Dangerous driving determination system and dangerous driving determination method

Abstract

To more quickly extract an elderly driver who is likely to perform dangerous driving at the time when the driver falls into a situation that may cause dangerous driving.SOLUTION: A dangerous driving determination system manages, for each elderly driver, dangerous driver relevant information indicating whether or not the driver is dangerous, and personal information for each elderly driver including health examination result information indicating the health condition of the elderly driver, nursing care information related to nursing care certification, resident information related to resident registration in a municipality, or pension receiving information in association with each other. The dangerous driving determination system determines, for each item of the personal information, the corresponding one of a plurality of determination results of the item under which the elderly driver who is considered the dangerous driver falls, determines whether the result of determination that the elderly drivers are distributed at a cumulative ratio more than a predetermined ratio matches the Pareto principle, and then determines that the item matching the Pareto principle meets a risk degree determination condition for determining whether the elderly driver is a dangerous driver.SELECTED DRAWING: Figure 15

Description

[Technical field]

[0001] The present invention relates to a driving risk assessment system and a driving risk assessment method. [Background technology]

[0002] In recent years, there have been many car accidents involving elderly drivers. According to the results of a survey on the causes of accidents, the biggest factor in fatal accidents involving people under the age of 75 is "failure to check for safety," whereas in accidents involving people 75 and older, "improper operation" is often cited as a cause, especially improper steering and mistaking the accelerator for the brake.

[0003] On the other hand, there are also reports that older people tend to think that "my driving technique is sufficient to avoid danger," and it is speculated that overconfidence in one's own cognitive and physical functions is also a factor in the high number of accidents. (National Police Agency Traffic Bureau, "Characteristics of Traffic Fatalities in 2017," "Super-Aging Society and Automobile Traffic (National Consumer Affairs Center of Japan, "National Life," November 2016)").

[0004] Against this background, in order to prevent traffic accidents caused by the decline in cognitive function of elderly drivers, a cognitive function assessment system has been devised that evaluates the cognitive function of elderly drivers related to driving a car based on the steering wheel rotation angle of the vehicle. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2023-59751 A Summary of the Invention [Problem to be solved by the invention]

[0006] However, it is assumed that the cognitive function test using the above-mentioned conventional cognitive function assessment system is conducted at the time of license renewal. The cognitive function test is conducted, for example, for elderly drivers who have a history of violations in the past three years. License renewal is conducted every three to five years. For this reason, the conventional technology may not be able to promptly extract elderly drivers who may engage in dangerous driving at the time when they reach a state of cognitive decline or the like that causes dangerous driving.

[0007] The present invention has been made in consideration of the above-mentioned circumstances, and aims to make it possible to more quickly extract elderly drivers who are likely to engage in dangerous driving at the point when they reach a situation that could cause dangerous driving. [Means for solving the problem]

[0008] As one aspect for solving the above-mentioned problem, there is provided a driving risk assessment system for assessing a driving risk level indicating a risk level of an elderly driver causing a car accident by driving a car, the driving risk assessment system having a processor, a memory, and a storage unit, the storage unit determining that an elderly driver who has a history of causing a car accident in the past or a history of surrendering a driver's license is a dangerous driver who is at risk of causing a car accident, and storing, for each elderly driver, dangerous driver information indicating whether or not the elderly driver is a dangerous driver, medical examination result information indicating the elderly driver's health condition, nursing care information related to nursing care certification, self-care information, and other information. The processor manages the elderly driver's personal information, including resident information related to resident registration with a local government or personal information for each elderly driver including pension benefit information, in association with the elderly driver's personal information, and for each item of the personal information, the processor determines which of a plurality of judgment results for the item the elderly driver who corresponds to the dangerous driver corresponds to, and for each item, determines whether the judgment result matches Pareto's law, which indicates that the elderly drivers are distributed at a cumulative ratio equal to or greater than a predetermined value, and determines that the item that matches Pareto's law corresponds to a risk judgment condition for determining whether the elderly driver is a dangerous driver. Effect of the Invention

[0009] According to the present invention, it is possible to more quickly extract elderly drivers who are likely to engage in dangerous driving when they reach a situation that may cause dangerous driving. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram showing the overall system configuration including the elderly driver driving risk assessment system. [Diagram 2] FIG. 1 is a diagram showing the configuration of a system for determining the driving risk of elderly drivers. [Diagram 3] FIG. 4 is a diagram showing the structure of a user management table. [Figure 4] FIG. 13 is a diagram showing the layout of a health checkup table. [Diagram 5] FIG. 13 is a diagram showing the structure of a nursing care information table. [Figure 6] FIG. 13 is a diagram showing the structure of the Resident Registration Linkage Table. [Figure 7] Layout diagram of pension entitlement table. [Figure 8] FIG. 13 is a diagram showing the configuration of an elderly support organization management table. [Figure 9] FIG. 13 is a diagram showing the structure of a risky driver statistics management table. [Figure 10] FIG. 4 is a diagram showing the configuration of a driving risk determination table. [Figure 11] 4 is a flowchart showing the overall processing in the entire system. [Figure 12] 11 is a flowchart showing details of a user information registration / update process. [Figure 13] 10 is a flowchart showing details of a dangerous driver determination process. [Figure 14] 11 is a flowchart showing details of the elderly support group registration and update process. [Figure 15] 11 is a flowchart showing details of a dangerous driver statistical analysis process. [Figure 16A] FIG. 13 is a diagram showing an example of an extracted risk determination condition (sitting position). [Figure 16B] FIG. 13 is a diagram showing an example of extraction of risk level determination conditions (easy cooking). [Figure 16C] FIG. 13 is a diagram showing an example of an extracted danger level determination condition (suddenly speaking loudly). [Figure 16D]FIG. 13 is a diagram showing an example of extraction of risk determination conditions (heart rate). [Figure 16E] FIG. 13 is a diagram showing an example of extraction of risk determination conditions (excretion, urination). [Figure 17] 10 is a flowchart showing details of a driving risk addition process. [Figure 18] 11 is a flowchart showing details of a driving danger determination and notification process. [Figure 19A] FIG. 13 is a diagram showing an example of a total risk index and a driving risk judgment result. [Figure 19B] FIG. 13 is a diagram showing an example of a total risk index and a driving risk judgment result. [Figure 19C] FIG. 13 is a diagram showing an example of a total risk index and a driving risk judgment result. [Figure 20] Computer hardware diagram. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. Note that the embodiments described below do not limit the invention according to the claims, and all of the elements and combinations thereof described in the embodiments are not necessarily essential to the solution of the invention.

