JP2002150468A - System and method for operation analysis, and computer program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an operation analysis system, enabling objective analysis of operation situations. SOLUTION: Electronic information, collected by each of plural companies for expressing operation situations of vehicles by drivers belonging to the respective companies, is received via the Internet L or a high-density recording medium MO. A processing device 17 makes analysis on the contents of the electronic information received from each company to make a relative evaluation process to operation situations of the same driver or between different drivers, and specify the drivers having a special operation situation with difference by a prescribed value or more in the result of the relative evaluation process. Information for the result of the relative evaluation process is provided to the companies of the drivers via the Web or the like.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention collectively receives electronic information indicating the operating state of a mobile unit by a driver belonging to a plurality of customers and collects the information.
The present invention relates to a mechanism of information processing for individually presenting, for each driver, each customer, a relative evaluation of the operation status of a driver among customers, and corresponding message information and the like. here,
“Operating status” refers to the forward / retreat state, stop state, start state, acceleration state,
It refers to a deceleration state, a turning state, and other states related to operation.

[0002]

BACKGROUND OF THE INVENTION When a traffic accident occurs, it is difficult for a person other than the person concerned to analyze the cause and situation of the accident ex post facto. Normally, such an analysis is performed using, for example, evidence of a situation at a site, testimony from a driver or a witness, or the like. However, this form of analysis is probably sensory, general, and inaccurate. Therefore, attempts have been made to reproduce the accident situation by recording data representing the behavior and running conditions of the vehicle in a data recorder, and analyzing the recorded data by a computer when an accident occurs. This data recorder is equipped with a behavior sensor such as an angular velocity meter and an accelerometer, a vehicle speed sensor that inputs a traveling pulse from a speedometer and a vehicle instrument, a nonvolatile memory and a recording control unit thereof, and stores data measured by each sensor. It is configured to record the data in the memory for a fixed time while updating it as needed. When a traffic accident occurs, the recorded data is read from the memory of the data recorder and analyzed. For example, a running state that is traced back from the time when the vehicle stopped after the occurrence of the accident by a predetermined time is reproduced through image processing by a computer device. As a result, the situation at the time of the occurrence of the accident is objectively clarified, and the cause of the occurrence of the accident can be correctly grasped.

[0003] However, such analysis is only performed completely at the level of a specific company or individual, and there is a certain limit in spreading it. For example, in a company, it is necessary to construct a system environment of a certain level or higher including a data recorder, but this requires a great deal of cost and is difficult unless there is strong motivation for constructing the system. In addition, analysis requires specialists with advanced analysis skills and experience,
Since the number of such experts is very small, it is not practical to secure each company.

[0004] In the case of a company with a small number of drivers, an objective relative comparison with other drivers cannot be made. In this regard, if the analysis can be performed using not only information on one company but also information on other companies in the same industry, there is a possibility that more objective analysis can be performed. In addition, it may be possible to solve the problem by concentrating information indicating the operation status from a plurality of companies and performing an expert analysis based on the information by the experts. However, it requires a specialized third-party governing body that is not bound by the interests of the company. Conventionally, there is no such third-party management organization. Even if a third-party management organization exists, an infrastructure for quickly and effectively collecting operation status from each company and feeding back analysis results has not been established. Further, even if an attempt is made to collect the operation status collected by each company, it is not usually possible to motivate each company to transmit data.

SUMMARY OF THE INVENTION [0005] In view of such a background, it is a main object of the present invention to provide a technique which enables an objective analysis of an operation situation and effectively distributes an analysis result.

[0006]

According to the present invention, there is provided a receiving means for receiving electronic information, which is collected by each of a plurality of customers and indicates the operation status of a moving body by a driver belonging to each customer, Evaluating means for performing relative evaluation processing of the operation status between the same driver or different drivers by analyzing the content of the received electronic information, and information on the result of the relative evaluation processing by this evaluating means is used as the evaluation target driving And an information presenting means for presenting the information to a customer to which the user belongs.

[0007] The present invention also provides a computer which is connectable to a customer terminal operated by each of a plurality of customers via a communication network and has a recording medium reading mechanism. A process of receiving first electronic information representing the operation status of a moving body by a driver belonging to the customer online through a customer terminal operated by the customer and the communication network; collected over a certain period of time by each customer Receiving the stored second electronic information as the basis of the first electronic information via the recording medium;
By performing the content analysis of each received electronic information, perform the relative evaluation processing of the operation status between the same driver or different drivers,
A process of presenting the result information of the relative evaluation process to a customer to which the driver to be evaluated belongs; and an operation analysis method by a computer, and a process for causing the computer to execute the process. Provide a computer program. This computer program may be in any form as long as it can be read by a computer.

[0008]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment in which the present invention is applied to an operation analysis system for intensively analyzing the operation status of a vehicle will be described below. As shown in FIG. 1, the operation analysis system according to the present embodiment allows a customer terminal 2 provided for a customer (hereinafter simply referred to as “company”) such as a company or a private office to be accessible via the Internet L. Provided on the site. The entity that operates this site is a third-party management organization for each company. The customer terminal 2 is capable of recording information on a high-density recording medium MO such as a magneto-optical disk. The operation analysis system 1 may be provided at only one site or a plurality of sites.
In the case where a plurality of sites are provided, the electronic information indicating the operation status managed by each site is updated at the same time in cooperation with each other. In the following description, an example in which one operation analysis system 1 is provided at one site will be described.

<Customer Terminal> First, the customer terminal 2 will be described. The customer terminal 2 is operated by the customer and has a CP
U, various RAM, ROM, external storage device, BIO
It is a computer that operates under a control program such as S or an operating system (OS). As shown in FIG. 2, this computer includes a reader / writer 21 which stores a memory medium MB such as a memory card or a memory chip of a data recorder 3 to be described later and performs data recording and reading, and a high-density recording medium MO. , A display device 23 for inputting various setting information and an analysis result, a data input device 24 for inputting data and commands, and a communication connection mechanism for making a communication connection with the Internet L 25, an input / output control mechanism 26 for performing input / output control between these devices or mechanisms and internal functions, and a CPU for reading / executing a predetermined computer program to execute operation analysis and information transmission on the company side. And a data processing mechanism 27 for performing processing.

[0010] The processing on the company side referred to here is a processing for totaling electronic information indicating the operation status that occurs every day, a processing for generating "one-line total data per day", a "risk behavior list", and the like, which will be described later. The communication connection mechanism 2 generates the generated one-line total data per day.
5, processing for sending raw data and the like to the high-density recording medium MO, accessing the operation analysis system 1 via the communication connection mechanism 25, and acquiring evaluation results and messages. Processing. A well-known Internet Explorer (trademark of Microsoft Corporation) having a Web browser function or a browser having the same function is preferably installed in the data processing mechanism 27, and it is desirable that the evaluation result and the like can be obtained through the browser. .

