JP2006172012A - Uneasiness detection device and uneasiness detection method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To detect that a driver holds a sense of uneasiness to a travel route or the like during traveling. <P>SOLUTION: This detection device of a sense of uneasiness has: a stop operation decision part 15 deciding a brake operation start and a stop of a vehicle from a brake operation signal from a brake detection part 13 and a vehicle speed from a vehicle speed detection part 11, and making a vehicle information temporary storage part 17 store them as vehicle information; and an estimation part for a sense of uneasiness 19 finding an average jerk wherein a jerk that is second order differential of the vehicle speed during stop operation and an average deceleration is averaged, from the vehicle information by a time to the stop from the brake operation start and the vehicle speed when the brake operation starts, and estimating that the driver has the sense of uneasiness when a relation value between the average deceleration and the average jerk is within a prescribed range. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to an anxiety detecting device and an anxiety detecting method for detecting a driver's anxiety while driving a vehicle.

In recent years, automobiles are equipped with devices for providing various information to a driver. For example, the stray state is detected from the number of times of passing through the same spot or nearby area, unnecessary turn signal operation, etc. There is known a travel information providing apparatus that provides effective information for quickly recognizing whether the vehicle is present (see Patent Document 1).
JP-A-10-122881

  However, in the conventional travel information providing device, the behavior of overlapping passage near the same point and the vicinity is used for detection of the stray state. However, it is possible to detect such a stray state relatively quickly, but for example, a state where the user is worried about whether the current road is heading for the destination. There is a problem that a driver who does not appear directly on the trajectory cannot detect anxiety about the course while driving.

  In addition, when detecting the passage of the same point, as described above, the same point can be passed in a short time at a place close to the destination as described above. Since it takes a long time, it takes time to detect that the vehicle is in a stray state.

  An anxiety detection device according to the present invention includes vehicle speed detection means for detecting a current speed of a vehicle and outputting vehicle speed information, brake detection means for detecting a brake operation and outputting brake operation information, the vehicle speed information and the brake An anxiety estimation means that acquires operation information and estimates whether or not the driver of the vehicle has anxiety based on vehicle behavior from the start of brake operation to the stop of the vehicle is provided.

  Further, the anxiety detection method according to the present invention includes a step of determining whether or not a brake operation is started while the vehicle is traveling, a step of determining whether or not the vehicle is stopped after the brake operation, and a brake operation start. And a step of estimating whether or not the driver of the vehicle is uneasy based on the vehicle behavior from the start to the stop.

  In the present invention, since the driver's anxiety is detected from the vehicle behavior from when the driver steps on the brake to when the vehicle stops, whether or not there is a clear consciousness of stopping in the driver. Therefore, it is possible to detect anxiety in a state that is less susceptible to disturbances other than the brake operation, regardless of the actual travel route.

  Embodiments of an anxiety detection device and anxiety detection method according to the present invention will be described below with reference to the drawings.

  FIG. 1 is a block diagram showing a functional configuration of an anxiety detection apparatus according to Embodiment 1 of the present invention.

  This anxiety detection device 1 includes a vehicle speed detection unit 11 that detects the current speed of the vehicle, a brake detection unit 13 that detects a brake operation by the driver, a stop operation determination unit 15 that determines the stop of the vehicle, a vehicle speed, A vehicle information temporary storage unit 17 that temporarily stores vehicle information such as brake operation, an anxiety estimation unit 19 that estimates whether or not there is anxiety from vehicle information such as vehicle speed and brake operation, and a driver based on the estimation result And a display information creating unit 21 for creating information display data required by the user. In addition, a navigation device 31 and a display device 33 are connected to the anxiety detection device 1.

  The anxiety detection device 1 configured as described above displays information created by the display information creation unit 21 based on the information of the navigation device 31 on the display device 33 when it is determined that the driver has anxiety. indicate.

  Each part will be described below.

  The vehicle speed detection unit (vehicle speed detection means) 11 is attached to the axle of a normal vehicle and detects the current speed of the vehicle. The detected speed is output to the stop operation determination unit 15 as vehicle speed information.

  A brake detection unit (brake detection means) 13 is attached to a brake pedal or a pre-key cylinder and detects that a brake operation has been performed. Output to the determination unit 15. The brake detection unit 13 continues to output this ON signal during the brake operation, that is, while the brake pedal is depressed. On the other hand, when the brake operation is not performed, no signal is output.

