KR101116330B1 - Advanced apparatus for navigation - Google Patents

Abstract

The present invention relates to an improved navigation device. More specifically, the present invention relates to a device for performing a road guidance using an avatar from an navigation device to a destination. In addition, the present invention relates to an apparatus for inducing a user to drive a safe driving by displaying a degree of safe driving according to a user's driving situation.
In the present invention, a navigation device, a navigation device for displaying an avatar road guidance screen for performing a road guide using an avatar, and a navigation device, the navigation device comprising a means for expressing the risk of an accident to a driver The device is presented.

Description

Advanced apparatus for navigation

The present invention relates to an improved navigation device. More specifically, the present invention relates to a device for performing a road guidance using an avatar from an navigation device to a destination. In addition, the present invention relates to an apparatus for inducing a user to drive a safe driving by displaying a degree of safe driving according to a user's driving situation.

A vehicle navigation system refers to a system that selects a route from a current location to a destination and then guides a road. The navigation system consists of GPS, electronic maps (including optimal path calculation programs), DMB, video, audio, and car account book.

Navigation systems are equipped with a variety of processes as performance increases. In particular, the navigation function is the main function of the navigation, and provides specific information to the user using a pop-up screen or a static screen to display the navigation information status.

The way of providing the guidance information has a problem in that the user's eyes are out of concentration in front of the user in order to recognize the text of the pop-up screen.

In addition, there is a need to avoid boring driving and provide a pleasant driving environment by providing information in a three-dimensional and active manner rather than providing a flat road guide.

In addition, it is necessary to enable the driver to be provided with improved safe driving information reflecting his or her driving habits rather than providing partial road guide information.

The present invention is to solve the above problems, the present invention, to guide the road by using the movement of the avatar (avatar) in order to entertain the eyes of the user, the degree of safe driving according to the driving conditions of the user, etc. It is an object of the present invention to provide a device that allows a user to induce safe driving by displaying it to the user.

As a technical idea for achieving the above object, in the present invention,

As a first aspect,

In the navigation device,

A navigation device for displaying an avatar directions screen for performing directions using an avatar is provided.

In addition, the avatar is characterized in that the body takes action according to the guidance information,

In addition, the body movement is characterized in that any one of danger, caution, warning, slow, direction indication, direction unknown,

The avatar may indicate whether the driver is driving safely by using a facial expression.

In addition, the facial expression of the avatar is characterized in that any one of joy, basic, sadness, fear, surprise, anger,

In addition, the facial expression of the avatar is characterized in that it is determined according to the value determined according to the driving situation of the driver,

In addition, the driving situation of the driver is characterized in that any one or more of the details of the driving cumulative time, the number of rapid acceleration, the speed exceeded number,

In addition, the value determined according to the driver's driving situation,

It is characterized by the following equation.

[Equation]

G = (k-Mi) / Ma

k = (y ₁ +… + y _n ) / n (where k = y ₁ if n = ₁ )

y _j = σ _j * x _j

Ma = (Max (V ₁ ) +… + Max (V _n )) / n (where Ma = Max (V ₁ ) when n = 1)

Mi = (Min (V ₁ ) +… + Min (V _n )) / n (but if Mi = 1, Mi = Min (V ₁ ))

Where G is a value determined according to the driver's driving situation, n is a positive integer, the number of subitems, Max (V) is the maximum accident rate for the subitem, and Min (V) is the minimum for the subitem. Incident incidence rate, σ is the standard deviation for the sub-items, x is the accident incidence rate of the factor determined among the sub-items, and j is a positive integer from 1 to n.

As a second aspect,

In the navigation device,

A navigation device is provided, comprising a means for expressing any one or more of the driving risk determined using the driving experience information, the driving risk determined using the driving time information, and the driving risk determined using the driving situation information. ,

In addition, the driving experience information includes any one or more of age, driving experience, the number of years of license acquisition, the driving time information includes any one or more of the season, day of the week, time zone, the driving situation information includes the number of rapid acceleration, Characterized in that it includes any one or more of the speed exceeded, the accumulated operation time,

In addition, the driving risk is characterized in that determined by the following equation,

[Equation]

G = (k-Mi) / Ma

k = (y ₁ +… + y _n ) / n (where k = y ₁ if n = ₁ )

y _j = σ _j * x _j

Ma = (Max (V ₁ ) +… + Max (V _n )) / n (where Ma = Max (V ₁ ) when n = 1)

Mi = (Min (V ₁ ) +… + Min (V _n )) / n (but if Mi = 1, Mi = Min (V ₁ ))

Where G is the driving risk, n is the positive integer, the number of subitems, Max (V) the maximum incident rate for the subitem, Min (V) the minimum accident rate for the subitem, and σ the detail The standard deviation for the item, x is the incident incidence of the factors determined from the subitems, and j is a positive integer from 1 to n, respectively.