[0012] In the following description, identical or similar components are given the same reference numerals, and in the following embodiments and modified examples, the description may be omitted or only the differences may be described. In addition, when there are multiple identical or similar components, the same reference numerals may be given different subscripts. In addition, when there is no need to distinguish between these multiple components, the subscripts may be omitted. The number of each component may be singular or plural unless otherwise specified.

[0013] In the following explanation, the processing performed by the programs may be described. The programs realizing each processing function unit are executed by a processor to perform a predetermined process using a storage resource (e.g., a RAM (Random Access Memory)) and / or a communication interface device (e.g., a port). The processor may be a CPU (Central Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), etc. The processing executed by each program or each processing function unit may be processing performed by a processor or a computer having the processor.

[0014] In the following description, various information will be described in a table format, but the format of the various information is not limited to the table format and may be other formats such as CSV format.

[0015] (Configuration of the overall system S) 1 is a configuration diagram of an overall system S including an elderly driver driving risk determination system 1. The overall system S is configured to include the elderly driver driving risk determination system 1, a local government system 2, a police system 3, and a terminal 4.

[0016] The elderly driver driving risk assessment system 1 assesses the driving risk level that indicates the risk level of an elderly driver causing a car accident by driving a car. The elderly driver driving risk assessment system 1 is connected to a local government system 2 and a police system 3 via a network N2 such as a local government wide area network (LGWAN).

[0017] The elderly driver driving risk assessment system 1 includes a WEB server 11, an AP server 12, and a DB server 13. The DB server 13 is an example of a storage unit. The WEB server 11 accepts user operations from the terminal 4 via a network N1 such as the Internet. The DB server 13 stores data provided from the local government system 2 and the police system 3 via the network N2.

[0018] The local government system 2 stores user data 21, medical checkup data 22, nursing care data 23, basic resident register data 24, and pension data 25. The police system 3 stores accident data 31 and license data 32.

[0019] The health check data 22 is the health check result for each user, including items such as height, weight, BMI (Body Mass Index), waist circumference measurement, eyesight, etc. The nursing care data 23 is nursing care information for each user (nursing care certification information, home nursing care records, etc.) including items such as nursing care insured person number, certification history serial number, organization (medical institution), organization (nursing care business), reason for application, certification date, nursing care need state classification, etc.

[0020] The resident registration data 24 is basic resident information for each user, including items such as address, address before moving, reason for moving, registered domicile, national health insurance eligibility, late-stage elderly eligibility, nursing care eligibility, etc. The pension data 25 is pension receipt information for each user, including items such as basic pension number, official application category, eligibility category, spouse basic pension number, insured person type, eligibility acquisition date, etc.

[0021] The AP server 12 executes various processes based on the data stored in the DB server 13 in response to a user operation from the terminal 4 .

[0022] (Configuration of Elderly Driver Driving Risk Assessment System 1) 2 is a configuration diagram of the elderly driver driving risk determination system 1. The elderly driver driving risk determination system 1 includes a WEB server 11, an AP server 12, and a DB server 13.

[0023] The WEB server 11 is equipped with WEB server software 111 that realizes the functions of the WEB server 11 .

[0024] The AP server 12 is implemented with AP server software 121 that realizes the functions of the AP server 12. The AP server software 121 includes a user information registration and update program 122 and a dangerous driver determination program 123. The AP server software 121 also includes an elderly support group registration and update program 124, a dangerous driver statistical analysis program 125, a driving danger level addition program 126, and a driving danger level determination and notification program 127.

[0025] The DB server 13 is implemented with DB server software 131 that realizes the functions of the DB server 13. The DB server software 131 stores various data in a user management table D100, a medical examination result table D200, a nursing care information table D300, a resident registration linkage table D400, and a pension receipt table D500. The DB server software 131 also stores various data in an elderly support organization management table D600, a dangerous driver statistics management table D700, and a driving risk assessment table D800.

[0026] The user management table D100 stores user data 21 acquired from the local government system 2. The medical checkup result table D200 stores medical checkup data 22 acquired from the local government system 2. The nursing care information table D300 stores nursing care data 23 acquired from the local government system 2. The resident registration linkage table D400 stores resident registration data 24 acquired from the local government system 2. The pension receipt table D500 stores pension data 25 acquired from the local government system 2. The elderly support organization management table D600 manages information on support organizations that provide elderly support.

[0027] (Configuration of user management table D100) 3 is a configuration diagram of the user management table D100. The user management table D100 is a table for managing personal information of each user (elderly driver). The user management table D100 has columns of user ID_D101, name D102, gender D103, date of birth D104, phone number D106, address D107, My Number D108, driver's license status D109, license surrender flag D110, accident history D111, etc. The driver's license status D109, license surrender flag D110, and accident history D111 are data of the accident data 31 and license data 32 of the police system 3 linked by the My Number D108 and other information that can identify an individual.

[0028] The driver's license status D109 is information on whether the user holds a driver's license. The license surrender flag D110 is information on whether the user has surrendered his / her driver's license. The accident history D111 is information on the number of driving accidents the user has caused in the past.

[0029] (Configuration of medical examination result table D200) 4 is a diagram showing the structure of the medical examination result table D200. The medical examination result table D200 is a table for managing the results of the medical examination of each user. The medical examination result table D200 has columns for user ID 201, risky driver flag D202, height D203, weight D204, BMI_D203, waist circumference measurement value D206, eyesight D207, etc. The risky driver flag D202 indicates whether the corresponding user has been determined to be a risky driver.

[0030] (Configuration of nursing care information table D300) 5 is a diagram showing the structure of the nursing care information table D300. The nursing care information table D300 is a table for managing the health condition related to nursing care, including the nursing care required category and the state of physical functions of each user. The nursing care information table D300 has columns for user ID_D301, dangerous driver flag D302, insured person number D303, certification date D304, nursing care required state category D305, ..., left arm D306, left foot D307, right arm D308, right foot D309 ....

[0031] The dangerous driver flag D302 is the same as the dangerous driver flag D202 in the medical examination result table D200. It indicates whether the corresponding user has been determined to be a dangerous driver. The certification date D304 is the date on which the corresponding user received the nursing care certification indicated in the nursing care state classification D305. The left arm D306, the left foot D307, the right arm D308, and the right foot D309 indicate the functional status of the corresponding user's limbs.