  The stop operation determination unit 15 determines whether or not the vehicle has stopped based on the speed information from the vehicle speed detection unit 11, and performs brake operation based on the brake operation information from the brake detection unit 13 (whether there is an ON signal). It is determined whether or not. These determination results are stored in the vehicle information temporary storage unit 17 as vehicle information together with the brake operation start time, the vehicle stop time, and the like.

  The vehicle information temporary storage unit 17 temporarily stores vehicle information such as the current vehicle status, that is, whether the vehicle is stopped, whether a brake operation is being performed, or the like.

  The anxiety estimation unit 19 functions as an anxiety estimation unit together with the stop operation determination unit 15 in this embodiment. The anxiety estimation unit 19 estimates whether or not the driver has anxiety based on the vehicle information stored in the vehicle information temporary storage unit 17.

  The display information creation unit 21 creates display screen data based on the estimation result by the anxiety estimation unit 19 and displays it on the display device 33.

  The navigation device 31 is a normal navigation device 31 that displays the current vehicle position on the map based on the map data from the current vehicle position, and provides route guidance to the destination.

  The display device 33 displays screen data created by the display information creation unit 21 for the driver. The display device 33 used in the navigation device 31 can be used as it is.

  In this anxiety detection device 1, the stop operation determination unit 15, the anxiety estimation unit 19, and the display information creation unit 21 are, for example, in-vehicle computers, and each unit is caused by executing a program that causes the computer to perform a procedure described later. The function is implemented. The vehicle information temporary storage unit 17 is a high-speed readable / writable storage medium such as a RAM in the computer.

  The vehicle speed detection unit 11 and the brake detection unit 13 are sensors attached to each part of the vehicle as described above. However, vehicle speed and brake operation information is obtained from a network provided for use in control of each part of the vehicle. May be.

  Next, the operation of the anxiety detection device 1 will be described.

  FIG. 2 is a flowchart showing an operation procedure of anxiety detection processing in the anxiety detection device 1.

  The anxiety detection device 1 starts in response to the ignition switch of the vehicle being turned on and starts processing.

  First, based on the vehicle speed information acquired by the stop operation determination unit 15 via the vehicle speed detection unit 11, it is determined whether or not the host vehicle is traveling (S101). If it is not running (S101: No), it continues to monitor whether it is running.

  If it is determined that the host vehicle is traveling (S101: Yes), whether or not the driver has started to step on the brake according to the brake on signal acquired by the stop operation determination unit 15 via the brake detection unit 13. That is, it is determined whether or not the brake operation is started. If it is determined that the brake has been started (S102: Yes), the process proceeds to step S103. On the other hand, if the brake operation is not performed (S102: No), the process directly returns to step S101.

  After it is determined that the brake operation has been started, the stop operation determination unit 15 uses information (vehicle speed and brake operation start time) necessary for calculating the average jerk and average deceleration in the subsequent step S108 as a vehicle information temporary storage unit. 17 starts to be stored (S103).

  Subsequently, the stop operation determination unit 15 determines whether or not the driver has released the brake from the presence or absence of the brake on signal acquired via the brake detection unit 13 (S104). When the brake is released (the ON signal from the brake detection unit 13 is interrupted, and it is assumed that the brake is released. S104: Yes). At this stage of processing, it is assumed that the current brake operation has not resulted in stopping of the vehicle, the vehicle information stored in the vehicle information temporary storage unit 17 is discarded (S105), and the processing returns to step S101.

  On the other hand, when the brake is continuously depressed (a state in which an on signal is output from the brake detection unit 13; S104: No), the stop operation determination unit 15 subsequently obtains the vehicle speed information acquired via the vehicle speed detection unit 11, It is determined whether the own vehicle has stopped (S106). Here, when it is determined that the vehicle is not stopped (S106: No), the process returns to step S104, and it is continuously monitored whether or not the brake is released.

  On the other hand, if it is determined that the host vehicle has stopped (S106: Yes), the vehicle stop time is stored in the vehicle information temporary storage unit 17 as vehicle information, and then the vehicle information is stored in the vehicle information temporary storage unit 17. Is stopped (S107).

  Subsequently, the stop operation determination unit 15 passes the vehicle information stored in the vehicle information temporary storage unit 17 to the anxiety estimation unit 19, and the anxiety estimation unit 19 calculates average jerk and average deceleration from the vehicle information. (S108).

