JP3593502B2 - Vehicle driving technology diagnosis system, components thereof, and driving technology diagnosis method - Google Patents

Description

[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to a driving skill diagnosis system, a component thereof, and a driving skill diagnosis method that enable risk management of vehicle driving by diagnosing a driving skill of a vehicle by a driver.
[0002]
[Prior art]
There is known an operation management system that measures the behavior of a vehicle and determines a driving operation tendency of a driver based on the measurement result.
This type of operation management system includes a sensor unit including an angular velocity meter, an accelerometer, a GPS receiver, and a vehicle speed sensor, and a recorder unit for recording measurement data output from the sensor unit. The data measured by the sensor unit include angular velocity data of roll, pitch, and yaw, two-dimensional or three-dimensional acceleration data, GPS data representing latitude, longitude, speed, and direction, and a vehicle speed that receives a vehicle speed pulse from a vehicle instrument. Data.
[0003]
Among the measurement data recorded in the recorder section, the turning angular velocity of the vehicle can be obtained from the angular velocity data, and the starting acceleration and the brake acceleration of the vehicle can be obtained from the acceleration data. From the GPS data, the current position, current time, and operating speed of the vehicle can be obtained.
[0004]
In the operation management system, from the measured data of the vehicle operated by a certain driver, sudden start or sudden stop (change of the acceleration data above the threshold), sudden steering (change of the angular velocity data above the threshold), excessive speed (above the threshold) The number of vehicle speed pulses) is calculated by calculation, and the driving operation tendency of the driver is determined. Alternatively, the presence or absence of a dangerous operation is determined from a predetermined change pattern of the measurement data. In this way, by judging the driving operation tendency of the driver, the driver's operation contents at the time of the traffic accident can be grasped afterward, or the driver's operation tendency can be grasped in advance to prevent the traffic accident from occurring. Useful for prevention.
[0005]
[Problems to be solved by the invention]
With conventional operation management systems, it is possible to identify characteristics of vehicle behavior exceeding a certain threshold, such as sudden start or stop, sudden steering, excessive speed, but rough steering wheel operation, slow braking, curve It is not possible to quantify the actual feeling of the driving operation, such as sudden running. Further, although data such as the number of times of sudden start or stop, sudden steering, and excessive speed can be grasped, it is not possible to grasp information such as that there is little sudden start but there is a certain bad habit in steering operation. Therefore, it has not been possible to objectively and relatively diagnose the driving skill of the driver.
This is one of the causes of the fact that the conventional operation management system does not have a viewpoint that considers the rate of change or fluctuation of the driving operation during a certain period of time.
[0006]
The fluctuation of the driving operation can be explained as follows.
For example, the steering wheel of a vehicle makes two and a half turns, but a person who drives the vehicle for the first time does not know how much to turn the steering wheel to turn the course of the vehicle. The reason why the person can drive is to repeat the correction of the consistency between the estimated operation amount of the steering wheel and the operation result, and to remember this as experience. When a clear operation amount is not known, meandering is repeated and the amplitude of the meandering is reduced.
Also, for a driving veteran, sudden jumping out of the road while driving has already been learned empirically and knows what driving operation is appropriate next. Therefore, the vehicle can return to stable running immediately. However, those who have little driving experience or are unfamiliar have not learned how to respond to the above-mentioned suddenly occurring event, and cannot estimate the result that will occur next, so that they repeat meandering again. Such a tendency can be grasped as a relative characteristic of the driving operation.
[0007]
It is considered that human estimated thinking is a closed loop in which an error from the result is fed back (corrected) to the next estimated thought. The magnitude of the error in this estimated thinking is “fluctuation”. Small fluctuations are necessary for stable running, but unstable and divergent fluctuations create dangerous behaviors, which can lead to worst "accidents". As a characteristic of the driving operation, a driver whose fluctuation increases or whose fluctuation always appears large has a high possibility of causing dangerous behavior.
The same tendency as the fluctuation is seen in the change rate of the driving operation.
[0008]
An object of the present invention is to provide a driving technology diagnosis system and a component thereof that can correctly extract a relative characteristic of a driving operation of a driver and apply the extracted characteristic to a driving technology diagnosis.
Another object of the present invention is to provide a driving technique diagnosis method that appropriately diagnoses the characteristics of a driver's driving operation using the above-described driving technique diagnosis system.
[0009]
[Means for Solving the Problems]
The behavior of the vehicle is a repetition of three elements: start (acceleration), stop (deceleration), and turning. In the driving technology diagnosis system of the present invention, data representing the above three factors, that is, measurement data including data representing the behavior of the vehicle, which is generated by the driver's driving operation, is recorded in the data recording means in time series. I do. Further, there is provided a diagnostic device for reading the measurement data recorded in the data recording means and diagnosing the driving operation technique of the driver based on the read measurement data.
[0010]
The diagnostic device can specify the behavior of the vehicle by extracting the characteristics of the above three elements from the measurement data. However, it is not realistic to collect and analyze all measurement data in all traffic environments. In addition, in order to make the diagnosis result objective, it is necessary to diagnose the driving technique based on a common reference regardless of the traffic environment and even if the driver is different.
The present inventionCondition setting means for setting conditions for specifying a desired behavior of the vehicle to be diagnosed after the driving operation;Out of the measurement data recorded in the data recording meansSet by the condition setting meansconditionsToBy detecting the appropriate measurement dataThe desiredA behavior specifying means for specifying the behavior;CeremonyMeasurement data in motionIs extracted from the data recording means and based on the extracted measurement data,Change rate of driving operation over a certain period of timeAnd the saidDriving operation of the driver in motionButMuInSo muchIts value isIncludes fluctuation components that decrease, Driving operationFeature information generating means for generating feature information representing relative features ofPre-generatedPredeterminedReference informationDiagnostic information generating means for generating diagnostic information quantifying the driver's driving operation technique based on the result of the comparison with the diagnostic device.
PreviousBaseAssociateinformationMay be the characteristic information of the exemplary driver obtained by measuring in advance. Thereby, the deviation amount from the model driving can be objectively grasped.
For example, the condition setting means determines a combination of a longitudinal acceleration generated when the vehicle is accelerated or decelerated, a turning angular velocity and a lateral acceleration generated when the vehicle turns, for specifying the desired vehicle behavior. Set as conditionIt is configured to
[0011]
For example, assuming Tokyo and Hokkaido, the traffic environment in these areas differs only in the length and width of the road, but the structure of the intersection is almost the same. Therefore, the behavior at the intersection is almost the same in Tokyo and Hokkaido. When turning right, there is a characteristic that the vehicle turns right while decelerating and slowing down after stopping temporarily. In this way, by comparing and evaluating measured data of vehicle behavior that shows some relative characteristics in driving operation, regardless of the driver, efficiency of analysis processing can be improved and multiple driving under common conditions The driver's driving skill can be evaluated objectively.
[0012]
In particular, the traveling behavior at an intersection is easy to grasp the individuality of the driver. Driving operation at an intersection usually involves depressing a brake and depressing an accelerator while operating a steering wheel. The driver drives the vehicle while entangled them in a complicated manner, so that the situation determination ability, the reflex nerve, the exercise ability, and the like differ significantly depending on the driver. In the driving technology diagnosis system of the present invention, the characteristics of the behavior at the intersection are diagnosed, so that the driving skill for each driver can be easily diagnosed with the integrated power.
