JP2023131329A - Driving evaluation system, driving evaluation method, and computer program - Google Patents

Abstract

To provide a driving evaluation system capable of presenting an evaluation result to be easily accepted by a driver.SOLUTION: A driving evaluation system comprises: an acquisition section for acquiring own vehicle information including own vehicle position information expressing a position of an own vehicle and a driving behavior feature of the own vehicle at the position; an accumulation section for accumulating the acquired own vehicle information in a storage section; an evaluation section for calculating a deviation of present driving from normal driving with the use of a secular change of the driving behavior feature in the accumulated own vehicle information, so as to evaluate whether the present driving is being shifted to non-safety driving where safety is lower than that of the normal driving; and an output control section for outputting an evaluation result by the evaluation section.SELECTED DRAWING: Figure 1

Description

The present invention relates to a technique for evaluating driving.

BACKGROUND ART Technologies are known that collect data such as vehicle speed and acceleration, and use the data to evaluate individual driving and perform driving support control. For example, in Patent Document 1, an onboard device generates characteristic information based on driving behavior data and transmits it to a center, and the center calculates an evaluation value by comparing the accumulated characteristic information and the received characteristic information. It is stated that if the cumulative value of the evaluation values is large, it is determined that the driving of the vehicle is unusual.

For example, in Patent Document 2, vehicle state quantities of a plurality of vehicles are accumulated in a management center server, and a target vehicle state quantity of the own vehicle is calculated based on the degree of deviation from the average value of the vehicle state quantities of the own vehicle. , it is described that the driving support control of the own vehicle is executed also with respect to the target vehicle state quantity. For example, Patent Document 3 discloses that the next traffic scene of a vehicle is estimated from local position information and map information, and advice information is presented when the driver's driving skill level evaluated in a similar traffic scene is low. Are listed. For example, Patent Document 4 describes estimating the driver's condition from the driver's past driving history and controlling the content to be notified to the driver based on the estimated driver's condition.

JP 2018-10407 Publication Japanese Patent Application Publication No. 2017-191502 JP2009-222746A Japanese Patent Application Publication No. 2012-118951

Here, there are individual differences among drivers in driving behavior characteristics such as speed and acceleration. In this regard, in the technologies described in Patent Documents 1 and 2, individual driving is evaluated using data widely collected from the general public, so the receptivity of the evaluation results by the driver is low, and the driver is not satisfied with the evaluation results. There was a risk that the system itself would be rejected because the driver found the guidance and driving support control based on the system to be cumbersome. In addition, even if the driver is paying full attention to driving, the speed or acceleration may suddenly increase too much due to operational errors or depending on the situation at the time. In other words, abnormal driving Behavioral characteristics may occur. In this regard, the techniques described in Patent Documents 1, 3, and 4 do not take into consideration the evaluation of changes in driving behavior characteristics over time, so they may give poor evaluations to unique driving behavior characteristics that suddenly occur. As a result, there is a risk that the driver may find the guidance and driving support control based on the evaluation results troublesome and reject the system itself.

The present invention has been made to solve at least part of the above-mentioned problems, and an object of the present invention is to provide a driving evaluation system that can present evaluation results that are easily accepted by drivers.

The present invention has been made to solve at least part of the above-mentioned problems, and can be realized as the following forms.

(1) According to one embodiment of the present invention, a driving evaluation system is provided. This driving evaluation system includes an acquisition unit that acquires own vehicle information including own vehicle position information representing the position of the own vehicle and driving behavior characteristics of the own vehicle at the position, and a storage unit that stores the acquired own vehicle information. By calculating the deviation of the current driving from the normal driving using the storage unit stored in the storage unit and the change over time of the driving behavior characteristics of the stored own vehicle information, the current driving The vehicle includes an evaluation section that evaluates whether the driving is shifting to unsafe driving, which is less safe than normal driving, and an output control section that outputs the evaluation result by the evaluation section.

According to this configuration, the evaluation section evaluates the current driving of the individual driver using the driving behavior characteristics of the own vehicle information stored in the storage section. Here, the driving behavior characteristics used for evaluation are information about the own vehicle (in other words, information about the individual driver), so compared to cases where driving is evaluated using data widely collected from the general public. , the driver's receptivity to the evaluation results is high, and it is possible to reduce the possibility that the driver will find the guidance and driving support control based on the evaluation results bothersome. Further, according to this configuration, the evaluation unit calculates the deviation of the current driving from the normal driving using changes over time in the driving behavior characteristics, thereby determining whether the current driving is less safe than the normal driving. Evaluate whether the situation is shifting to unsafe driving. For this reason, it is possible to reduce the possibility that a bad evaluation will be given to a unique driving behavior characteristic that suddenly occurs due to an operation error or the situation at the time. As a result, according to the present configuration, it is possible to provide a driving evaluation system that can present evaluation results that are easily accepted by the driver.

(2) In the driving evaluation system of the above embodiment, the evaluation unit calculates the current driving and the normal driving using a moving average of the driving behavior characteristics, and calculates a deviation value of the current driving with respect to the normal driving. By calculating a deviation value as an index representing the deviation, it may be evaluated whether the current driving is transitioning to the unsafe driving.
According to this configuration, the evaluation unit can easily evaluate current driving using changes over time in driving behavior characteristics by determining current driving and normal driving using a moving average of driving behavior characteristics. . In addition, by using the deviation value of the current operation with respect to the normal operation as an index representing the deviation, the evaluation unit can obtain an evaluation result that is standardized based on the variation in the normal operation and has less blur.