  Here, the jerk (jumping degree) is a rate at which the acceleration changes with time, and is an index representing the smoothness of the vehicle running state in the vehicle. Jerk is determined by the second derivative of speed. The average jerk is calculated by averaging the jerk during the stop operation period.

  The average deceleration is the speed at the start of the stop operation at which the driver starts to step on the brake divided by the time taken for the stop operation. Here, the time taken for the stop operation is a time obtained by subtracting the brake operation start time from the vehicle stop time stored as the vehicle information. This average deceleration represents how much the driver brakes suddenly without depending on the speed at the start of the stop operation.

  Thereafter, the anxiety estimation unit 19 estimates anxiety using the calculated average jerk and average deceleration (S109). For this estimation, the relationship graph between the average deceleration and the average jerk shown in FIG. 3 is used. That is, the presence / absence of anxiety is estimated based on whether or not the relationship between the average deceleration and the average jerk (each point in FIG. 3) is within a predetermined range that varies according to the average deceleration.

  Here, the predetermined range that changes according to the average deceleration is the threshold lines 301 and 302 in the graph shown in FIG. If the relationship value between the average deceleration and the average jerk is not less than the threshold line 301 and not more than 302 in the graph, it is determined that there is anxiety and the process proceeds to step S110. On the other hand, if there is no relationship between the average deceleration and the average jerk between the threshold lines 301 and 302, it is determined that there is no anxiety and the process proceeds to step S111. When the relationship value between the average deceleration and the average jerk exceeds the threshold line 302, it is highly possible that the driver has responded in a sudden situation, and an alarm or the like may be issued.

  One threshold line 301 defining the predetermined range is specifically expressed by the following equation (1).

{Average jerk (0.5 m / s3) 2} = 46 × {Average deceleration (km / h / s) +40 (1)
In the above equation (1), 46, which is a coefficient of average deceleration, represents how much the average jerk increases when the average deceleration increases (as it seems to suddenly stop). This value is considered that the average deceleration is within the range of 2 to 10 (km / h / s) during normal driving (excluding accidents and illegal driving) (average deceleration 10 (km / h / s ) Is about 0.28G, but normal sudden braking is said to be 0.3G), but the coefficient was determined from the relationship between average jerk and average deceleration within that range. The method of determination is the minimum jerk model (Flash, T., Hogan, N. 1985. The coordination of arm), which modeled the reaching movement of the human hand, proposed by Flash and Hogan in 1985. movements: an experientially conformed mathematical model. J. Neurosci., 5, 1688-1703).

  According to this, for example, as a stop from 40 km / h, the coefficient is calculated as 36 based on the values of average deceleration 2 (km / h / s) and 10 (km / h / s). The coefficient was set to 46, assuming that more disturbed driving operation would occur when the speed was in the range of 4 to 10 (km / h / s).

  This time, 40 km / h is used to determine the coefficient, but the ideal coefficient changes depending on the speed. However, the 40km / h model deviates from the average jerk value at two speeds: the low speed and the minimum stop operation time, and the higher speed state. Since it can hardly be performed, it can be omitted at low speeds, and even when the speed is high, the value deviates when the stop operation is short. km / h / s), it is considered that there is no problem.

  Further, the intercept value 40 in the above equation (1) is a value that determines the extent to which the driver's error and operation variation are allowed with respect to the ideal coefficient obtained above. This is a regression analysis based on the driver's normal driving data, and the average standard error of the intercept was around 40, so even if it is minus 40 from the ideal coefficient, the average jerk (cannot be minus because it is a square value) The section was set to 40 so as not to be negative.

  The other threshold line 302 that defines this predetermined range is specifically expressed by the following equation (2).

{Average jerk (0.5 m / s3) 2} = 46 × {Average deceleration (km / h / s)} + 500 (2)
The intercept 500 of the above equation (2) will be described. Here, the average deceleration of 10 (km / h / s) or more is out of the range, but at the average deceleration of 10 (km / h / s), the average jerk increases by 460 in an ideal stop (infinitely close to 0). Therefore, 500 obtained by adding 460 to the intercept 40 of Equation 1 is used.

  These threshold lines (that is, predetermined ranges) are stored in advance in the anxiety estimation unit 19.

