JP2008298979A - Evaluation device for driving skill and method for evaluating driving skill and program for evaluating driving skill - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To accurately and objectively evaluate a driving skill and to increase entertainment properties of driving itself. <P>SOLUTION: A driving operation data creating unit 35 extracts a status of driving operation caused by only the operation of a driver of a car, based on real traveling behavior data representing a traveling status when the car actually travels in a predetermined section to a desired destination, and based on estimated behavior data estimating an ideal traveling status assuming that the car actually travels in the predetermined section to the desired destination; and the unit 35 creates driving operation data based on the extraction results. A driving operation evaluation unit 37 evaluates the driving skill of the driver based on the driving operation data 45. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a driving skill evaluation device, a driving skill evaluation method, and a driving skill evaluation program for guiding a route of a vehicle toward a desired destination.

  In recent years, various techniques have been developed to ensure safe driving with respect to vehicles. As such a technology, there is a system (hereinafter referred to as “driving technology diagnostic system”) that objectively evaluates the driving technology of the driver by diagnosing the driving technology of the vehicle by the driver.

  In this driving technology diagnosis system, the characteristics of vehicle behavior detected by a sensor unit are recorded in a memory medium, and this is diagnosed by a diagnostic device. This diagnostic device specifies, for example, a driving behavior at an intersection as a predetermined vehicle behavior from a memory medium, extracts only measurement data in this driving behavior, and generates feature information representing the driving characteristics of the driver. . The diagnostic device diagnoses the driving technique by the driver based on the comparison result between the feature information and the safety standard information as a reference, and generates diagnostic information indicating the driving situation of the driver.

In such a conventional driving technology diagnosis system, when the measurement data exceeds a certain value, it is detected that the vehicle behavior is caused by an unreasonable driving operation (see Patent Document 1). As a case where such measurement data exceeds a certain value, for example, a case where the measurement data conforms to the conditions set by the condition setting unit can be cited.
Japanese Patent No. 3593502

  However, in the conventional driving technology diagnosis system, judging the measurement data based on the preset threshold value in this way may not be an accurate judgment in relation to the actual road shape. . In other words, in the conventional driving technology diagnosis system, even if it is determined that the driver has performed an abrupt steering operation based on this measurement data, this is an unavoidable operation due to the road shape, for example, or driving It was not possible to accurately reflect whether it was a problem of the driver's driving skill.

  The problem to be solved by the present invention includes the above-described problem as an example.

  In order to solve the above-mentioned problem, the invention according to claim 1 detects a traveling situation when the vehicle actually travels in a predetermined section to a desired destination, and generates actual traveling behavior data representing the detection result. It is assumed that the vehicle actually travels the predetermined section to the desired destination based on the actual travel behavior data generating means and the road shape data representing the road shape of the predetermined section to the desired destination. In this case, an estimated behavior data generating unit that estimates an ideal driving situation and generates estimated behavior data representing the estimation result, and based on the actual driving behavior data and the estimated behavior data, the driver of the vehicle A driving operation data generating means for extracting driving operation status caused only by the operation and generating driving operation data based on the extraction result; and the driving operation data based on the driving operation data And a driving skill evaluation means for evaluating the driving skill.

  In order to solve the above-mentioned problem, the invention according to claim 7 detects the traveling situation when the vehicle actually travels in the predetermined section to the desired destination by the actual traveling behavior data generating means, and the detection result Based on road shape data representing a road shape of a predetermined section to the desired destination by the actual behavior data generating step for generating actual driving behavior data representing the vehicle and the estimated behavior data generating means. An estimated behavior data generation step for estimating an ideal driving situation when it is assumed that the vehicle has actually traveled a predetermined section to the destination of the vehicle, and generating estimated behavior data representing the estimation result, and driving operation data generating means Based on the actual driving behavior data and the estimated behavior data, the situation of the driving operation caused only by the operation of the driver of the vehicle is extracted Has a driving operation data generation step of generating the driving operation data based on the extraction result, by driving skill evaluation means, and a driving skill evaluation step of evaluating the driving skill of the driver based on the driving operation data.

  In order to solve the above-mentioned problem, the invention according to claim 8 detects the traveling situation when the vehicle actually travels the predetermined section to the desired destination by the actual traveling behavior data generating means, and the detection result Based on road shape data representing a road shape of a predetermined section to the desired destination by the actual behavior data generating step for generating actual driving behavior data representing the vehicle and the estimated behavior data generating means. An estimated behavior data generation step for estimating an ideal driving situation when it is assumed that the vehicle has actually traveled a predetermined section to the destination of the vehicle, and generating estimated behavior data representing the estimation result, and driving operation data generating means Based on the actual driving behavior data and the estimated behavior data, the situation of the driving operation caused only by the operation of the driver of the vehicle is extracted Driving skill data generation step for generating driving operation data based on the extraction result, and driving skill evaluation step for evaluating the driving skill of the driver based on the driving operation data by driving skill evaluation means Run on the device.

  Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

  FIG. 1 is a block diagram illustrating a hardware configuration example of the navigation device 100 according to the present embodiment.

  The navigation device 100 has a vehicle guidance function for guiding the vehicle to a desired destination. The navigation device 100 corresponds to a driving skill evaluation device, and a storage device 18, a calculation device 20, a display control circuit 14, and an interface 6 are connected to the bus 12. A display 15 is connected to the navigation device 100. Various sensors 22 are connected to the navigation device 100 via the interface 6. The display 15 and various sensors 22 may be part of the navigation device 100.

  The driving skill evaluation device may be incorporated as one function of the navigation device 100, or may be incorporated as a separate function that is exhibited separately from the vehicle guidance function by the navigation device 100. That is, the driving skill evaluation device may be configured to operate almost constantly even when the vehicle guidance function is not exhibited by the navigation device 100.

  A storage device 18, an interface 6, an arithmetic device 20 and a display control circuit 14 are connected to the bus 12. Therefore, the arithmetic unit 20 is configured to exchange data with the storage device 18, the interface 6, and the display control circuit 14.