[0032] (Configuration of the Resident Registration Linkage Table D400) 6 is a diagram showing the configuration of the resident registration linkage table D400. The resident registration linkage table D400 manages information on the address, registered domicile, and health insurance enrollment status that can be obtained from the resident registration of each user. The resident registration linkage table D400 has columns for user ID_D401, dangerous driver flag D402, address D403, address before moving D404, reason for moving D405, registered domicile D406, national health insurance eligibility D407, etc. The dangerous driver flag D402 is the same as the dangerous driver flag D202 in the medical examination result table D200.

[0033] (Configuration of pension receipt table D500) 7 is a diagram showing the structure of the pension receipt table D500. The pension receipt table D500 manages information related to the pension of each user. The pension receipt table D500 has columns for user ID_D501, risky driver flag D502, basic pension number D503, special certification category D504, benefit type D505, total pension amount D506, monthly pension payment amount D507, etc. The risky driver flag D502 is the same as the risky driver flag D202 in the medical examination result table D200.

[0034] (Configuration of elderly support organization management table D600) 8 is a diagram showing the configuration of an elderly support group management table D600. The elderly support group management table D600 is a table for managing information related to groups that provide elderly support. The elderly support group management table D600 has columns for group ID_D601, group name D602, representative designation D603, representative phone number D604, representative email address D605, number of members D606, activity details D607, activity area D608, and so on.

[0035] (Configuration of Dangerous Driver Statistics Management Table D700) 9 is a diagram showing the configuration of the dangerous driver statistics management table D700. The dangerous driver statistics management table D700 has columns for a judgment condition ID D701, a judgment item D702, a judgment result D703, a distribution D704, a ratio D705, a risk judgment flag D706, and an added risk index D707.

[0036] The risky driver statistics management table D700 stores the number of risky drivers belonging to each group (distribution D704), the distribution ratio (ratio D705), and a risk level determination flag D706 when each user is classified into each group (determination result D703) for each determination item D702. The risk level determination flag D706 indicates whether or not the corresponding group is determined to be a risky driver who engages in dangerous driving.

[0037] 9 indicates the identification information of a column in the table storing the data of the judgment item D702. For example, if the first four digits of the judgment condition ID_D701 are "D203", the judgment item D702 is "height", which is determined from the code "D203" of the height D203 in the medical examination result table D200.

[0038] In addition, in FIG. 9, the distribution D704 is calculated assuming that the total number of risky drivers is 100 as an example. The added risk index D707 is a score given according to each rank, for example, A rank, B rank, and C rank, which are accumulated from the lowest rank when the judgment item D702 is an item indicating the health condition including the user's physical function and ability. The added risk index D707 indicates that the higher the value, the more dangerous it is. The A rank occupies an accumulated ratio of 0 to 80%, and a score of 5 points is given. The B rank occupies an accumulated ratio of 81 to 95%, and a score of 1 point is given. The C rank occupies an accumulated ratio of 96 to 100%, and a score of 0 point is given.

[0039] The additional risk index D707 is assigned a larger value for each judgment item D702 representing the health state of a user whose distribution D704 of dangerous drivers matches the Pareto law, since the higher the degree of match, the higher the possibility of the user being a dangerous driver. The Pareto law is an empirical rule that the top 20% account for 80% of the total. In this embodiment, it is based on ABC analysis (focused analysis) that applies Pareto analysis. A user whose total of the additional risk index D707 is 5 points or more is determined to be a dangerous driver.

[0040] In FIG. 9, judgment conditions ID_D31001 to D31005 are an example of a plurality of judgment conditions to which an added risk index, which is a score according to a cumulative ratio, is assigned.

[0041] (Configuration of driving risk determination table D800) 10 is a diagram showing the configuration of a driving risk level determination table D800. The driving risk level determination table D800 stores the results of risky driver determination based on the determination items D702 for each user. The driving risk level determination table D800 has columns for user ID_D801, risky driver flag D802, presence / absence of driver's license D803, and total risk level index D804. The driving risk level determination table D800 also has columns for driving risk level determination result D805, determination grounds D806, determination grounds D807, determination grounds D808, available organizations D809, and notification flag D810.

[0042] The determination grounds D806, D807, and D808 are used to register up to three pieces of identification information for the corresponding determination condition ID_D701, but are not limited to three.

[0043] The driving risk assessment result D805 is determined as follows according to the total risk index D804 obtained by adding up the added risk index D707 for each user. That is, if the total risk index D804 is 5 points or more, it is determined that "driving is very dangerous", if it is 3 or 4 points, it is determined that "driving is quite dangerous", if it is 1 or 2 points, it is determined that "driving is dangerous", and if it is 0 points, it is determined that "driving requires caution". Note that even if the total risk index D804 is 0 points, the user is extracted as an elderly person, and it is determined that "driving requires caution" because elderly people's driving is always dangerous.

[0044] Hereinafter, the medical examination result table D200, the nursing care information table D300, the resident registration linkage table D400, and the pension receipt table D500 used for the input of the analysis are collectively referred to as the "IN table group". Each table of the IN table group manages dangerous driver information and personal information of each elderly driver in association with each elderly driver. The personal information here is each item indicating the personal attributes, physical condition, etc. in the medical examination result table D200, the nursing care information table D300, the resident registration linkage table D400, and the pension receipt table D500. A dangerous driver who is at risk of causing a car accident is an elderly driver who has an accident history of causing a car accident in the past or a history of returning a driver's license, as described later. The dangerous driver information is information indicating whether or not an elderly driver corresponds to a dangerous driver. The personal information of each elderly driver includes medical examination result information indicating the health condition of the elderly driver, nursing care information related to nursing care certification, resident information related to resident registration in a local government, or pension receipt information.

[0045] (Overall processing in the overall system S) 11 is a flowchart showing the overall processing in the overall system S. In the overall processing, steps S1 to S4 are executed in any order as needed, and steps S5, S6, S7, and S100 to S700 are executed at regular intervals.

[0046] In step S1, the user 6 submits user data 21 to a local government official / police official 7. In step S2, the local government official / police official 7 registers the user data 21 in the local government system 2 or the police system 3. In step S3, the elderly support organization 5 submits elderly support organization data (not shown) to the local government official / police official 7. In step S4, the local government official / police official 7 registers the elderly support organization data in the local government system 2 or the police system 3.

[0047] In step S5, the local government system 2 and the police system 3 extract update data related to the user data registered in step S2 and the elderly support organization data registered in step S5. Next, in step S6, the local government system 2 and the police system 3 transmit the update data extracted in step S5 to the elderly driver driving risk assessment system 1. Next, in step S7, the elderly driver driving risk assessment system 1 receives the update data transmitted in step S6, and stores and reflects the update difference based on the update data in the user management table D100 and the elderly support organization management table D600.