[0013]
As an example of the condition, the condition setting means sets a state in which the longitudinal acceleration and the turning angular velocity are generated in the same phase or a state in which a product of the longitudinal acceleration and the lateral acceleration exceeds a predetermined value as an intersection traveling. It can be set to be specified. In this case, the behavior specifying means is configured to specify the intersection traveling based on such a condition. Also,The feature information generating means isAt the specified intersectionMeasured data representing the speed when the vehicle entered the intersection, the speed when turning right and left, the turning speed, and the accelerationFrom the data recording meansExtracted and extracted these measurement dataOn the basis of theIt is configured to generate the feature information when traveling at an intersection.Further, the diagnostic information generating means is configured to generate the diagnostic information based on a comparison result between the characteristic information and the reference information at the time of traveling at the intersection..
The characteristic information generating means may be configured to generate the characteristic information for each of a plurality of predetermined diagnosis items. In this case, the diagnostic information generating means generates the diagnostic information including a diagnostic result for each diagnostic item based on the characteristic information for each of the plurality of diagnostic items. A comprehensive diagnosis result obtained by comprehensively evaluating the diagnosis results in the plurality of diagnosis items, comment data prepared in advance according to each of the diagnosis results in the plurality of diagnosis items, and all the diagnosis results in the plurality of diagnosis items are expressed. The diagnostic information may be generated by posting a graph that has been set. The apparatus may further include means for plotting the vehicle behavior based on the diagnosis results in the plurality of diagnosis items, and generate the diagnosis information by posting a diagram of the vehicle behavior together with each diagnosis result. .
[0014]
Said driverUser registration in advanceMultiple drivers belonging to the entityOne ofIn this case, the diagnostic information generating means includes a form including diagnostic information of each driver belonging to the business entity, and a form for a business entity side manager including diagnostic information of all drivers belonging to the business entity. And are selectively generated.
[0015]
The data recording unit is mounted on the vehicle at the time of diagnosis, for example, and records, in chronological order, measurement data including data indicating behavior of a vehicle driven and operated by the driver together with identification information of a driver to be diagnosed. A data recorder having a memory medium for reading the identification information and measurement data of the driver recorded in the memory medium, and specified by the identification information based on the read measurement data. It is configured to diagnose the driving operation technique of the driver.
[0016]
The memory medium is portable so as to be detachably attached to the data recorder, and the diagnostic device accumulates the diagnostic information generated by the diagnostic information generating means by linking the diagnostic information with the identification information of the driver. And a means for reading and outputting time-series diagnostic information for each driver from the diagnostic information database. The output means may, for example, transmit the diagnostic information to the driver or the driver via the Internet.Of the entity to which the driver belongsThis is a communication control mechanism provided to the administrator.
[0017]
The present invention also provides a driving technique diagnosis device and a driving technique diagnosis program as components of the driving technique diagnosis system.
The diagnostic device of the present invention is a measurement data reading unit that reads the measurement data from a data recording unit that records measurement data including data representing the behavior of the vehicle in a time series, which is generated by a driver's driving operation,Condition setting means for setting conditions for specifying a desired behavior of the vehicle to be diagnosed after the driving operation;Among the measurement data read by the measurement data reading means.Set by the condition setting meansconditionsToBy detecting the appropriate measurement dataThe desiredA behavior specifying means for specifying the behavior;CeremonyMeasurement data in motionIs extracted from the data recording means and based on the extracted measurement data,Change rate of driving operation over a certain period of timeAnd the saidDriving operation of the driver in motionButMuInSo muchIts value isIncludes fluctuation components that decrease, Driving operationFeature information generating means for generating feature information representing relative features ofPre-generatedPredeterminedReference informationDiagnostic information generating means for generating diagnostic information quantifying the driver's driving operation technique based on the result of comparison with the above.
[0018]
The driving technology diagnosis program of the present invention is a process of reading the measurement data from a data recording unit that records, in a time series, measurement data including data representing behavior of a vehicle, which is generated by a driver's driving operation,Process for setting conditions for specifying desired behavior of a vehicle to be diagnosed after driving operation,SaidOf the read measurement dataSaid setconditionsToBy detecting the appropriate measurement dataThe desiredProcessing to identify behavior, identifiedCeremonyMeasurement data in motionAnd based on the extracted measurement data,The rate of change of the drivingCeremonyDriving operation of the driver in motionButMuInSo muchIts value isIncludes fluctuation components that decrease, Driving operationProcessing to generate feature information representing the relative features ofPre-generatedPredeterminedReference informationA computer-readable driving technique diagnosis program for causing a computer to execute a process of generating diagnostic information quantifying the driver's driving operation technique based on a comparison result with the driving technique.
[0019]
The present invention also provides a driving skill diagnosis method.
This driving technique diagnosis method is a method in which a data recording unit mounted on a vehicle to be diagnosed is generated when a driver performs a driving operation.Both handsRecording time-series measurement data including data representing the motion on a portable memory medium in which the identification information of the driver is recorded;
A diagnostic device comprising means for reading the measurement data and the identification information recorded on the memory medium,And read the measurement datahome,Under the conditions set to specify the desired behavior of the vehicle to be diagnosed after the driving operationApplicable measurement dataAnd, based on the extracted measurement data,Change rate of driving operation over a certain period of timeAnd the saidDriving operation of the driver in motionButMuInSo muchIts value isIncludes fluctuation components that decrease, Driving operationGenerate feature information representing relative features ofAndWith this feature informationPre-generatedPredeterminedReference informationGenerating diagnostic information quantifying the driver's driving skill based on the result of the comparison.
[0021]
BEST MODE FOR CARRYING OUT THE INVENTION
Hereinafter, embodiments of the present invention will be described.
<Configuration of driving technology diagnostic system>
FIG. 1 shows a configuration example of the driving technique diagnosis system of the present invention.
The driving technique diagnosis system 1 includes a data recorder 10 mounted on a vehicle, a portable memory medium 20 detachably mounted on the data recorder 10, and a diagnosis processing of the driving technique in cooperation with the memory medium 20. And a diagnostic device 30 for performing the above. The diagnostic device 30 is connected to the Internet L so that the driver or his / her manager can view or print the information of the diagnostic result on his / her personal computer.
The data recorder 10 has a function of recording measurement data including data representing the behavior of the vehicle, generated by the driver's driving operation, in the memory medium 20 in a time-series manner.
The diagnostic device 30 mainly reads data recorded in the memory medium 20, diagnoses the driving operation technique of the driver based on the read data, generates various diagnostic information, and transmits the diagnostic information to the driver and its management. It has a function to provide to the user.
[0022]
Hereinafter, specific examples of these configurations will be described.
<Data recorder>
As shown in FIG. 1, the data recorder 10 includes a sensor unit 11, a medium accommodation mechanism 12, and a recorder unit 13. The sensor unit 11 includes an gyro sensor 111 such as a gyro sensor, a lateral accelerometer 112x, a longitudinal accelerometer 112y, a GPS (Global Positioning Systems) receiver 113, and a pulse acquisition mechanism 114.
[0023]
The gyro 111 measures the attitude of the vehicle on which the data recorder 10 is mounted. The measured data is defined as angular velocity data. By integrating this angular velocity data, it is possible to represent angle information, for example, a steering wheel angle (behavior of steering wheel operation) or the like operated by the driver.
The lateral accelerometer 112x and the longitudinal accelerometer 112y can measure the acceleration (accelerator operation, brake operation, turning operation, and the like) of the vehicle in the left-right and front-rear directions. The measured data is referred to as lateral acceleration data and longitudinal acceleration data. The GPS receiver 113 receives GPS data indicating the current latitude, longitude, speed, direction, current time, and the like of the vehicle. The pulse acquisition mechanism 114 acquires a vehicle speed pulse from a vehicle instrument or the like.
