JP5838577B2 - Travel evaluation device - Google Patents

Description

  The present invention relates to a traveling evaluation technique for evaluating the smoothness of traveling of a host vehicle. In particular, the present invention is suitable for evaluating the smoothness of traveling while traveling against obstacles (such as preceding vehicles) around the host vehicle.

  The technique described in Patent Document 1 reads the position and time data from a storage device in which the position and time data of the moving body is stored based on the GPS reception information, and calculates the speed and acceleration. And the technique of patent document 1 produces | generates the diagnostic parameter | index regarding the moving characteristic (driving characteristic) of the driver who is the user of the said mobile body by carrying out the statistical process of the value of the calculated speed and acceleration.

JP 2008-276316 A

Acceleration and deceleration are limited in scenes such as when traffic signal signals change or near intersections, and there are few driving environments such as highways, arterial roads, and traffic signals that occupy a lot of cruising. On roads and the like, the frequency of acceleration and deceleration is low. As described above, since the evaluation is performed in a limited travel scene, there is a possibility that the evaluation result of the driving tendency is biased.
The present invention has been made in consideration of the above points, and an object of the present invention is to make it possible to more accurately diagnose the traveling tendency of the host vehicle.

In order to solve the above-described problems, the present invention provides a travel evaluation device that evaluates the smoothness of travel of the host vehicle when the host vehicle follows the preceding vehicle, and the vehicle speed of the host vehicle per unit time that is set in advance. A behavior index value acquisition unit that acquires the relationship between the vehicle and the jerk, and obtains a diagnostic value from the acquired relationship , and compares the diagnostic value with a preset reference comparison value, thereby automatically A travel evaluation unit that evaluates the smoothness of travel of the vehicle, and the behavior index value acquisition unit targets only the jerk on the deceleration side as the jerk of the host vehicle, and the jerk on the deceleration side includes an accelerator pedal. This includes that caused by deceleration when the operation is performed .

According to the present invention, even when there is no information on the inter-vehicle distance from the preceding vehicle, the traveling tendency can be evaluated when following the preceding vehicle .

It is a conceptual diagram explaining the structure of the driving | running | working evaluation apparatus which concerns on embodiment based on this invention. It is a figure explaining the structure of the information processing part which concerns on embodiment based on this invention. It is a figure which shows the example of how to obtain | require a reference | standard comparison value. It is a figure which shows an example of a reference | standard comparison value. It is a figure explaining the structure of a diagnostic server. It is a figure explaining the process of a diagnostic calculating part. It is a figure which shows the example of the jerk regression value and deviation value of the own vehicle made into object. It is a figure which shows the example of a display of evaluation shown to a driver | operator. It is a figure which shows the relationship between speed and the jerk integral value for every diagnostic time, Comprising: (a) is time series data in all the sections, (b) is the jerk regression line in some sections, (c) is all The jerk regression line in each section is shown. It is a figure which shows the relationship between the vehicle speed and the jerk integral value in a some driver | operator. It is a figure which shows the relationship between the distance between vehicles in a several driver | operator, and a jerk integral value.

Next, embodiments of the present invention will be described with reference to the drawings.
FIG. 1 is a system configuration diagram including a travel evaluation apparatus according to the present embodiment.
(Constitution)
In the host vehicle of this embodiment, the vehicle behavior is controlled in a state corresponding to the driving operation of the driver. The host vehicle includes a drive control device and a braking control device. The drive control device controls a drive source such as an engine or a motor so as to obtain a target drive force according to the accelerator opening of the accelerator pedal operated by the driver. The braking control device controls the braking device of each wheel so as to obtain a target braking force according to the brake opening degree of the brake pedal operated by the driver. Further, the steering device steers the steered wheels according to the steering angle of the steering wheel operated by the driver.