[0048] Next, in step S100, the elderly driver driving risk assessment system 1 executes a user information registration and update process. The details of the user information registration and update process will be described later with reference to FIG. 12. Next, in step S200, the elderly driver driving risk assessment system 1 executes a dangerous driver assessment process. The details of the dangerous driver assessment process will be described later with reference to FIG. 13.

[0049] Next, in step S300, the elderly driver driving risk assessment system 1 executes elderly support group registration and update processing. Details of the elderly support group registration and update processing will be described later with reference to FIG. 14. Next, in step S400, the elderly driver driving risk assessment system 1 executes dangerous driver statistical analysis processing. Details of the dangerous driver statistical analysis processing will be described later with reference to FIG. 15.

[0050] Next, in step S500, the elderly driver driving risk assessment system 1 executes a driving risk addition process. The details of the driving risk addition process will be described later with reference to Fig. 16. Next, in step S600, the elderly driver driving risk assessment system 1 executes a driving risk assessment and notification process. The details of the driving risk assessment and notification process will be described later with reference to Fig. 17.

[0051] Next, in step S700, the terminal operated by the user 6 receives the notification (such as an email) sent by the elderly driver driving risk assessment system 1 in step S600, and displays the received notification to the user 6.

[0052] (Details of User Information Registration / Update Process (Step S100)) FIG. 12 is a flowchart showing the details of the user information registration / update process.

[0053] First, in step S 101 , the user information registration and update program 122 checks the data received from the local government system 2 and the police system 3 .

[0054] Next, the user information registration / update program 122 repeats steps S102 to S104, S105, S107, and S109 for the number of data received in step S101.

[0055] In step S102, the user information registration / update program 122 determines whether the received data is the user data 21, the accident data 31, the license data 32, the medical checkup data 22, the nursing care data 23, the resident registration data 24, or the pension data 25.

[0056] If the user information registration and update program 122 determines in step S102 that the received data is user data 21, it repeats steps S103 to S104 and S105 the number of times corresponding to the user data 21 determined in step S102. In step S103, the user information registration and update program 122 determines whether the user data 21 determined in step S102 has already been registered. If the user information registration and update program 122 determines that the user data 21 has already been registered (YES in step S103), it proceeds to step S104, and if the user information registration and update program 122 determines that the user data 21 has not already been registered (NO in step S103), it proceeds to step S105.

[0057] In step S104, the user information registration and update program 122 updates the user data 21 already registered in the user management table D100 with the new user data 21. Meanwhile, in step S105, the user information registration and update program 122 newly registers the new user data 21 in the user management table D100. Then, the user information registration and update program 122 newly registers a user record corresponding to the new user data 21 in the IN tables.

[0058] On the other hand, if the user information registration and update program 122 determines in step S102 that the received data is the accident data 31 or the license data 32, it repeats steps S106 to S107 for the target data determined in step S102. In step S106, the user information registration and update program 122 determines whether the target data determined in step S102 has already been registered. If the target data has already been registered (step S106 YES), the user information registration and update program 122 proceeds to step S107, and if the target data has not already been registered (step S106 NO), it skips step S107. In step S107, the user information registration and update program 122 updates the user management table D100 by reflecting the accident data 31 or the license data 32 determined in step S102 in the record of the corresponding user in the user management table D100.

[0059] On the other hand, when the user information registration and update program 122 judges in step S102 that the received data is the medical checkup data 22, the nursing care data 23, the resident registration data 24, or the pension data 25, it repeats steps S108 to S109 for the number of target data judged in step S102. In step S108, the user information registration and update program 122 judges whether the target data judged in step S102 has been registered. If the data has been registered (step S108 YES), the user information registration and update program 122 moves the process to step S109, and if the data has not been registered (step S108 NO), it skips step S109. In step S109, the user information registration and update program 122 reflects the medical checkup data 22, the nursing care data 23, the resident registration data 24, or the pension data 25 judged in step S102 in the corresponding table of the IN table group to update it.

[0060] (Details of risky driver determination process (step S200)) 13 is a flowchart showing details of the risky driver determination process. The risky driver determination program 123 repeats steps S201 to S204 and S205 for the number of users registered in the user management table D100.

[0061] First, in step S201, the risky driver determination program 123 refers to the driver's license status D109 in the user management table D100 to determine whether the target user has a license. If the target user has a license (step S201 YES), the risky driver determination program 123 proceeds to step S202, and if the target user does not have a license (step S201 NO), the risky driver determination program 123 proceeds to step S203.

[0062] In step S202, the risky driver determination program 123 refers to the accident history D111 of the user management table D100 and determines whether the target user has one or more accidents in his / her accident history. If the target user has one or more accidents in his / her accident history (YES in step S202), the risky driver determination program 123 proceeds to step S204, and if the number of accidents is zero (NO in step S202), the risky driver determination program 123 proceeds to step S205.

[0063] On the other hand, in step S203, the risky driver determination program 123 refers to the license surrender flag D110 in the user management table D100 to determine whether the target user has surrendered the license. If the target user has surrendered the license (step S203 YES), the risky driver determination program 123 proceeds to step S204, and if the target user has not surrendered the license (step S203 NO), the risky driver determination program 123 proceeds to step S205.

[0064] In step S204, the dangerous driver determination program 123 sets all of the dangerous driver flags of the target users in the IN table group to "TRUE." On the other hand, in step S205, the dangerous driver determination program 123 sets all of the dangerous driver flags of the target users in the IN table group to "FALSE."

[0065] Since it can be assumed that an elderly person who has already surrendered their driver's license has done so for health reasons (because they judged driving to be dangerous), the process proceeds from step S203 YES to step S204, where the dangerous driver flag is set to "TRUE." However, since the elderly person no longer holds a license, the driving risk level is not judged.

[0066] (Details of the elderly support group registration / update process (step S300)) 14 is a flow chart showing details of the elderly support group registration and update process. The elderly support group registration and update program 124 repeats steps S301 to S302 and S303 for the number of groups registered in the elderly support group management table D600.