Some companies construct an intranet and connect a plurality of customer terminals 2 for each section, while others do not. Regardless of whether or not an intranet network has been established, in addition to a program for performing the above-described processing that the data processing mechanism 27 has at a minimum based on data recorded in the memory medium MB of the data recorder 3, An operation analysis program (hereinafter, “dedicated software”) for performing operation analysis according to the purpose of the company and displaying the analysis result is provided by the data processing mechanism 27.
Some are not included in the system and some are not. The dedicated software, in addition to the function of performing the above-described processing that the data processing mechanism 27 has at a minimum, collects data measured by the data recorder 3 every predetermined period, for example, every business day, or every month, By performing statistical processing, automatically create a form that visually represents data such as the operation history of vehicles and the date and time of occurrence of dangerous behavior, occurrence location, occurrence frequency, etc. using graphs, histograms, lists, etc. Software for The created form is displayed on the display device 23, and is output and printed to a printing device as needed, if necessary. A report compiled per business day is called a daily report, which is classified into an operation management report and a safe driving report according to the purpose of the report. A monthly report is totaled on a monthly basis. For example, the occurrence of dangerous behavior occurring during the month, the time, and the like are recorded on a form in chronological order. Hereinafter, a company that has established an intranet and has the above-mentioned dedicated software loaded in the data processing mechanism 27 is referred to as an “A-type company,” and a company that has not established an intranet but has loaded the dedicated software is referred to as a “B-type company.” A company that does not build an intranet and does not have the dedicated software described above is referred to as a “C type company”.

In this embodiment, in each of the three types of companies described above, the data recorder 3 is used to collect electronic information indicating the operation status of all the drivers for each company, and to collect this information into the company name, section name, The management data including the type of the vehicle, the driver's name, and the like is concentrated on the operation analysis system 1 through the customer terminal 2 connected to the Internet L or through the high-density recording medium MO.

<Data Recorder> The data recorder 3
What was described in Unexamined-Japanese-Patent No. 2000-171267 can be used. That is, the data recorder 3
As an example, as shown in FIG. 3, it is configured to include a sensor unit 31, a medium accommodation mechanism 32, and a recorder unit 33.

The sensor unit 31 measures the two-dimensional attitude of the vehicle on which the data recorder 3 is mounted. The sensor unit 31 measures an angular velocity data (yaw rate) around a three-dimensional axis of the vehicle. Accelerometers 312x and 312y for measuring acceleration data (accelerator acceleration, brake acceleration, turning acceleration, etc.), a GPS receiver 313 for receiving GPS data indicating the current latitude, longitude, speed, direction, time, etc. of a vehicle, a vehicle instrument And a pulse acquisition mechanism 314 for acquiring a vehicle speed pulse from the same. Among the data measured by the sensor unit 31, the angular velocity data, the acceleration data, and the data representing the vehicle speed are measurement data representing behavior characteristics important in evaluating the driving tendency of the driver. The GPS data and the vehicle speed pulse can be appropriately switched or one of them can be output with priority. For example, GPS
On a normal road where data can be received, GPS data is used, and in a tunnel where GPS data does not reach, a vehicle speed pulse can be used to indicate speed or the like, or the current position can be corrected based on GPS data received so far. It has become. The medium accommodation mechanism 32 accommodates the memory medium MB in a detachable manner and supports data reading and data writing with the recorder unit 33.

The recorder unit 33 includes a CPU and a memory, and is formed by the CPU reading and executing a predetermined program recorded in a part of the internal memory. The preprocessor 331, the event extractor 332, Data recording unit 3
It comprises at least 33 functional blocks.
The pre-processing unit 331 temporarily stores the measurement data output from the sensor unit 31 in the buffer 331a,
The offset component and the drift component included in the angular velocity data and the acceleration data in the accumulated data are removed. Further, a matching process between the autonomous data including the angular velocity data and the acceleration data and the GPS data is performed.
That is, since the GPS data has a delay of about 2 seconds with respect to the autonomous data, the matching processing with the autonomous data two seconds before is performed. The event extraction unit 332 generates data (angular velocity data, acceleration data, GPS data) representing a behavior exceeding a predetermined threshold (this state is referred to as an “event”) from the accumulated data from which the offset component and the like have been removed by the preprocessing unit 331. Data, vehicle speed pulse, etc .: Hereinafter, “event data”) is extracted for each preset aggregation time, and the extracted event data, event occurrence date and time (GPS time), event occurrence location and initial information (recorder number, driver name) , Vehicle number, etc.) to the data recording unit 333. Measurement date and time (G
PS time) is the date and time obtained by adding 9 hours to the universal standard time received by the GPS receiver 312. The event occurrence location is position information that can be specified by GPS latitude / longitude.

The data recording section 333 stores the data processed through the processing by the pre-processing section 331 and the processing by the event extracting section 332 as state collection data, event data,
The data is classified into total data, and the classified data is recorded on the memory medium MB. Also, the vehicle ignition O
In addition to N / OFF, power ON / OFF of the data recorder 3, running / stopping, when GPS communication is normal / abnormal, etc., the time and details of the occurrence (when, where, and what happened) are determined in advance. Recording is performed using the determined bit pattern.

The memory medium MB is, for example, a portable memory medium having a nonvolatile memory area. In the memory area, the above-described management data, status collection data, event data, and total data are recorded as needed.

The procedure for recording information indicating the operation status on the memory medium MB in the data recorder 3 is as follows. As a premise, in the memory medium MB, data for identifying the vehicle and its driver and data for identifying the driving purpose are set as a part of the management data. When driving is started and the vehicle starts to move, various measurement data representing the behavior characteristics of the vehicle, which are measured by the sensor unit 31, are sequentially accumulated in the buffer 331a. The recorder unit 33 determines the measurement start time from the GPS data (GPS time), and records this in the memory medium MB as a part of the state collection data. When an event occurs, the buffer 331a scans and extracts measurement data for a certain period before and after the event, for example, 30 seconds, and records this as event data in the memory medium MB. The threshold value is not a fixed value but a variation range so as to be able to cope with an offset or a slope of the instrument. For example, gyro 311z
Difference between the output of the sensor and the average value of the past 3 seconds, or accelerometer 3
It is determined whether an event has occurred based on whether one of the differences between the outputs of 12x and 312y and the average value in the past three seconds has exceeded a preset fluctuation range. The instrument output and the average value can be obtained by vector synthesis of each of the three instrument outputs.

Whenever there is a change in the running condition, the running distance, the GPS latitude / longitude, and the GPS time are read out from the buffer 331a each time, and together with a state flag (ignition ON / OFF, running / stop, etc.) described later, Is recorded in the memory medium MB as state collection data. If the read data exceeds the maximum value of the measurement data of the type, ie, the positive absolute maximum value, the read data is updated to a new maximum value. If the read data exceeds the previous minimum value, that is, the negative absolute maximum value,
The read data is updated to a new minimum value. In order to obtain an average value, the read data is integrated, and “1” is added to the number of times of integration. The above processing is repeated until the preset total time elapses, and when the total time has been reached,
An average value of the individual measurement data is obtained by dividing each of the accumulated read data by the number of accumulations. The maximum value, the minimum value, and the average value of each measurement data are used as aggregation data in the memory medium M.
After recording in B, each variable is cleared and the same processing is repeated.