(3) In the driving evaluation system of the above embodiment, the evaluation unit calculates the current driving and the normal driving using a moving average of the driving behavior characteristics, and calculates the deviation rate of the current driving from the normal driving. By calculating a deviation rate as an index representing the deviation, it may be evaluated whether the current driving is transitioning to the unsafe driving.
According to this configuration, the evaluation unit can easily evaluate current driving using changes over time in driving behavior characteristics by determining current driving and normal driving using a moving average of driving behavior characteristics. . Further, the evaluation unit can obtain clear evaluation results based on normal operation by using the deviation rate of the current operation with respect to normal operation as an index representing the deviation.

(4) In the driving evaluation system of the above embodiment, the evaluation unit sets the moving average of the driving behavior characteristics included in the own vehicle information for past w1 (w1 is a natural number) times as the current driving, The normal driving may be a moving average of the driving behavior characteristics included in the own vehicle information for the past w2 times (w2 is a natural number) from the present.
According to this configuration, the evaluation unit determines the moving average of the driving behavior characteristics for the past w1 times from the present as the current driving, and the moving average of the driving behavior characteristics for the past w2 times from the present as the normal driving. , the smoothed current operation and normal operation can be determined.

(5) In the driving evaluation system of the above embodiment, the evaluation unit may be able to change at least one of the value of w1 and the value of w2 within a range that satisfies w1<w2.
According to this configuration, the evaluation unit calculates at least one of the value of w1 and the value of w2, w1<w2
Since it can be changed within a range that satisfies the above, it is possible to change the degree of smoothing between the current operation and the normal operation. For example, by increasing the value of w1, current driving can be evaluated from a long-term perspective, while by decreasing the value of w1, current driving can be evaluated from a short-term perspective. For example, by increasing the value of w2, it is possible to evaluate current driving based on normal driving from a long-term perspective, while by decreasing the value of w2, it is possible to evaluate from a short-term perspective. It is possible to evaluate current driving based on (recent) normal driving.

(6) In the driving evaluation system of the above embodiment, the driving behavior characteristics include the speed of the own vehicle, the acceleration of the own vehicle, the average speed of the own vehicle in a predetermined section, and the maximum deceleration of the own vehicle in the predetermined section. , the section minimum speed of the own vehicle in a predetermined section.
According to this configuration, the driving behavior characteristics include the speed of the own vehicle, the acceleration of the own vehicle, the average speed of the own vehicle in the predetermined section, the maximum deceleration of the own vehicle in the predetermined section, and the own vehicle in the predetermined section. It is possible to realize evaluation using at least one of the minimum speed in the section.

(7) In the driving evaluation system of the above embodiment, the storage section stores the own vehicle information at a predetermined specific point in the storage section, and stores the own vehicle information at a point different from the specific point in the storage section. It does not have to accumulate in the body.
According to this configuration, the storage section stores own vehicle information at a predetermined specific point in the storage section, and does not store own vehicle information at a point different from the specific point in the storage section. For this reason, a specific point may be a point where a large change in driving behavior characteristics (e.g. speed, acceleration, section average speed, maximum deceleration) is expected (e.g. position of a stop line, position of a railroad crossing, etc.), By selecting a point where the own vehicle passes relatively frequently (for example, an arbitrary point on the driver's commuting route), it is possible to efficiently collect and store own vehicle information by the storage unit. Furthermore, compared to the case where own vehicle information is accumulated without narrowing down to a specific point (for example, when own vehicle information is accumulated periodically), the amount of data accumulated in the storage unit can be reduced, and the processing device The processing load can be reduced.

Note that the present invention can be realized in various aspects, such as an information processing device, a traffic behavior evaluation device, a determination device, an information providing device, a monitoring device, a recording device, and realizing the functions of each of these devices. A system that includes each of these devices, a computer program for realizing the functions of each of these devices and systems, a server device for distributing the computer program, and a computer program that stores the computer program. It can be implemented in the form of a non-transitory storage medium or the like.

1 is a schematic diagram of a driving evaluation system as an embodiment of the present invention. 3 is a flowchart illustrating an example of a procedure of evaluation processing. FIG. 2 is an explanatory diagram showing an example of own vehicle information. It is a figure explaining a moving average. It is a figure explaining the output of an evaluation result. It is a schematic diagram of a driving evaluation system of a 2nd embodiment.

<First embodiment>
FIG. 1 is a schematic diagram of a driving evaluation system 1 as an embodiment of the present invention. The driving evaluation system 1 is a system that evaluates the current driving of the driver P using the temporal changes in the driving behavior characteristics of the driver P of the own vehicle 90. Here, "driving behavior characteristics" means any index representing the characteristics of driving behavior, and examples of driving behavior characteristics include speed, acceleration, section average speed, maximum deceleration, and section minimum speed. At least one of these can be used. In the following example, a case where "speed" is used as the driving behavior feature will be exemplified. As described above, the driving evaluation system 1 of the present embodiment performs evaluation using changes over time in the driving behavior characteristics of the driver P of the own vehicle 90, and therefore can present evaluation results that are more easily accepted by the driver P.