In addition, the above details,

Include any one or more of your age, driving experience, or license years,

Include one or more of seasons, days of the week, or time zone,

It characterized in that it comprises any one or more of the number of rapid acceleration, the speed exceeded number, the driving cumulative time.

As a third aspect,

A first group comprising at least one of age, driving experience, or license years,

A second group containing at least one of seasons, days of the week, time zones,

      An apparatus for determining a driving risk of a driver is provided, wherein the driving risk is determined by using any one of a third group including at least one of a rapid acceleration count, a speed overrun count, and a driving accumulation time.

In addition, the driving risk may be determined by using a maximum accident occurrence rate and a minimum accident occurrence rate for a specific item among the one group, and an accident occurrence rate for a specific factor selected from the specific item.

As a fourth aspect,

An apparatus for determining a driver's driving risk using the following equation is provided.

[Equation]

G = (k-Mi) / Ma

k = (y ₁ +… + y _n ) / n (where k = y ₁ if n = ₁ )

y _j = σ _j * x _j

Ma = (Max (V ₁ ) +… + Max (V _n )) / n (where Ma = Max (V ₁ ) when n = 1)

Mi = (Min (V ₁ ) +… + Min (V _n )) / n (but if Mi = 1, Mi = Min (V ₁ ))

Where G is the driving risk, n is the positive integer, the number of subitems, Max (V) the maximum incident rate for the subitem, Min (V) the minimum accident rate for the subitem, and σ the detail The standard deviation for the item, x is the incident incidence of the factors determined from the subitems, and j is a positive integer from 1 to n, respectively.

In addition, the above details,

Include any one or more of your age, driving experience, or license years,

Include one or more of seasons, days of the week, or time zone,

It characterized in that it comprises any one or more of the number of rapid acceleration, the speed exceeded number, the driving cumulative time.

According to the present invention, it is effective to make the user forget boredom by performing the road guidance using the movement of a lively avatar, and also displays the risk according to the user's driving situation to the user so that the user is safe. It is effective to induce driving.

1 is a block diagram of a navigation device according to an embodiment of the present invention.
2 is a flowchart illustrating a way guidance method in a navigation device according to an embodiment of the present invention.
3 is an example of the operation of each avatar corresponding to the road guidance information.
4 is an example of facial expressions in a female avatar.
5 is an example of a facial expression in an avatar of a male figure.
6 is an example of a mouth shape of an avatar displayed on a display unit.
FIG. 7 is an example of an avatar route guide screen in which a facial expression of an avatar according to a risk for each habit is combined with a general route guide screen.
8 is an example of an avatar route guidance screen in which an operation state of an avatar according to a route guidance instruction is combined with a general route guidance screen.
9 is another example of displaying a risk for each classification.
10 is an example of an input interface for receiving a career-specific element.
11 is a view showing rapid acceleration information for each driving time.
12 is a view showing a change in the risk of each major category during driving according to the running time.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, configurations and operations of embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a block diagram of a navigation device according to an embodiment of the present invention.

As can be seen from the figure, the configuration is a GPS module 100 for generating general road guidance basic information such as the current position, time, speed based on the information received from the GPS satellites; An input unit 200 for inputting basic user information and function command of the user; A safe driving system 300 for generating information for inducing safe driving of a user; A route guidance system 400 for generating route guidance information; An avatar system 500 for generating an operation, facial expression, etc. of the avatar based on the information from the safe driving system and the road guidance system, and combining the avatar with a road guidance screen; And a display unit 600 for displaying the road guidance screen.

The GPS module 100 receives the satellite information from the GPS satellites, generates general road guide basic information such as current location, date, time, speed, and the like, and transmits the basic information to the safe driving system 300 and the road guide system 400. ).