When the engine is turned off, the power supply of the data recorder 3 is maintained (for example, by a capacitor) until the last counting time elapses, and the data recording process ends when the last counting time elapses. To do. By adopting such a recording mode, the tendency of the driving operation can be expressed more remarkably, and the data capacity of the memory medium MB can be saved.

When it is clear that the vehicle is completely stopped, that is, when the engine is not turned off, but the measured data does not fluctuate continuously for a predetermined time or more, data recording is performed while thinning out the time. . As a result, the data capacity can be significantly reduced while detecting the vehicle stop state.

FIGS. 4 to 10 are explanatory diagrams showing images of electronic information recorded on the memory medium MB according to the above embodiment. FIG. 4 is a diagram showing an overall image.
A state is shown in which total data, event data, and status collection data are recorded in an arbitrary area in the order of data generation in chronological order. “ID” is identification data of a data field, and the upper few bits indicate the block configuration of the field. FIG. 5 is a structural diagram of a main part of the management data.
“30h” to “33h” are IDs, “Lot No.” is manufacturing lot identification data, “Ax sf” and “Ay sf” are scale factors of acceleration data in the X-axis and Y-axis directions, and “q sf”. Is the scale factor of the yaw rate. The scale factor is one of the condition data related to the measurement accuracy. The “vehicle speed” is speed data obtained from a vehicle speed pulse, and is adopted in preference to speed data based on GPS data. “Serial No.” is a unique number of the production lot.

FIGS. 6 and 7 show the structure of event data. The event data is recorded as a set from the previous event recording time to the subsequent event recording time, centering on the event occurrence time. FIG. 6A shows an event head arranged at the beginning or a break of this event.
(B) is autonomous data (Ax or the like) representing the content of the event and vehicle speed data. FIG. 7 shows the speed acquired from the GPS data, the information of the event occurrence location, and the GPS time. "S
“ts” is data representing the type of non-positioning / two-dimensional positioning / three-dimensional positioning / differential positioning. In addition, GPS
The data is generated every time the GPS is received in the event data. FIG. 8 is a structural diagram of the status collection data. This data is recorded in the structure shown in the figure at predetermined intervals (for example, one second) every time the traveling condition changes. "State" at the bottom
Is a status flag represented by a bit pattern. For example, the first bit is ignition (logic 1: ON, logic 0: OFF), and the second bit is power supply voltage (logic 1: abnormal,
The logic 3 assigns the third bit as vehicle state (logic 1: running, logic 0: stop). The number of bits and the corresponding state expression content can be arbitrarily added or changed according to the purpose of analysis. FIG. 9 and FIG. 10 are structural diagrams of the tally data. FIG. 9 shows autonomous and vehicle speed total data, and FIG. 10 shows GPS total data. In FIG. 10, “sts” is data indicating whether the GPS data has been collected without loss during the counting period. As for “latitude” and “longitude”, positioning data closest to the center (average value) is recorded. As the simplest processing, for example, if the totaling period is one minute, data of a part where the current second is 30 is adopted. If the counting period is less than one minute, it is determined that there is no positioning data, and no recording is performed. The event data, tally data, and status collection data that are recorded at random are IDs.
Can be identified by For example, if the IDs are "00h", "03h", "10h", and "11h", the event data, "02h", "20h", and "21"
In the case of "h" or "22h", they are identified like the aggregated data.

<Sending form of electronic information in customer terminal 2> As described above, the memory medium MB of the data recorder 3
Is stored in the customer terminal 2 once,
A certain processing is performed. The A-type company performs aggregation, relative comparison, and display for a certain period for each section (office, branch, etc.) connected to the intranet. Then, the result information is stored in a memory area (not shown) in the customer terminal. In the B-type company, since no intranet is constructed, the sections are not classified for each section, but are counted, relative compared, and displayed for a certain period, and the result information is stored in the memory area of the customer terminal. Since the C-type company cannot display the information using the dedicated software, the information recorded on the memory medium MB is analyzed so that the information can be transmitted and stored in the memory area of the customer terminal 2. All the information stored in the customer terminal 2 is finally sent to the operation analysis system 1. At this time, there are two transmission modes. The first form is
This is a transmission via the Internet L, in which the stored electronic information is transmitted once a day or in real time through electronic mail or the like. The second mode is a mode in which all data accumulated for a certain period of time, for example, one month, is recorded on a high-density recording medium and sent periodically once a month. In the case of the second embodiment, the operation analysis system 1 stores raw data for a certain period of time on behalf of each company so that past data can be analyzed according to company needs. Hereinafter, the transmission mode of the first mode is “online transmission”, and the transmission mode of the second mode is “offline transmission”.
Called.

The electronic information transmitted online is one-line total data, dangerous behavior list, and hidden data generated on the day. The “one-line total data per day” is data that is totaled into one line of data for each driver of each company (in the case of an A-type company, for each section connected to the intranet). This one-line total data per day includes vehicle release information (time / location, ODO meter value), travel distance (detected distance by data recorder, ODO meter input distance), and total travel time (running during operation). Time), total operation time (time from departure to entry), longest continuous running time, average speed of high-speed running and general running, maximum speed and total time, total idling time, total stop time, maintenance record, accident / delay -Includes the status / cause of abnormalities, departure time / place, arrival time / place, work contents (running, actual or empty vehicle, unloading after arrival, loading or rest, etc.) for each work place. The following data is also included as needed.・ The total number of sudden accelerators and the ratio of sudden accelerators that exceed the predetermined set value and indicate the behavior considered to be the habit of the person (total of sudden accelerators / number of accelerations)・ Total number of sudden steering and ratio of sudden steering (total steering / number of steering) ・ Number of stop operations during start / acceleration, number of stop operations during braking, number of stop operations during turning, number of stop operations during lane change ・The number of retreats on the road ・ The number of dangerous behaviors ・ Increase in fuel consumption due to sudden start, etc., increase in cost The operation analysis system 1
On the side, basic data on the operation status of each driver,
The data can be accumulated in a state where counting and relative comparison are possible.

The "dangerous behavior list" is a list of occurrence times and locations of dangerous behaviors for each type of dangerous behavior.

The "hidden data" is more detailed data than one-line-per-day total data that cannot be seen by the company itself. By performing a detailed evaluation process based on the hidden data, it is possible to obtain a detailed analysis and evaluation result that cannot be obtained by using dedicated software, thereby allowing each company to concentrate electronic information on the operation analysis system 1. Motivation. Examples of hidden data include digitized data of speed histogram, digitized data of acceleration / deceleration G histogram, digitized data of horizontal G histogram, and one-minute total data (data obtained by totalizing various data every one minute and averaging them. Numerical data, etc.). Acceleration / deceleration G histogram digitized data is divided into two stages of speed range (can be set arbitrarily) like general driving and high-speed driving because the degree of danger differs depending on the speed range even for the same G. For example, it is divided into less than 20 kilometers per hour and more than 20 kilometers per hour. In the horizontal G histogram numerical data, the speed range is divided into three stages. For example, less than 40 kilometers per hour, 40
80 km / h or more and less than 80 km / h, 80
It should be more than kilometers per hour.