Among the data measured by the sensor unit 11, the angular velocity data, the respective acceleration data, and the data representing the vehicle speed are measurement data representing the characteristics of the behavior of the vehicle, which are important in diagnosing the relative characteristics of the driver's driving operation. It becomes.
[0024]
The sensor unit 11 can switch and output the GPS data and the vehicle speed pulse as appropriate. That is, as for the speed and the traveling distance, when the vehicle speed pulse is acquired, it is used, and when it is not acquired, the GPS data is used. For example, on a normal road where GPS data can be received, GPS data is used, and in a tunnel where GPS data does not reach, a vehicle speed pulse is used to represent speed, etc., or the current position is corrected based on GPS data received so far. To do.
Note that information corresponding to the operation of the turn signal, the brake, and the reverse gear is input to the sensor unit 11.
[0025]
The medium accommodating mechanism 12 accommodates the memory medium 20 in a detachable manner and supports data reading and data writing with the recorder unit 13.
The recorder unit 13 converts the analog measurement data sent from the sensor unit 11 into digital measurement data and develops the data in an internal buffer endlessly. In addition, among the measurement data developed in the internal buffer, the offset component and the drift component of the angular velocity data are removed, and further, autonomous data (sometimes called inertial data) composed of the angular velocity data and the respective acceleration data. A matching process with the GPS data is performed. Then, from the data from which the offset component and the drift component have been removed, only measurement data satisfying a predetermined condition (for example, a predetermined behavior exceeding a threshold has occurred or ended) is extracted, and this is extracted as the position data and time at that time. The data is recorded on the memory medium 20 together with the data. The conditions for recording various data are usually set by the diagnostic device 30 described later and are recorded on the memory medium 20.
[0026]
<Memory medium>
The memory medium 20 has a semiconductor memory mounted on a card medium or a stick medium. In the semiconductor memory, a management data area for recording driver ID (ID is an abbreviation of identification information, the same applies hereinafter) and other management data, and measurement data for recording data measured by the sensor unit 11. A region is formed.
The shape and mechanism of the memory medium 20 are the shapes and mechanisms detachably attached to the medium accommodating mechanism 12 of the data recorder 10. However, it is preferable that the diagnostic apparatus 30 be configured with a general-purpose computer system. , A card-shaped memory medium having a shape and mechanism (type II or type III) according to the PCMCIA standard. The semiconductor memory is a non-volatile memory, but may be a flash memory such as an EEPROM (Electrically Erasable and Programmable Read Only Memory).
[0027]
<Diagnostic device>
The diagnostic device 30 includes a CPU, a RAM, a ROM, a disk drive device, an external storage device, and a printer, and controls programs such as a basic input / output system (BIOS) and an operating system (OS); The present invention is realized by a computer system operated by a driving technique diagnosis program in a disk mounted on a drive device.
[0028]
For example, as shown in FIG. 2, the computer system includes a medium accommodating mechanism 31 for detachably accommodating the memory medium 20, reading data from the memory medium 20 accommodated in the medium accommodating mechanism 31, and writing data to the memory medium 20. (Including initialization), a memory control mechanism 32, an input screen for various condition information, a display device 33 such as an LCD (Liquid Crystal Display) for confirming a diagnosis result, and data for inputting data and commands. It has an input device 34, a communication control mechanism 35 for controlling bidirectional communication with the Internet L, and a main control unit 36.
The main control unit 36 is a condition setting unit 361, a vehicle behavior identification unit 362, a feature extraction unit 363, and a diagnosis information management unit that are formed by the CPU reading the driving technology diagnosis program and executing it in cooperation with the control program. 364, a user management database (database is abbreviated as “DB”) 365, and a diagnostic information DB 366.
[0029]
The condition setting unit 361 stores the initial condition setting when starting to use the data recorder 10 (memory medium 20) and the condition setting when diagnosing the driving technique after the driving operation is completed by the data input from the data input device 34. (Including clearing conditions). The former condition setting includes the ID of the driver to be diagnosed, the ID of the memory medium 20 for recording data representing the characteristics of the driving operation by the driver, and the information on the vehicle on which the data recorder 10 is mounted. This means setting in 20 management data areas. The condition setting for recording the data measured by the sensor unit 11 on the memory medium 20 as described above is also performed.
The latter condition setting refers to setting conditions for specifying a predetermined vehicle behavior from measurement data recorded in the memory medium 20. The condition setting unit 361 guides a setting interface screen having a predetermined embedded dialog window on the display device 33 for the convenience of the administrator, and the administrator corresponds to the embedding area of these dialog windows. Conditions can be set by inputting data.
[0030]
The vehicle behavior specifying unit 362 reads the measurement data recorded in the memory medium 20 and detects various measurement data that meet predetermined conditions, thereby specifying various behaviors of the vehicle.
The specified vehicle behavior includes curve running (including curve running at intersections), lane change running, slow / re-acceleration during curves, pause on slow roads, sudden braking, sudden steering, sudden accelerator, sudden Turning, back running, etc. are mentioned.
For example, a behavior (a state in which a turn is generated by a steering wheel operation) when the lateral acceleration generated during a turn for a right turn or a left turn is equal to or greater than a specific magnitude is specified as a curve run or an intersection run. Lateral acceleration does not occur when the vehicle runs straight and stops. It only occurs on curves or intersections with speed. Brake operation and steering operation of the vehicle when the lateral acceleration is occurring are generally impossible operations. Since the vehicle is designed to run straight and stop, it can be said that the curve running behavior deviates from the original characteristics. Therefore, if the degree of such lateral acceleration is quantified and this value exceeds a certain value (condition If the condition set by the setting unit 361 is satisfied), it is possible to detect that the vehicle behavior is caused by an unreasonable driving operation.
[0031]
At the same time, a plurality of behaviors (deceleration by brake operation, right or left turn by steering wheel operation, acceleration by accelerator operation, etc.) also occur in a complex manner. Therefore, in the condition setting unit 361, data representing these behaviors occurring at the same time (turning is angular velocity data, slowing or acceleration is longitudinal acceleration data, turning speed is lateral acceleration data, speed is vehicle speed pulse number, change rate is The conditions of the combination of the time data) are set, and the vehicle behavior that meets the conditions is specified.
For example, measurement data at an intersection traveling can be represented by a product Mxy (= Gx × ω) of the longitudinal acceleration as Gx and the turning angular velocity as ω.
FIG. 3 shows the outputs of the longitudinal accelerometer 112y and the gyro 111 at this time. When the case where the behavior when the longitudinal acceleration exceeds 0.1 G and the angular velocity also exceeds 10 degrees / sec occurs in the same phase is the condition of the intersection traveling, Mxy (G degrees / sec) at this time is 0. 1 G × 10 degrees / sec = 1.0 G degrees / sec.
That is, a state where the product of the longitudinal acceleration and the angular velocity exceeds 0.1 can be specified as the intersection traveling state.
The intersection traveling can also be specified by the product Mgxy (= Gx × Gy) of the longitudinal acceleration Gx and the lateral acceleration Gy. For example, if the case where the longitudinal acceleration is Gx> 0.1G and the lateral acceleration occurs at Gy> 0.1G is the intersection traveling, the product Mgxy> 0.1G × 0.1G = 0.01G · G Can be specified as an intersection traveling state.