In addition, the host vehicle MM includes a vehicle speed sensor 1 that detects the vehicle speed, as shown in FIG. The vehicle speed sensor 1 detects the vehicle speed information of the host vehicle MM for each preset control time by detecting, for example, the number of rotations of the wheels 2. The vehicle speed sensor 1 also outputs the detected vehicle speed information to the information processing unit 3 described later.
The host vehicle MM of this embodiment includes an information processing unit 3. The information processing unit 3 is a controller that includes a microcomputer and its peripheral circuits. As shown in FIG. 2, this information processing unit 3 is functionally configured to include at least a vehicle speed calculation unit 3A, a jerk value calculation unit 3B, a vehicle information generation unit 3C, and a vehicle information input / output unit 3D. Yes.

The vehicle speed calculation unit 3A calculates the vehicle speed of the host vehicle MM every control time (for example, 50 msec) based on the vehicle speed information from the vehicle speed sensor 1.
The jerk value calculation unit 3B executes a calculation process for differentiating the vehicle speed value for each control time calculated by the vehicle speed calculation unit 3A twice, and sets the jerk value (the jerk) every preset calculation time (for example, 100 msec). Value). Here, the acceleration direction is positive. The jerk value calculation unit 3B acquires acceleration information for each preset control time from an acceleration sensor (gyro) equipped in the navigation device, and calculates a jerk value for each preset calculation time from the acquired acceleration information. You may do it.

The vehicle information generation unit 3C generates diagnostic information data including a set of the vehicle speed (own vehicle speed) of the host vehicle MM and the jerk-related value every preset diagnosis time (for example, 1 minute).
In the present embodiment, the host vehicle speed serving as the diagnosis information is an average value of the vehicle speed during the diagnosis time. As the own vehicle speed serving as the diagnosis information, a vehicle speed at the start time or end time of the target diagnosis time, a maximum speed or a minimum speed in the target diagnosis time, and the like may be used.

In addition, the jerk-related value in the present embodiment is an integral value of each jerk value (absolute value) generated at the target diagnosis time. The jerk relationship value, Ja chromatography click value generated diagnosis time of interest may be an average value (an absolute value), (an absolute value) Ja chromatography click value generated diagnosis time to the subject it may be the frequency of occurrence of a preset threshold value or more sizes of Jia over click value among.
Here, the diagnostic information data generated by the vehicle information generation unit 3C may include information such as own vehicle position information in addition to data consisting of a set of the own vehicle speed and the jerk relation value.

In the present embodiment, the smoothness of traveling during traveling in the evaluation of traveling tendency is targeted. Diagnostic data of travel evaluation items other than smoothness evaluation other than smoothness evaluation (for example, rapid acceleration, rapid deceleration, sudden steering, continuous operation time, overspeed, etc.) may be included.
The transmission of the diagnostic information or the generation of the diagnostic information is performed only when the vehicle speed of the host vehicle MM is equal to or higher than a preset information acquisition vehicle speed (for example, 50 km / h or higher).
The vehicle information input / output unit 3D has a wireless communication function, and transmits the diagnosis information data generated by the vehicle information generation unit 3C to the diagnosis server 5 through the communication network together with the vehicle identification information of the host vehicle MM. The diagnosis information data may be transmitted for each of a plurality of data.

  The vehicle information input / output unit 3D transmits a diagnosis request signal to the diagnosis server 5 via the communication network. When the vehicle information input / output unit 3D receives the diagnosis result information from the diagnosis server 5 in response to the diagnosis request signal, the vehicle information input / output unit 3D outputs the diagnosis result information to the display unit 4 to notify the driver of the diagnosis result. To do. The transmission of the diagnosis request signal may be output by a driver's operation, or may be performed when a preset number of information data is acquired from the start of diagnosis or when a preset time (for example, 30 minutes) has elapsed. The diagnosis request signal may be transmitted continuously.