The contents of the electronic information transmitted offline are as follows:
All processed data stored for each company and section (for A type company), all processed data stored for each company (for B type and C type companies), and raw data (recorded on the memory medium MB) Binary data).

<Configuration of Operation Analysis System> Next, the configuration of the operation analysis system 1 of the present embodiment will be described. The operation analysis system 1 includes a CPU, various RAMs, a ROM, and an external storage device, and is realized by a computer device that operates under a control program such as a BIOS or an OS. The computer device includes a communication connection mechanism 11 for making a communication connection for performing data communication with each customer terminal 2 owned by each of the above types of companies via the Internet L, Disk drive 12, display device 13, and data input device 1 for reading recorded electronic information
4 and an input / output control mechanism 15 for performing input / output control between these devices or mechanisms and internal functions, and further includes a customer-specific DB 161, a message DB 162, and a form DB
163, a database management system (DBMS) 16 for controlling storage and reading of information in these DBs 161 to 163, and operation status based on information stored in each of the DBs 161 to 163 and electronic information received each time. Processing device 1 that performs various data processing related to management
7 is provided.

In the customer-specific DB 161, data relating to the operation status of all drivers of each company is stored for each item for a certain period of time, and can be read and analyzed according to needs. The customer-specific DB 161 includes a company-specific master and a plurality of folders. The folders are divided for each company and managed by customer code numbers. Items to be stored include total data per line, hidden data, dangerous behavior list, and raw data. The company master records the data transmission status and the like for each company by assigning a customer code number. Recorded data includes company information (manage various types of information such as business type, region, company size, number of employees, and number of units owned), total information (data transmission status of the relevant company, distribution status of evaluation results from the operation analysis system 1, etc.) ), And evaluation result information for each company (information representing the latest evaluation result for each company that is analyzed and updated and stored).

The message DB 162 stores message information to be output according to the evaluation result of the operation status in association with the evaluation items, and can output the information by applying the corresponding company, driver name and the like. For example, if a driver who has a lot of sudden braking during a turn can be identified, a message to the company to which the driver belongs is "Mr. XX seems to have a lot of sudden braking while turning. It is one of the major factors leading to an orbital departure accident. It is necessary to keep in mind predictive driving such as curves with poor visibility. "

The form DB 163 records forms for evaluation results to be distributed to each company.

The processing device 17 is a Web server function 1 formed by the CPU of the computer device reading and executing the computer program of the present invention.
71, an evaluation processing unit 172, a data editing unit 173, and a data output unit 174. The Web server function is a publicly known server function for presenting an HTML screen to each customer terminal 2 and passing e-mail (including attached documents) through the communication connection mechanism 11.

The evaluation processing unit 172 activates and executes any one of the behavior analysis module M11, the statistical analysis module M12, the tendency analysis module M13, and the fuel correlation analysis module M14, or a plurality of modules at the same time, so that each type of customer can be operated. Performing a relative evaluation process of the operation status based on the electronic information received from the terminal 2 and the information stored in the customer-specific DB 161 to identify a driver who has exhibited a special operation status having a difference of a predetermined value or more in the evaluation result. You can also. The predetermined value here is a threshold value set in advance,
It is an average value or a specific value of data from a plurality of customer terminals 2 that change every moment. `` Special operation status '' means an operation status exhibiting characteristics different from the normal operation status, such as dangerous behavior, an operation status that is not dangerous but has a certain habit, or a specific operation status compared to the past operation status. Refers to the recording date or time zone. The details of the evaluation processing unit 172 will be described later.

The data editing unit 173 includes an evaluation processing unit 172
Are classified according to any of within a company, between similar companies, and between different companies, and are classified into Web server functions 171.
Edit into electronic information format for presentation to companies through If necessary, the form DB 16
3 is read out, and electronic information is mapped on this form. The data output unit 174 includes a data editing unit 173.
A process is performed to output the electronic information edited in the above to the corresponding company through the Web server function 171 or to output the electronic information by e-mail.

<Detailed Function of Evaluation Processing Unit> Here, the function of the evaluation processing unit 172 will be described in detail. First, the functions of the modules M11 to M14 will be described. The behavior analysis module M11 specifies a behavior characteristic of the vehicle from the start of driving to the end of driving from the electronic information received from each company. The specification of the behavior feature is simply performed by extracting a combination of data representing the behavior feature and comparing the extracted combination with an evaluation condition pattern predetermined for each behavior feature. When the behavior feature is specified in detail, it is analyzed by the expert system using the raw data measured by the data recorder 3 or the expert's knowledge in a database. In order to more accurately identify behavioral features,
By recognizing the driving purpose from the management data, an evaluation condition pattern corresponding to the driving purpose is selected even for the same event in the same vehicle. For example, 80 per hour
The km is determined to be high-speed running for general road running, but to be determined to be normal running for highway running. Also,
The data read interval in the case of traveling on a highway is made longer than that in the case of traveling on a general road. Similarly, in the case of private use, for example, the place where the operation is interrupted is not recorded. By performing the behavior analysis as described above, it is possible to quantitatively determine the presence / absence of a dangerous behavior or bad habit, the frequency of occurrence, and the traveling history.

The statistical analysis module M12 performs a statistical analysis of the behavioral operation for each driver and each company, and generates information for determining driving tendency based on the statistics. For example, in the case of analysis by driver, data representing behavioral operations by all drivers of each company or all companies are averaged for each type of behavior,
The relative value of each driver to the data with respect to the average value is determined. The type in this case is, for example, the number of behavior occurrences,
Running speed, constant speed running time, idling time, etc.,
As a result, the characteristics of the driving tendency of the individual with respect to the whole can be statistically grasped. In addition, from the viewpoint that there are few people who are willing to drive dangerously, the data area of the driver with statistically low risk behavior is defined as the safe driving area, and whether the vehicle deviates from this data area is determined to be a dangerous driving tendency person. An analysis form for grasping whether or not it is possible is also possible.

The tendency analysis module M13 generates determination information for determining the driving tendency of each driver or the difference in driving tendency of another driver with respect to the driving tendency of a specific driver. . The behavior analysis module M11 can objectively grasp the driving tendency from the history of the behavior during traveling, and the statistical analysis module M12 can grasp the difference in the driving tendency of the individual with respect to the whole. However, the behavior analysis module M11 and the like determine the correlation between the running speed and the motion acceleration (front and rear G, lateral G), the correlation between the angular speed and the motion acceleration, or the change of the accelerator or steering wheel operation during running due to the date and time zone. Not a consideration. For example, it is a common experience that, even when the driver steps on the accelerator with the same strength, the risk is higher in high-speed running than in low-speed running. The same applies to handle operation. Even when driving in a tired state, the operation tends to be different from that in a healthy state.
These operations are, for example, G before and after the average speed is the same,
It appears as the magnitude of the displacement of the lateral G or the azimuth angular velocity, or appears as an average value or standard deviation that is extraordinarily large as compared to usual. In other words, it analyzes the correlation between different types of data such as speed data and acceleration data, and analyzes the change over time or the change over time of various data to evaluate the driving tendency and to determine the degree of traffic accidents and the degree of fatigue. It is presumed that it becomes easy to determine the correlation of Therefore, the tendency analysis module M13 considers the cross-correlation between the collected speed data, the longitudinal G, the lateral G, the azimuth velocity data, and the like, so that the driving tendency, the driving traffic accident, the degree of fatigue of the driver, and the like are obtained. The determination information for determining the correlation of is generated.