The input unit 200 receives a destination and transmits it to a road guidance system, and receives a user's personal information to be described below and transmits it to a safe driving system.

The input unit may operate in a touch screen method or a voice recognition method.

The safe driving system 300 includes a career module 310, a time module 320, and a habit module 330, and calculates the calculated risks of the career, time, and habit of the avatar system 500. send.

The career module 310 receives a user's age, driving experience, license years, etc. from the input unit 200 to calculate a career percentage indicating the risk for each career.

The hourly module 320 receives the current date and time from the GPS module 100 and calculates an hourly percentage indicating an hourly risk.

The habit-specific module 330 receives the speed and time from the GPS module 100, calculates the number of accelerations and driving accumulation time, calculates the excess speed in conjunction with the road guidance system, and shows the risk for each habit. Calculate the star percentage.

The risk for each career, time, habit is calculated as described below.

First, Table 1 classifies by category, experience, time, and habits, and calculates the percentage of traffic accidents (that is, the probability of accidents is%) by the factors of each subclass belonging to each major category. Use).

These reference statistics are basically databased in the safe operation system.

Main Category Small classification Factor ＃ 1 Factor ＃ 2 Factor ＃ 3 Factor ＃ 4 Factor ＃ 5 Factor ＃ 6 Factor ＃ 7

By career By age Under 20 21-30 years old 31-40 years old 41-50 years old 51-60 years old 61 years old or older 6.2 26.9 28.4 20.7 14 3.8 By driving experience Less than 3 years 4-5 years 6 ~ 10 years 11-15 years 16-20 years Over 21 years 34.8 8.5 16.9 17.8 9 13 License years Less than 2 years 2-5 years 6 to 10 years 11-15 years 16-20 years Over 21 years Unlicensed 19.7 33.7 21.6 12.6 3.8 0.9 77

Hourly Seasonal spring summer autumn winter 36 20.7 18.3 25 By day month anger Number neck gold Sat Work 11.5 12.5 17.8 8.2 19.2 16.4 14.4 Hourly morning afternoon dinner dawn 14.4 17.3 29.8 38.5

By habit Rapid acceleration 0 1 ~ 2 times 3 ~ 4 times 5 or more times 10 20 32 38 Per speed exceeded 0 1 ~ 2 times 3 ~ 4 times 5 or more times 10 20 32 38 By driving time in 1 hour 1-2 hours 3-4 hours More than 5 hours 10 20 32 38

Based on Table 1 above, Table 2 below is generated.

Main Category Small classification Maximum value Minimum Standard Deviation By career By age 31-40 years old 61 years old or older 9.5 By driving experience Less than 3 years 4-5 years 8.8 Year of License 2-5 years Over 21 years 10.7 Hourly Crab spring autumn 6.8 By day Friday Thursday 3.6 Hourly dawn morning 9.7 By habit Rapid acceleration 5 or more times 0 10.8 Per speed exceeded 5 or more times 0 10.8 By driving time More than 5 hours in 1 hour 10.8

The larger the difference in value between the factors in Table 1, the higher the standard deviation. In particular, the standard deviation is measured as 3.6 because the difference between the days of the week is not big in the major category by hour, and the standard deviation is measured as 10.8 because the small category by rapid acceleration / speed exceeded / operation time has a large deviation per factor.

Using Tables 1 and 2 above, the following equations can be used to determine the percentages for major categories of risk by major categories.

[ Equation  One]

y ₁ = (σ ₁ * x ₁ ), y ₂ = (σ ₂ * x ₂ ), y ₃ = (σ ₃ * x ₃ )

y ₄ = (σ ₄ * x ₄ ), y ₅ = (σ ₅ * x ₅ ), y ₆ = (σ ₆ * x ₆ )

y ₇ = (σ ₇ * x ₇ ), y ₈ = (σ ₈ * x ₈ ), y ₉ = (σ ₉ * x ₉ )

k ₁ = (y ₁ + y ₂ + y ₃ ) / 3

k ₂ = (y ₄ + y ₅ + y ₆ ) / 3

k ₃ = (y ₇ + y ₈ + y ₉ ) / 3

Ma ₁ = (Max (V ₁ ) + Max (V ₂ ) + Max (V ₃ )) / 3

Mi ₁ = (Min (V ₁ ) + Min (V ₂ ) + Min (V ₃ )) / 3

Ma ₂ = (Max (V ₄ ) + Max (V ₅ ) + Max (V ₆ )) / 3

Mi ₂ = (Min (V ₄ ) + Min (V ₅ ) + Min (V ₆ )) / 3

Ma ₃ = (Max (V ₇ ) + Max (V ₈ ) + Max (V ₉ )) / 3

Mi ₃ = (Min (V ₇ ) + Min (V ₈ ) + Min (V ₉ )) / 3

H ₁ = (y ₁ -Min (V ₁ )) / Max (V ₁ )

......