[0032]
The feature extracting unit 363 extracts measurement data of the vehicle behavior specified by the vehicle behavior specifying unit 362, and generates characteristic information representing a relative characteristic of a driving operation performed by the driver from the extracted measurement data.
For example, when the specified vehicle behavior is a curve running at an intersection, a driver generally pays attention to a pedestrian or an oncoming vehicle during a turning operation. Various characteristics that are unique to the driver appear in the movement of the vehicle, that is, in the manner of driving operation. This feature is quantified and used to diagnose the driver's driving skills. When turning while excessively blowing the accelerator when making a right turn, this appears as a rapid change rate of the driving operation (right turn: right turn). Conversely, when turning right while excessively slowing, the change rate becomes Appears as less careful operation. Generally, when the time of occurrence and termination of a behavior is short, it can be determined that a driving operation with a rapid change rate has been performed. The fluctuation component is as described above.
Note that the feature detection may be performed by including only the change rate of the driving operation, only the fluctuation component, or both.
[0033]
A plurality of diagnosis items are set in the feature extraction unit 363 in advance, and feature information is generated for each diagnosis item.
FIG. 4 is a graph showing an example of how to generate feature information for each diagnosis item.
Here, examples of the brake diagnosis, the intersection diagnosis, the lane change diagnosis, the back diagnosis, and the fluctuation diagnosis are described. In the figure, the “purpose of quantification” indicates what state the measurement data representing is extracted, and the “quantification method” indicates an example of a technique for quantifying relative features.
[0034]
<Brake diagnosis>
In the brake diagnosis of FIG. 4, “B-time” in the right column is a time interval from when a certain speed is determined to be slow / stop to when stop / slow is detected, as shown in FIG. 5. That is, it is the brake timing. With this data, the relative characteristics of the driving operation stopped and slowed down by the brake can be quantified. “Α” is the acceleration data at this time.
In the case of a brake operation for avoiding a rear-end collision accident, since the brake operation itself becomes sharp, the longitudinal acceleration changes abruptly. The product of the maximum value of the rate of change of longitudinal acceleration (G / sec) and the instantaneous longitudinal acceleration (G) is evaluated. If the product is equal to or greater than a predetermined threshold, it is determined that a brake operation for avoiding a rear-end collision has been performed. Then, the data at this time is quantified as feature information. In this way, the actual feeling of the driver is quantified.
FIG. 6 is an example of data of a brake operation for avoiding a rear-end collision collected at the time of an accident that actually occurred. In the case shown in the figure, deceleration due to the brake operation occurs up to -0.6 G at 200 msec. The product at this time is 2.4 (G · G / sec) from the calculation of 0.6 (G) × 4 (G / sec). When the threshold value is set to 1.0 (G · G / sec) and the vehicle behavior beyond this is specified as the behavior for avoiding a rear-end collision, the above 2.4 (GG · sec) becomes the characteristic information.
[0035]
FIG. 7 shows the state of the temporary stop determination by the brake operation on the slow road. For example, traveling at a speed of 30 km / h or less is determined to be a slow road, and measurement data generated in that environment is used as feature information in a stopped state on the slow road.
The feature of the brake operation at high speed can be quantified by the product of the instantaneous maximum value of the longitudinal acceleration ((Δα) max) and the vehicle speed V.
At the time of the brake diagnosis, regardless of the threshold value, data representing all behaviors in which a deceleration operation of 0.1 G or more has been performed is extracted and statistically performed. It can be diagnosed that an operation has been performed.
[0036]
<Intersection diagnosis>
When the integral value of the angular velocity data exceeds a predetermined value (for example, 30 degrees), the turning is started. When the integrated value of the angular speed data returns to or below the value, the turning is completed, and the occurrence of the behavior at the intersection is detected. Decision of slowing / stop), judgment of slowing / stopping when turning right and left, and judgment of acceleration timing after right / left turn In the speed determination before turning, as shown in FIGS. 8A and 8B, the speed at which the intersection behavior is started, that is, the intersection approach speed is determined. In the slow / stop determination when turning right or left, the average value and the maximum value of the angular velocity ω of the turn × the speed V during the turn are obtained. At this time, the speed during turning right and left and the turning speed are simultaneously determined. In the acceleration timing determination after turning right and left, as shown in FIG. 9, the angular velocity (degree) and the acceleration (G) are simultaneously determined. Gmax / tmax represents the magnitude of the acceleration after the right or left turn (change rate of the accelerator operation). This value increases as the vehicle accelerates immediately after the end of the turn.
It is the correct driving operation to turn at a constant speed when turning and accelerating after the end of turning, and the simultaneous occurrence indicates that there is such a relative characteristic that the driving operation is impossible. . In such a driving operation, the center of gravity of the vehicle moves forward due to, for example, a brake operation during turning, and spin occurs. Therefore, by quantifying the magnitude of the brake operation and the accelerator operation during turning, this can be used as the characteristic information at that time.
[0037]
It should be noted that the unevenness (or “fluctuation”) of the steering wheel operation can be quantified from the measurement data during the intersection traveling. The steering angle δ, angular velocity ω, and velocity V of the steering wheel have a relationship of ω = δ × V. Therefore, by evaluating the result of the frequency analysis of ω / V and its statistical value, it is possible to quantify the unevenness of the steering operation.
[0038]
<Lane change diagnosis>
In FIG. 10, (a) shows a lane change for passing, (c) shows a change in lateral acceleration Gy at that time, (b) shows a lane change after passing, and (d) shows a lateral acceleration Gy at that time. Changes. At this time, the state of the lane change is detected based on the magnitude of G that occurs in a complex manner, and the lateral acceleration (G), speed V, complex G, and the like at that time are used as the characteristic information.
[0039]
<Back diagnosis>
In the back diagnosis, the back speed during the back behavior, the maximum value of the acceleration and its change rate are detected, and when it exceeds a threshold value, or when the statistical value of these accelerations reaches a predetermined standard, It is quantified as feature information.
In addition, the time required for turning the steering wheel, the number of times of turning, and the maximum angular velocity at the time of turning are detected to quantify the smoothness of driving, that is, the degree of maturity of the driving technique. Further, by calculating the stop time before the back movement, it is possible to quantify the degree of attention of the surroundings, such as backing after confirming the safety with a rearview mirror or the like in advance.
[0040]
<Fluctuation diagnosis>
The magnitude of the fluctuation component at the time of each driving operation is quantified and used as feature information. Here, for example, a fluctuation component at the time of a brake operation or a steering wheel operation is quantified to be feature information. In addition, “complex fluctuation” at the time of turning such as a curve running (including an intersection running) is quantified to be feature information.
As a technique for quantifying the fluctuation component, for example, a frequency analysis of 0.1 to 0.2 Hz of the deceleration (negative value of the longitudinal acceleration) may be performed. That is, the angular velocity data and each acceleration data are passed through a band-pass filter of the above-described frequency to extract a fluctuation component, quantify the magnitude (amplitude value), and use the result as feature information.
[0041]
FIG. 11 is a diagram illustrating a relationship between an output (angular velocity data or acceleration data) from the sensor unit 11 and a frequency when a certain vehicle behavior is measured. By subjecting the data of the area specified in the figure to Fourier transform, a fluctuation component can be extracted. The “complex fluctuation” at the time of turning is calculated, for example, by calculating a composite value (√ (Gx · Gx + Gy · Gy)) of the lateral acceleration Gy (= ω · V) at an angular velocity of 10 degrees / sec or more and the longitudinal acceleration Gx. Then, it can be extracted by passing it through a band-pass filter. The fluctuation component of the accelerator operation can also be quantified by calculating the resultant acceleration (= √ (Gx · Gx + Gy · Gy)) as the lateral acceleration Gy and the longitudinal acceleration Gx generated during turning.