The diagnostic server 5 sequentially accumulates the transmitted diagnostic information for each vehicle in the diagnostic information accumulation database 6. The database 6 also stores reference comparison values used for diagnosis.
The reference comparison value of the present embodiment was set as follows. In the figure, “1 minute jerk” indicates a jerk integral value for each diagnosis time (1 minute in the present embodiment).

First, as shown in FIG. 3 (a), data consisting of a set of an average vehicle speed for each diagnostic time when driving on a highway and a jerk relation value consisting of a jerk integral value is collected until a statistically significant number is exceeded. To do. This is done for each driver. The collected data is statistically processed.
Specifically, for each driver, as shown in FIG. 3B, a regression line represented by the following equation using the average vehicle speed x and the jerk integral value y as variables was obtained.
y = −ax + b

  Next, using a plurality of regression lines (jerk regression lines) obtained for each driver, a plurality of vehicle speeds for diagnosis (in this embodiment, 70, 80, 90, 100, 110 (in this embodiment) The unit is km / h)), and the average and deviation of the jerk integral value (jerk regression value) are obtained, and the average and deviation of the jerk integral value for each vehicle speed are stored in the database 6 as the reference comparison value. Remember. An example of the reference comparison value is shown in FIG.

The jerk regression value is a value on the jerk regression line. A regression line for the jerk relation value is called a jerk regression line. Two variables are required for the regression line, but in the present embodiment, an example is described in which the jerk relation value (the jerk integral value is taken as an example) and the speed are variables.
Moreover, the jerk regression line corresponding to the reference | standard comparison value of this embodiment can be represented, for example with a following formula.
y = −0.0063x + 1.0254
here,
x: Vehicle speed y: Jerk integral value in diagnosis time unit.

As shown in FIG. 5, the diagnostic server 5 includes a diagnostic information storage unit 5A, a diagnostic calculation unit 5B, and a diagnostic result information transmission unit 5C.
The diagnostic information storage unit 5A stores the received diagnostic information data in the database 6 in association with the vehicle identification information. In addition to the vehicle identification information, the driver identification information may be included.
The diagnosis calculation unit 5B evaluates the traveling tendency of the host vehicle MM for the smoothness of the traveling while the host vehicle MM is traveling.

The processing of the diagnostic calculation unit 5B will be described with reference to FIG.
The diagnosis calculation unit 5B operates when a diagnosis request signal is received.
When operated, the diagnostic calculation unit 5B acquires a set of diagnostic information data associated with the corresponding vehicle identification information from the database 6 as a population in step S10.
Further, in step S20, statistical processing is performed on the set of diagnostic information data acquired in step S10, thereby calculating jerk regression line variables A and B that can be expressed by the following equations.
y = −Ax + B

Next, in step S30, based on the jerk regression line in which variables A and B are determined in step S20, x (= vehicle speed) is set in advance for a plurality of diagnostic vehicle speeds (70, 80, 90, 100, 110 (km / h)), y (= jerk regression value) is calculated.
Next, in step S40, the deviation value of the corresponding vehicle is calculated for each of a plurality of (5 in the present embodiment) vehicle speeds for diagnosis.
The deviation value is calculated by the following formula, for example.
Deviation value = 50-[((Jerk regression value of the target vehicle)
-(Jerk regression value of reference comparison value)) x constant / deviation]
Here, in the present embodiment, the constant is set to “10”.

For example, when the reference comparison value is FIG. 4 and the jerk regression value for each vehicle speed of the target vehicle is FIG. 7, the deviation value shown in FIG. 7 is calculated for each diagnostic vehicle speed. Since a regression value, the actual Ja over click integral value at each vehicle speed for diagnosis is not always there is a statistically significant number only data.
Next, in step S50, an average value of deviation values for each of the plurality of diagnostic vehicle speeds obtained in step S40 is obtained.
In the example of FIG. 7, the average value of the deviation values is 53.3.
Here, the center of the deviation value is 50 points, and it is difficult to understand as an evaluation if the numerical value is used as it is.