Various types of information can be considered as judgment information. Here, the average value and the standard deviation of the acceleration for each speed range are used so that each driver can grasp the tendency of safe driving or dangerous driving. An example is given below. The average value and the standard deviation represent, for example, the distribution of acceleration in a certain speed range. FIG. 12 is a diagram showing the average value (bar X) of accelerator acceleration by a driver who performs standard driving and its distribution, wherein the horizontal axis represents acceleration (G), and the vertical axis represents acceleration occurrence frequency (1a). It is. FIG. 13 is a diagram showing the distribution of acceleration by the driver in each speed range. "Low speed range" is 30km
/ H, the "medium speed range" assumes a speed range of less than 70 km / h, and the "high speed range" assumes a speed range of 70 km / h or more. FIG. 13 shows that the accelerator operation is relatively safe in the low speed range, but becomes more dangerous in the high speed range. More simply, the tendency to drive safely is determined based on how small the average value and standard deviation of individual drivers are, or how much the distribution of the analyst is different from the distribution of multiple drivers. can do.
In the latter case, it can be determined that a driver having a smaller deviation has a tendency to drive safely. However, such a method alone does not always provide sufficient determination accuracy.
In order to increase the accuracy, it is reasonable to make a comparison based on the distribution of drivers who have actually driven safely. Therefore, in this embodiment, a distribution based on the total data of the drivers in which the number of occurrences of the dangerous behavior in the predetermined period is relatively small, more preferably 0 is obtained, and this is set as a safe driving pattern. Then, by comparing the safe driving pattern with the distribution of the analysis subject, information indicating whether the analysis subject has a tendency to perform safe driving is generated. For example, FIG. 14 shows a difference in the distribution of Mr. A who is an analysis subject with respect to the safe driving pattern of Mr. B who is a safe driving tendency person in a certain speed range. In the example shown, A
Mr.'s distribution deviates considerably from the safe driving pattern, so it is hard to say that it is a safe driving tendency.

The standard deviation of acceleration by all or individual drivers of a plurality of drivers can be obtained as follows. First, the low speed range (speed range below 30 km / h),
Medium speed range (speed range less than 70 km / h), high speed range # 1 (70
speed range from km / h to less than 100 km / h), high speed range # 2
(Average speed range of 100 km / h or more). That is, the speed data and the front and rear G are read for each frame. If the speed is less than 30 km / h, the front and rear G are added to the “total # 1” area of the work memory (not shown), and one is added to the “number of additions # 1”. If the speed is more than 30 km / h and less than 70 km / h, the "total #
G is added to the “2” area, and 1 is added to “addition number # 2”. The speed exceeds 70 km / h and 100 km / h
If less than h, the front and rear G are added to the “total # 3” area of the working memory, and one is added to the “number of additions # 3”. When the speed is 100 km / h or more, the “Total #
G is added to the “4” area, and 1 is added to “addition number # 4”. If it is within the totaling period, the process returns to the first processing, and if the totaling period ends, “Total # 1” to “Total # 4”
(The cumulative value of the preceding and following G / the number of additions: the first average value to the fourth average value) of each area.

After calculating the average values, the front and rear G of the driver for each speed range are read out for each frame from the beginning of the counting period. If the speed is less than 30 km / h, the square of (first average value—G around) is added to the “distribution # 1” area of the working memory. If the speed is more than 30 km / h and less than 70 km / h, the square of (the second average value—G around) is added to the “dispersion # 2” area of the working memory. Speed is 70km / h
If it is more than 100 km / h, the square of (third average value—G before and after) is added to the “dispersion # 3” area of the working memory. When the speed is 100 km / h or more, the square of (fourth average value—G before and after) is added to the “dispersion # 4” area of the working memory. If it is within the counting period, the process returns to the first process, and if the counting period ends, “share # 1” to “share # 4”
The standard deviation in each area is calculated. Each standard deviation is
It can be calculated by calculating the square root of a value obtained by dividing the addition value in each dispersion area by the number of additions.

When the parent to be compared is the entire company or the entire sales office, the information for determination is generated in the following procedure, for example. First, the average value of the front and rear G for each speed range is obtained by the above procedure, and is defined as X. The front and rear G for each speed range
Is obtained in the same manner, and is defined as S. Further, the average value of the front and rear G for each speed range of each driver is similarly obtained, and this is set to M. The relative magnitude of the deviation of each driver with respect to the whole can be calculated by the formula of “(M−X) / S). It can be determined that a driver with a smaller value is more likely to drive safely.

The fuel correlation analysis module M14 analyzes and quantifies the fuel consumption tendency of the vehicle for each driver, and generates determination information for distinguishing between efficient travel and inefficient travel. Specifically, the quantification in this case is performed by calculating a predetermined fuel consumption amount using the idling time, the traveling speed, and the cumulative acceleration value based on the aggregated data of the vehicle specified by the behavior analysis module M11 as variables. Assuming, for example, that the idling time is I, the cumulative acceleration value is Gd, and other factors, for example, are constants corresponding to the running average speed and the running time, α, the fuel consumption is substantially represented by the calculation result of aI + bGd + α. That is, the accumulated acceleration value Gd approaches “0” as long as the number of starts is small and the constant-speed traveling time is continued, so that the consumed fuel is represented by a time element such as the idling time I or the traveling time and an average traveling speed. Function with various speed factors. Each coefficient a, b
Can be obtained as follows. (Coefficient a) In the case of “Gd = 0, α = 0”, the consumed fuel amount is a calculation result of the coefficient a and the idling time I. Therefore, the idling state is maintained for a certain period of time, and the fuel consumption at this time is measured. By substituting this into the above equation, the coefficient a is obtained. (Coefficient b) The vehicle travels at the same average speed while the idling time I is 0. Assuming that the fuel consumption and the cumulative acceleration value during the n-th run are “fuel consumption n” and “accumulated acceleration value Gdn”, respectively, the fuel consumption n is “b · Gdn +
α ”. Since α is common because of the same average speed, the coefficient b can be specified by dividing the difference between the fuel consumptions n each time by the difference between the cumulative acceleration values Gdn. (Evaluation) The coefficients a and b and the constant α are determined according to the above procedure, the idling time I and the cumulative acceleration value Gd are obtained from the state collection data and the like, and the calculation result of “aI + bGd + α” is obtained. If this calculation result is relatively small, it can be evaluated as “efficient driving”, and if it is large, it can be evaluated as “inefficient driving”. For example, by displaying the evaluation results of a plurality of drivers in the same data field in an integrated manner, the tendency of fuel consumption by each driver can be determined at a glance.

