicle, information is displayed on the in-vehicle display device 500 to the effect that curve 3 is a difficult curve that requires caution. The display on the in-vehicle display device 500 is controlled by the display control unit 408 . In the next step S42, when the vehicle travels on curve 3, the color of the display on the in-vehicle display device 500 is changed, or the speaker 900 notifies the driver by voice, etc., to call the driver's attention.

In the process of FIG. 4, curves to be careful are determined based on the drivers extracted as skilled drivers. The degree of difficulty of the curve may be determined based on the ratio of the determined persons. For example, if 20% of the drivers on a certain curve are determined to be skilled drivers and 80% of the drivers are determined to be unskilled drivers, then that curve can be determined as a curve that requires caution. .

Next, based on FIGS. 6 and 7, the process of selecting a route that is slightly more difficult than the driver's driving level will be described. 6 and 7 are mainly performed by the route selection section 2040. FIG. FIG. 6 is a flow chart showing the process of determining the level of the driver. According to this processing, it is possible to improve the driving of the driver and to provide the pleasure of driving.

First, in step S50, the ratio of skilled and unskilled judgment results (skilled ratio J) at each curve is calculated for the driver whose level is to be judged. The skill ratio is the ratio of the number of curves determined to be skilled to the total number of curves determined 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 level of the driver is determined to be level 1. After step S54, the process advances to step S56, and the route selection unit 2040 selects a route including curves of unskilled determination percentage level 2. FIG. Information on 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>proficiency ratio J≧0 is not satisfied in step S52, the process proceeds to step S58. In step S58, it is determined whether or not 66>skilled ratio J≧33, and if 66>skilled ratio J≧33, the process proceeds to step S60. In step S60, the level of the driver is determined to be level 2. After step S60, the process proceeds to step S62 to select a route including a curve with an unskilled judgment percentage level 3. After step S62, the process ends.

If 66>proficiency ratio J≧33 is not satisfied in step S58, the process proceeds to step S64. In step S64, it is determined whether or not 100≧skilled ratio J≧66, and if 100≧skilled ratio J≧66, the process proceeds to step S66. In step S66, the level of the driver is determined to be level 3. After step S66, the process proceeds to step S68 to select a route including a curve with an unskilled judgment percentage level 4. After step S62, the process ends.

Here, it is assumed that driver level 1 corresponds to unskilled determination level 1, driver level 2 corresponds to unskilled determination level 2, and driver level 3 corresponds to unskilled determination level 3. Then, when the driver's level and the unskilled determination level are the same, it is assumed that the vehicle can travel along a curve that corresponds to the skill of the driver. Based on this premise, in the process of FIG. 6, a route including a curve with an unskilled judgment percentage level one step higher than the driver's level is selected. Therefore, by selecting a route that is slightly more difficult than the driving level of the driver, it is possible to improve the driver's driving and provide driving pleasure.

FIG. 7 is a flowchart showing the processing of the curve level determination method, and shows the processing of determining the above-described unskilled determination percentage level. The processes of steps S70, S72, and S74 are performed in the same manner as steps S30, S32, and 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%. If the unskilled determination ratio H is 0, the process proceeds to step S78. In step S78, the non-skilled determination percentage 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 advances to step S80 to determine whether or not the unskilled determination ratio H calculated in step S74 satisfies 33>unskilled ratio H≧0. If the unskilled rate H≧0, the process proceeds to step S82. In step S82, the non-skilled determination percentage level is determined to be "2". After step S82, the process ends.

If it is not 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 non-skilled determination percentage level is determined to be "3". After step S86, the process ends.

If 66>unskilled ratio H≧33 is not satisfied 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 percentage 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 above with reference to the accompanying drawings, the present invention is not limited to such examples. It is obvious that a person having ordinary knowledge in the technical field to which the present invention belongs can conceive of various modifications or modifications within the scope of the technical idea described in the claims. It is understood that these also naturally belong to the technical scope of the present invention.

2000 server 2010 skill acquisition unit 2020 difficulty level determination unit 2030 skilled driver extraction unit 2040 route selection unit

Claims (7)

a proficiency acquisition unit that acquires the driving proficiency of the driver traveling on a curve;
a skilled driver extracting unit for extracting, as skilled drivers, drivers who are determined to be skilled drivers on the basis of the skill levels obtained from the plurality of drivers;
a difficulty determination unit that determines the difficulty of the curve based on the skill levels obtained from a plurality of drivers and the extraction results of the skilled drivers ;
with
The difficulty level determination unit determines the difficulty level of the curve based on the ratio of the number of skilled drivers determined as unskilled drivers to the total number of skilled drivers on each curve. , driving information processing device. 2. The driving information processing apparatus according to claim 1 , wherein information about the degree of difficulty of the curve is transmitted to each vehicle. The skill level and the difficulty level are associated according to the level,
3. The driving information processing apparatus according to claim 1, 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 according to the level,
5. The driving information processing apparatus according to claim 4 , 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. the computer
obtaining the driving proficiency of the driver while traveling on a curve;
a step of extracting, as a skilled driver, a driver who is determined to be a skilled driver on the basis of the skill levels obtained from the plurality of drivers;
Determining the difficulty level of the curve based on the skill levels obtained from a plurality of drivers and the extraction results of the skilled drivers ;
and run
The step of determining the difficulty level of the curve includes determining the difficulty level of the curve based on the ratio of the number of skilled drivers determined as unskilled drivers to the total number of skilled drivers on each curve. A driving information processing method characterized by: Means for acquiring driving proficiency of a driver while traveling on a curve;
A means for extracting, as a skilled driver, a driver determined to be a skilled driver on the basis of the skill levels obtained from the plurality of drivers, with a predetermined ratio or more of curves out of the plurality of curves;
means for determining the degree of difficulty of the curve based on the skill levels obtained from a plurality of drivers and the extraction results of the skilled drivers ;
make the computer function as
The means for determining the degree of difficulty of the curve is a program for determining the degree of difficulty of the curve based on the ratio of the number of skilled drivers determined as unskilled drivers to the total number of skilled drivers on each curve.

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