[0042]
Although not shown, for the speed and the like, statistics are taken for a certain period of time, and the magnitude of the fluctuation component can be quantified from the maximum value, the minimum value, and the average value. For example, FIG. 12 is a graph showing a state of a speed change accompanied by a fluctuation with respect to a traveling distance. (A) is a speed graph by the driver A, and (b) is a speed graph by the driver B. The driver B runs stably at around 50 km / h, whereas the driver A fluctuates in driving speed sharply. Fluctuations in speed are accompanied by changes in the energy consumption of the vehicle, and thus greatly affect fuel efficiency. Therefore, by quantifying the fluctuation component of the speed, the fuel consumption calculation and its evaluation can be performed.
The fluctuation component may be used as it is as the characteristic information, or the characteristic information may be generated in a form including the fluctuation information as a part. In short, it is only necessary that the fluctuation component can be extracted not as a feeling but as a numerical value or data equivalent thereto.
[0043]
The diagnostic information management unit 364 recognizes the driver ID, the ID of the memory medium 20, the scale factor of the data, and the like from the management data recorded in the memory medium 20. Then, for each of the plurality of diagnostic items, the relative characteristics of the driver's driving operation are analyzed in more detail based on the above-mentioned characteristic information of the driver's driving operation, and the results are multilaterally evaluated. Then, diagnostic information as an evaluation result is generated, and the driver ID is stored in the user management DB 365, and the diagnostic information is stored in the diagnostic information DB 366 in association with the driver ID or the like. Storing diagnostic information is useful for grasping changes in information over time.
The stored information is read out as appropriate and output to the display device 33, or is presented to the driver and its manager via the communication control mechanism 35 and the Internet L.
The diagnostic information management unit 364 has prepared comment data prepared according to the evaluation result in advance. In addition, a tool for statisticizing evaluation (diagnosis) results and a tool for graphing or plotting are prepared. By activating such a tool when generating diagnostic information, not only the diagnostic result but also the basis of the diagnostic can be grasped objectively.
[0044]
Hereinafter, an example of an analysis method in the diagnostic information management unit 364 will be described.
FIG. 13 is a graph summarizing the characteristic analysis method in steady running. The analysis items are speed “uneven”, brake “fluctuation”, and steering wheel “fluctuation”. Information relating to speed is extracted from the above-mentioned characteristic information, and the maximum speed and average speed among them are used as primary analysis data. Then, “unevenness” is evaluated from these fluctuation components. As the evaluation value, the average value of each speed and the deviation (for example, the half width from the center line of the average value distribution) are multiplied to obtain evaluation reference data, and this data and safety reference data (for example, data from a model driver) Is used. As for the brake “fluctuation” and the steering wheel “fluctuation”, the result of multiplying the average value and the deviation by the safety standard data (actual data by the model driver or an ideal value, hereinafter referred to as safety standard data). In this case, use the same data).
[0045]
FIG. 14 is a graph summarizing an example of an analysis method in a case where stop diagnosis, that is, a brake timing and a magnitude of a stop brake (a brake for stopping) are set as analysis items. As the primary analysis data of the brake timing, the former data is divided by the latter data by using the speed at the start of the brake and the time required until the brake is stopped. The higher the speed and the shorter the time to stop, the slower the brake timing is evaluated.
The primary analysis data of the magnitude of the stop brake is an average magnitude of the stop brake (longitudinal acceleration G), which is made relative to, for example, safety reference data.
[0046]
FIG. 15 is a graph summarizing an example of an analysis method when abrupt steering change and abrupt steering acceleration are used as analysis items. As the primary analysis data, the longitudinal acceleration (G) at the time of a sharp steering operation and the steering wheel change rate (degrees / sec) are used. .
Here, it is possible to simultaneously evaluate a change in acceleration at the time of a sudden operation of the steering wheel and a shake or "fluctuation" of the steering wheel. The greater the blur, the greater the calculated result.
In the analysis of the sudden steering wheel acceleration, a composite acceleration (= √ (Gx · Gx + Gy · Gy)) of the lateral acceleration Gy and the longitudinal acceleration Gx generated during the turning and the maximum speed are used as primary analysis data, and the product of both data is used. Then, the average value and the deviation are calculated, the average is calculated, and the average is calculated based on, for example, safety standard data.
[0047]
FIG. 16 is a diagram summarizing an example of an analysis method in the case of evaluating the relationship between the brake accelerator and the speed in a curve traveling, particularly in an intersection traveling. Here, a graph summarizing an example of an analysis method when the curve speed and acceleration and the handle “fluctuation” are used as analysis items.
In analyzing the curve speed / acceleration, the average speed during the turn and the above-described composite acceleration are used as primary analysis data, the average value and deviation of the product of the two data are calculated, and the average is obtained to make the relative value. I do. During turning, the higher the speed or the greater the accelerator operation and the brake operation, the more dangerous driving operation characteristics will be exhibited.
With respect to the handle “fluctuation”, the “fluctuation” (degree / sec) of the handle operation among the feature information extracted by the feature extraction unit 363 is used as primary analysis data, the average value and the deviation thereof are obtained, and the product of both data is calculated. An average is calculated and relativized based on, for example, safety reference data. The smoother the movement of the handle, the smaller the "fluctuation". The angular velocity data when turning at an intersection is as shown in FIG. 17A, for example. When the components are decomposed, the data component of (b) and the data component of (c) are added. (B) is data when a smooth steering operation is performed, and data corresponding to (c) is a fluctuation component. By estimating the magnitude, the handle “fluctuation” can be quantified.
[0048]
FIG. 18 is a graph summarizing an example of an analysis method in the case of evaluating the relationship between the braking method and the speed. As the primary analysis data, the longitudinal value (G) indicating the magnitude of the brake and the brake change rate (G / sec) are used, the average value and the deviation of the product of both data are calculated, and the average is calculated to obtain the relative value. Become Thereby, the magnitude and smoothness of the braking can be simultaneously quantified.
With regard to the speed and acceleration of the brake, the average value and the deviation of both data are obtained by using the starting speed of the brake and the magnitude of the brake (longitudinal acceleration (G)) as primary analysis data, and the average is calculated. Is evaluated based on, for example, safety standard data (data by a model driver). In this way, by applying the brake start speed and the brake magnitude, it is possible to objectively evaluate (quantify) at what speed and how much the brake is applied.
[0049]
The results of the analysis as described above are totaled for each driver, and are stored in a memory area (not shown) as objective evaluation data of the driving technique using various conditions as parameters. Then, it is sequentially read out according to the application, and is expressed as a statistical diagnosis and a driving diagnosis table for each driver.
For example, FIG. 19 is a graph, which is an example of a statistical diagnosis, and generates a time-dependent result of “fluctuation” of a general driving operation by a certain driver in response to a request from the driver. This graph shows the result of statistical diagnosis of a certain driver's analysis results for one month, sorted in chronological order. Through such a graph, it is possible to grasp at which time the "fluctuation" becomes large throughout the day or vice versa.
[0050]
FIG. 20 is a graph in which statistics are obtained by the same method as in FIG. 19 and the day-dependent results of “fluctuations” of the general driving operation are generated in response to the driver's request. In the case of this driver, it can be seen that there is a peak of “fluctuation” on the second day of the week.