In the example of FIG. 1, the driving evaluation system 1 is mounted on the own vehicle 90 and includes an information processing device 10, a GPS receiver 30, and an information presentation device 40.

The information processing device 10 includes a CPU 11, a storage section 12, and a ROM/RAM (not shown), and each section is interconnected by a bus. The information processing device 10 may be implemented by a personal computer or an electronic control unit (ECU). The CPU 11 controls each part of the information processing device 10 by loading a computer program stored in the ROM into the RAM and executing it. In addition, the CPU 11 also functions as an acquisition section 111, a storage section 112, an evaluation section 113, and an output control section 114.

The acquisition unit 111 acquires own vehicle information in an evaluation process described below. Here, "own vehicle information" refers to location information representing the position of the own vehicle 90 (for example, latitude and longitude) and driving behavior characteristics of the own vehicle 90 at the relevant location (for example, speed, acceleration, section average speed, maximum reduction At least one of the speeds (acceleration in the example of this embodiment). Note that the own vehicle information may include location information and accompanying information accompanying driving behavior characteristics. The accompanying information includes, for example, the date and time when the location information and driving behavior characteristics were acquired, information for identifying the specific point where the location information and driving behavior characteristics were acquired, and the time when the location information and driving behavior characteristics were acquired. The external environment (eg, season, weather, temperature, etc.) may be included.

The storage unit 112 stores the own vehicle information acquired by the acquisition unit 111 in the own vehicle information 121 of the storage unit 12 in the evaluation process described below.

In the evaluation process described below, the evaluation unit 113 calculates the deviation of the current driving from the normal driving using the temporal changes in the driving behavior characteristics of the own vehicle information 121 stored in the storage unit 12. Evaluate whether or not driving is shifting to unsafe driving, which is less safe than normal driving. Here, "current driving" does not mean the "current" driving of the driver P, but means the smoothed current driving. Therefore, the current driving can also be said to be the driver's P's recent driving. Moreover, "normal driving" means smoothed normal driving of the driver P.

The output control unit 114 causes the information presentation device 40 to output the evaluation result by the evaluation unit 113 in evaluation processing to be described later. In this way, the acquisition unit 111, the storage unit 112, the evaluation unit 113, and the output control unit 114 cooperate to execute the evaluation process described below. Details of the processing will be described later.

The storage unit 12 includes a flash memory, a memory card, a hard disk, and the like. The storage unit 12 stores own vehicle information 121 and specific point information 122. Own vehicle information 121 is own vehicle information that is accumulated by the accumulation unit 112 through evaluation processing that will be described later.

The specific point information 122 stores in advance information (for example, latitude and longitude) for identifying a specific point used in the evaluation process described later. Here, the "specific point" means a point where a large change in driving behavior characteristics is expected or a point where the own vehicle 90 passes relatively frequently. Specifically, the specific point information 122 stores information (latitude and longitude) for identifying a point corresponding to at least one of a1 to a3 below. (a1) A point where a large change in driving behavior characteristics is expected: a point where a stop line is provided on the road.
(a2) A point where a large change in driving behavior characteristics is expected: a temporary stop position at a railroad crossing.
(a3) A point where the host vehicle 90 passes relatively frequently: Any point on the road that the driver P often passes (for example, a commuting route connecting home and work, or a route calculated from the travel history of the host vehicle 90) point.

The GPS receiver 30 is installed in the cabin 91 of the own vehicle 90. The GPS receiver 30 receives radio waves transmitted from artificial satellites that constitute a GPS (Global Positioning System), and obtains the latitude and longitude representing the current position of the own vehicle 90.

The information presentation device 40 is installed on a dashboard 93 provided at the bottom of a windshield 92 of the own vehicle 90. The information presentation device 40 is a display device (monitor) that includes a display that outputs images and a speaker that outputs audio. Note that the information presentation device 40 may be configured only with a display or may be configured only with a speaker. Furthermore, in the above-described configuration, instead of the information processing device 10, the GPS receiver 30, and the information presentation device 40, an in-vehicle device, a smartphone, a robot, etc. that includes all of these functions may be used.

FIG. 2 is a flowchart illustrating an example of the procedure of evaluation processing. The evaluation process is a process of accumulating the own vehicle information of the own vehicle 90 and evaluating the current driving of the own vehicle 90 by the driver P. The evaluation process is started at any timing. For example, the evaluation process may be started when the engine of the host vehicle 90 is started, the information processing device 10 is powered on, the driver P issues a start instruction, or the like.

In step S10, the acquisition unit 111 acquires current position information from the GPS receiver 30 and uses it as own vehicle position information. Note that the acquisition unit 111 may correct the current position information acquired from the GPS receiver 30 using map information stored in the storage unit 12 in advance. Note that the execution order of this step S10 and step S12 to be described next may be switched, or they may be executed in parallel (simultaneously). Step S10 and step S12 correspond to a "step of acquiring own vehicle information".