  The relationship graph between average deceleration and average jerk shown in FIG. 3 will be further described. The graph of FIG. 3 is a graph with the average jerk ((0.5 m / s3) 2) on the vertical axis and the average deceleration (km / h / s) on the horizontal axis. The average jerk on the vertical axis represents the smoothness of the movement of the vehicle as described above, but represents the smoothness at the time of braking since it is an operation when the brake is depressed. The average deceleration on the horizontal axis is a value obtained by dividing the speed at the time of starting the stop operation by the time taken for the stop operation, and indicates how much the stop operation has been stopped with a margin.

  Here, for example, when the driver is performing predictive driving (for example, when the signal is likely to turn red due to the shadow of the future curve, or when the surroundings are predicted to turn red soon, for example) ) If the driver feels suddenly stopped, the driver's movement (ie, the brake pedaling action) can predict the stopping position and the movement of the front car. Should not be too high (since the deceleration itself is higher, the average jerk is also higher). Therefore, the average jerk value generally falls within the range below the threshold line 301 in FIG. 3 when the predicted operation is performed.

  On the other hand, when the driver is driving with some sense of anxiety, driving resources are reduced and the predicted driving cannot be performed well. For this reason, the brake control is not smooth, and the average jerk appears greatly even in a situation where the average deceleration is low. Therefore, in such a case, the average jerk value falls between the threshold lines 301 and 302 in FIG. In this case, the present embodiment determines that the driver feels uneasy.

  On the other hand, sudden response by sudden jumping out or overlooking of a signal is very unlikely to cause anxiety. Thus, a large average jerk value is generated and exceeds a threshold line 302 that defines a predetermined range. Therefore, when the threshold line 302 is exceeded, it can be considered that the driver is taking a sudden response and can be removed from anxiety detection (effects of claims 3 and 9).

  Next, when the anxiety estimation unit 19 determines in step S109 that there is anxiety (S109: Yes), the display information creation unit 21 uses the information of the navigation device 31 to reduce anxiety. Anxiety reduction information is created and displayed on the display device 33 (S110). If the anxiety reduction information created by the display information creation unit 21 is anxious, the driver may, for example, check whether the road he is currently running matches the route he / she thinks. It is thought that I want to know where the road is currently running, and how long it is going to turn, and the current map display provided by the navigation device 31 shows the city name, station name, Data for displaying POI information such as the name of a current road, a name of a landmark on the traveling direction such as a name of a road currently traveling, a name of a large road in the traveling direction, and a landmark on the traveling direction is created.

  As for the POI information displayed on the screen, the POI information displayed on the map is only displayed on the road such as a gas station, convenience store, family restaurant, etc. It is preferable to reduce the number to increase visibility. In addition, when the route to the destination is set in the navigation device 31, only the easy-to-understand POI and the name of the place around the vehicle for easily recognizing the current location and the distance to the next intersection to make a right or left turn are displayed. You may do it.

  However, the navigation display is not changed when the driver performs a navigation operation. In addition, it is conceivable that the navigation display is not changed even when an on-vehicle device such as a hands-free mobile phone is operated during the stop operation.

  When the above series of processing is completed, the stop operation determination unit 15 discards the vehicle information stored in the vehicle information temporary storage unit 17 (S111), terminates the series of processing so far, and returns to the original step. Returning to S101, this process is repeated continuously.

  As is clear from the above description, according to the present embodiment, the stop operation determination unit 15 and the anxiety estimation unit 19 cause the driver to feel anxiety from the vehicle behavior from the start of the brake operation to the stop of the vehicle. It is possible to detect anxiety without depending on the number of passages at the same point or its neighboring area, and to detect any route and process regardless of the vehicle's travel trajectory. (Effects of claims 1 and 7).

  In this embodiment, the average jerk and average deceleration during the stop operation by the brake operation are calculated, and the presence or absence of anxiety is determined from the relationship between the two values. By limiting to the stop operation based on the operation, it is possible to estimate only with the operation data with the intention of the driver to stop, and it is possible to determine in a state where the influence of the disturbance is small. For example, if anxiety is detected not only by the brake operation but also by various operations of the driver during driving, such as the steering wheel operation and the depression of the accelerator, these operations are affected by the influence of the front car, the shape of the road, Because it is caused by various situations such as turning left or changing the curve lane, the disturbance is large and it is difficult to detect anxiety. Therefore, it is easier to detect (estimate) anxiety when only the brake is operated as in this example. (Effects of claims 2 and 8).