H ₉ = (y ₉ -Min (V ₉ )) / Max (V ₉ )

G ₁ = (k ₁ -Mi ₁ ) / Ma ₁

G ₂ = (k ₂ -Mi ₂ ) / Ma ₂

G ₃ = (k ₃ -Mi ₃ ) / Ma ₃

Where σ is the standard deviation for the small category, x is the probability of accident for a specific factor belonging to a particular category, y is the minor classification weight for a specific factor, k is the major classification weight for a major category, and V is For a particular category of subclasses, H represents the percentage for the subclass, which is the risk for each subcategory, and G represents the major category, the risk for each of the major categories.

Tables 3, 4, and 5 show examples of obtaining the major classification percentages, which are the major classification risks calculated by the user's A, B, and BASIC risk calculation basic data.

Here, the selection by career in the selection column is an item directly input by the user, the selection by time may be determined through the GPS module, and the selection by habit may be changed according to the current driving situation of the user. In addition, the probability of selection indicates the probability of occurrence of an accident with respect to the factor (the factors in Table 1) to which the selected content belongs.

Main Category Small classification Selection Selection probability Small classification weight Small classification percentage Major classification weight Major classification percentage By career By age 34 years old 28.4 269.64 86.6 553.36 46.2 By driving experience 10 years 16.9 149.43 24.1 Year of License 15 years 12.6 134.28 34.7 Hourly Seasonal winter 25 169.73 18.6 517.48 32.7 By day Saturday 16.4 58.467 42.7 Hourly dinner 29.8 289.28 40 By habit Rapid acceleration number 1 20 216.33 26.3 908.6 47.4 Per speed exceeded number 3 32 346.13 57.9 By driving time 3 hours 32 346.13 57.9

Main Category Small classification Selection Selection probability Small classification weight Small classification percentage Major classification weight Major classification percentage By career By age 24 years old 26.9 255.4 81.3 922.3 85.6 By driving experience 2 years 34.8 307.7 75.6 Year of License 3 years 33.7 359.16 97.3 Hourly Seasonal summer 20.7 140.54 6.67 371.9 11.5 By day Wednesday 17.8 63.458 50 Hourly afternoon 17.3 167.94 7.53 By habit Rapid acceleration number 3 32 346.13 57.9 973.5 52.6 Per speed exceeded 5 times 38 411.03 73.7 By driving time 2 hours 20 216.33 26.3

Main Category Small classification Selection Selection probability Small classification weight Small classification percentage Major classification weight Major classification percentage By career By age 45 years old 20.7 196.5 59.51 480.25 38.38 By driving experience 7 years 16.9 149.4 24.14 Year of License 15 years 12.6 134.3 34.72 Hourly Seasonal autumn 18.3 124.2 0 538.98 35.79 By day Monday 11.5 41 17.19 Hourly dawn 38.5 373.7 62.6 By habit Rapid acceleration 0 10 108.2 0 463.67 8.772 Per speed exceeded 0 10 108.2 0 By driving time 1 hours 20 216.3 26.32

The route guidance system 400 generates general route guidance screen information and text information including the found route and route guidance information according to the route and transmits the generated route information to the avatar system.

The route search module 410 receives a destination from the input unit 200 and searches for a route from the current location to the destination.

The route guidance module 420 generates avatars by textually generating route guidance information (speeding camera alert, signal speeding alert, traffic collection information, accident occurrence region notification, sudden curve alert, direction indication, etc.) along the searched route. Transfer it to the system.

The avatar system 500 receives information from the safe driving system 300 and the road guidance system 400 to generate an avatar or pop-up screen corresponding to the information, and guides the generated avatar or pop-up screen to a general road guide. It is displayed on the display unit 600 in combination with the screen.