<Evaluation Processing Mode> In this embodiment, two types of relative evaluation processing are executed. One is a routine immediate processing for electronic information transmitted online, and the other is a routine one.
One is a badge process based on expert evaluation of electronic information transmitted off-line.

The immediate process is a process in which a standard relative evaluation process based on an evaluation condition pattern predetermined according to the needs of the company is activated by automatically activating each of the modules M11 to M14. More specifically, a routine numerical analysis process based on one-line total data per day, a warning process for outputting a message for calling attention to a suddenly changing data or the like from the one-line total data or a dangerous behavior list. A simplified hidden-data standardized analysis process for performing a fixed-value numerical analysis based on hidden data; and a section-by-section and driver-by-driver comparison and aggregation process for customer terminals for which an intranet has not been established. Further, based on the management data included in the electronic information from each customer terminal, comparison of the same type of data between the same type of business or different types of business, correlation of different types of data, comparison by region, etc. are performed. The comparison result is immediately presented to the corresponding company in the form of an individual message, or the customer freely browses his / her data from the terminal and browses it.

In the badge processing, after the raw data is analyzed in detail using the above-described modules M11 to M14, the unit is determined based on the judgment of an expert or using an expert system in which expert knowledge is stored in a database. This is a process for performing in detail the driving habit data analysis of the period, the risk behavior data analysis by comparison with the condition pattern, and the correlation analysis using the analysis results. This badge processing may be performed retroactively to accumulated data of a certain period in the past, or may be performed on accumulated data for a predetermined time starting from the present. The results of the badge processing are tabulated on a radar chart or graph, further mapped on a form such as a daily report, a seasonal report, or a monthly report, and presented to the corresponding company. Also,
It is presented to the relevant company in the form of an individual message based on the evaluation results.

<Operation Form> Next, an operation form of the operation analysis system 1 will be described. FIG. 15 is a processing procedure diagram of information collection and transmission performed in a company. Each company compiles the daily operation status of all the vehicles owned by the company and stores the raw data (step S10).
1). That is, the behavior of the vehicle driven by the driver for one day is recorded in the memory medium MB of the data recorder 3. Then, after the operation is completed, the memory medium MB is mounted on the reader / writer 21, and the recorded information is read, and the data is counted every day. When the dedicated software is installed in the data processing mechanism 27 of the customer terminal 2 (A type company and B type company), various forms are created (step SS102: Yes, S103), and the data content of the form Check. If necessary, the data is corrected (step S104). Based on this data, one line per day total data is created, and a dangerous behavior list is created (step S105). When the dedicated software is not installed in the customer terminal 2, the process immediately proceeds from step S101 to step 105. Thereafter, the one-line total data and the dangerous behavior list are transmitted online together with the hidden data to the operation analysis system 1 (step S10).
6). Further, the transmitted information and the raw data are stored in a predetermined memory area (step S107). The process of step 101 is repeated until one month has passed since the closing date of the previous month (step S108: No). If one month has elapsed, the stored raw data and the like are recorded on the high-density recording medium MO, and are sent off-line to the operation analysis system 1 (step S108: Yes, S109).

The operation analysis system 1 performs operation analysis according to the procedure shown in FIG. That is, if you receive electronic information,
If it is received online, the above-described immediate processing is executed (Step S201: Yes, S202: Yes)
s, S203), if the receipt is offline, the above-described badge processing is executed (step S201: Yes, S
202: No, S204). Then, each processing result is presented to the transmission source company (step S205). In this case, the result of the immediate processing is presented on the next day, and the result of the badge processing is presented on a predetermined day of the next month. Specifically, the information is presented by extracting a corresponding form from the form DB 163, mapping the processing result to the form, and attaching the processing result to an e-mail, and posting the mapped form screen on the Web. There is a presentation. After that, the received electronic information and the result of each process are stored in the corresponding customer field of the customer-specific DB 161 and used as comparison information of the driving condition analysis by the driver of another company (step S206).

FIG. 17 shows a procedure in which each company obtains, through the Web, the analysis result of the electronic information transmitted by itself online or offline. That is,
After connecting to the Internet L via the communication connection mechanism 25, the URL (Uniform Resource Locator) of the operation analysis system 1 is displayed on the browser screen displayed on the display device 23.
Is accessed (step S301). When the page screen of the operation analysis system 1 is displayed, the user inputs the company ID, the password, and other data required by the system, and moves to the evaluated guide page (step S302). A desired item (evaluated data item) is selected by the data input device 24 (step S303). The operation analysis system 1
Upon recognizing the selected item, a required form is created in form DB16.
3, the result of the immediate process or the badge process is mapped and presented, so that the analysis result of the item is displayed on the browser screen (step S304). If necessary, the analysis result is printed or stored on a disk or the like (step S305). As described above, the operation analysis system 1 of the present embodiment receives the electronic information indicating the operation status of the vehicle by the driver belonging to each company, collected by each of the plurality of companies, and analyzes the content of the electronic information. Performs the relative evaluation of the operation status between the same driver or different drivers, identifies the driver who exhibited the special operation status, and sends the result of the relative evaluation process to the company to which the specified driver belongs. Since we have provided information,
It is possible to provide each company with an objective relative evaluation result of the operation status that cannot be grasped by only one company. This effect is remarkable in the case of a small company with a small number of drivers. In addition, immediate processing and badge processing are prepared.
The analysis results are presented to each company on a daily basis.
Since we have provided specialized evaluation results to each company,
Immediate processing results for improvements in the early cycle,
The result of badge processing can be used for the presence or absence of fundamental improvements. In addition, since the evaluation result with high added value is fed back to the company that has transmitted the electronic information, it is possible to motivate each company to transmit the electronic information indicating the operation status collected by itself. Also,
Since the electronic information collected by a plurality of companies and the results of the evaluation have been accumulated and can be used at any time, comparison between various types of business is also possible. Further, since accurate evaluation results can be obtained even if each company does not have analysis ability or experience, there is also an effect that analysis can be performed. Also, even if an intranet is not established between a plurality of offices of one company, since electronic information and evaluation results from all offices are accumulated, comparison between offices of the company can be performed. .

<Message Example> As described above, in the operation analysis system 1 of the present embodiment, message information relating to an improvement is also presented according to the result of the relative evaluation processing. An example of a message presented to each company is shown below.

(1) In the case of immediate processing (1-1) The special operation status is the total number of dangerous behaviors during turning (rapid braking during turning), the company-wide average and the national average during the data collection period in January. (The average value of all companies in the same or different industries, the same applies hereafter.) The number of times is 1 for the company-wide average (1 month average) and 0.5 for the national average (1 month average), whereas the number of times by Mr. A, a driver belonging to a certain company, is 6 times (1 If it is (monthly average), the operation analysis system 1 extracts the corresponding fixed text data from the message DB 162 and edits the data for the company, and says, "Mr. A seems to have a lot of sudden braking while turning. Sudden braking is one of the major factors that can lead to a departure accident. You need to be careful about predictive driving such as curves with poor visibility. " Proper nouns and numerical values are mapped based on the evaluation results. Hereinafter, similar processing is performed.