  In addition, when it is determined that the driver has anxiety, the display information creation unit 21 creates and displays a display that makes it easy to confirm the vehicle position, so that the driver can quickly confirm the vehicle position. .

  In addition, by using the relationship between average jerk and average deceleration, it is possible to take into account differences in the deceleration method (deceleration magnitude, stop distance, stop start speed) at each stop, and the driver's delicate brake operation You can see the effect of. For this reason, it is possible to detect that the driver is deprived of things other than driving (for example, a display inside or outside the vehicle or a signboard).

  FIG. 4 is a block diagram illustrating a functional configuration of the anxiety detection apparatus according to the second embodiment of the present invention. In addition, about each part which has a function similar to each part in Example 1 mentioned above, the same code | symbol is attached | subjected and those description is abbreviate | omitted.

  Similar to the anxiety detection device 1, the anxiety detection device 2 in this embodiment includes a vehicle speed detection unit 11, a brake detection unit 13, a stop operation determination unit 15, a vehicle information temporary storage unit 17, and an anxiety estimation unit 19. Further, an anxiety estimation learning unit 41 which is an anxiety estimation learning means is provided.

  In this anxiety detection device 2, an anxiety estimation learning unit 41 learns, stores and accumulates the relationship between average deceleration and average jerk when the driver can concentrate on driving from daily driving operations. Thus, a predetermined range for determining anxiety from the information is obtained. Such anxiety estimation learning unit 41 is preferably, for example, a readable / writable nonvolatile memory of an in-vehicle computer, and may be a hard disk unit or the like.

  The operation of the anxiety detection device 2 will be described.

  FIG. 5 is a flowchart showing an operation procedure of the anxiety detection process in the anxiety detection device 2.

  In the anxiety detection device 2 as well, as in the first embodiment described above, processing is started in response to the ignition switch of the vehicle being turned on. The processing from step S101 to step S108 is the same as that in the first embodiment. Therefore, only the processing after step S209 will be described here.

  After the average jerk and the average deceleration are calculated from the vehicle information by the anxiety estimation unit 19 (S108), the anxiety estimation unit 19 estimates anxiety using the average jerk and the average deceleration (S209). Here, for the estimation of the anxiety, learning type threshold lines 601 and 602 for detecting anxiety in the relationship graph of average jerk and average deceleration shown in FIG. 6 are used as a predetermined range.

  That is, when the calculated average jerk value is between the threshold lines 601 and 602, it is determined that there is anxiety, and the anxiety estimation unit 19 performs the above-described steps S110 and S210 in the process of step S210. Similarly, in order to provide information for quickly recognizing the current location, the display information creation unit 21 creates anxiety reduction information using the information of the navigation device 31, and allows the driver to go on the way or on the way POI information such as a place name is displayed on the display device 33.

  On the other hand, when there is no average jerk value between the threshold lines 601 and 602 (S209: No), it is determined that there is no anxiety, and the anxiety estimation unit 19 subsequently continues with the average jerk and the average decrease. It is determined whether or not the speed exceeds the threshold line 602 and the driver is responding suddenly (S211). Here, the case of sudden response corresponds to a case where a very large average jerk value is obtained even if the average deceleration is not high, and specifically, is an upper limit value of a predetermined range. This is a case where the value line 602 is exceeded.

  Here, when it is determined that the driver does not respond suddenly (S211: No), the average jerk and average when the anxiety estimation learning unit 41 determines that the anxiety estimation estimation unit 19 does not respond suddenly. The deceleration value is stored (S213). Therefore, the anxiety estimation learning unit 41 sequentially accumulates the average jerk value and the average deceleration value when it is determined by the anxiety estimation unit 19 that there is no anxiety and it is not a sudden response.

  Then, the anxiety estimation learning unit 41 creates threshold lines 601 and 602 within a predetermined range that the anxiety estimation unit 19 uses to determine the presence or absence of anxiety from the accumulated data. If the stored average jerk and average deceleration data amount exceeds a predetermined storage capacity, for example, the oldest data may be deleted in order.

  Here, a specific method for calculating the threshold lines 601 and 602 will be described.

  Considering the average jerk and average deceleration in a certain stop operation as one set, the average jerk is the objective variable Y and the average deceleration is the explanatory variable X, and a single regression analysis is performed.

  The model formula at this time is as shown in the following formula (3).