  Examples of the various sensors 22 include the acceleration sensor 5, the gyro sensor 2, the vehicle speed pulse detector 3, the GPS (Global Positioning System) 4, the back sensor 21, the geomagnetic sensor 1, or any combination thereof. . In the present embodiment, when the outputs of the various sensors 22 are collectively referred to, they are also called “sensor data”.

  The acceleration sensor 5 has a function of detecting, for example, at least one of a vehicle acceleration and an inclination angle. The gyro sensor 2 has a function of detecting the moving direction of the vehicle, for example. The gyro sensor 2 is a kind of angular velocity sensor that outputs angular velocity data accompanying a change in the direction of the vehicle. The gyro sensor 2 may measure the tilt angle instead of the acceleration sensor 5.

  The vehicle speed pulse detector 3 has a function of detecting the amount of movement and acceleration of the vehicle, for example. The vehicle speed pulse detector 3 detects whether the vehicle is moving or stopped, and outputs the detected state. The vehicle speed pulse detector 3 has a function of outputting travel state data relating to the travel speed and travel distance of the vehicle when the vehicle is moving. The GPS 4 has a function of receiving and calculating radio waves from a plurality of GPS satellites and performing positioning. For example, the GPS 4 generates positioning data of any one of latitude, longitude, altitude, and traveling direction, or any combination thereof.

  Specifically, the GPS 4 has a function of, for example, measuring pseudo distances to four satellites observed at the same time, and positioning the current location based on a difference in pseudo distances to these four satellites. The back sensor 21 has a function of detecting the moving direction of the vehicle. Specifically, the back sensor 21 has a function of detecting, for example, the position of the transmission gear and detecting whether the vehicle is moving forward or backward. The geomagnetic sensor 1 is a kind of azimuth detecting device that detects an angle representing an absolute azimuth of a vehicle based on geomagnetism. Examples of such an angle include an azimuth angle.

  The storage device 18 includes a ROM 8, a RAM 9, and a recording medium 16. The ROM 8 is an information storage medium in which various processing programs described later and other necessary information are written in advance. The RAM 9 is an information storage medium on which information necessary for executing the various programs is written and read.

  The RAM 9 is a memory that can store volatile driving behavior data, estimated behavior data, driving operation data, and driving operation evaluation values described later in a volatile manner. The recording medium 16 is an information storage medium such as a flash memory or a hard disk. The recording medium 16 can store map information and road shape data, which will be described later, in a nonvolatile manner.

  The arithmetic unit 20 includes a CPU 7 and a graphic controller 13. The CPU 7 has a function of performing various calculations and controls according to the various programs. The graphic controller 13 has a function of acquiring image data from a video RAM (not shown) under the control of the CPU 7 and causing the display control circuit 14 to display an image based on the image data on the display 15.

  Specifically, the graphic controller 13 has a function of displaying, for example, a map based on the map information on the display 15 or displaying a mark representing the position of the own vehicle on the map under the control of the CPU 7. Have.

  FIG. 2 is a block diagram illustrating a configuration example of software in the navigation device 100 illustrated in FIG. FIG. 2 shows a schematic configuration example of various programs and various data operating in the arithmetic unit 22 shown in FIG.

  The navigation device 100 includes, as software corresponding to a driving skill evaluation program, a vehicle position detection unit 31, an actual traveling behavior data generation unit 32, an estimated behavior data generation unit 33, a driving operation data generation unit 35, a driving operation evaluation unit 37, and A display output unit 39 is provided. In addition, the navigation device 100 includes, for example, map information 41, road shape data 42, actual travel behavior data 43, estimated behavior data 44, driving operation data 45, and driving operation evaluation value 46 as information and data.

  Among these, the map information 41 and the road shape data 42 are stored in, for example, the recording medium 16. Further, the actual traveling behavior data 43, the estimated behavior data 44, the driving operation data 45, and the driving operation evaluation value 46 are stored in the RAM 9, for example.

  The host vehicle position detection unit 31, the estimated behavior data generation unit 33, the driving operation data generation unit 35, the driving operation evaluation unit 37, and the display output unit 39 are, for example, programs and are stored in the ROM 8. The own vehicle position detection unit 31 and the like operate by being read from the ROM 8 under the control of the CPU 7 and developed in the RAM 9.

  The map information 41 represents information relating to a map necessary for guiding the vehicle to a desired destination. The road shape data 42 is data representing the shape of each road on the map. The actual traveling behavior data 43 is behavior data representing behavior when the own vehicle detected by the various sensors 22 actually travels. The estimated behavior data 44 is behavior data representing the behavior of the host vehicle that is estimated when the vehicle travels on the route to the destination. The estimated behavior data 44 is generated by the arithmetic device 20.

  The driving operation data 45 is data representing the driving skill of the driver who drives the vehicle. The driving operation evaluation value 46 is an evaluation value that numerically represents the driving skill of the driver based on the driving operation data 45.

  The own vehicle position detection unit 31 controls the GPS 4 to measure the position of the own vehicle. The vehicle position detection unit 31 has a function of guiding a route to a desired destination based on the map information 41 and the road shape data 42. The road shape data 42 is information for specifying the shape of each road using, for example, nodes and links.

  Specifically, for example, in a digital road map, a road network is expressed by a combination of nodes and links. Each node is given a unique node number. On the other hand, each link is also given a unique link number. The node represents an intersection or a nodal point on the road network expression. On the other hand, the link represents a road section between nodes.

  The actual traveling behavior data generating unit 32 corresponding to the actual traveling behavior data generating means detects actual traveling behavior data when the vehicle actually travels in a predetermined section to a desired destination, and actual traveling behavior data representing the detection result. 43 is generated. The actual travel behavior data generation unit 32 uses sensor data from the various sensors 22 in generating the actual travel behavior data 43.

  The estimated behavior data generating unit 33 corresponding to the estimated behavior data generating means is configured to determine a predetermined section from the vehicle to the desired destination based on the road shape data 42 representing the road shape of the predetermined section to the desired destination. It has a function of estimating an ideal traveling situation when it is assumed that the vehicle actually traveled and generating estimated behavior data 44 representing the estimation result. The estimated behavior data 44 is information used as an evaluation criterion when evaluating the driving skill of the driver as will be described later.