In step S12, the acquisition unit 111 acquires driving behavior characteristics. Driving behavior characteristics can be acquired by various methods, for example, as illustrated in b1 to b5 below.
(b1) When speed is used as a driving behavior characteristic, the acquisition unit 111 may acquire the speed (vehicle speed) measured by a speedometer mounted on the own vehicle 90, and the current position information and one hour ago. The speed may be calculated using the position information acquired during that time and the elapsed time.
(b2) When using acceleration as a driving behavior characteristic, the acquisition unit 111 may acquire the acceleration measured by an accelerometer mounted on the own vehicle 90, and perform calculations from the speed acquired by the above-mentioned means. Acceleration may also be calculated.
(b3) When using the section average speed as a driving behavior feature, the acquisition unit 111 acquires each in a predetermined section (specifically, for example, with an arbitrary point as a reference, a range of a certain distance before and after the point) The average speed is calculated from the calculated speed, and the calculated average speed can be used as the section average speed.
(b4) When using the maximum deceleration as a driving behavior feature, the acquisition unit 111 acquires each in a predetermined section (specifically, for example, with an arbitrary point as a reference, a range of a certain distance before and after the point) One of the maximum accelerations (decelerations) is selected, and the selected acceleration can be made the maximum deceleration.
(b5) When using the section minimum speed as a driving behavior feature, the acquisition unit 111 acquires each in a predetermined section (specifically, for example, with an arbitrary point as a reference, a range of a certain distance before and after the point) The minimum speed is determined from the determined speed, and the determined minimum speed can be used as the minimum speed for the section.

In step S<b>14 , the storage unit 112 stores the own vehicle position information at the specific point and the driving behavior characteristics in the own vehicle information 121 of the storage unit 12 . Specifically, the storage unit 112 first compares the own vehicle position information acquired in step S10 with the specific point information 122 in the storage unit 12, so that the own vehicle position information acquired in step S10 is It is determined whether the indicated position (that is, the position of own vehicle 90) is within a predetermined error range from the specific point (a1 to a3). At this time, the storage unit 112 may use information (such as a vector) representing the traveling direction in order to grasp the traveling direction of the own vehicle 90. If the position indicated by the own vehicle position information is at a specific point (including within the error range), the storage unit 112 stores the date and time when step S10 was executed, the own vehicle position information acquired in step S10, and the own vehicle position information acquired in step S12. and the driving behavior characteristics that have been determined are stored in the own vehicle information 121 in association with each other. If the position indicated by the own vehicle position information is not at a specific point, the storage unit 112 moves the process to the next step without accumulating the own vehicle information (the own vehicle position information and driving behavior characteristics). Note that step S14 corresponds to "a step of accumulating own vehicle information in the storage section".

FIG. 3 is an explanatory diagram showing an example of own vehicle information 121. As a result of repeating the processes of steps S10 to S14, data as illustrated in FIG. 3 is accumulated in the own vehicle information 121. In the illustrated example, the own vehicle information 121 is stored in which acquisition date and time, own vehicle position information, and driving behavior characteristics are associated with each other. "X" in FIG. 3 is an arbitrary character string. The entry E1 of the own vehicle information 121 stores the acquisition date and time of information acquired at a certain specific point A, the own vehicle position information, and driving behavior characteristics. Further, in the entry E2 of the own vehicle information 121, the acquisition date and time of information acquired at another specific point B, own vehicle position information, and driving behavior characteristics are stored. Note that the entry E6 stores the acquisition date and time of information acquired at a different date and time than the entry E1 at the same specific point A as the entry E1, own vehicle position information, and driving behavior characteristics. In this way, the own vehicle information 121 includes a history representing the driving behavior characteristics of the own vehicle 90 (in other words, of the driver P himself), along with the own vehicle position information and accompanying information (in the illustrated example, the date and time of acquisition). It keeps accumulating.

Note that step S14 in FIG. 2 (accumulation of data in the own vehicle information 121) may be executed sequentially together with steps S10 and S12 as the own vehicle 90 moves, and only steps S10 and S12 may be repeatedly executed. The process may be executed at any timing on the data set stored in the RAM or the like as a result.

In step S16, the evaluation unit 113 determines whether a predetermined evaluation trigger has occurred. As the evaluation trigger, for example, any opportunity as shown in c1 to c4 below can be adopted. If an evaluation trigger occurs (step S16: YES), the evaluation unit 113 shifts the process to step S18. On the other hand, if the evaluation trigger has not occurred (step S16: NO), the evaluation unit 113 shifts the process to step S10 to continue accumulating own vehicle information.
(c1) When starting to drive the own vehicle 90: For example, when starting the engine of the own vehicle 90.
(c2) When driving of the own vehicle 90 is completed: For example, when the vehicle 90 has arrived at the destination, or when the speed of the own vehicle 90 has been zero for a predetermined period of time.
(c3) When the driver P has time to spare: For example, when the speed of the host vehicle 90 remains constant for a predetermined period of time.
(c4) When an evaluation instruction operation by the operator P is detected.

In step S18 in FIG. 2, the evaluation unit 113 uses the own vehicle information 121 to evaluate the driving behavior of the own vehicle 90 (that is, the driver P). Specifically, the evaluation unit 113 calculates the deviation value _Rtk of the current operation from the normal operation using the following equation (1). Note that "k" and "i" are variables (natural numbers) representing the number of times of processing. xm _k in equation (1) is a value representing current operation, and μ _k in equation (1) is a value representing normal operation. σ _k in equation (1) is the standard deviation of the kth accumulated value over the past w2 times. Note that step S18 corresponds to an "evaluation step".