[0051]
The results of the statistical diagnosis can be summarized for each driving operation.
FIG. 21 is a graph summarizing the results of monthly extraction of the relative characteristics of the driver's steering operation in response to the driver's request. In the case of this driver, a peak of “fluctuation” appears in July and August. This indicates that attention should be paid to driving during the summer.
[0052]
FIG. 22 is a diagram illustrating a result obtained by summing up composite evaluation results by a plurality of drivers for each month. This example shows a monthly evaluation example of multi-dimensional “fluctuations” of three drivers.
[0053]
FIG. 23 is a diagram illustrating an example of an individual driving diagnosis table output as a form.
In this example, the diagnosis item and the diagnosis result are expressed by a five-level evaluation together with the driver's personal information (management data) input prior to the diagnosis. This evaluation value is obtained by relativity with the above-mentioned safety standard data. In this driving diagnosis table, comment data prepared in advance according to each of the diagnosis results of the diagnosis items is posted.
The diagnostic information as shown in FIGS. 19 to 23 can be browsed by the driver or its manager through the Internet L as necessary.
[0054]
【Example】
Next, an embodiment of the above-described driving technique diagnosis system 1 will be described.
The driving technique diagnostic system 1 of the present embodiment lends the data recorder 10 or the memory medium 20 to a driver of a general vehicle, analyzes the data recorded in the lent data recorder 10 or the memory medium 20, and analyzes the driving technique. It can be used as a tool for performing diagnostic services.
[0055]
That is, a business processing system for performing business processing related to the driving skill diagnosis service and the above-described diagnostic device 30 are prepared in a service establishment. The business processing system is a known database system in which general-purpose software is mounted on a personal computer to which a printer is connected, and includes a data recorder 10 for driving technology diagnosis, a memory medium 20 used in combination with the data recorder 10, And the driver to be diagnosed is linked and managed by each ID.
The functions of the diagnostic device 30 may be formed by installing the above-mentioned driving technology diagnostic program on the same personal computer, and the business processing system and the diagnostic device 30 may be linked.
[0056]
The data recorder 10 is generally capable of detachably mounting the memory medium 20, but may be an integrated type incorporating the memory medium 20 therein. In the latter case, the data recorder 10 is to be lent. In the following description, it is assumed that the memory medium 20 is detachable from the data recorder 10 for convenience.
In this example, the data recorder 10 is attached to a vehicle owned by a service office in advance, and the memory medium 20 and the vehicle are lent to a driver (rental car / lease car). A mode in which only the driver 10 and the memory medium 20 are lent to the driver (using a private vehicle) is prepared.
[0057]
The operation mode of the service is performed, for example, according to the procedure shown in FIG.
That is, when the driver has applied for a diagnosis (step S101: Yes), it is determined whether or not to make a diagnosis using a private vehicle. If the diagnosis is not based on a private car, it is determined that the diagnosis is based on a rental car, and a vehicle (rental car) to which the data recorder 10 is attached in advance is loaned (step S102: No, S103), and the memory medium 20 is loaned (step S104). ). In the case of a diagnosis application using a private car, the data recorder 10 and the memory medium 20 are lent (Step S102: Yes, S105). In any case, after the diagnostic device 30 (the condition setting unit 361) records the driver's ID in the memory medium 20, the ID of the memory medium 20 is recorded in the business processing system together with the driver's ID (Step 106). .
Note that the recording of the driver ID in the memory medium 20 may be omitted and the driver ID may be directly recorded in the business processing system.
[0058]
When the driver mounts the memory medium 20 on the data recorder 10 and drives the vehicle, the measurement data including the data representing the behavior of the vehicle, generated by the driving operation, is time-sequentially recorded by the data recorder 10 on the memory medium. 20 is recorded. When the driving operation is completed and the driver returns the data recorder 10 and / or the memory medium 20 to the business establishment (step S107: Yes), the person in charge at the business establishment executes the business processing related to the return in the business processing system. At the same time, the memory medium 20 is set in the diagnostic device 30.
[0059]
When the business processing system and the diagnosis device 30 cooperate, the diagnosis device 30 identifies the driver and the memory medium 20 from at least one of the IDs when the memory medium 20 is returned. Then, the process of specifying the vehicle behavior described above from the measurement data recorded in the memory medium 20 (step S108), the measurement data of the specified vehicle behavior is extracted, and the driver to be diagnosed is extracted from the extracted measurement data. (Step S109) for generating the above-described feature information indicating the relative feature including the change rate and / or the fluctuation component of the driving operation by the driver, and based on the feature information (or the comparison result between the feature information and the reference information). The process (step S110) of generating diagnostic information quantifying the driving operation technique of the above is executed in this order. Then, the diagnostic information is printed on a form in a predetermined format by a printer, or is presented to the driver or its manager via the Internet L (step S111).
[0060]
The diagnostic information is a personalized driving diagnosis table for a driver who does not belong to a company in which the driver has been registered in advance, and a driver who belongs to a company in which the driver has been registered in advance. In addition to the driving diagnosis table, a driving diagnosis table for an administrator is generated.
[0061]
25 is a driving diagnosis table for an individual driver, FIG. 26 is a driving diagnosis table for a manager showing a diagnosis result of one driver, and FIG. 27 is a driving diagnosis table of a manager showing a diagnosis result of a plurality of drivers. It is. Here, the brake, the steering wheel, the stop, the right / left turn, and the smoothness are set as the diagnosis items. Of course, how the diagnosis items are set can be arbitrarily set by the condition setting unit 361 described above.
[Brake] is a diagnosis of the brake operation technique, and specifies a vehicle behavior in which the rate of change of acceleration (G / sec) at the time of brake operation and the speed (km / h) at the start of brake operation are equal to or more than a certain value. At the same time, based on the rate of change (G / sec) and the speed (km / h) of the vehicle behavior, how steep the brake operation is used as a reference for diagnosis. The larger the amount of deviation from the safety standard data, the lower the evaluation.
[Handle] is a diagnosis of how much the "fluctuation component" of the handle operation has occurred. The acceleration at the time of operating the steering wheel and the rate of change of the steering wheel are used as primary analysis data for each driver, and the product of (acceleration × change rate of steering wheel) at the time of operating the steering wheel is obtained. This is the result of calculating and relativizing the product. The frequency of the acceleration change at the time of steering wheel operation, the magnitude of the shake of the steering wheel, and the magnitude of the fluctuation component are simultaneously evaluated. The higher the frequency is, the lower the evaluation is, the larger the blur and the fluctuation component are.
[Stop] is a diagnosis result of the brake timing and the magnitude of the stop brake. The criteria for diagnosis (evaluation) in this case are as described above. [Right and left turn (curve running)] is a diagnosis result of the skill level of the complex operation at the time of running at an intersection.
[Smooth] is a diagnosis of how smoothly the accelerator operation, the brake operation, the reverse operation, and other driving operations were performed, for example, how large the fluctuation component in each operation was. The extent to which the fluctuation component deviates from the safety standard data is an evaluation target. The larger the deviation amount, the lower the evaluation.
These diagnostic results are expressed in five stages from A (highest) to E (lowest). In addition, the overall balance is graphed, and comment data on the diagnosis result is added.
[0062]
The driving diagnosis table for the manager in FIG. 26 also expresses the same contents. The driving diagnosis table of the manager shown in FIG. 27 has a format in which only the diagnosis results are posted so as to be able to cope with a large number of drivers who have been consulted.