[0067] First, in step S301, the elderly support group registration and update program 124 determines whether data of the target elderly support group has already been registered in the elderly support group management table D600. The data of the target elderly support group is included in the update data received in step S7 (FIG. 11) as an update difference of the elderly support group data (not shown). If the target elderly support group has already been registered in the elderly support group management table D600 (YES in step S301), the elderly support group registration and update program 124 proceeds to step S302, and if the target elderly support group has not already been registered (NO in step S301), the elderly support group registration and update program 124 proceeds to step S303.

[0068] In step S302, the elderly support group registration / update program 124 updates the elderly support group management table D600 with the data of the target elderly support group, while in step S303, the elderly support group registration / update program 124 newly registers the data of the target elderly support group in the elderly support group management table D600.

[0069] (Details of Risky Driver Statistical Analysis Process (Step S400)) FIG. 15 is a flowchart showing the details of the dangerous driver statistical analysis process.

[0070] First, in step S401, the dangerous driver statistical analysis program 125 counts the total number of users whose dangerous driver flags are set to "TRUE" in the IN tables, excluding overlaps between the tables.

[0071] Next, the dangerous driver statistics analysis program 125 repeats steps S402 to S406, S407, and S408 the number of times corresponding to the determination condition IDs registered in the dangerous driver statistics management table D700.

[0072] In step S402, the dangerous driver statistical analysis program 125 calculates the number of dangerous drivers and the cumulative ratio that satisfy the judgment condition identified by the corresponding judgment condition ID, and registers them in the distribution D704 and the proportion D705, respectively.

[0073] The dangerous driver statistical analysis program 125 performs the following processes of steps S403 to S406, S507, and S408 for each judgment item.

[0074] In step S403, the dangerous driver statistical analysis program 125 judges whether the distribution of dangerous drivers complies with the Pareto Law. Specifically, the dangerous driver statistical analysis program 125 judges whether the distribution D704 is the most common judgment result D703 alone and the proportion D705 is a predetermined proportion (e.g., 80%) or more when the judgment results D703 of the same judgment item D702 are arranged in descending order of the distribution D704 of dangerous drivers. If the distribution of dangerous drivers complies with the Pareto Law (step S403 YES), the dangerous driver statistical analysis program 125 moves the process to step S404, and if it does not comply with the Pareto Law (step S403 NO), the dangerous driver statistical analysis program 125 moves the process to step S409.

[0075] In step S404, the dangerous driver statistical analysis program 125 sets "TRUE" to the risk level determination flag D706 corresponding to the determination item D702 conforming to the Pareto principle.

[0076] Next, in step S404, the dangerous driver statistical analysis program 125 executes ABC analysis to determine whether the cumulative ratio corresponds to rank A (0-80%), rank B (81-95%), or rank C (96-100%). The dangerous driver statistical analysis program 125 transfers processing to step S406 when the cumulative ratio corresponds to rank A. The dangerous driver statistical analysis program 125 transfers processing to step S407 when the cumulative ratio corresponds to rank B. The dangerous driver statistical analysis program 125 transfers processing to step S408 when the cumulative ratio corresponds to rank C.

[0077] In step S406, the dangerous driver statistical analysis program 125 sets the added risk index D707 corresponding to the judgment result D703 of the corresponding judgment item D702 to "5". In step S407, the dangerous driver statistical analysis program 125 sets the added risk index D707 corresponding to the judgment result D703 of the corresponding judgment item D702 to "1". In step S408, the dangerous driver statistical analysis program 125 sets the added risk index D707 corresponding to the judgment result D703 of the corresponding judgment item D702 to "0".

[0078] On the other hand, in step S409, the dangerous driver statistical analysis program 125 sets "FALSE" to the risk determination flag D706 corresponding to the determination item D702 that does not conform to the Pareto principle.

[0079] Incidentally, simply by checking the judgment items D702 of the elderly driver user for which the danger judgment flag D706 has been set in step S404 or S409, it is possible to determine whether the elderly driver is likely to engage in dangerous driving.

[0080] (Example of extraction of risk assessment conditions) Next, the processing of steps S402 and S403 (FIG. 15) will be described with reference to FIG. 16A to FIG. 16E. FIG. 16A to FIG. 16E are diagrams showing an example of extraction of risk level determination conditions. In FIG. 16A to FIG. 16E, for ease of explanation, the total number of dangerous drivers counted in step S401 (FIG. 15) will be described as 100.

[0081] 16A shows a case where the judgment item D702 is "maintaining a sitting position" (judgment condition ID_D701="D31001"). "Maintaining a sitting position" is an item included in the care information table D300, and indicates the degree of ability of the user to maintain a sitting position. Table 511 shows a distribution D704 of the number of risky drivers for each of the judgment results D703 for the judgment item D702 "maintaining a sitting position" of "cannot", "sometimes can", "neither can nor can", "sometimes can not", and "can" in step S402.

[0082] As can be seen from the Pareto chart 512, the distribution D704 in table 511 has a ratio D705 of 80% or more for the most common judgment result D703 "cannot" alone. In other words, it is determined in step S403 that the distribution D704 conforms to the Pareto law, and is therefore selected as a risk judgment condition. This suggests that elderly drivers who cannot sit for long periods of time tend to be more likely to cause accidents. In addition, an additive risk index D707 is set according to the rank determined in step S405 for the cumulative ratio of each judgment result D703.

[0083] 16B shows a case where the judgment item D702 is "simple cooking." "Simple cooking" is an item included in the care information table D300, and indicates the degree of the user's ability to perform simple cooking. Table 521 shows, in a distribution D704, the number of risky drivers for each of the judgment results D703 for the judgment item D702 "simple cooking" - "cannot do it," "sometimes can do it," "neither can nor can," "sometimes can do it," and "can do it" - in step S402.

[0084] As can be seen from the Pareto chart 522, the distribution D704 of the table 521 has a ratio D705 of 80% or more for the most common judgment result D703 "cannot do" alone. In other words, it is determined in step S403 that the distribution D704 conforms to the Pareto law, and is therefore selected as a risk judgment condition. This suggests that elderly drivers who cannot do simple cooking tend to be more likely to have driving accidents, and that there is a correlation between driving skills and cooking skills. In addition, the cumulative ratio of each judgment result D703 is set to an additive risk index D707 according to the rank determined in step S405.

[0085] 16C shows a case where the judgment item D702 is "suddenly shouting loudly." "Suddenly shouting loudly" is an item included in the care information table D300, and indicates the degree of the user's emotion control ability. Table 531 shows a distribution D704 of the number of dangerous drivers for each of the judgment results D703 "often," "occasionally," "neither," "occasionally," and "none" for the judgment item D702 "suddenly shouting loudly" in step S402.