FIG. 4 is a diagram explaining the moving average. As shown in Equation (2), the current driving xm _k is obtained using the moving average of the driving behavior characteristics x. Specifically, the current driving xm _k is calculated by the moving average of the driving behavior characteristics x included in the own vehicle information 121 for the past w1 times (w1 is a natural number) from the current time. For example, when w1 = 3, the current driving xm _k is calculated by the moving average of the driving behavior characteristics x included in the own vehicle information 121 for the past three times from the current time (Figure 4: Within the bold frame range The value of the).

As shown in equation (3), normal driving μ _k is obtained using a moving average of driving behavior characteristics x. Specifically, the normal driving μ _k is calculated by the moving average of the driving behavior characteristics x included in the own vehicle information 121 for the past w2 times (w2 is a natural number) from the current time. For example, when w2=10, normal driving μ _k is calculated by the moving average of the driving behavior characteristics value).

The evaluation unit 113 determines whether the current driving is safer than normal driving by comparing the value of the deviation value Rt _k obtained by equation (1) with a predetermined threshold value (for example, deviation value "50"). Evaluate whether or not the situation is shifting to less safe and unsafe driving. That is, the deviation value Rt _k can be said to be an index representing the deviation of the current operation from the normal operation.

Note that the evaluation unit 113 may calculate the deviation rate Rd _k of the current operation from the normal operation using the following expression (4) instead of the expression (1). xm _k and μ _k in equation (4) are as explained in equations (2) and (3). The evaluation unit 113 determines whether the current driving is safer than normal driving by comparing the value of the deviation rate Rd _k calculated by equation (4) with a predetermined threshold value (for example, deviation rate "0"). It may also be possible to evaluate whether or not the situation is shifting to less safe driving. That is, the deviation rate Rd _k can be said to be an index representing the deviation of the current operation from the normal operation, similar to the deviation value Rt _k .

Note that the evaluation unit 113 uses the deviation value Rt _k and the deviation rate Rd _k together to evaluate whether the current driving is transitioning to unsafe driving, which is less safe than normal driving. You may. In addition, when adopting two or more of the information exemplified in b1 to b5 above (for example, speed and acceleration) as driving behavior characteristics, the evaluation unit 113 calculates the deviation value Rt _k and/or Alternatively, by using the deviation rate Rd _k together with the deviation value Rt _k and/or the deviation rate Rd _k obtained using acceleration, the current driving becomes unsafe driving that is less safe than normal driving. It is possible to evaluate whether the transition is progressing or not.

Note that the evaluation unit 113 may be able to change the value of w1 and the value of w2 used in equations (2) and (3) within a range that satisfies w1<w2. This change may be executable by the administrator of the driving evaluation system 1, or may be executable by the driver P.

In step S20 of FIG. 2, the output control unit 114 refers to the evaluation result by the evaluation unit 113 and determines whether there are signs of unsafe driving (in other words, if the current driving is transitioning to unsafe driving). whether or not). If there is a sign of unsafe driving (step S20: present), the output control unit 114 shifts the process to step S22. On the other hand, if there is no sign of unsafe driving (step S20: none), the output control unit 114 shifts the process to step S10 and continues to accumulate own vehicle information.

FIG. 5 is a diagram illustrating the output of evaluation results. In step S22 of FIG. 2, the output control unit 114 generates information (presentation information) for presenting the evaluation results to the driver P. In step S24, the output control unit 114 causes the information presentation device 40 to output presentation information. As a result, as shown in FIG. 5, presentation information representing the evaluation result is presented to the driver P. For example, in Example 1 of FIG. 5, an image is displayed and/or a voice is output to alert the user that the driver has been speeding a lot lately. Example 1 is a warning about recent trends, so it can be output regardless of the current position of the own vehicle 90. For example, in Example 2 of FIG. 5, an image is displayed and/or a voice is output to alert the driver that "there will be a lot of excessive speeding in the future." Example 2 is a warning related to a specific point, so it is output when the vehicle is a predetermined distance from a point where it is determined that excessive speeding is common. Note that the image display includes the display of characters and the display of icons. Note that step S22 and step S24 correspond to "a step of outputting the evaluation result."

Note that the output control unit 114 may cause the information presentation device 40 to output the evaluation result by the evaluation unit 113 regardless of the presence or absence of signs of unsafe driving. In this case, step S20 in FIG. 2 is omitted. In this case, the output control unit 114 may adopt content such as "The deviation value (deviation rate) of recent driving is XX" or content such as "Thank you for always driving safely" as the presentation information. Further, the output control unit 114 may cause the information presentation device 40 to output the transition of the evaluation result by the evaluation unit 113 (the transition of the deviation value or deviation rate).

As explained above, according to the driving evaluation system 1 of the first embodiment, the evaluation unit 113 of the information processing device 10 uses the driving behavior characteristics of the own vehicle information 121 accumulated in the storage unit 12 to Evaluate personal P's current driving. Here, since the driving behavior characteristics used for evaluation are information about the own vehicle 90 (in other words, information about the individual driver P), driving may be evaluated using data widely collected from the general public. In comparison, the receptivity of the evaluation results by the driver P is high, and it is possible to reduce the possibility that the driver P finds guidance and driving support control based on the evaluation results bothersome. Further, according to the driving evaluation system 1 of the first embodiment, the evaluation unit 113 calculates the deviations Rt _k and Rd _k of the current driving xm _k from the normal driving μ _k using the temporal changes in the driving behavior characteristics. This evaluates whether current driving is shifting to unsafe driving, which is less safe than normal driving. For this reason, it is possible to reduce the possibility that a bad evaluation will be given to a unique driving behavior characteristic that suddenly occurs due to an operation error or the situation at the time. As a result, the driving evaluation system 1 of the first embodiment can provide a driving evaluation system that can present evaluation results that are easily accepted by the driver.