The operation module 510 determines the operation of the avatar.

Table 6 below shows avatar behaviors determined in response to general directions received from the directions system.

3 is an example of the operation of each avatar corresponding to Table 6. FIG.

Information type Avatar action Fixed Unmanned Camera going slow Mobile Unmanned Enforcement Camera going slow Signal crackdown caution Bus lane warning Accident area danger A sharp curve danger Highway rest area going slow tunnel caution Toll gate going slow Direction Direction sign

The facial expression module 520 determines the facial expression of the avatar.

The facial expressions of the avatars are determined by joy, basic, sadness, fear, surprise, anger, etc. according to the large percentage of habits calculated by the safe driving system.

4 is a facial expression in the avatar of a female figure, and FIG. 5 shows an example of a facial expression in the avatar of a male figure.

If driving habit classification calculated by the module for each habit 330 is often less than 20% based on the driving, the face expression of joy is displayed as safe driving, and if more than 20%, each 10% In each section, facial expressions are determined by basic (20-30%), sadness (30-40%), etc., and when exceeding 60%, an facial expression is determined and displayed on the display unit.

The TTS module 530 receives the major classification risks from the safe driving system 300 and the road guide information text from the road guidance system 400, converts them into voices, and outputs them through the display unit. In order to correspond, the shape of the avatar is determined and displayed through the display unit.

6 shows an example of the shape of the avatar of the avatar displayed on the display unit.

The display unit 600 receives a screen signal and a voice signal from the avatar system, and displays an avatar route guidance screen and a voice including an avatar.

FIG. 7 illustrates an example of an avatar route guide screen in which a facial expression of an avatar according to a risk for each habit is combined with a general route guide screen.

FIG. 7 illustrates a joy state among six facial expressions, and indicates that the user is well driving safely. In addition, the voice "I am happy to drive safely" may be output together with the voice.

8 illustrates an example of an avatar route guidance screen in which an operation of an avatar according to a route guidance instruction is combined with a general route guidance screen.

As shown in FIG. 8, by displaying the direction of the avatar and the operation of the avatar by synchronizing the avatar operation with the direction of the directions, the direction to go to the user can be effectively transmitted.

9 shows another example in which the risk level for each major category is displayed to the user. A pop-up window showing the risk indicator is located on the right side of the screen, and the avatar is displayed on the right side.

In the case of Table 3, 46.2% of risks by career, 32.7% of risks by hour, and 47.4% of risks by habit will be represented. ).

2 is a flowchart illustrating a way guidance method in a navigation device according to an embodiment of the present invention.

First, a career-specific element is received from the user through the input unit 200 (S210). 10 shows an example of the input interface.

For example, the touch screen screen is displayed, and the user selects the corresponding item. As an input method, an input method using voice recognition may be used. In this case, a corresponding item is selected based on a user's voice input. In other words, if the user says "age is 24 years old", the input unit recognizes and analyzes the voice and treats the item as 21 to 30 years old.

Next, the destination is input by a touch screen method or a voice recognition method (S220).

Next, the route from the current location to the destination is searched using the provided electronic map (S230).

Next, the road guidance is started (S240).

Next, the safe driving situation is displayed during the road guidance (see FIGS. 7, 8, and 9).

At this time, the risk of each habit is changed according to the driving time. That is, as the driving time is accumulated in the habit-specific module, the weight for each driving time is calculated according to the driving time, and the risk is calculated according to the number of speed exceeded and the rapid acceleration during driving measured based on the received speed information. Major classification risks change from time to time to reflect on the facial expressions of the avatar.

In some cases, if the driving time zone is changed from AM to PM due to long driving, the risk may be affected as much as the change factor, and the change value will be displayed on the avatar guidance screen.

11 is a view showing rapid acceleration information for each driving time.

As a criterion of rapid acceleration, a difference of more than 10 km / h from the previous speed was assumed, and it can be seen that a total of six rapid accelerations occurred in the range of FIG. 11.

According to the example of Table 1 above, when the first, third and fifth sudden acceleration occurs, the small classification risk by rapid acceleration will be affected, and thus the large classification risk by habit will be affected.

12 is a diagram showing the risk of each major category during driving according to the running time.