Y = β0 + β1X (3)
Since single regression analysis is a general analysis method, description thereof is omitted here. Using the standard error Se of β0, β1, and β0 obtained by this method, an anxiety detection relational expression is calculated. The relational expression for anxiety detection is a relational expression obtained by adding the standard error Se of β0 to the intercept β0 as shown in the following equation (4).

Y = β0 + Se + β1X (4)
The threshold line 601 for the next anxiety detection is obtained using this equation (4), and anxiety detection is performed in step S209.

  On the other hand, the threshold line 602 may be fixed, but may be obtained by the following expression (5) using the expression (4) which is the relational expression of the anxiety threshold line obtained previously.

Y = β0 + Se + 460 + β1X (5)
460 in the above formula (5) is the same reason as the formula (2) in the first embodiment. However, since the coefficient is β1 in the formula (5), a value of β1 × 10 may be used. Good.

  Such threshold lines 601 and 602 are possible if there are at least two pairs of average jerk and average deceleration accumulated in the processing of step S213. However, if a certain amount of data is not accumulated, the reliability of the obtained threshold line itself is lowered, so that the threshold line is not calculated until a certain amount of data is accumulated. At the time when the threshold lines 601 and 602 are not calculated, for example, the anxiety may be determined using the threshold lines 301 and 302 in the first embodiment described above.

  Further, in this flowchart, the threshold line is obtained every stop, but the calculation of the threshold line may be moved simultaneously with the vehicle ignition switch being turned on ( (The threshold line relational expression is changed once per engine start).

  Thereafter, the processing discards the vehicle information stored in the vehicle information temporary storage unit 17 by the stop operation determination unit 15 (S214), and returns to step S101.

  If it is determined in step S211 that the driver is responding suddenly (S211: No), the vehicle information stored in the vehicle information temporary storage unit 17 by the stop operation determination unit 15 is discarded (S214). ), The process returns to step S101.

  As is clear from the above description, according to the present embodiment, the average jerk and average deceleration when the driver is not anxious and does not respond suddenly are accumulated from those values. Since the threshold line that is a predetermined range for determining anxiety is obtained, the anxiety detection accuracy can be improved (effects of claims 4 and 10).

  Since these values are accumulated sequentially during driving, for example, if accumulation is started every time ignition is turned on, anxiety detection can be applied to individual driver characteristics. it can. In addition, by performing learning of anxiety detection at every stop or every run, it is possible to cope with changes in the driving preferences of the driver little by little. This is because the relationship between jerk and average deceleration is concentrated in driving, and even if the predicted driving is possible, the individual driver seems to brake suddenly, the person who brakes a little bit, There are people who make a smooth stop, etc., and by learning the characteristics of each individual driver from daily driving, the relationship between the average jerk and average deceleration of each individual driver can be estimated. Based on the above, it is possible to detect anxiety in accordance with the characteristics of individual drivers (effects of claims 5 and 11).

  The average jerk and average deceleration used in calculating the threshold lines 601 and 602 are values corresponding to extreme sudden events, for example, even if the average deceleration is not high. If the values are very high, the anxiety estimation learning unit 41 may not store these values. This makes it possible to reduce the deviation of the threshold line calculated by single regression analysis and bring the learning threshold line for anxiety detection closer to that of normal driving without anxiety. This is particularly effective when the number of data is small (effects of claims 6 and 12).

  As mentioned above, although the Example of this invention was described, implementation of this invention is not limited to these Examples. For example, in each of the above-described embodiments, the vehicle speed and the brake operation are temporarily stored in the vehicle information temporary storage unit 17 and then used by the anxiety estimation unit 19. However, the configuration for performing such temporary storage is generally used. Instead of this, instead of temporarily storing the vehicle speed and brake operation signals, the CPU of the computer that becomes the anxiety estimation unit 19 directly acquires the anxiety. It may be determined whether or not there is.

  In the present embodiment, the anxiety estimation means is configured by the stop motion determination unit 15 and the anxiety estimation unit 19, but this is a separate process for estimating anxiety and determining whether the vehicle is stopped or the like. This is intended to increase the processing speed of the anxiety detection device. Therefore, if there is no problem with the processing speed, one function is to perform, for example, all the processing performed by the anxiety estimation unit 19 from the vehicle speed and the brake operation signal to the stop operation determination unit 15 such as stopping the vehicle. May be.