[0086] As can be seen from the Pareto chart 532, the distribution D704 of the table 531 has a ratio D705 of 80% or more for the most frequent judgment result D703 "frequently" alone. In other words, it is determined in step S403 that the distribution D704 conforms to the Pareto law, and is therefore selected as a risk judgment condition. This suggests that elderly drivers who tend to suddenly shout loudly tend to be more likely to cause driving accidents, and that there is a correlation between driving skills and emotional control. In addition, the cumulative ratio of each judgment result D703 is set to an additive risk index D707 according to the rank determined in step S405.

[0087] 16D shows a case where the judgment item D702 is "heart rate". "Heart rate" is an item included in the medical checkup result table D200, and indicates one aspect of the user's health condition. Table 541 shows a distribution D704 of the number of risky drivers for each of the judgment results D703 of the judgment item D702 "heart rate" - "30 bpm or less", "30 to 60 bpm", "60 to 90 bpm", "90 to 120 bpm", and "120 bpm or more" - in step S402.

[0088] As can be seen from the Pareto chart 542, the distribution D704 in table 541 does not have a ratio D705 of 80% or more when the most common judgment result D703 "60 to 90 bpm" is used alone. In other words, since it is not judged in step S403 that the distribution D704 complies with the Pareto principle, it is not selected as a risk judgment condition. This suggests that there is no correlation between heart rate and driving skill. Also, since it does not comply with the Pareto principle, all of the added risk indexes D707 are set to "0".

[0089] 16E shows a case where the judgment item D702 is “excretion, urination.” Table 551 shows the number of risky drivers in each of the judgment results D703 of “cannot do it”, “can sometimes do it”, “can’t say either way”, “can sometimes do it”, and “can do it” in step S402 for the judgment item D702 “excretion, urination”.

[0090] As can be seen from the Pareto chart 552, the distribution D704 in table 551 does not have a ratio D705 of 80% or more for the most common judgment result D703 "cannot" alone. In other words, since it is not determined in step S403 that the distribution D704 complies with the Pareto principle, it is not selected as a risk judgment condition. This suggests that whether or not one can excrete or urinate on one's own is not correlated with driving skill. Also, since it does not comply with the Pareto principle, all of the added risk indexes D707 are set to "0".

[0091] (Details of Driving Risk Addition Process (Step S500)) 17 is a flowchart showing details of the driving risk level addition process. The driving risk level addition program 126 repeats steps S501 to S505 for the number of users registered in the user management table D100. The driving risk level addition program 126 also repeats steps S502 to S505 for the number of judgment condition IDs D701 registered in the risky driver statistics management table D700.

[0092] First, in step S501, the driving risk level addition program 126 determines whether the target user registered in the user management table D100 holds a license by referring to the driver's license status D109. If the target user holds a license (step S501 YES), the driving risk level addition program 126 proceeds to step S502, and if the target user does not hold a license (step S501 NO), the driving risk level addition program 126 proceeds to the next target user in the loop of steps S501 to S505.

[0093] In step S502, the driving risk addition program 126 judges whether the risk judgment flag D706 of the target judgment condition ID_D701 is "TRUE". If the risk judgment flag D706 is "TRUE" (step S502 YES), the driving risk addition program 126 proceeds to step S503. On the other hand, if the risk judgment flag D706 is "FALSE" (step S502 NO), the driving risk addition program 126 proceeds to the next target judgment condition ID_D701 in the loop of steps S502 to S505.

[0094] In step S503, the driving risk addition program 126 judges whether the target user's information (registered in the IN tables) matches the judgment condition corresponding to the target judgment condition ID_D 701. Here, "target user's information (registered in the IN tables)" refers to the column of the IN tables that is the judgment condition.

[0095] If there is a match with the judgment condition corresponding to the target judgment condition ID_D701 among the target user information (registered in the IN table group) (YES in step S503), the driving risk level addition program 126 proceeds to step S504. On the other hand, if there is no match (NO in step S503), the driving risk level addition program 126 proceeds to the process of the next target judgment condition ID_D701 in the loop of steps S502 to S505.

[0096] In step S504, the driving risk addition program 126 adds the added risk index D707 of the target judgment condition to the total risk index D804 of the relevant user in the driving risk judgment table D800. Next, in step S505, the driving risk addition program 126 registers, for example, up to three target judgment conditions in the judgment grounds D806, S807, and S808 of the driving risk judgment table D800. The number of registered judgment conditions is not limited to three, and no limit may be set. When step S505 ends, the driving risk addition program 126 moves the process to the next target judgment condition ID_D701 in the loop of steps S502 to S505.

[0097] (Details of Driving Risk Assessment and Notification Processing (Step S600)) 18 is a flowchart showing details of the driving risk level determination and notification process. The driving risk level determination and notification program 127 repeats steps S601 to S610 for the number of users registered in the user management table D100.

[0098] In step S601, the driving risk determination / notification program 127 determines the value of the total risk index D804 of the target user. The driving risk determination / notification program 127 transfers the process to step S602 when the value of the total risk index D804 of the target user is 5 or more. The driving risk determination / notification program 127 transfers the process to step S603 when the value of the total risk index D804 of the target user is 3 or 4. The driving risk determination / notification program 127 transfers the process to step S604 when the value of the total risk index D804 of the target user is 1 or 2. The driving risk determination / notification program 127 transfers the process to step S605 when the value of the total risk index D804 of the target user is 0. Note that the criteria for determining the value of the total risk index D804 of the target user in step S601 ("5 or more", "3, 4", "1, 2", "0") are merely examples.

[0099] In step S602, the driving risk level judgment and notification program 127 sets the driving risk level judgment result D805 to "driving is in a very dangerous state". In step S603, the driving risk level judgment and notification program 127 sets the driving risk level judgment result D805 to "driving is in a very dangerous state". In step S604, the driving risk level judgment and notification program 127 sets the driving risk level judgment result D805 to "driving is in a dangerous state". In step S605, the driving risk level judgment and notification program 127 sets the driving risk level judgment result D805 to "driving requires caution". Steps S602 to S605 are processes for replacing the total risk level index D804 with an expression that allows a person to intuitively grasp the driving risk level.

[0100] When steps S602 to S605 are completed, the driving risk assessment / notification program 127 advances the process to step S606.

[0101] In step S606, the driving risk level judgment / notification program 127 acquires judgment conditions corresponding to the judgment condition ID_D701 stored in the judgment basis IDs D806 to S808 of the driving risk level judgment table D800.