  The driving operation data generating unit 35 corresponding to the driving operation data generating means extracts the driving operation status caused only by the operation of the driver of the vehicle based on the actual driving behavior data 43 and the estimated behavior data 44. , And has a function of generating driving operation data 45 based on the extraction result.

  The driving operation evaluation unit 37 corresponding to the driving skill evaluation means has a function of evaluating the driving skill of the driver based on the driving operation data 45. The display output unit 39 has a function of outputting information on the driving skill of the driver who drives the vehicle based on the driving operation evaluation value 46, at least one of video and sound.

  The vehicle guidance program has a correction unit 36. The correction unit 36 as correction means generates correction data 47 corresponding to the vehicle travelable situation in the predetermined section based on the actual travel behavior data 43, and the estimated behavior data 44 based on the correction data 47. It has a function to correct.

  For example, the correction unit 36 generates the correction data according to a plurality of driving situations by the vehicle based on the plurality of actual driving behavior data 43. Here, “according to a plurality of traveling situations by the vehicle based on the plurality of actual traveling behavior data 43” can be obtained by superposing these plural traveling situations and taking an average, for example. In the following description, such processing is referred to as “superimposition of actual traveling behavior data 43”.

  The driving operation evaluation unit 37 as a driving skill evaluation means records the driving operation data 45 in the recording medium 16 in association with the road shape data 42. That is, the navigation device 100 includes the storage medium 16 corresponding to a storage unit that records the driving operation data 45 in association with the road shape data 42.

  The driving operation evaluation unit 37 corresponding to driving skill evaluation means includes a jerk calculation function and a jerk determination function. First, the jerk calculation function corresponding to the jerk calculation means is a function for differentiating the driving operation data 45 with respect to three mutually perpendicular directions in the vehicle and calculating the resultant jerk. The “jerk acceleration” represents a value obtained by differentiating acceleration with respect to time, that is, a change amount of acceleration per unit time. On the other hand, the jerk determination function corresponds to jerk determination means, and is a function that determines that the driving state of the vehicle is bad when the jerk exceeds a prescribed threshold. As the driving situation here, for example, riding comfort of the vehicle can be cited.

  Further, the driving operation evaluation unit 37 corresponding to the driving skill evaluation means has a control data calculation function and a control data amount determination function. First, the control data calculation function corresponding to the control data calculation means is a function for inputting the driving operation data 45 to a feedback control function and calculating control data necessary for vehicle stability. On the other hand, the control data amount judging function corresponding to the control data amount judging means is a function for judging the driving situation of the vehicle according to whether or not the amount of the control data exceeds a prescribed threshold value. The driving situation here may be, for example, the ride comfort of the vehicle as described above.

  The navigation device 100 is configured as described above. Next, an example of a procedure of a vehicle guidance method executed in the navigation device 100 will be described with reference to FIGS. 1 and 2.

  FIG. 3 is a flowchart illustrating an example of the procedure of the vehicle guidance process. In this flowchart, it is assumed that the driver operates the navigation device 100 while driving the vehicle and the route to the desired destination is guided.

  First, in step S1, the vehicle position detection unit 31 determines whether or not the driver has set a route to a desired destination, for example, and performs a waiting process until the route setting is completed. Next, in step S2, the vehicle position detection unit 31 starts route guidance to the set destination. Next, in step S3, the host vehicle position detection unit 31 detects the position of the host vehicle using the GPS4. In step S <b> 4, the own vehicle position detection unit 31 performs control to display the position of the own vehicle on the map and the road based on the map information 41 and the road shape data 42.

  In step S5, the driving operation evaluation unit 37 evaluates the driving skill by the driver. This driving operation evaluation process will be described later. Next, in step S <b> 6, the display output unit 39 visually displays the evaluation of the driving skill of the driver based on the driving operation evaluation value 46. This driving evaluation display process will also be described later.

  Next, in step S7, the vehicle position detection unit 31 determines whether or not the route guidance to the destination is finished. Specifically, the own vehicle position detecting unit 31 determines whether or not the measured vehicle position is close to the set destination and closes the route guidance if it is close, S8 is executed. On the other hand, if the measured position of the vehicle is not close, the process returns to step S3 and executed. In step S <b> 8, the display output unit 39 displays a comprehensive evaluation related to the driver's driving skill. In the present embodiment, such comprehensive evaluation is also expressed as “total review”.

  FIG. 4 is a flowchart showing an example of each process included in the driving operation evaluation process S5 shown in FIG. In addition, this flowchart represents the procedure included in the driving skill evaluation method. This flowchart also shows the procedure executed by the driving skill evaluation program.

  First, in step S10, the actual traveling behavior data generation unit 32 executes actual traveling behavior data generation processing. In the actual travel behavior data generation process, first, the actual travel behavior data generation unit 32 detects a travel situation when the vehicle actually travels in a predetermined section to a desired destination (actual travel behavior data generation step). Equivalent). Further, the actual travel behavior data generation unit 32 generates actual travel behavior data 43 representing the detection result (corresponding to an actual travel behavior data generation step).

  Next, in step S11, correction data generation processing is executed. In the correction data generation process, first, the correction unit 36 generates correction data 47 corresponding to the vehicle travelable situation in a predetermined section based on the actual travel behavior data 43 (corresponding to a correction data generation step). Further, the correction unit 36 corrects the estimated behavior data 44 based on the correction data 47 (corresponding to a correction data generation step).

  Next, in step S12, estimated behavior data generation processing is executed. In this estimated behavior data generation process, first, the estimated behavior data generation unit 33 determines a predetermined section from the vehicle to the desired destination based on the road shape data representing the road shape of the predetermined section to the desired destination. An ideal driving situation is estimated when it is assumed that the vehicle actually traveled (corresponding to an estimated behavior data generation step). Further, the estimated behavior data generation unit 33 estimates estimated behavior data 44 representing the estimation result (corresponding to an estimated behavior data generation step). The estimated behavior data 44 is information that serves as an evaluation criterion when evaluating the driving skill of the driver as described above.