In any case, by constructing an environment in which such a diagnostic service can be performed using the driving technology diagnosis system 1, even if the driver does not normally have an opportunity to objectively grasp his / her driving technology, it is easy to use. It is possible to make a diagnosis of the driving technique. In a company having a large number of drivers, by receiving a driving diagnosis table as shown in FIG. 26 or FIG. 27 periodically, it becomes possible to appropriately take measures for safe driving. For a business that provides a service of renting a vehicle, by performing such a diagnostic service together, a higher value-added service can be provided, and the utilization rate of the renting service of the vehicle can be improved. There is an advantage. When handing over the driving diagnosis table, it is expected that the use of the lending service and the driving skill diagnosis service can be promoted by handing out the vehicle lending discount ticket to the driver according to the diagnostic score.
In addition, the fact that the data recorder 10 for driving diagnosis and the memory medium 20 are mounted provides a psychological tension to the driver of the vehicle, and a secondary effect of reducing the accident rate can be expected. .
It is common practice to lend a vehicle to a user in the form of a lease car in addition to a rental car. In this case, too, a procedure similar to that of a private car or a procedure similar to that of a rental car is used. In addition, a driving skill diagnosis service can be provided to the user.
[0063]
The driving skill diagnosis system of the present invention is also suitable for use in a driving school. That is, the data recorder 10 is attached to each vehicle for training, and the driving skill of the trainer (driver) can be objectively grasped by the procedure of FIG.
At the start of the lesson, the memory medium 20 is lent to each student (step S201), and the IDs of the memory medium 20 and the trainee are recorded in a business processing system or the like (step S202). Each time the trainer drives the vehicle, the trainer mounts his or her memory medium 20 on the data recorder 10 and performs a driving operation. As a result, the measurement data is recorded in the memory medium 20 by the data recorder 10 in chronological order.
When the trainee has completed the driving operation, the memory medium 20 removed from the data recorder 10 is mounted on the diagnostic device 30 (step S203: Yes). The diagnostic device 30 performs the same processing as steps S108 to S110 in FIG. 24 to generate a diagnostic table in which diagnostic information is visualized (steps S204 to S206). The generated diagnostic table is presented to the trainee (step S207), and is stored in chronological order in association with the learner's ID (step S208).
[0064]
In the case of a driving school, the traveling course of the vehicle is fixed, and the course location to be noted when driving is determined. Therefore, as shown in FIG. 29, a schematic diagram (course diagram) of the course is drawn on the left side of the driving diagnosis table, and a diagnosis result at a corresponding portion of the course is described on the right side, so that improvement points and the like during driving can be objectively determined. Will be able to understand it. In addition, by accumulating the diagnosis table in chronological order, it is possible to objectively grasp the state of improvement in driving skills from entrance to graduation.
As a driving diagnosis table in the case of a driving school, as shown in FIG. 30, a diagnosis result of an instructor who can be safety standard data and a diagnosis result of an accident-prone person (or a trainee who has the possibility of doing so) are graphed together. It is also possible to generate the result.
[0065]
【The invention's effect】
As is apparent from the above description, according to the present invention, the driver's operation is performed based on the characteristic information indicating the relative characteristics of the driver's driving operation generated from the measurement data of the predetermined vehicle behavior, for example, the traveling behavior at the intersection. Because diagnostic information that quantifies driving operation technology is generated, the characteristics of the driver can be extracted from a small amount of measurement data, and the time required for data processing is significantly reduced compared to the case where all measurement data is used. Has the effect. Therefore, it is possible to efficiently diagnose the driving technique of the vehicle.
In addition, while detecting the change rate of the driver's driving operation, the fluctuation component, or both, the characteristic information is generated such that the detected change rate or the like is part or all of the relative characteristics of the driving operation by the driver. Therefore, for example, it is possible to quantify the actual feeling of the driving operation, such as a rough steering wheel operation, a slow braking, a sharp curve running, and the like, which were not possible in the past.
In addition, a plurality of diagnostic items are set, and for each diagnostic item, predetermined reference information, for example, comparison with a diagnostic result by the exemplary driver is performed. You will be able to understand accurately.
[Brief description of the drawings]
FIG. 1 is a configuration diagram of a driving technique diagnosis system to which the present invention is applied.
FIG. 2 is a configuration diagram of a diagnostic device in the driving technique diagnostic system of the present embodiment.
FIG. 3 shows measured data of longitudinal acceleration and angular velocity in an intersection.
FIG. 4 is a diagram summarizing a method of extracting characteristics of a driving operation in a vehicle behavior.
FIG. 5 shows measurement data representing longitudinal acceleration and speed at the time of brake diagnosis.
FIG. 6 shows measured data of a rear-end collision avoidance brake in an accident that actually occurred.
FIG. 7 shows measurement data in a temporary stop diagnosis on a slow road.
8A is measurement data showing a change in a steering wheel angle before turning at an intersection, and FIG. 8B is measurement data showing a change in a speed.
FIG. 9 shows measurement data for specifying an acceleration timing after turning right or left in an intersection.
FIG. 10 (a) shows a lane change at the start of passing, (b) shows a lane change after passing, (c) shows a change in lateral acceleration in (a), and (d) shows a change in (b). The figure which showed the mode of change of the lateral acceleration.
FIG. 11 is a graph showing an example of a fluctuation component extraction technique.
FIGS. 12A and 12B are graphs each showing a state in which speed fluctuations occur.
FIG. 13 is a graph summarizing a detailed analysis method of speed fluctuation, brake fluctuation, and steering fluctuation.
FIG. 14 is a graph summarizing a detailed analysis technique when performing stop diagnosis.
FIG. 15 is a graph summarizing a method of a detailed analysis of a steering wheel operation.
FIG. 16 is a graph summarizing a detailed analysis method when diagnosing a driving operation when performing a curve running.
17A is a diagram illustrating measurement data at an intersection, FIG. 17B is a diagram illustrating measurement data serving as a safety standard, and FIG. 17C is a diagram illustrating fluctuation components.
FIG. 18 is a graph summarizing a detailed analysis method when performing a brake diagnosis.
FIG. 19 is statistical data showing a time-dependent state of “fluctuations” of a general driving operation of a certain driver.
FIG. 20 is statistical data showing how the “fluctuation” of the driving operation depends on the day of the week.
FIG. 21 is statistical data showing a month-dependent state of “fluctuation” of a steering wheel operation.
FIG. 22 is statistical data showing a monthly dependency of a complex “fluctuation” by a plurality of drivers.
FIG. 23 is an explanatory view showing an example of a driving diagnosis table for an individual driver.
FIG. 24 is an explanatory diagram of a procedure when a driving skill diagnosis service is performed.
FIG. 25 is a diagram showing an example of a driver's personal driving diagnosis table.
FIG. 26 is a diagram showing an example of a driving diagnosis table for an administrator.
FIG. 27 is a diagram showing another example of a driving diagnosis table for an administrator.
FIG. 28 is an explanatory diagram of a procedure when a driving skill diagnosis system is used in a driving school.
FIG. 29 is a diagram showing an example of a driving diagnosis table given to a driver at a driving school.
FIG. 30 is a diagram showing an example of statistical data generated when used in a driving school.