It is a block diagram which shows the functional structure of the anxiety detection apparatus concerning Example 1 of this invention. 3 is a flowchart illustrating an operation procedure of anxiety detection processing according to the first embodiment. It is a graph which shows the relationship between average deceleration and average jerk. It is a block diagram which shows the functional structure of the anxiety detection apparatus concerning Example 2 of this invention. 10 is a flowchart illustrating an operation procedure of anxiety detection processing according to the second embodiment. It is a graph which shows the relationship between average deceleration and average jerk.

Explanation of symbols

1, 2 Anxiety detection device 11 Vehicle speed detection unit 13 Brake detection unit 15 Stop operation determination unit 17 Vehicle information temporary storage unit 19 Anxiety estimation unit 21 Display information creation unit 31 Navigation device 33 Display device 41 Anxiety estimation estimation learning unit

Claims (12)

Vehicle speed detection means for detecting the current speed of the vehicle and outputting vehicle speed information;
Brake detection means for detecting brake operation and outputting brake operation information;
Anxiety estimation means for acquiring the vehicle speed information and the brake operation information, and estimating whether the driver of the vehicle has anxiety based on a vehicle behavior from a brake operation start to a vehicle stop;
An anxiety detection device comprising:   The anxiety estimation means is a second-order derivative of an average deceleration and a vehicle speed during a stop operation, which is obtained from the vehicle speed information and the brake operation information, depending on the vehicle speed at the time of brake operation start and the time from the start of brake operation to the stop. 2. An anxiety detection apparatus according to claim 1, wherein an average jerk obtained by averaging a certain jerk is obtained, and anxiety is estimated when the relationship value between the average deceleration and the average jerk is within a predetermined range. 3. The anxiety detection apparatus according to claim 2, wherein the predetermined range is between threshold lines represented by the following formulas (1) and (2).
{Average jerk (0.5 m / s3) 2} = 46 × {Average deceleration (km / h / s) +40 (1)
{Average jerk (0.5 m / s3) 2} = 46 × {Average deceleration (km / h / s)} + 500 (2)   3. The anxiety estimation learning means according to claim 2, further comprising anxiety estimation learning means for determining the predetermined range from an average deceleration and an average jerk value when there is no anxiety by the anxiety estimation means. Detection device.   The anxiety estimation learning means saves and accumulates the average deceleration and average jerk values every time the anxiety estimation means determines that there is no anxiety, and simply stores the accumulated average deceleration and average jerk values. 5. The anxiety detection device according to claim 4, wherein the anxiety detection device is obtained by analysis.   The anxiety estimation learning means, when the average deceleration and the average jerk determined that there is no anxiety by the anxiety estimation means exceeds the upper limit value of the predetermined range obtained by the single regression analysis 6. The anxiety detection device according to claim 5, wherein the storage and accumulation is not performed. Determining whether a brake operation has been started while the vehicle is running;
Determining whether the vehicle has stopped after the brake operation;
Estimating whether the driver of the vehicle has anxiety from the vehicle behavior from the start to the stop of the brake operation;
An anxiety detection method comprising: The step of estimating whether there is anxiety includes
The average jerk is obtained by averaging the jerk, which is the second derivative of the average deceleration and the vehicle speed during the stop operation, according to the vehicle speed at the start of the brake operation and the time taken to stop, and the relationship between the average deceleration and the average jerk is within a predetermined range 8. The method of detecting anxiety according to claim 7, wherein it is presumed that there is anxiety during the period. 9. The anxiety detection method according to claim 8, wherein the predetermined range is between threshold lines represented by the following formulas (1) and (2).
{Average jerk (0.5 m / s3) 2} = 46 × {Average deceleration (km / h / s) +40 (1)
{Average jerk (0.5 m / s3) 2} = 46 × {Average deceleration (km / h / s)} + 500 (2)   9. The anxiety detection method according to claim 8, wherein the predetermined range is determined from a value of an average deceleration and an average jerk when there is no anxiety.   The predetermined range includes storing and accumulating average deceleration and average jerk values every time when there is no anxiety, and obtaining the accumulated average deceleration and average jerk values by single regression analysis. Item 15. The method of detecting anxiety according to Item 10. 12. The storage / accumulation is not performed when the average deceleration and average jerk determined to have no anxiety exceeds an upper limit value of a predetermined range obtained by the single regression analysis. The anxiety detection method described.

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