Further, according to the driving evaluation system 1 of the first embodiment, the evaluation unit 113 of the information processing device 10 easily calculates the current driving xm _k and the normal driving μ _k using the moving average of the driving behavior characteristics. Furthermore, it is possible to evaluate current driving using changes in driving behavior characteristics over time. According to equation (1), the evaluation unit 113 uses the deviation value Rt _k of the current operation xm _k from the normal operation μ _k as an index representing the deviation, so that the deviation It is possible to obtain evaluation results with fewer errors. Furthermore, according to equation (4), the evaluation unit 113 uses the deviation rate Rd _k of the current operation xm _k with respect to the normal operation μ _k as an index representing the deviation, thereby obtaining a clear evaluation result based on the normal operation. can be obtained. Furthermore, since both the deviation value and the deviation rate are standardized values, it is possible to obtain evaluation results that are less affected by differences in the absolute values of speed and acceleration depending on the driver or location.

Further, according to the driving evaluation system 1 of the first embodiment, the evaluation unit 113 of the information processing device 10 sets the moving average of the driving behavior characteristics of the past w1 times, going back from the present, to the current driving xm _k , and Since the moving average of the driving behavior characteristics for the past w2 times is set as normal driving μ _k , it is possible to obtain the smoothed current driving and normal driving.

Furthermore, according to the driving evaluation system 1 of the first embodiment, the evaluation unit 113 of the information processing device 10 allows at least one of the value of w1 and the value of w2 to be changed within a range satisfying w1<w2. Therefore, the degree of smoothing between the current operation xm _k and the normal operation μ _k can be changed. For example, by increasing the value of w1, current driving can be evaluated from a long-term perspective, while by decreasing the value of w1, current driving can be evaluated from a short-term perspective. For example, by increasing the value of w2, it is possible to evaluate current driving based on normal driving from a long-term perspective, while by decreasing the value of w2, it is possible to evaluate from a short-term perspective. It is possible to evaluate current driving based on (recent) normal driving.

Furthermore, according to the driving evaluation system 1 of the first embodiment, the driving behavior characteristics include the speed of the host vehicle 90, the acceleration of the host vehicle 90, the average speed of the host vehicle 90 in a predetermined section, and the drive behavior characteristics of the host vehicle 90 in the predetermined section. It is possible to realize evaluation using at least one of the maximum deceleration of the vehicle 90 and the maximum deceleration of the vehicle 90.

Further, according to the driving evaluation system 1 of the first embodiment, the storage unit 112 of the information processing device 10 stores own vehicle information at a specific point predetermined in the specific point information 122 in the storage unit 12, and Own vehicle information at a point different from the point is not stored in the storage unit 12. For this reason, the specific point is the point explained in a1 to a3, specifically, a point where a large change in driving behavior characteristics (e.g. speed, acceleration, section average speed, maximum deceleration) is expected (e.g. , the position of a stop line, the position of a railroad crossing, etc.) or a point where the own vehicle 90 passes relatively frequently (for example, an arbitrary point on the commuting route of the driver P, etc.). It is possible to efficiently collect and store own vehicle information. Furthermore, the amount of data accumulated in the storage unit 12 (the amount of data of the own vehicle information 121 ) can be reduced, and the processing load on the information processing device 10 can be reduced.

<Second embodiment>
FIG. 6 is a schematic diagram of a driving evaluation system 1A according to the second embodiment. The driving evaluation system 1A includes an information processing device 10A mounted on the own vehicle 90 shown in FIG. 1, and a server 20 connected via a network. In addition, in FIG. 6, illustration of the GPS receiver 30, the information presentation device 40, the own vehicle 90, and the driver P shown in FIG. 1 is omitted. In the driving evaluation system 1A of the second embodiment, the server 20 executes the driving behavior evaluation (FIG. 2: step S18) and the process of generating and displaying presentation information (steps S20 to S24).

The information processing device 10A has the configuration described in the first embodiment, but includes a CPU 11A instead of the CPU 11. The CPU 11A does not have the evaluation section 113 and the output control section 114 described in the first embodiment, but does have a communication section 115. The communication unit 115 executes the evaluation process described in FIG. 2 by communicating with the server 20 connected via the network. Details will be described later.

The server 20A includes a CPU 21, a storage section 22, and a ROM/RAM (not shown), and each section is interconnected by a bus. The CPU 21 controls each part of the server 20 by loading a computer program stored in the ROM into the RAM and executing it. In addition, the CPU 21 also functions as an evaluation section 213, an output control section 214, and a communication section 215. The processing in the evaluation unit 213 is similar to that in the evaluation unit 113 of the information processing device 10 described in the first embodiment. The processing in the output control unit 214 is similar to the output control unit 114 of the information processing device 10 described in the first embodiment. The communication unit 215 executes the evaluation process described in FIG. 2 by communicating with the information processing device 10A connected via the network. Details will be described later.