[Explanation of symbols]
1 Driving technology diagnosis system
10 Data recorder
11 Sensor section
12 medium storage mechanism
13 Recorder section
20 Memory media
30 Diagnostic device
31 Medium storage mechanism
32 Memory control mechanism
33 Display device
34 Data input device
35 Communication control mechanism
36 Main control unit
361 Condition setting section
362 Vehicle behavior identification unit
363 Feature extraction unit
364 Diagnostic information management unit
L Internet

Claims (17)

Data recording means for recording measurement data including data representing the behavior of the vehicle, which is generated by the driver's driving operation, in chronological order,
A diagnostic device that reads measurement data recorded in the data recording unit and diagnoses the driver's driving operation technique based on the read measurement data,
The diagnostic device,
Condition setting means for setting conditions for specifying a desired behavior of the vehicle to be diagnosed after the driving operation ;
By detecting the matching measurement data to the condition set by said condition setting means of the measurement data recorded in the data recording unit, a behavior specifying means for specifying the desired behavior,
The measurement data in the identified behavior dynamic based on the extracted measurement data is extracted from the data recording means is in the driver's driving operation gas mu's in the rate of change and the elevation movement at a certain time of the driving operation Characteristic information generating means for generating characteristic information representing a relative characteristic of the driving operation , including a fluctuation component whose value decreases as the value decreases,
Diagnostic information generating means for generating diagnostic information quantifying the driving operation technique of the driver based on a comparison result between the characteristic information and predetermined reference information generated in advance ,
Driving technology diagnosis system. The condition setting means may determine a combination of a longitudinal acceleration generated when the vehicle is accelerated or decelerated, a turning angular velocity and a lateral acceleration generated when the vehicle turns, as a condition for specifying the desired vehicle behavior. Characterized in that it is configured to be set as
The driving technique diagnosis system according to claim 1. The condition setting means sets a condition for specifying a state in which the longitudinal acceleration and the turning angular velocity are generated in the same phase or a state in which a product of the longitudinal acceleration and the lateral acceleration exceeds a predetermined value as intersection traveling. Is configured to
The behavior specifying means is configured to specify the intersection traveling based on the condition,
The feature information generating unit extracts the rate at which those said vehicle enters an intersection in the intersection traveling identified, speed during right and left turns, turning speed, the measurement data representing the acceleration from the data recording means, extracting It is configured to generate the feature information at the time of intersection driving based on these measured data ,
The diagnostic information generating means is configured to generate the diagnostic information based on a comparison result between the characteristic information and the reference information during the intersection .
The driving technique diagnosis system according to claim 2. The feature information generating means is for generating the feature information for each of a plurality of predetermined diagnostic items,
The diagnostic information generating unit generates the diagnostic information including a diagnostic result for each diagnostic item based on the characteristic information for each of the plurality of diagnostic items,
The driving technique diagnosis system according to claim 1. The diagnostic information generating unit generates the diagnostic information including a comprehensive diagnostic result that comprehensively evaluates the diagnostic results in the plurality of diagnostic items,
The driving technique diagnosis system according to claim 4. The diagnostic information generating means generates the diagnostic information by posting comment data prepared in advance in accordance with each of the diagnostic results in the plurality of diagnostic items together with each diagnostic result.
The driving technique diagnosis system according to claim 5. The diagnostic information generating unit generates the diagnostic information by posting a graph expressing all the diagnostic results in the plurality of diagnostic items.
The driving technique diagnosis system according to claim 5. The diagnostic information generating means includes means for plotting a vehicle behavior based on the diagnostic results in the plurality of diagnostic items, and generates the diagnostic information by posting a diagram of the vehicle behavior together with each diagnostic result. Characterized by the fact that
The driving technique diagnosis system according to claim 5. Before Kimoto quasi information, characterized in that it is a characteristic information by the model driver obtained by previously measured,
The driving technique diagnosis system according to claim 1. The driver is one of a plurality of drivers belonging to a business entity registered in advance by a user ,
The diagnostic information generating means selectively selects a form including diagnostic information of each driver belonging to the business entity and a form for a business entity side manager including diagnostic information of all drivers belonging to the business entity. Characterized in that,
The driving technique diagnosis system according to claim 1. The data recording unit is mounted on the vehicle at the time of diagnosis, and together with identification information of a driver to be diagnosed, for recording in time series measurement data including data representing behavior of a vehicle that the driver operates. A data recorder having a memory medium,
The diagnostic device reads driver identification information and measurement data recorded in the memory medium, and diagnoses a driving operation technique of the driver specified by the identification information based on the read measurement data. Characterized in that,
The driving technique diagnosis system according to claim 1. The memory medium is portable and is detachably attached to the data recorder,
The driving technique diagnosis system according to claim 11. The diagnostic device includes: a diagnostic information database for storing the diagnostic information generated by the diagnostic information generating means in a state linked to the identification information of the driver; and a time-series diagnosis for each driver based on the diagnostic information database. Output means for reading and outputting information, further comprising:
The driving technique diagnosis system according to claim 11. The output means is a communication control mechanism that provides the diagnostic information to the driver or a manager of a business entity to which the driver belongs through the Internet.
The driving technique diagnosis system according to claim 13. A measurement data reading unit that reads the measurement data from a data recording unit that records measurement data including data representing the behavior of the vehicle, which is generated by the driver's driving operation, including data representing the behavior of the vehicle, in time series,
Condition setting means for setting conditions for specifying a desired behavior of the vehicle to be diagnosed after the driving operation ;
And the measurement by detecting the matching measurement data to the condition set by said condition setting means of the measurement data read by the data reading means, the behavior specifying means for specifying the desired behavior,
The measurement data in the identified behavior dynamic based on the extracted measurement data is extracted from the data recording means is in the driver's driving operation gas mu's in the rate of change and the elevation movement at a certain time of the driving operation Characteristic information generating means for generating characteristic information representing a relative characteristic of the driving operation , including a fluctuation component whose value decreases as the value decreases,
Diagnostic information generating means for generating diagnostic information quantifying the driving operation technique of the driver based on a comparison result between the characteristic information and predetermined reference information generated in advance ,
A diagnostic device for driving skills. A process of reading the measurement data from a data recording unit that records in a time series measurement data including data representing a behavior of the vehicle, which is generated by a driver's driving operation,
A process of setting conditions for specifying a desired behavior of a vehicle to be diagnosed after a driving operation ;
The fit measurement data in the set condition among the measurement data read by detecting, processing for specifying the desired behavior,
Based on the measured data extracted extracts the measured data in the identified behavior dynamic, as is the driver's driving operation gas mu's in the rate of change and the elevation movement at a certain time of driving operation the value is smaller A process of generating feature information representing a relative feature of a driving operation , including a fluctuation component,
Processing for generating diagnostic information quantifying the driving operation technique of the driver based on a comparison result between the characteristic information and predetermined reference information generated in advance , and causing the computer to execute the processing.
Computer-readable driving technology diagnosis program. Carried the diagnosis subject to on-board data recording unit on the vehicle, generated by the driver has driving operation, the measurement data including data representative of the vehicle both elevation movement, identification information of the driver is recorded Recording in chronological order on a non-volatile memory medium;
A diagnostic apparatus comprising a unit for reading the measurement data and the identification information recorded on the memory medium,
Reading the measurement data recorded in the memory medium, and among the read measurement data , extracting measurement data that meets a condition set to specify a desired behavior of the vehicle to be diagnosed after the driving operation. , based on the extracted measurement data, its value as is driving operation gas mu's of the driver in the rate of change and the elevation movement at a certain time of driving operation includes a smaller fluctuation component, the driving operation relative characterized by having; it generates characteristic information representing the steps of generating a quantified diagnostic information a driving operation technique of the driver based on a comparison result between a pre generated predetermined reference information and the feature information Features,
A method for diagnosing driving skills of vehicles .

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