  Next, in step S13, a driving operation data generation process is executed. In this driving operation data generation process, first, the driving operation data generation unit 35 extracts the driving operation status caused only by the operation of the vehicle driver based on the actual traveling behavior data 43 and the estimated behavior data 44 (driving) Equivalent to operation data generation step). Further, the driving operation data generation unit 35 generates driving operation data 45 based on the extraction result (corresponding to a driving operation data generation step).

  Next, in step S14, a driving operation evaluation process is executed. In the driving operation evaluation process, the driving operation evaluation unit 37 evaluates the driving skill of the driver based on the driving operation data 45 (corresponding to a driving skill evaluation step).

  FIG. 5 is a flowchart showing an example of the procedure of the actual travel behavior data generation process shown in FIG.

  This actual traveling behavior data generation processing represents processing in which the actual traveling behavior data generation unit 32 controls the various sensors 22 to generate actual traveling behavior data 43. In step S11, the gyro sensor 2 detects the moving direction of the vehicle. In step S12, the vehicle speed pulse detector 3 detects the amount of movement of the vehicle. At this time, the vehicle speed pulse detector 3 also detects the acceleration of the vehicle. In step S13, the acceleration sensor 5 detects the acceleration of the vehicle. At this time, the acceleration sensor 5 may detect the tilt angle of the vehicle.

  In step S14, the back sensor 21 detects the moving direction in the front-rear direction of the vehicle. As such a moving direction, for example, it can be mentioned whether it is a forward direction or a backward direction. In step S <b> 15, the CPU 7 calculates the relative movement amount of the vehicle based on the data from the various sensors 22. In step S16, the CPU 7 calculates so as to decompose the relative movement amount of the vehicle into three-direction components. Here, the three directions represent the traveling direction D1, the horizontal direction D2, and the vertical direction D3 of the vehicle when the vehicle 99 is disposed as shown in FIG.

  The traveling direction D1, the horizontal direction D2, and the vertical direction D3 are perpendicular to each other. Next, in step S17, the CPU 7 second-order differentiates the relative movement amount of the vehicle with respect to time, and acquires acceleration components in three directions. The information acquired in this way corresponds to the actual running behavior data 43 of the vehicle.

  FIG. 7 is a flowchart showing an example of the procedure of the correction data generation process shown in FIG. This correction data generation process represents a process executed by the correction unit 36.

  First, in step S <b> 21, the correction unit 36 determines whether or not the actual running behavior data 43 stored in the past exists in the RAM 9. When the actual running behavior data 43 stored in the past exists, the CPU 7 superimposes the actual running behavior data 43 acquired now and the actual running behavior data 43 stored in the past. Specifically, the CPU 7 takes an average value of both actual traveling behavior data 43.

  Next, in step S23, it is determined whether or not the actual traveling behavior data 43 includes suddenly varying actual traveling behavior data 43 that cannot be attributed to the driving operation. When there is actual traveling behavior data 43 including a sudden change, the CPU 7 executes the following step S24. In step S <b> 24, the CPU 7 records the actual running behavior data 43 including a sudden change in the RAM 9 as the correction data 47. As the correction data 47, data for correcting the road shape can be exemplified.

  On the other hand, when the CPU 7 determines that there is no actual travel behavior data 43 that includes abrupt changes, step S25 shown below is executed. In step S <b> 25, the CPU 7 determines whether the actual traveling behavior data 43 includes the actual traveling behavior data 43 having no correlation that cannot be estimated from the road shape data 42. Here, “no correlation” can be expressed as, for example, “uncorrelated”. The CPU 7 ends the process when the actual traveling behavior data 43 having no correlation exists, and executes the following step S26 when the actual traveling behavior data 43 having no correlation exists.

  In this step S26, the CPU 7 records the actual traveling behavior data 43 having no correlation as the correction data 47 as the RAM 9. The correction data 47 here represents data for correcting the road shape, for example. Here, the actual traveling behavior data 43 having no correlation represents, for example, a case where acceleration of sudden fluctuation in the vertical direction D3 is detected when the vehicle 99 crosses a gap (not shown) on the road as shown in FIG. ing.

  Further, as the actual traveling behavior data 43 having no correlation, for example, when the vehicle 99 bypasses the obstacle 98 on the road, an acceleration having no correlation with the road shape in the traveling direction D1 and the horizontal direction D2 is detected. Represents.

  FIG. 9 is a flowchart showing an example of a specific procedure of the estimated behavior data acquisition process 30 shown in FIG. This estimated behavior data acquisition process represents a procedure executed by the estimated behavior data generation unit 33.

  First, in step S <b> 31, the CPU 7 calculates an estimated movement amount of the vehicle from the road shape data 42. The estimated movement amount here refers to a movement amount estimated based on the road shape data 42. Next, in step S32, the CPU 7 decomposes the estimated movement amount of the vehicle into components in three directions. The three directions here represent, for example, a traveling direction D1, a horizontal direction D2, and a vertical direction D3. Next, in step S33, the CPU 7 second-order differentiates the estimated movement amount of the vehicle with respect to time, and calculates an estimated acceleration component in three directions.

  Next, in step S34, the CPU 7 adds the estimated acceleration component and the correction data 47, and generates estimated behavior data 44 as a result of the addition. That is, the correction data 7 here represents information that should be used to bring behavior data predicted for a vehicle based on the road shape data 42 closer to behavior data estimated when the vehicle actually travels.

  Here, as a specific example of the road shape data 42, the road has a predetermined radius of curvature R and the road width is W as shown in FIG. At this time, when the speed limit of the road is 50 km / h, the CPU 7 considers that the vehicle travels below the speed limit and has the road width W and the radius of curvature R, and the estimated acceleration component. Is calculated. Further, the CPU 7 calculates to decompose the components in the above three directions.

  Further, when the CPU 7 determines that the vehicle travels on the road having the inclination angle θ as shown in FIG. 11 as well as the speed limit, the curvature radius R, and the road width W based on the road shape data 42, for example, Based on this information, the estimated movement amount of the vehicle 99 can be uniquely derived. In addition, as a structure of the correction data 47 of this road shape data 42, it can illustrate that the acceleration component of the said 3 directions is included.