For this reason, in step S60, a value obtained by adding the raised points to the average value of the deviation values as shown in the following equation is set as an evaluation value D of running smoothness. Note that “15” as the raising point is an example, and other values may be used, and the raising is not necessarily required.
D = (average deviation value) +15
The diagnosis result information transmission unit 5C transmits the evaluation value D calculated by the diagnosis calculation unit 5B to the diagnosis request destination through the communication network.

(Operation other)
The own vehicle MM generates diagnostic information data consisting of a set of (average speed, jerk relation value) at every predetermined diagnosis time interval (for example, 1 minute) when the own vehicle speed is equal to or higher than the information acquisition vehicle speed. Then, the generated diagnostic information data is transmitted to the diagnostic server 5 by wireless communication. The road infrastructure may be used for wireless communication.
Here, the generation of the diagnostic information data may be started when the host vehicle MM exceeds the preset information acquisition vehicle speed, or may be started by a driver's switch operation. Further, resetting of diagnostic information data and the like may be performed by a driver's switch operation. Further, for example, it may be configured to automatically delete diagnostic information data after elapse of a preset time (for example, three weeks).

The diagnostic server 5 sequentially accumulates the diagnostic information data received for each vehicle in the database 6.
Further, when receiving the diagnosis request signal, the diagnosis server 5 uses the diagnosis information data group corresponding to the corresponding vehicle identification to obtain the jerk regression line of the corresponding vehicle. Subsequently, the diagnosis server 5 obtains a jerk regression value of the corresponding vehicle for each diagnostic vehicle speed set in advance from the jerk regression line, and further compares it with a preset reference comparison value to thereby evaluate the corresponding vehicle evaluation value D. And the diagnosis result value D is transmitted to the request destination.

The host vehicle MM that has received the evaluation value D displays the evaluation value D on the display unit 4. FIG. 8 shows a display example of evaluation notification to the driver.
At this time, when the evaluation value D is continuously received and displayed, when the evaluation value D becomes smaller than a preset gradient, the driver may be notified by a warning display or a warning. .
The driver can evaluate the traveling tendency with respect to the smoothness of traveling while the host vehicle MM is traveling by the evaluation value D. In this case, unless the host vehicle MM is traveling automatically, the evaluation of the traveling tendency of the host vehicle MM is the driver's driving evaluation.
Here, the generation of the diagnostic information data may be performed only when an accelerator pedal or a brake pedal is operated, for example.

Further, the diagnosis request signal is not limited to transmission from a corresponding vehicle. A user may connect a terminal 10 such as a personal computer or a mobile phone to the diagnostic server 5 through a communication network, and transmit a diagnostic request signal together with vehicle identification information to the diagnostic server 5. In this case, the evaluation value D of the diagnosis result is transmitted to the personal computer.
Here, when the jerk integral value and the vehicle speed for each minute (diagnostic time unit) when a specific driver travels on the expressway were obtained, the result shown in FIG. 9A was obtained.

  The evaluation shown in FIG. 9B shows the jerk regression line up to the middle section, and the evaluation shown in FIG. 9C shows the jerk regression line in all the target sections. In the evaluation shown in FIG. 9C, it is considered that the evaluation of smoothness can be expressed with higher accuracy by the amount of diagnosis information data. However, as in the evaluation shown in FIG. 9B, it is possible to obtain the same tendency as the evaluation with the diagnostic information data in all sections (the evaluation in FIG. 9C) even from only the diagnostic information data up to the middle. I understand that I can do it. As shown in FIG. 9 (a), the vehicle speed variation is larger in the latter half of the section than in the first half of the section. It turns out that evaluation is possible.

FIG. 10 is a plot of the relationship between the vehicle speed per unit time and the jerk integral value for a plurality of drivers.
As can be seen from FIG. 10, it can be seen that jerk tends to increase as the vehicle speed decreases due to a short inter-vehicle distance from the preceding vehicle. As described above, the diagnosis information data including (average speed, jerk-related value) is a smoothness of traveling (driving) during traveling of the host vehicle MM with respect to the traveling environment (obstacle, preceding vehicle, passing vehicle, etc.) around the vehicle. That is, it can be seen that the value can be used as an indicator of the driving tendency.