[0102] Next, in step S607, the driving risk level judgment / notification program 127 judges whether the driving risk level judgment result D805 has changed since the previous notification. If the driving risk level judgment result D805 has changed since the previous notification, the driving risk level judgment / notification program 127 proceeds to step S608, and if not, proceeds to the next target user in the loop of steps S601 to S610.

[0103] Next, in step S608, the driving risk assessment / notification program 127 refers to the elderly support group management table D600 and determines whether there is an elderly support group available to the target user. For example, it determines whether there is an elderly support group that provides mobility support available to the target user whose driving risk assessment result D805 is "very dangerous driving" or "very dangerous driving" at the current address. If there is an elderly support group available to the target user (step S608 YES), the driving risk assessment / notification program 127 proceeds to step S609, and if there is not (step S608 NO), it proceeds to step S601.

[0104] In step S609, the driving risk level assessment / notification program 127 registers the organization ID of the organization determined to be available in step S608 in the driving risk level assessment table D800. Next, in step S610, the driving risk level assessment / notification program 127 notifies the target user's email address of the driving risk level assessment result, the assessment conditions (including the reasons), available elderly support organizations, etc. The terminal that receives the email sent to the email address is an example of a contact means for each elderly driver.

[0105] By performing notification in step S610 only for elderly drivers whose driving risk assessment result D805 has changed since the previous notification in step S607, unnecessary notifications are reduced, the load of notification processing is lightened, and the annoyance for elderly drivers is reduced.

[0106] Furthermore, by notifying the elderly driver of the judgment condition (including the basis) in step S610, the elderly driver knows the basis for being judged to be a dangerous driver and can take appropriate measures according to the basis.

[0107] (Total danger index D804 and driving danger assessment results) 19A to 19C are diagrams showing examples of a total risk index D804 and a driving risk assessment result D805. As shown in Fig. 19A to 19C, in step S504 (Fig. 17), the added risk indexes D707 are summed up for each user (elderly driver) to calculate the total risk index D804. Then, in steps S601 to S605 (Fig. 18), the driving risk assessment result D805 is determined.

[0108] (Effects of the embodiment) In the above-described embodiment, ABC analysis based on the Pareto principle is used to determine elderly drivers who are at high driving risk based on the consistency between the characteristics indicated in the personal information items, such as the health condition of the dangerous driver, and the characteristics indicated in the personal information items of the driver to be determined.

[0109] Therefore, according to the above-mentioned embodiment, the elderly driver can automatically determine the driving risk based on the data held by the local government or the police, without taking a test or taking a course, or registering data, and can know promptly and in a timely manner whether his / her cognitive function or physical function is a problem for driving. In addition, the data on the health condition that is the input for the analysis is the results of annual health checkups and records of regular home care visits by care managers and doctors, so that the judgment can be made from data that is close to the current health condition (high real-timeness).

[0110] In addition to factors that can be easily inferred to affect driving skills, such as "sitting position maintenance," "eyesight," and "hearing," data analysis can also extract special factors that cannot be inferred to affect driving skills at first glance. For example, diagnostic items such as "simple cooking" and "suddenly shouting loudly" may not seem to be related to driving skills at first glance. However, there may be hidden factors such as "people who lack the skills to simultaneously perform two or more tasks required for cooking are prone to operating errors" and "people who cannot control their emotions, such as suddenly shouting loudly, are prone to dangerous driving." In this embodiment, such hidden factors can be extracted.

[0111] In addition to encouraging elderly drivers who are judged to be "highly dangerous drivers" to surrender their licenses, the system also matches them with available volunteer groups and local welfare officers. Therefore, even elderly people living in rural areas who have no supermarkets or pharmacies near their homes and for whom driving is essential can reduce the inconvenience of life after surrendering their licenses by using groups that provide services such as designated driving and shopping assistance. This promotes voluntary license surrender and reduces car accidents caused by elderly drivers.

[0112] Moreover, according to this embodiment, by introducing the system in local governments (especially in rural areas where there are many elderly drivers), it is possible to contribute to reducing automobile accidents caused by elderly drivers. In addition, by linking information on dangerous drivers from multiple local governments and using it as input for analysis, more reliable judgments can be made.

[0113] (Hardware configuration of computer 1000) 20 is a diagram showing an example of a hardware configuration of a computer 1000. The computer 1000 realizes various systems, servers, devices, terminals, and the like (including an elderly driver driving risk assessment system 1, a local government system 2, a police system 3, a terminal 4, a WEB server 11, an AP server 12, and a DB server 13) by executing a predetermined program.

[0114] The computer 1000 includes a processor 1001 including a CPU, a main memory device 1002, an auxiliary memory device 1003, a network interface 1004, an input device 1005, and an output device 1006, all of which are interconnected via an internal communication line 1007 such as a bus.

[0115] The processor 1001 controls the overall operation of the computer 1000. The main memory device 1002 is composed of, for example, a volatile semiconductor memory, and is used as a work memory for the processor 1001. The auxiliary memory device 1003 is composed of a large-capacity nonvolatile memory device such as a hard disk device, an SSD (Solid State Drive), or a flash memory, and is used to store various programs and data for long periods of time.

[0116] An executable program 1003a stored in the auxiliary storage device 1003 is loaded into the main storage device 1002 when the computer 1000 is started up or when necessary, and is executed by the processor 1001. This realizes the various systems, servers, devices, terminals, etc. according to the above-mentioned embodiments.

[0117] The executable program 1003a may be recorded on a non-transitory recording medium, read from the non-transitory recording medium by a medium reading device, and loaded into the main storage device 1002. Alternatively, the executable program 1003a may be obtained from one or more external computers via a network, and loaded into the main storage device 1002. The executable program 1003a may be divided into multiple programs as appropriate.

[0118] The network interface 1004 is an interface device for connecting the computer 1000 to each network in the system or for communicating with other computers. The network interface 1004 is, for example, configured with a NIC (Network Interface Card) for a wired LAN (Local Area Network) or a wireless LAN.

[0119] The input device 1005 is composed of a keyboard, a pointing device such as a mouse, and the like, and is used by the user to input various instructions and information to the computer 1000. The output device 1006 is composed of, for example, a display device such as a liquid crystal display, and an audio output device such as a speaker, and is used to present necessary information to the user when necessary.

[0120] Although the embodiments of the present disclosure have been described above in detail, the present disclosure is not limited to the above-described embodiments, and various modifications can be made without departing from the gist of the present disclosure. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and are not necessarily limited to those having all of the configurations described. In addition, it is possible to add, delete, or replace some of the configurations of the above-described embodiments with other configurations. In addition, the execution order of each process described in the above-described embodiments may be appropriately changed as long as the processing result does not change.