In step S16 of the evaluation process in FIG. 2, the communication unit 115 of the information processing device 10A determines whether a predetermined evaluation trigger (c1 to c4) has occurred. If an evaluation trigger occurs (step S16: YES), the communication unit 115 transmits the evaluation request and the own vehicle information 121 stored in the storage unit 12 to the server 20. On the other hand, if the evaluation trigger has not occurred (step S16: NO), the communication unit 115 shifts the process to step S10 to continue accumulating own vehicle information.

The evaluation unit 213 of the server 20 that has received the evaluation request executes step S18 of the evaluation process in FIG. Thereafter, the output control unit 214 of the server 20 executes steps S20 to S24 of the evaluation process in FIG. Specifically, in step S20, the output control unit 214 transitions the process to step S22 if there is a sign of unsafe driving (step S20: present). On the other hand, if there is no sign of unsafe driving (step S20: none), the output control unit 214 responds only the evaluation result to the information processing device 10A, and ends the process. This evaluation result can be in any form; for example, the response may be that there is no sign of unsafe driving, or the deviation value Rt _k or deviation rate Rd _k obtained in step S18 may be responded to. Alternatively, other embodiments may be adopted. The communication unit 115 that has received the response from the server 20 may or may not cause the information presentation device 40 to output the evaluation result included in the response.

In step S22 of the evaluation process in FIG. 2, the output control unit 214 of the server 20 generates information (presentation information) for presenting the evaluation result to the driver P. Thereafter, the output control unit 214 of the server 20 responds to the information processing device 10A with the evaluation result and the generated presentation information, and ends the process. This evaluation result can be in any form; it may be a response that "there are signs of unsafe driving", or it may be a response of the deviation value Rt _k or the deviation rate Rd _k obtained in step S18. It may be omitted (if omitted, the response from the server 20 will be only the presentation information). The communication unit 115 that has received the response from the server 20 causes the information presentation device 40 to output the presentation information included in the response.

In this way, the configuration of the driving evaluation system 1A can be changed in various ways, and at least some of the functional units described in the first embodiment may be realized by the server 20 provided externally. In the example of FIG. 6, an example is shown in which the functions of the evaluation section 213 and the functions of the output control section 214 are realized by the server 20. However, other functions may be implemented by the server 20. For example, the vehicle information 121 and specific point information 122 of the information processing device 10A may be stored in the storage unit 22 of the server 20. In this case, the own vehicle information 121 further stores information for identifying the own vehicle 90 (or information for identifying the driver P) in association with the information explained in FIG. 3.

In this way, the driving evaluation system 1A of the second embodiment can also achieve the same effects as the first embodiment described above. Further, according to the driving evaluation system 1A of the second embodiment, the processing load on the information processing device 10A can be reduced.

<Modification of this embodiment>
The present invention is not limited to the above-described embodiments, and can be implemented in various forms without departing from the gist thereof. For example, a part of the configuration that is realized by hardware may be implemented by software. Alternatively, a part of the configuration realized by software may be replaced by hardware. In addition, the following modifications are also possible, for example.

[Modification 1]
In the above embodiment, the configuration of the driving evaluation system 1, 1A is illustrated. However, as described in the second embodiment, the configuration of the driving evaluation system 1 can adopt any configuration. For example, the driving evaluation system 1 may be configured by an in-vehicle device, a smartphone, a robot, etc. that has all the functions of the information processing device 10, the GPS receiver 30, and the information presentation device 40. For example, the function of the storage section 112 may be realized by the server 20.

[Modification 2]
In the embodiment described above, the evaluation process (FIG. 2) has been described using an example of the processing procedure. However, these processing procedures can be changed in various ways, and the processing contents in each step may be added/omitted/changed, and the execution order of the steps (procedures) may be changed.

For example, in step S14, the storage unit 112 stores own vehicle information (own vehicle position information, driving behavior characteristics, and accompanying information) in the own vehicle information 121 in all processing cycles, regardless of whether it is a specific point or not. It's okay. In this case, the specific point information 122 described in FIG. 1 can be omitted.

For example, in step S18, the evaluation unit 113 may calculate the deviation of the current operation from the normal operation using an index different from the above-mentioned equations (1) to (4). For example, by using a neural network that inputs changes in the driving behavior characteristics of the own vehicle 90 over time (in other words, the history of the driving behavior characteristics of the own vehicle 90) and outputs the deviation of the current driving from the normal driving, the current The deviation of the driving from the normal driving may be calculated. In addition, in the above-mentioned equations (1) to (4) and the neural network, additional information (for example, date and time, location information, and external environment when the driving behavior characteristics were acquired: season, weather, temperature, etc.) is further taken into consideration. The evaluation results may be output. In this way, the deviation of current driving from normal driving can be determined by taking into account the conditions that tend to cause differences in driving behavior characteristics (for example, during the day when the sun is high or on clear skies, and when it is night or rainy). can be calculated, further improving evaluation accuracy.