Also, it can be seen from FIG. 10 that the tendency of jerk varies depending on the driver. Therefore, it is understood that the target driver can be evaluated by comparing with a specific reference position such as an average value of a plurality of drivers.
FIG. 11 shows the inter-vehicle distance and the jerk integral value for the preceding vehicle by the same driver group. FIG. 11 shows the traveling tendency of the host vehicle MM when following the preceding vehicle, and it can be seen that the jerk integral value tends to increase as the host vehicle MM is approached (the distance between the vehicles is smaller). .

And when FIG. 10 is compared with FIG. 11, it turns out that the tendency of the specific driver with respect to the driving | running | working tendency of a several driver | operator has the same tendency as FIG. 10 and FIG. For example, a driver whose data is relatively concentrated in the lower left in FIG. 10 has data concentrated relatively in the lower left in FIG.
From this result, it can be seen that the evaluation based on the diagnostic information data composed of the above (average speed, jerk relation value) also shows the running characteristics when following the preceding vehicle. That is, it is understood that the traveling tendency can be evaluated when following the preceding vehicle even if there is no information on the distance from the preceding vehicle by evaluating the traveling tendency based on the diagnostic information data consisting of (average speed, jerk relation value). .

As described above, it can be seen that the evaluation of the traveling tendency according to the present embodiment can evaluate the smoothness of the traveling (driving) while the host vehicle MM is traveling. In addition, this traveling evaluation can also evaluate the traveling tendency other than the traveling zone acquired for traveling evaluation.
Here, in the said embodiment, the case where the database 6, the diagnostic information storage part 5A, the diagnostic calculating part 5B, and the diagnostic result information transmission part 5C existed in the diagnostic server 5 outside a vehicle was illustrated. However, the database 6, the diagnostic information storage unit 5A, the diagnostic calculation unit 5B, and the diagnostic result information transmission unit 5C may be mounted on the vehicle.

  Moreover, in the said embodiment, the diagnosis calculating part 5B calculates | requires all the deviation values for every several preset vehicle speed (in the said embodiment), calculates the average value of all the deviation values, and evaluates it. The case was illustrated. Instead of this, the diagnosis calculation unit 5B is based on the accumulated diagnostic information data group (average speed, jerk-related values), in the vicinity of each preset vehicle speed (for example, target vehicle speed ± 5 km / h). When there are vehicle speeds that do not exist more than a preset number of data, for example, a number that is regarded as a statistically significant number, the following may be performed.

  That is, when the data in the vicinity of each preset vehicle speed for diagnosis is less than the preset number, the diagnosis calculation unit 5B does not obtain the deviation value for the vehicle speed, and the data in the vicinity of the preset vehicle speed. As described above, the deviation value is obtained only for vehicle speeds in which there are vehicle speed zones in which more than a preset number exists. Then, the diagnosis calculation unit 5B calculates the average value based on the obtained deviation value.

  Further, in the above-described embodiment, the deviation value of the target reference vehicle MM with respect to the jerk regression value of the preset reference comparison value for the jerk regression value at a plurality of preset vehicle speeds is obtained, and evaluation is performed based on the deviation value. The case of doing was illustrated. Instead, evaluation may be performed based on whether the obtained jerk regression value is larger or smaller than the reference comparison value jerk regression value. Moreover, although the deviation value was illustrated as statistical processing, you may evaluate by other statistical processing.