  FIG. 12 is a flowchart illustrating an example of the procedure of the driving operation data generation process S50 illustrated in FIG. The driving operation data generation process S50 represents processing executed by the driving operation data generation unit 35.

  First, in step S <b> 51, the CPU 7 acquires the actual travel behavior data 43 from the RAM 9. Next, in step S <b> 52, the CPU 7 acquires the estimated behavior data 44 from the RAM 9. Next, in step S53, the CPU 7 generates driving operation data 45 by dividing the estimated behavior data 44 from the actual traveling behavior data 43. The division here refers to subtracting the component represented by the estimated behavior data 44 from the component represented by the actual traveling behavior data 43. Here, “subtracting” may be expressed as “thinning”, for example. The CPU 7 generates the driving operation data 45 in the RAM 9. Further, the CPU 7 stores the driving operation data 45 generated in the RAM 9 in the storage medium 16 so that the past driving operation data 45 can be used later.

  Here, as a specific example of the driving operation data 45, the behavior of the vehicle 99 shown in FIG. 13 is represented by the following behavior data. First, in the traveling direction D1, the behavior of the vehicle 99 is represented by behavior data SK1 resulting from the road and behavior data US1 resulting from the driving operation. Here, the behavior data SK1 corresponds to the estimated behavior data 44, and the behavior data US1 corresponds to the driving operation data 45.

  In the horizontal direction D2, the behavior of the vehicle 99 is represented by behavior data SK2 resulting from the road shape and behavior data US2 resulting from the driving operation. Here, the behavior data SK2 corresponds to the estimated behavior data 44, and the behavior data US2 is the driving operation data 45. In the vertical direction D3, the behavior of the vehicle 99 is represented by behavior data SK3 resulting from the road shape and behavior data SU3 resulting from the driving operation. Here, the behavior data SK3 corresponds to the estimated behavior data 44, and the behavior data SU3 corresponds to the driving operation data 45.

  As described above, when the CPU 7 executes step S53, the estimated behavior data 44 is thinned out from the actual traveling behavior data 43 of the vehicle 99 in the traveling direction D1, the horizontal direction D2, and the vertical direction D3. Therefore, the driving operation data 45 as the calculation result is the behavior data US1 in the traveling direction D1, the behavior data US2 in the horizontal direction D2, and the behavior data US3 in the vertical direction D3.

  Since the above-described driving operation data 45 is composed of the behavior data US1, US2, US3, the behavior data resulting from the road shape is not included. The behavior data resulting from the road shape is not related to the skill of the driver. For this reason, such driving operation data 45 is an index that accurately reflects the skill of the driver from which the factors caused by the road shape are removed.

  FIG. 14 is a flowchart illustrating an example of a procedure of the driving operation evaluation process illustrated in FIG. This driving operation evaluation process is a process executed by the driving operation evaluation unit 37.

  First, in step S51, the CPU 7 corresponding to the jerk calculating means calculates the jerk by differentiating the driving operation data 45 with time as a jerk calculating function. The driving operation data 45 can exemplify the acceleration components in the three directions, for example.

  In step S52, the CPU 7 determines whether or not the calculated jerk exceeds a threshold value. When the CPU 7 corresponding to the jerk determination means determines that the jerk exceeds the threshold, the CPU 7 determines that the riding comfort of the vehicle is poor as a jerk determination function (step S53). On the other hand, when the CPU 7 determines that the jerk does not exceed the threshold value, it is determined that the ride comfort of the vehicle is good as the jerk determination function (step S54). The CPU 7 executes the driving operation evaluation process as described above, and stores information related to the evaluation result in the RAM 9 in association with the road shape data 42 as the driving operation evaluation value 46.

  FIG. 15 is a diagram illustrating an example of a screen displayed by the driving evaluation general comment display process S8.

  In this screen, the display output unit 39 reads the driving operation evaluation value 46 from the RAM 9, and the driving skill of the driver is displayed by display control by the CPU 7.

  That is, the CPU 7 reads the driving operation evaluation value 46 from the RAM 9 and displays the map information and the road shape necessary for guiding the vehicle for the driving operation evaluation value 46, and controls the graphic controller 13. The graphic controller 13 controls the display control circuit 14 to display an image on the display 15.

  As shown in the figure, the display 15 newly displays a determination result relating to the riding comfort of the vehicle itself in addition to the map information necessary for guiding the vehicle. When the determination result related to the riding comfort is displayed on the display 15 in this way, the driver can recognize his / her driving skill by touching this objective driving skill evaluation and You will try to drive safely so as not to be burdened.

<Modification of driving operation evaluation process>
FIG. 16 is a flowchart illustrating an example of a procedure of a modified example of the driving operation evaluation process illustrated in FIG. 4. This modified example of the driving operation evaluation process represents a modified example of the procedure executed by the driving operation evaluation unit 37.

  First, in step S61, the CPU 7 corresponding to the control data calculation means inputs the driving operation data 45 to a predetermined human body model as a control data calculation function. This human body model can exemplify the feedback control system described above. Moreover, as this driving | operation operation data 45, the acceleration component of the said 3 directions can be illustrated, for example.

  Here, a specific example of the human body model is an inverted pendulum model. In this human body model, when the variation of the human body model becomes larger as an output, it is determined that the driving operation by the driver is uncomfortable. On the other hand, when the state of the human body model with little fluctuation continues, it is determined that this driving operation is comfortable.

  Next, in step S62, the CPU 7 corresponding to the control data calculation means calculates control data necessary for the stability of the human body model based on the input data as a control data calculation function. Next, in step S63, the CPU 7 assumes that the calculated control data amount is a burden on the human body of the vehicle. Next, in step S64, the CPU 7 corresponding to the control data amount determination means determines whether or not this control data amount exceeds a threshold value as a control data amount determination function.

  If the amount of control data exceeds the threshold, the CPU 7 determines that the ride comfort of the vehicle is poor based on the determination result (step S65). On the other hand, if the control data amount does not exceed the threshold value, the CPU 7 determines that the riding comfort of the vehicle is good (step S66). As described above, the CPU 7 executes a modified example of the driving operation evaluation process, and records the driving operation evaluation value 46 as the evaluation result in the RAM 9 in association with the road shape data 42.