The risk level by career and time is maintained at a constant risk level because no change factor occurs, and the risk level by habit indicates that the risk level is changing according to the number of rapid accelerations, speed excesses, and accumulated driving time.

Finally, all procedures are terminated by reaching the destination (S260).

In the above embodiment, it was implemented using .NET (Visual Studio .NET 2005) in the WINCE Windows platform.

The embodiments of the present invention have been described in detail above, and the protection scope of the present invention is not limited to the above embodiments, and the ordinary skilled artisan also has a configuration that can be easily modified from this embodiment, and the protection of the present invention. The scope is defined by the claims set forth below.

Therefore, in the above, the information on the safe driving situation is provided to the user using the avatar, but it is natural that the vehicle management information may be provided to the user using the avatar.

The present invention performs the road guidance using the movement of the avatar (avatar) in order to entertain the user's eyes, and the user to induce safe driving by displaying the degree of safe driving according to the user's driving situation, etc. In order to enable the application program to be used in addition to the existing navigation device, it can be usefully used in the navigation device and related program industries.

100: GPS module 200: input unit
300: safe driving system 400: road guidance system
500: avatar system 600: display unit

Claims (16)

In the navigation device,
Display the Avatar Directions screen, which uses the avatar to navigate.
The avatar indicates whether the driver is driving safely by facial expressions,
The facial expression of the avatar is determined according to a value determined according to the driver's driving situation,
The value determined according to the driving situation of the driver,
Navigation apparatus characterized in that determined by the following equation.
[Equation]
G = (k-Mi) / Ma
k = (y ₁ +… + y _n ) / n (where k = y ₁ if n = ₁ )
y _j = σ _j * x _j
Ma = (Max (V ₁ ) +… + Max (V _n )) / n (where Ma = Max (V ₁ ) when n = 1)
Mi = (Min (V ₁ ) +… + Min (V _n )) / n (but if Mi = 1, Mi = Min (V ₁ ))
Where G is a value determined according to the driver's driving situation, n is a positive integer, the number of sub-items, Max (V) the maximum accident rate for the sub-item, and Min (V) the minimum for the sub-item. Incident incidence rate, sigma represents standard deviation for subitems, x represents an accident incidence rate of the factor determined among the subitems, and j represents a positive integer from 1 to n, respectively. The method according to claim 1,
The avatar is a navigation device, characterized in that to take a body action in accordance with the guidance information. The method according to claim 2,
The body movement is navigation device, characterized in that any one of danger, attention, warning, slow, direction indication, direction unknown. delete The method according to claim 1,
The facial expression of the avatar is a navigation device, characterized in that any one of joy, basic, sadness, fear, surprise, anger. delete The method according to claim 1,
The driving situation of the driver, the navigation device, characterized in that any one or more of the details of the cumulative driving time, the number of rapid acceleration, the speed exceeded. delete delete In the navigation device,
Means for expressing any one or more of the driving risk determined using the driving experience information, the driving risk determined using the driving timing information, and the driving risk determined using the driving situation information;
The driving risk is a navigation device, characterized in that determined by the following equation.
[Equation]
G = (k-Mi) / Ma
k = (y ₁ +… + y _n ) / n (where k = y ₁ if n = ₁ )
y _j = σ _j * x _j
Ma = (Max (V ₁ ) +… + Max (V _n )) / n (where Ma = Max (V ₁ ) when n = 1)
Mi = (Min (V ₁ ) +… + Min (V _n )) / n (but if Mi = 1, Mi = Min (V ₁ ))
Where G is the driving risk, n is the positive integer, the number of subitems, Max (V) the maximum incident rate for the subitem, Min (V) the minimum accident rate for the subitem, and σ the detail The standard deviation of the items, x represents the accident incidence of the factors determined among the subitems, and j represents a positive integer from 1 to n, respectively. The method according to claim 10,
The above details,
Include any one or more of your age, driving experience, or license years,
Include one or more of seasons, days of the week, or time zone,
Navigation device comprising any one or more of the number of rapid acceleration, the speed exceeded number, the cumulative driving time. delete delete delete delete The method according to claim 10,
The driving experience information includes any one or more of age, driving experience, license years,
The driving time information includes any one or more of seasons, days of the week, time zones,
And the driving status information includes any one or more of a rapid acceleration count, a speed exceeded count, and a driving cumulative time.

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