  Moreover, in the said embodiment, 70, 80, 90, 100, 110 (km / h) was illustrated as a vehicle speed for diagnosis, However, You may set the vehicle speed below 70 km / h to the vehicle speed for diagnosis. In addition, the jerk regression value of the reference comparison value may be set individually for each traveling environment classified by the target traveling section or the number of vehicles per unit area. It seems that the higher the diagnostic vehicle speed for evaluation, the better the accuracy. However, as described above, the reference comparison value is individually set in consideration of the driving environment. Even if the vehicle speed zone is set low, the smoothness of travel during traveling can be evaluated with a predetermined accuracy.

In the above embodiment, the jerk regression values at a plurality of vehicle speeds for diagnosis that have been set in advance are obtained using the jerk regression line obtained from the diagnostic information data group (average speed, jerk relation value). The case where the deviation value between the jerk regression value and the jerk regression value as the reference comparison value set in advance was calculated and evaluated was illustrated. However, the evaluation method is not limited to this.
For example, the following may be performed.
That is, a reference jerk regression line is set in advance as a reference comparison value. Then, the jerk-related value at an arbitrary vehicle speed, for example, 72 km / h is obtained, and the degree of divergence of the jerk-related value at the arbitrary vehicle speed from the reference jerk regression line is determined as the vehicle MM is traveling. You may diagnose and evaluate the running tendency about smoothness.

  Moreover, in the said embodiment, (average speed, jerk relation value) was used as diagnostic information data, but it is not limited to this. As shown in FIG. 10 and FIG. 11, (the inter-vehicle distance for each diagnosis time, the jerk-related value) and the (average speed, the jerk-related value) have a correlation, so May be diagnostic information data. In this case, the running smoothness of the running tendency when following the preceding vehicle can be particularly evaluated.

Moreover, in the said embodiment, although illustrated in the case of using a jerk relation value as diagnostic information data, you may use (inter-vehicle distance and vehicle speed) for every diagnostic time as diagnostic information data. In this case, a regression line with the inter-vehicle distance and the vehicle speed as variables may be considered.
Here, instead of the inter-vehicle distance, the inter-vehicle time may be used as the inter-vehicle distance information. The inter-vehicle time is the time for the host vehicle to reach the position of the preceding vehicle.
Here, the information processing unit 3 constitutes a behavior index value acquisition unit. The diagnosis calculation unit 5B constitutes a travel evaluation unit. The jerk regression value constitutes the diagnostic value.

(Effect of this embodiment)
(1) The behavior index value acquisition unit acquires an index value of vehicle behavior that can estimate the smoothness of travel while the host vehicle MM is traveling. The traveling evaluation unit evaluates the traveling tendency of the host vehicle MM by comparing a diagnostic value obtained from one or more index values acquired by the behavior index value acquiring unit with a preset reference comparison value.
The smoothness of the running is evaluated using the vehicle behavior that can estimate the smoothness of the running during the running as an index value. As a result, the traveling tendency of the host vehicle MM during traveling can be diagnosed more accurately.

(2) The vehicle behavior capable of estimating the smoothness of travel is jerk generated in the host vehicle MM, and the index value is obtained based on jerk generated in a preset unit time.
By evaluating based on jerk generated per unit time, it is possible to reduce the influence of the dependence on the driving environment such as the road structure, and to evaluate the running smoothness with less variation.
(3) The vehicle behavior index value that can estimate the smoothness of the travel is the inter-vehicle distance of the host vehicle MM with respect to the preceding vehicle for each preset unit time.
By evaluating the inter-vehicle distance as an index, it is possible to evaluate the smoothness of travel when following the preceding vehicle.

(4) The index value is a jerk-related value including any one of an integrated value of jerk, an average value of jerk, or a frequency of occurrence of jerk exceeding a preset threshold value in the unit time.
By making the jerk-related value an integrated value of jerk, an average value of jerk, or an occurrence frequency of jerk exceeding a preset threshold value, jerk as a smoothness index can be quantified.