(1-2) The total number of dangerous behaviors during the lane change when the special operation status is changed (sudden lane change, V lane change)
The speed, idling time, and the number of stops indicate that traffic for 10 minutes or less per hour for 30 minutes or more is determined to be "congestion," and the data is collected in January and compared with the company-wide average and the national average. Assume that a relative evaluation has been performed. The number of times is 18 times for Mr. A (Mostly dangerous behavior during traffic jam for Mr. A (15 out of 18 times during traffic jam)), 13 times for Mr. B, 9 times for Mr. C (average in January), company-wide average of 0 It is assumed that the average was 7 times (January average) and the national average was 0.5 times (vehicle type). The message in this case is, for example, "Mr. A, B, and C seem to have many sudden lane changes.
Mr. A has a lot of zigzag running in traffic. Shortening the time by the zigzag running method is not so effective. During traffic jams, the risk of contact accidents increases, so it is necessary to give instructions such as reviewing driving. Also, I guess Mr. A is driving like this because of his business. It may be necessary to check whether the dispatch plan is reasonable. ".

(1-3) The special operation status is the number of dangerous behaviors during braking (sudden braking). Mr. A records this once on a certain day, and uses acceleration / deceleration G using hidden data. Judging from the side G, if there was unevenness only on this day, a message such as "Dangerous sudden braking was recorded only once. However, from the data on this day, acceleration / deceleration G (accelerator operation It seems that there is unevenness in brake operation) and side G (handle operation) .I am also concerned about sudden braking, but I am also concerned about acceleration / deceleration G side G. It may not be directly related to poor physical condition or work But how about checking the situation in the home? "

(1-4) The special operation status is the number of suspensions, and the number of times is 8 times for A, 12 times for B, and 14 times for C (average per day). If the average value of the people running is 29 times (average per day), the message is that "Mr. A, B, and C" have relatively few "pauses", for example. If you follow the same route and you get this result, you may have neglected "pause". It is necessary to instruct "pause enforcement" to cope with unexpected jumping out of children. ".

(1-5) The special operation situation is the total number of dangerous behaviors, the number of which is Mr. A once at the beginning of the month, twice during the month, and 30 at the end of the month. When performing an analysis, the message is, for example, "It seems that the dangerous behavior tends to increase at the end of the month. It is unknown whether the work is concentrated at the end of the month or due to the road condition, We need to find out and take countermeasures. "

(1-6) The special operation situation is the total number of dangerous behaviors, and the number of times is Mr. A once in the morning, twice in the afternoon, and five times in the evening (1
If the analysis comparison is performed by dividing the average value of the day by time zone, the message is, for example, "It seems that the dangerous behavior tends to increase in the evening. Road conditions also deteriorate in the evening, It is also possible that the driver's fatigue has accumulated, and if this situation continues, it is possible that an accident may occur someday, so it is necessary to take measures such as "5 minutes before departure" . ".

(1-7) When the special operation situation is a sudden change in data and the frequency of occurrence of such a sudden change of Mr. A suddenly increases, the analysis comparison is performed by comparing with the past data of Mr. A. The message states, for example, "Mr. A has been driving relatively quietly until now, but many dangerous behaviors have occurred in the past few days. Why don't you look at it? "

(1-8) The special operation situation is an accident avoidance brake operation, the number of times is Mr. A 5 (average value), company-wide average value 0.7, national average value 0.5, and analysis comparison Whole country·
When performing comparative analysis with company-wide averages, the message is, for example, "When you analyze Mr. A's data, it seems that there are many" brake operations to avoid accidents. " It is expected that there will be more opportunities to encounter dangerous situations. Guidance is required to keep in mind predictive driving. ".

(2) In the case of badge processing (2-1) The special operation status included in the raw data is the average value of the maximum brake G, and the result is 0.30 G (average value) of Mr. A who often has a dangerous behavior of sudden braking. If the company-wide average is 0.19G and the national average is 0.17G, and the analysis comparison is to compare and analyze with the company-wide and national average based on the one-minute total data, the message is, for example, "A He has shown that there are many dangerous behaviors of sudden braking from normal times.This raw data analysis shows that the normal brake operation itself also has a high G. To prevent accidents, "early and early brake"
Please be aware of. ".

(2-2) The special operation status included in the raw data is unevenness in brake and accelerator operation, and the result is as follows.
If the standard deviation of the accelerator and the brake varies from day to day, and the analysis comparison is to determine the standard deviation for each analysis day based on the one-minute total data, the message is, for example, "Mr. There is unevenness in operation.It does not lead to dangerous behavior, but it is a bit worrisome.I need to improve it if there is a problem with the delivery plan or the content of the work.I tend to think that it is not related to direct driving, Driving can be uneven in this way due to family issues. "

(2-3) The special operation status included in the raw data is that there is a large amount of dangerous behavior (sudden braking) of all the drivers at a certain point. If the analysis comparison is to analyze the dangerous behavior by searching the approximate latitude and longitude information based on the event data, the message is, for example, "All drivers near point A. Is suddenly braking. Since everyone is behaving dangerously at this point, there may be some external factors.
Needs measures. Also, it is necessary to set a course that does not pass this point. ".

By presenting such a message together with the information mapped on the form, it is possible to objectively grasp the cause of dangerous behavior and bad habits and measures for improvement, and to improve safe driving and work efficiency. Can be contributed to.

Although the present invention has been described with reference to the specific embodiments, the scope of the present invention is not limited to the above examples. For example, in the above-described embodiment, a vehicle has been described as an example of a moving object. However, the present invention can be similarly applied to all moving objects that require operation analysis, for example, a train or a motorcycle.

[0064]

According to the present invention, it is possible to achieve a unique effect that it is possible to objectively analyze the operation status and to effectively distribute the analysis result to the customer.

[Brief description of the drawings]

FIG. 1 is an overall configuration diagram showing an application scene of an operation analysis system of the present invention.

FIG. 2 is a configuration diagram of a customer terminal.

FIG. 3 is a configuration diagram of a data recorder.

FIG. 4 is an image diagram of electronic information recorded on a medium of the data recorder.

FIG. 5 is a structural diagram of a main part of management data.

FIG. 6A is an event head arranged at the beginning or a break of an event, and FIG. 6B is a structural diagram of autonomous data (Ax or the like) representing the content of the event and vehicle speed data.

FIG. 7 is a diagram showing an array of speed, information of an event occurrence location, and GPS time, which are obtained from GPS data, of event data.

FIG. 8 is a structural diagram of state collection data.

FIG. 9 is a structural diagram of autonomous and vehicle speed total data.

FIG. 10 is a structural diagram of GPS total data.

FIG. 11 is a configuration diagram of an operation analysis system.

FIG. 12 is a diagram showing an average value (bar X) by a driver who performs standard driving and its fluctuation.

FIG. 13 is a diagram showing fluctuations in acceleration in different speed ranges by a driver.

FIG. 14 shows a person B who tends to drive safely in a certain speed range.
The figure which showed the difference of the distribution of Mr. A who is an analysis subject with respect to his safe driving pattern.