[0121] Furthermore, the above-mentioned configurations, functional units, processing units, etc. may be realized in part or in whole by hardware, for example, by designing them as integrated circuits. The above-mentioned configurations, functions, etc. may be realized in software by a processor interpreting and executing a program that realizes each function. Information such as the program, table, file, etc. that realizes each function can be stored in a memory, a storage device such as an HDD or SSD, or a recording medium such as an IC card, an SD card, or a DVD.

[0122] In addition, in each of the above figures, the control lines and information lines are shown as those considered necessary for the explanation, and do not necessarily show all the control lines and information lines in the actual implementation. For example, it may be considered that almost all the components are actually connected to each other.

[0123] The above-mentioned elderly driver driving risk assessment system 1, local government system 2, police system 3, terminal 4, WEB server 11, AP server 12, and DB server 13 are merely examples of the arrangement of the functions and data. The arrangement and integration and distribution of the functions and data can be changed to an optimal form in terms of the performance of the hardware and software, processing efficiency, communication efficiency, etc. [Explanation of symbols]

[0124] S: Overall system, 1: Elderly driver driving risk assessment system, 5: Elderly support organization, 6: User (elderly driver), 13: DB server, 21: User data, 22: Medical checkup data, 23: Nursing care data, 24: Resident registration data, 25: Pension data, 123: Dangerous driver assessment program, 125: Dangerous driver statistical analysis program, 126: Driving risk addition program, 127: Driving risk assessment and notification program, D100: User management table, D200: Medical checkup result table, D300 : Nursing care information table, D400: Resident registration linkage table, D500: Pension receipt table, D600: Elderly support organization management table, D700: Dangerous driver statistics management table, D704: Distribution, D705: Proportion, D707: Added danger index, D800: Driving danger assessment table, D804: Total danger index, D805: Driving danger assessment result, D806, D807, D808: Assessment basis, 1000: Computer, 1001: Processor, 1002: Main memory device, 1003: Auxiliary memory device.

Claims

1. A driving risk assessment system for assessing a driving risk level representing a risk level of an elderly driver causing a car accident by driving a car, comprising: The driving risk determination system includes a processor, a memory, and a storage unit, The storage unit is The elderly driver who has a history of causing a car accident or a history of returning his / her driver's license is regarded as a dangerous driver who is likely to cause a car accident, and for each elderly driver, dangerous driver information indicating whether or not the elderly driver corresponds to the dangerous driver is associated with personal information for each elderly driver, including medical examination result information indicating the health condition of the elderly driver, nursing care information related to nursing care certification, resident information related to resident registration in a local government, or pension receiving information, and managed. The processor, For each item of the personal information, it is determined to which of a plurality of determination results of the item the elderly driver who corresponds to the dangerous driver corresponds; For each of the items, it is determined whether the determination result in which the elderly driver is distributed at a cumulative ratio equal to or greater than a predetermined value matches the Pareto law, The item that matches the Pareto principle is determined to correspond to a risk level determination condition for determining whether the elderly driver is a dangerous driver. A driving risk assessment system comprising:

2. The driving risk assessment system according to claim 1, The processor, For the items determined to meet the risk determination conditions, an added risk index is assigned, which is a score according to the cumulative ratio for the plurality of determination conditions. A driving risk assessment system comprising:

3. The driving risk assessment system according to claim 2, The processor, Calculating a total risk index, which is the sum of the added risk indexes for the items determined to meet the risk determination condition for each elderly driver; The driving risk level is determined for each of the elderly drivers based on the total risk index. A driving risk assessment system comprising:

4. The driving risk assessment system according to claim 3, The processor, The driving risk level is notified to a contact means for each elderly driver. A driving risk assessment system comprising:

5. The driving risk assessment system according to claim 4, The storage unit is Manage the driving risk level notified to the contact means for each elderly driver; The processor, For each of the elderly drivers, Determine whether the driving risk level currently determined has changed from the driving risk level previously notified; If the driving risk level determined this time has changed from the driving risk level notified previously, the driving risk level determined this time is notified to the communication means. A driving risk assessment system comprising:

6. The driving risk assessment system according to claim 5, The storage unit is Manage the item to which the added risk index added to the driving risk is assigned together with the driving risk as a basis for determining the driving risk; The processor, The basis for the determination is notified to the communication means. A driving risk assessment system comprising:

7. The driving risk assessment system according to claim 4, The storage unit is Manage support group information regarding support groups that can provide support to the elderly driver according to the driving risk level; The processor, For each of the elderly drivers, Identifying the support organization capable of supporting the elderly driver according to the driving risk level based on the support organization information; Notifying the contact means of information regarding the identified support organization A driving risk assessment system comprising:

8. A driving risk assessment method implemented by a driving risk assessment system for assessing a driving risk level representing a risk level of an elderly driver causing a car accident by driving a car, comprising: The driving risk determination system includes a processor, a memory, and a storage unit, The storage unit is The elderly driver who has a history of causing a car accident or a history of returning his / her driver's license is regarded as a dangerous driver who is likely to cause a car accident, and for each elderly driver, dangerous driver information indicating whether or not the elderly driver corresponds to the dangerous driver is associated with personal information for each elderly driver, including medical examination result information indicating the health condition of the elderly driver, nursing care information related to nursing care certification, resident information related to resident registration in a local government, or pension receiving information, and managed. The processor, For each item of the personal information, it is determined to which of a plurality of determination results of the item the elderly driver who corresponds to the dangerous driver corresponds; For each of the items, it is determined whether the determination result in which the elderly driver is distributed at a cumulative ratio equal to or greater than a predetermined value matches the Pareto law, The item that matches the Pareto principle is determined to correspond to a risk level determination condition for determining whether the elderly driver is a dangerous driver. A driving risk assessment method comprising each process.

9. The driving risk determination method according to claim 8, The processor, For the items determined to meet the risk determination conditions, an added risk index is assigned, which is a score according to the cumulative ratio for the plurality of determination conditions. A driving risk assessment method comprising the steps of:

10. A driving risk assessment method according to claim 9, The processor, Calculating a total risk index, which is the sum of the added risk indexes for the items determined to meet the risk determination condition for each elderly driver; The driving risk level is determined for each of the elderly drivers based on the total risk index. A driving risk assessment method comprising each process.

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