For example, indicators other than the speed, acceleration, section average speed, maximum deceleration, and section minimum speed described in b1 to b5 above may be used as driving behavior characteristics. In this case, for example, speed exceeding the speed limit or presence or absence of sudden deceleration may be used as the driving behavior feature. Sudden deceleration can be determined when a G exceeding a predetermined reference G (for example, 0.25 G) is applied.

For example, in the above-described specific example, w1=3 and w2=10, but these can be changed arbitrarily. For example, if w1=1, the current driving can be evaluated. Furthermore, the range of smoothing may be expanded to w1=10. The same applies to w2. For example, in the above-mentioned specific example, the deviation value is 50 and the deviation rate is 0 as the threshold value for detecting a sign of shifting to unsafe driving. However, by changing these thresholds, the level of unsafety can be set. Further, the threshold value may be dynamically changed when an unsafe condition continues for a certain period of time or when the threshold value is frequently crossed. This makes it possible to reduce detection of unnecessary unsafe conditions.

[Modification 3]
The features of the first and second embodiments and the first and second modified examples described above can be combined as appropriate. For example, in the configuration of the second embodiment (configuration using the server 20), each feature described in Modifications 1 and 2 may be adopted.

Although the present aspect has been described above based on the embodiments and modified examples, the embodiments of the above-described aspect are for facilitating understanding of the present aspect, and do not limit the present aspect. This aspect may be modified and improved without departing from the spirit and scope of the claims, and this aspect includes equivalents thereof. Furthermore, if the technical feature is not described as essential in this specification, it can be deleted as appropriate.

1,1A...Driving evaluation system 10,10A...Information processing device 11,11A...CPU
12...Storage unit 20, 20A...Server 21...CPU
22...Storage unit 30...GPS receiver 40...Information presentation device 90...Vehicle 91...Interior 92...Windshield 93...Dashboard 111...Acquisition unit 112...Storage unit 113...Evaluation unit 114...Output control unit 115...Communication Section 121...Own vehicle information 122...Specific point information 213...Evaluation section 214...Output control section 215...Communication section

Claims (9)

A driving evaluation system,
an acquisition unit that acquires own vehicle information including own vehicle position information representing the position of the own vehicle and driving behavior characteristics of the own vehicle at the position;
a storage unit that stores the acquired own vehicle information in a storage unit;
By calculating the deviation of current driving from normal driving using changes over time in the driving behavior characteristics of the accumulated own vehicle information, it is possible to determine whether the current driving is safer than normal driving. An evaluation department that evaluates whether the driving is progressing to low levels of unsafe driving;
an output control unit that outputs the evaluation result by the evaluation unit;
A driving evaluation system equipped with The driving evaluation system according to claim 1,
The evaluation department is
determining the current driving and the normal driving using a moving average of the driving behavior characteristics;
A driving method that evaluates whether the current driving is transitioning to the unsafe driving by calculating a deviation value of the current driving with respect to the normal driving as an index representing the deviation. Rating system. The driving evaluation system according to claim 1 or 2,
The evaluation department is
determining the current driving and the normal driving using a moving average of the driving behavior characteristics;
Evaluating whether the current driving is transitioning to the unsafe driving by calculating a deviation rate as an index representing the deviation, which is a deviation rate of the current driving from the normal driving. Rating system. The driving evaluation system according to claim 2 or 3,
The evaluation department is
The moving average of the driving behavior characteristics included in the own vehicle information for the past w1 (w1 is a natural number) times from the present is set as the current driving,
A driving evaluation system in which a moving average of the driving behavior characteristics included in the own vehicle information for past w2 times (w2 is a natural number) from the present is taken as the normal driving. The driving evaluation system according to claim 4,
The evaluation unit is a driving evaluation system that allows at least one of the value of w1 and the value of w2 to be changed within a range that satisfies w1<w2. The driving evaluation system according to any one of claims 1 to 5,
The driving behavior characteristics include the speed of the own vehicle, the acceleration of the own vehicle, the average speed of the own vehicle in a predetermined section, the maximum deceleration of the own vehicle in the predetermined section, and the minimum section speed of the own vehicle in the predetermined section. A driving evaluation system that is at least one of the following. The driving evaluation system according to any one of claims 1 to 6,
A driving evaluation system, wherein the storage section stores the own vehicle information at a predetermined specific point in the storage section, and does not accumulate the own vehicle information at a point different from the specific point in the storage section. A method for evaluating driving, the information processing device comprising:
acquiring own vehicle information including own vehicle position information representing the position of the own vehicle and driving behavior characteristics of the own vehicle at the position;
a step of accumulating the acquired own vehicle information in a storage unit;
By calculating the deviation of current driving from normal driving using changes over time in the driving behavior characteristics of the accumulated own vehicle information, it is possible to determine whether the current driving is safer than normal driving. A process of evaluating whether the driving is progressing to a low level of unsafe driving;
outputting the results of the evaluation;
How to do it. A computer program, which is applied to an information processing device,
a function of acquiring own vehicle information including own vehicle position information representing the position of the own vehicle and driving behavior characteristics of the own vehicle at the position;
a function of accumulating the acquired own vehicle information in a storage unit;
By calculating the deviation of current driving from normal driving using changes over time in the driving behavior characteristics of the accumulated own vehicle information, it is possible to determine whether the current driving is safer than normal driving. A function to evaluate whether driving is shifting to a low level of unsafe driving,
A function to output the results of the evaluation,
A computer program that runs

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