  The processing as described above is continuously executed while the vehicle is traveling in a predetermined section, and the evaluation status as a result is presented to the driver. At the end of traveling in this predetermined section by the vehicle, the average of the evaluation is presented to the driver as a general comment. The CPU 7 records this evaluation value (corresponding to the driving operation evaluation value 46) in the RAM 9 in association with the predetermined section. That is, the CPU 7 records this evaluation value in the RAM 9 in association with the road shape data 42. Therefore, the driver can refer to the transition of the evaluation while traveling in the predetermined section later. Further, the driver or the like can relatively refer to the transition of the driving evaluation of the driver by comparing the driving operation evaluation value 46 recorded in the RAM 9 when traveling in such a predetermined section in the past. The record history here may be, for example, a driving operation evaluation value 46 recorded in the past.

  In the driving skill evaluation device 100 (corresponding to the navigation device) in the above embodiment, actual driving behavior data representing the detection result when the vehicle actually travels in a predetermined section to a desired destination is detected. 43 based on the actual travel behavior data generation means 32 (corresponding to the actual travel behavior data generation unit) and the road shape data 42 representing the road shape of a predetermined section to the desired destination. Estimated behavior data generation means 33 (estimated behavior data generation) for generating an estimated behavior data 44 representing an estimation result of the ideal driving situation when it is assumed that a predetermined section to the destination is actually assumed. Based on the actual running behavior data 43 and the estimated behavior data 44, and the driving operation caused only by the operation of the driver of the vehicle. The driving operation data generation means 35 (corresponding to the driving operation data generation unit) that generates the driving operation data 45 based on the extraction result, and the driving skill of the driver based on the driving operation data 45 are extracted. Driving skill evaluation means 37 (corresponding to a driving operation evaluation unit) to be evaluated is included.

  In this way, the driving skill evaluation means 37 determines that the estimated behavior data 44 to be used as the evaluation reference corresponds to the road shape of the predetermined section. The driving skill of the driver can be evaluated based on the equivalent). Therefore, the driving skill evaluation means 37 can objectively and accurately evaluate the driver's own driving skill excluding the influence of the road shape. The driver's own driving skill here may be, for example, an immaturity regarding the driving skill of a paper driver. In addition, a driver who knows the evaluation of such driving skill will concentrate on driving while feeling a sense of tension, and will try to drive safely.

  When such a driving skill evaluation device 100 is mounted on a vehicle, the driver can not only drive the vehicle but also have an opportunity to objectively grasp the driver's own driving skill. For this reason, the driver who has grasped the driver's own driving skill can come into contact with such driving skill evaluation and enjoy driving that tends to be boring as if it were amusement.

  In the driving skill evaluation device 100 according to the embodiment, in addition to the above configuration, the correction data 47 corresponding to the travelable situation of the vehicle in the predetermined section is generated based on the actual travel behavior data 43, and the correction data 47 The correction means 36 (equivalent to a correction | amendment part) which correct | amends the said estimated behavior data 44 based on this is provided.

  In this way, since the estimated behavior data 44 is corrected in accordance with the travelable situation of the vehicle within the predetermined section, the driving operation data generating unit 35 more accurately reflects the driving skill of the vehicle by the driver. Data 45 can be generated. For this reason, the driving skill evaluation means 37 can more accurately evaluate the driving skill of the driver according to the actual travelable situation in the predetermined section. Further, when such correction data 47 is generated, referring to the correction data 47, it can be derived that the road shape data 42 which should originally accurately represent the road shape has a changed part. .

  In the driving skill evaluation apparatus 100 in the embodiment, in addition to the above configuration, the correction means 36 (corresponding to the correction unit) further corrects the correction according to a plurality of traveling situations by the vehicle based on the plurality of actual traveling behavior data 43. Data 47 is generated.

  With such a configuration, correction data is generated based on a plurality of actual travel behavior data 43, and therefore the estimated behavior data 44 that takes this correction data into account becomes more accurate as an evaluation criterion. For this reason, the calculation accuracy of the driving operation data 45 is improved, and the evaluation of the driving skill of the driver is accurate.

  In addition to the above-described configuration, the driving skill evaluation device 100 in the embodiment further includes a storage unit 16 (corresponding to a storage medium) that records the driving operation data 45 in association with the road shape data 42.

  In this way, the driving operation data 45 representing the driving skill of the driver according to the road shape in the predetermined section can be accumulated in the storage medium 16, and the accumulated past driving operation data is stored. 45 can be compared with the past driving skill of the driver in the predetermined section at a later date to compare the past and current driving skill when traveling on the same road, for example.

  In the driving skill evaluation apparatus 100 in the above embodiment, in addition to the above configuration, the driving skill evaluation means 37 (corresponding to a driving operation evaluation unit) further stores the driving operation data 45 in three directions perpendicular to each other in the vehicle. A jerk calculation means (which corresponds to a jerk calculation function) that differentiates and calculates the jerk as a result, and jerk determination that determines that the driving condition of the vehicle is bad when the jerk exceeds a predetermined threshold Means (corresponding to a jerk determination function).

  In such a configuration, the jerk generally has a great influence on the ride comfort of the vehicle, so if a ride comfort determination method based on such jerk is adopted, only the driver who rides on this vehicle will In other words, it is possible to more accurately determine the passenger comfort.

  In the driving skill evaluation apparatus 100 in the above embodiment, in addition to the above configuration, the driving skill evaluation means 37 (corresponding to a driving skill evaluation unit) inputs the driving operation data 45 to a feedback control function, and Control data calculating means for calculating control data necessary for stability (corresponding to a control data calculating function), and the vehicle according to whether the amount of the control data (corresponding to the control data amount) exceeds a prescribed threshold value Control data amount judging means (corresponding to a control data judging function) for judging the driving state of the vehicle.

  If a determination is made using such a feedback control function, it can be determined whether there is an objective driving skill or no driving skill.