FIG. 15 is an explanatory diagram of a procedure of an operation analysis process (process performed by a company side).

FIG. 16 is an explanatory diagram of a procedure of an operation analysis process (processing performed by an operation analysis system).

FIG. 17 is an explanatory diagram of a procedure of an operation analysis process (process performed by a company).

[Explanation of symbols]

 REFERENCE SIGNS LIST 1 operation analysis system 16 DBMS 161 customer-specific DB 162 message DB 163 form DB 17 processing device 172 evaluation processing unit 173 data editing unit 174 data output unit 2 customer terminal 27 data processing mechanism 3 data recorder 31 sensor unit 32 medium accommodation mechanism 33 recorder Part MB memory medium MO high density recording medium

 ────────────────────────────────────────────────── ─── Continuing on the front page (72) Inventor Tomoho Tano 4-42-12 Kamata, Ota-ku, Tokyo Shinsei Building Data Tech Co., Ltd. F-term (reference) 5B049 CC00 EE59 5H180 AA01 BB12 BB13 BB15 FF05

Claims (18)

[Claims] 1. The method of claim 1, wherein each of the plurality of customers collects.
Receiving means for receiving electronic information indicating the operating status of the mobile unit by the driver belonging to each customer, and analyzing the content of the electronic information received from each customer to determine the operating status between the same driver or different drivers An operation analysis system comprising: an evaluation unit that performs a relative evaluation process; and an information presenting unit that presents information on a result of the relative evaluation process performed by the evaluation unit to a customer to which a driver to be evaluated belongs. 2. The method according to claim 1, wherein the evaluating unit is configured to identify a driver who has exhibited a special operation situation in which a difference between the results of the relative evaluation processing is equal to or more than a predetermined value. The operation analysis system according to claim 1, wherein the operation analysis system is configured to present the result information of the relative evaluation process to a customer to which a driver belongs. 3. The receiving means receives, on-line, first electronic information representing characteristics of the operating state of the moving body by each driver from a terminal operated by each customer, and stores the first electronic information stored for a certain period of time. The operation analysis system according to claim 1, wherein the operation analysis system is configured to receive off-line the second electronic information as a basis of the electronic information. 4. The evaluation means is configured to perform a standard relative evaluation process on the first electronic information and an atypical relative evaluation process on the second electronic information. The operation analysis system according to item 1. 5. A first processing means for performing an immediate process based on a comparison between the first electronic information received at a first time interval and a predetermined evaluation condition pattern, the evaluation means comprising: Second processing means for performing a badge process on the second electronic information received every time the second electronic information is accumulated for a long second time, wherein the first or second processing means is selected according to a data receiving form from a customer. The operation analysis system according to claim 4, wherein the relative evaluation is performed by activating the operation analysis. 6. The receiving means for receiving a part or all of the electronic information recorded by a predetermined data recorder mounted on the moving body, wherein the data recorder is provided at least before and after the moving body. A sensor unit for measuring the acceleration in the left-right direction in time series, and a recorder unit for recording the measurement data and processing data obtained from the sensor unit on a recording medium detachable from the data recorder. The unit considers that a behavior has occurred when the displacement width of the measurement data exceeds a predetermined threshold, records the behavior occurrence time and the measurement data for a predetermined time before and after the time, and a change occurs in the movement situation. In the case, at least the time and the position information at that time are recorded, and the average value of the measurement data is calculated and recorded every time a predetermined period elapses. In it, operating analysis system according to claim 1, wherein the. 7. The evaluation means is configured to calculate a relative change amount in the operation status of each driver, and recognize an operation status in which the calculated relative change amount exceeds a threshold as the special operation status. The operation analysis system according to claim 1. 8. The evaluation means calculates an average value and a standard deviation between drivers of the average value of the operation status of each driver for each predetermined period, and calculates a deviation of the average value of the individual drivers from the standard value. The operation analysis system according to claim 1, wherein an operation status exceeding a predetermined value of the deviation is recognized as the special operation status. 9. The evaluation means recognizes an operation status of a driver having a relatively small number of occurrences of a peculiar behavior within a predetermined period as an exemplary operation status, and determines the exemplary operation status and an operation status of another driver. The operation analysis system according to claim 1, wherein the operation analysis system is configured to specify a driving operation tendency of the other driver by comparing the driving operation tendency with the other driver. 10. The evaluation means performs a correlation analysis between different types of data included in the electronic information of each driver, and quantifies a causal relationship of an event occurrence by the driver based on a result of the correlation analysis. The operation analysis system according to claim 1, wherein the operation analysis system is configured as follows. 11. The evaluation means calculates an average value and a standard deviation 1 of the operating conditions of all the drivers, and an average value and a standard deviation 2 of the operating conditions of the individual drivers, and calculates the calculated standard deviation. The operation analysis system according to claim 1, wherein an operation status in which 2 exceeds a predetermined value multiple of the standard deviation 1 is recognized as the special operation status. 12. The evaluation means is configured to detect the presence or absence of occurrence of dangerous behavior and the habit of driving by the driver by comparing the received electronic information with a predetermined condition pattern. The operation analysis system according to claim 1. 13. The information presenting means categorizes the results of the relative evaluation into the same customer, between customers of the same industry, and between customers of different industries, and presents the results in a form that each customer can view. The operation analysis system according to claim 1. 14. The operation analysis system according to claim 1, wherein the information presenting means presents a message including information that has caused the relative evaluation in accordance with a result of the relative evaluation. 15. The operation analysis system according to claim 14, wherein the information presenting means constructs the message by embedding information corresponding to the result of the relative evaluation into standardized document data prepared in advance. 16. A computer which can be connected to a customer terminal operated by each of a plurality of customers via a communication network and also has a reading mechanism for a recording medium. Receiving the first electronic information indicating the operation status of the moving object by the driver online via the customer terminal operated by the customer and the communication network; collected by each customer and accumulated for a certain period of time; A process of receiving, via the recording medium, second electronic information serving as a basis of the first electronic information; analyzing the content of each of the received electronic information to perform a relative evaluation of the operation status between the same driver or different drivers A process of performing a process; a process of presenting result information of the relative evaluation process to a customer to which the driver to be evaluated belongs. Operation analysis method due. 17. A driver presenting a special operation status having a difference of a predetermined value or more in a result of the relative evaluation processing is specified, and the result information of the relative evaluation processing is addressed to a customer to which the specified driver belongs. 17. The operation analysis method according to claim 16, wherein the operation analysis method is provided. 18. A computer which can be connected to a customer terminal operated by each of a plurality of customers via a communication network and has a reading mechanism of a recording medium, and which is collected by each of the customers and belongs to the customer. Receiving the first electronic information indicating the operation status of the moving object by the driver online via the customer terminal operated by the customer and the communication network; collected by each customer and accumulated for a certain period of time; A process of receiving, via the recording medium, second electronic information serving as a basis of the first electronic information; analyzing the content of each of the received electronic information to perform a relative evaluation of the operation status between the same driver or different drivers A computer program for executing a process of performing a process; a process of presenting the result information of the relative evaluation process to a customer to which the driver to be evaluated belongs.