(5) The travel evaluation unit statistically processes diagnostic information data including the speed of the host vehicle MM per unit time and the jerk relation value to obtain the diagnostic value, and the diagnostic value and the reference comparison value Are compared to evaluate the traveling tendency of the host vehicle MM.
By performing statistical processing on the relationship between the vehicle speed and the jerk-related value, evaluation can be performed with higher accuracy.

(6) The travel evaluation unit obtains a jerk regression value from diagnostic information data including the speed of the host vehicle MM per unit time and the jerk relation value, and the obtained jerk regression value and a preset reference The traveling tendency of the host vehicle MM is evaluated by comparing the reference comparison value including the jerk regression value.
By performing regression processing as statistical processing, statistical processing can be reliably performed.

(7) The travel evaluation unit obtains a jerk regression line from the diagnostic information data, obtains a jerk regression value of the host vehicle MM at two or more preset vehicle speeds based on the obtained jerk regression line, The traveling tendency of the host vehicle MM is evaluated by comparing the jerk regression value at each vehicle speed with the reference comparison value including the reference jerk regression value set in advance for each of the two or more vehicle speeds set in advance. .
By using the jerk regression values of the host vehicle MM at a plurality of vehicle speeds, the evaluation accuracy is further improved.

(8) The reference comparison value is composed of a set of a reference jerk regression value and its deviation value for each vehicle speed. The traveling evaluation unit obtains a deviation value from the obtained jerk regression value at each vehicle speed and the reference comparison value, and evaluates the traveling tendency of the host vehicle MM using the obtained deviation value.
By using the deviation value from the reference comparison value, the evaluation can be performed with higher accuracy.
(9) The behavior index value acquisition unit is mounted on the host vehicle MM. The travel evaluation unit is provided in a server that can receive the index value acquired by the behavior index value acquisition unit via a communication network.
The processing load on the host vehicle MM can be reduced.

(10) A travel evaluation device that evaluates the smoothness of travel of the host vehicle MM when the host vehicle MM follows the preceding vehicle. When the own vehicle MM follows the preceding vehicle by obtaining a diagnosis value from the relationship between the vehicle speed of the own vehicle MM per unit time set in advance and the jerk, and comparing the diagnosis value with a preset reference comparison value The traveling tendency of the host vehicle MM is evaluated.
Even if a distance meter for measuring the distance between the preceding vehicle and the like is not installed, the tendency of the running smoothness of the host vehicle MM when the host vehicle MM follows the preceding vehicle can be evaluated.

(11) Only jerk on the deceleration side is targeted as the jerk of the host vehicle MM.
When following, it is particularly effective to evaluate the smoothness of travel on the deceleration side. Therefore, by using only the jerk on the deceleration side as the jerk, it is possible to evaluate the tendency of the running smoothness of the host vehicle MM when the host vehicle MM follows the preceding vehicle.

1 Vehicle speed sensor 2 Wheel 3 Information processing section (behavior index value acquisition section)
3A Vehicle speed calculation unit 3B Jerk value calculation unit 3C Vehicle information generation unit 3D Vehicle information input / output unit 4 Display unit 5 Diagnostic server 5A Diagnostic information storage unit 5B Diagnostic calculation unit (running evaluation unit)
5C Diagnosis result information transmission unit 6 Database 10 Terminal D Evaluation value MM Own vehicle x Average vehicle speed y Jerk integral value

Claims (1)

A travel evaluation device that evaluates the smoothness of travel of the host vehicle when the host vehicle follows the preceding vehicle,
A behavior index value acquisition unit for acquiring a relationship between a vehicle speed of the own vehicle per unit time set in advance and jerk ;
A travel evaluation unit that obtains a diagnostic value from the acquired relationship and evaluates the smoothness of the traveling of the vehicle when following the preceding vehicle by comparing the diagnostic value with a preset reference comparison value ;
With
The behavior index value acquisition unit is intended only for a deceleration-side jerk as the jerk of the host vehicle, and the deceleration-side jerk includes that caused by deceleration when an accelerator pedal operation is performed. Running evaluation device.

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