  In the driving skill evaluation method in the above embodiment, the actual driving behavior data generation means 32 (corresponding to the actual driving behavior data generation unit) determines the driving situation when the vehicle actually travels in a predetermined section to a desired destination. An actual traveling behavior data generation step S10 (corresponding to actual traveling behavior data generation processing) for detecting and generating actual traveling behavior data 43 representing the detection result, and estimated behavior data generating means 33 (corresponding to an estimated behavior data generating unit) Based on the road shape data 42 representing the road shape of the predetermined section to the desired destination, it is ideal when it is assumed that the vehicle actually traveled the predetermined section to the desired destination. Estimated behavior data generation step S30 (estimated behavior data generation process) for estimating the traveling situation and generating estimated behavior data 44 representing the estimation result And a driving operation data generation means 35 (corresponding to a driving operation data generation unit) based on the actual driving behavior data 43 and the estimated behavior data 44, driving caused only by the operation of the driver of the vehicle. A driving operation data generation step S40 (corresponding to driving operation data generation processing) that extracts the operation state and generates driving operation data 45 based on the extraction result, and driving skill evaluation means 37 (corresponding to the driving operation evaluation unit). And driving skill evaluation steps S50 and S60 (equivalent to driving operation evaluation processing) for evaluating the driving skill of the driver based on the driving operation data 45.

  In this way, in the driving skill evaluation steps S50 and S60, the estimated behavior data 44 to be used as the evaluation reference is in accordance with the road shape of the predetermined section, so that the driving is performed based on the criteria considering the road shape. A person's driving skill can be evaluated. Here, the reference in consideration of the road shape indicates the estimated behavior data 44. Therefore, in the driving skill evaluation steps S50 and S60, the driver's own driving skill excluding the influence of the road shape can be objectively and accurately evaluated. As described above, the driving skill of the driver himself can increase, for example, the level of immaturity regarding the driving skill of the paper driver. In addition, a driver who knows the evaluation of such driving skill will concentrate on driving while feeling a sense of tension, and will try to drive safely.

  When such a driving skill evaluation device 100 is mounted on a vehicle, the driver can not only drive the vehicle but also have an opportunity to objectively grasp the driver's own driving skill. For this reason, the driver who has grasped the driver's own driving skill can come into contact with such driving skill evaluation and enjoy driving that tends to be boring as if it were amusement.

  In the driving skill evaluation program in the above embodiment, the actual driving behavior data generation means 32 (corresponding to the actual driving behavior data generation unit) is used to determine the driving situation when the vehicle actually travels in a predetermined section to a desired destination. An actual traveling behavior data generation step S10 (corresponding to actual traveling behavior data generation processing) for detecting and generating actual traveling behavior data 43 representing the detection result, and estimated behavior data generating means 33 (corresponding to an estimated behavior data generating unit) Based on the road shape data 42 representing the road shape of the predetermined section to the desired destination, it is ideal when it is assumed that the vehicle actually traveled the predetermined section to the desired destination. Estimated behavior data generation step S30 (estimated behavior data) for estimating the traveling situation and generating estimated behavior data 44 representing the estimation result. Based on the actual running behavior data 43 and the estimated behavior data 44 by the driving operation data generating means 35 (corresponding to the driving operation data generating unit) and only the operation of the driver of the vehicle. A driving operation data generation step S40 (corresponding to a driving operation data generation process) for extracting the driving operation status resulting from the extraction and generating driving operation data 45 based on the extraction result, and driving skill evaluation means 37 (in the driving operation evaluation unit) The driving skill evaluation device 100 executes the driving skill evaluation steps S50 and S60 (corresponding to the driving operation evaluation process) for evaluating the driving skill of the driver based on the driving operation data 45.

  In this way, in the driving skill evaluation steps S50 and S60, the estimated behavior data 44 to be used as the evaluation reference is in accordance with the road shape of the predetermined section, so that the driving is performed based on the criteria considering the road shape. A person's driving skill can be evaluated. Note that the estimated behavior data 44 can be used as a reference in consideration of the road shape here. Therefore, in the driving skill evaluation steps S50 and S60, the driver's own driving skill excluding the influence of the road shape can be objectively and accurately evaluated. The driver's own driving skill may be, for example, an immaturity regarding the driving skill of a paper driver. In addition, a driver who knows the evaluation of such driving skill will concentrate on driving while feeling a sense of tension, and will try to drive safely.

  When such a driving skill evaluation device 100 is mounted on a vehicle, the driver can not only drive the vehicle but also have an opportunity to objectively grasp the driver's own driving skill. For this reason, the driver who has grasped the driver's own driving skill can come into contact with such driving skill evaluation and enjoy driving that tends to be boring as if it were amusement.

  In addition, this embodiment is not restricted above, A various deformation | transformation is possible. Hereinafter, such modifications will be described in order.

  In the above embodiment, the evaluation of the driving skill is displayed as shown in FIG. 5, but the presenting method is not limited to this, and the presentation method may be a numerical expression such as a score, An abstract expression that changes the expression according to the driving skill may be used.

  In the said embodiment, although the vehicle was mentioned as an example of a mobile body, it is not restricted to this, For example, you may apply to other mobile bodies, such as a two-wheeled vehicle, a four-wheeled vehicle, and a railway.

  Moreover, in the said embodiment, although evaluation of the driving skill by the driver using jerk and a human body model is performed in the above-mentioned driving evaluation processing S5, it is not limited to this, and other methods are used for the driver's skill. The skill may be judged.

  Moreover, in the said embodiment, although evaluation of the driving skill is displayed by the character in the said driving evaluation display process S6, it is not restricted to this, and it replaces with this or uses this in addition to this, and the driving skill is displayed. It is good also as a structure which outputs evaluation.

  Moreover, in the said embodiment, although the moving direction etc. of the vehicle acquired, for example by the gyro sensor are illustrated about the actual driving | running | working behavior data 43, it is not restricted to this, The actual vehicle of the vehicle acquired by various sensors is illustrated. You may use the behavior data showing a driving state.

It is a block diagram which shows the hardware structural example of the navigation apparatus in this embodiment. It is a block diagram which shows the structural example of the software in the navigation apparatus shown in FIG. It is a flowchart which shows an example of the procedure of a vehicle guidance process. It is a flowchart which shows an example of the procedure of a driving operation evaluation process. It is a flowchart which shows an example of the procedure of an actual driving | running | working behavior data acquisition process. FIG. 6 is a reference diagram for explaining the flowchart shown in FIG. 5. 5 is a flowchart illustrating an example of a procedure of correction data generation processing illustrated in FIG. 4. FIG. 8 is a reference diagram for explaining the flowchart shown in FIG. 7. It is a flowchart which shows an example of the procedure of the acquisition process of the estimation behavior data shown in FIG. FIG. 10 is a reference diagram used to explain the flowchart shown in FIG. 9. FIG. 10 is a reference diagram used to explain the flowchart shown in FIG. 9. It is a flowchart which shows an example of the procedure of the driving operation data generation process shown in FIG. FIG. 12 is a reference diagram for explaining the flowchart shown in FIG. 11. 5 is a flowchart illustrating an example of a procedure of driving operation evaluation processing illustrated in FIG. 4. It is a figure which shows an example of the screen which represented evaluation of driving operation visually. 6 is a flowchart illustrating an example of a procedure of a modified example of the driving operation evaluation process illustrated in FIG. 4.

Explanation of symbols

9 RAM
10 Display 16 Recording medium (an example of storage means)
22 Various sensors 32 Actual travel behavior data generation unit (an example of actual travel behavior data generation means)
33 Estimated behavior data generation unit (an example of estimated behavior data generation means)
35 Driving operation data generation unit (an example of driving operation data generation means)
36 Correction unit (an example of correction means)
37 Driving operation evaluation unit (an example of driving skill evaluation means)
39 Display Output Unit 41 Map Information 42 Road Shape Data 43 Actual Travel Behavior Data 44 Estimated Behavior Data 45 Driving Operation Data 46 Driving Operation Evaluation Value 47 Correction Data 100 Navigation Device (Example of Vehicle Guidance Device)
S10 Actual driving behavior data generation processing (an example of actual driving behavior data generation step)
S20 Correction data generation process (an example of a correction data generation step)
S30 Estimated behavior data generation process (an example of an estimated behavior data generation step)
S40 Driving operation data generation processing (an example of a driving operation data generation step)
S50 Driving operation evaluation process (an example of driving skill evaluation step)
S60 Driving operation evaluation process (an example of driving skill evaluation step)

Claims (8)

An actual traveling behavior data generating means for detecting a traveling situation when the vehicle actually travels a predetermined section to a desired destination, and generating actual traveling behavior data representing the detection result;
Based on road shape data representing the road shape of a predetermined section to the desired destination, an ideal driving situation in the case where it is assumed that the vehicle has actually traveled the predetermined section to the desired destination. Estimated behavior data generating means for generating estimated behavior data representing the estimation result, and
Driving operation data generating means for extracting a driving operation situation caused only by the operation of the driver of the vehicle based on the actual driving behavior data and the estimated behavior data and generating driving operation data based on the extraction result; ,
A driving skill evaluation device comprising driving skill evaluation means for evaluating the driving skill of the driver based on the driving operation data. In the driving skill evaluation device according to claim 1,
Driving comprising: correcting means for generating correction data corresponding to the travelable situation of the vehicle in the predetermined section based on the actual driving behavior data, and correcting the estimated behavior data based on the correction data Skill evaluation device. In the driving skill evaluation device according to claim 2,
The driving skill evaluation apparatus according to claim 1, wherein the correction means generates the correction data according to a plurality of driving situations by the vehicle based on the plurality of actual driving behavior data. In the driving skill evaluation apparatus according to any one of claims 1 to 3,
A driving skill evaluation apparatus comprising storage means for recording the driving operation data in association with the road shape data. In the driving skill evaluation apparatus according to any one of claims 1 to 4,
The driving skill evaluation means includes
A jerk calculating means for differentiating the driving operation data with respect to three directions perpendicular to each other in the vehicle and calculating a jerk as a result;
A driving skill evaluation device comprising: jerk determining means for determining that the driving condition of the vehicle is bad when the jerk exceeds a prescribed threshold. In the driving skill evaluation apparatus according to any one of claims 1 to 4,
The driving skill evaluation means includes
Control data calculating means for inputting the driving operation data into a feedback control function and calculating control data necessary for the stability of the vehicle;
A driving skill evaluation device comprising: control data amount judging means for judging the driving situation of the vehicle according to whether or not the amount of the control data exceeds a prescribed threshold value. An actual driving behavior data generating means for detecting a driving situation when the vehicle actually travels in a predetermined section to a desired destination by the actual driving behavior data generating means, and generating actual driving behavior data representing the detection result; ,
When it is assumed that the vehicle has actually traveled the predetermined section to the desired destination based on the road shape data representing the road shape of the predetermined section to the desired destination by the estimated behavior data generation means An estimated behavior data generation step for estimating an ideal driving situation and generating estimated behavior data representing the estimation result;
Based on the actual driving behavior data and the estimated behavior data, the driving operation data generation means extracts the driving operation status caused only by the operation of the vehicle driver, and generates the driving operation data based on the extraction result Driving operation data generation step
A driving skill evaluation method comprising: a driving skill evaluation step for evaluating the driving skill of the driver based on the driving operation data by a driving skill evaluation means. An actual driving behavior data generating means for detecting a driving situation when the vehicle actually travels in a predetermined section to a desired destination by the actual driving behavior data generating means, and generating actual driving behavior data representing the detection result; ,
When it is assumed that the vehicle has actually traveled the predetermined section to the desired destination based on the road shape data representing the road shape of the predetermined section to the desired destination by the estimated behavior data generation means An estimated behavior data generation step for estimating an ideal driving situation and generating estimated behavior data representing the estimation result;
Based on the actual driving behavior data and the estimated behavior data, the driving operation data generation means extracts the driving operation status caused only by the operation of the vehicle driver, and generates the driving operation data based on the extraction result Driving operation data generation step
A driving skill evaluation program for causing a driving skill evaluation device to execute a driving skill evaluation step for evaluating the driving skill of the driver based on the driving operation data by a driving skill evaluation means.

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