JP7227578B2 - Dangerous driving risk information output system and dangerous driving risk information output program - Google Patents

Description

The present invention relates to a dangerous driving risk information output system and a dangerous driving risk information output program for reducing traffic accidents.

In recent years, there has been known a traffic safety management system that uses an acceleration sensor to determine sudden acceleration and sudden steering (see, for example, Patent Document 1).

JP 2019-22022 A

By the way, in recent years, reverse driving and tailgating by elderly people have become social problems, and observance of road traffic laws and prevention of dangerous driving have become urgent needs.

However, although the system using the acceleration sensor can determine the state of driving, it does not determine compliance with the road traffic law, which leads to serious accidents. It is known that dangerous driving that leads to accidents depends on driving habits and the ability to judge situations. A system using an acceleration sensor only senses a person's behavior as an output. It is not possible to judge whether to avoid a dangerous situation caused by excessive speed or the like.

Therefore, the present invention provides a dangerous driving risk information output system that can contribute to reducing traffic accidents by detecting road traffic law violations with high accuracy based on vehicle position information and determining dangerous driving risks, and , aims to provide a dangerous driving risk information output program.

The present invention includes an acquisition unit for acquiring travel information including location information of a target vehicle, and at least one or more traffic rules applied to the location information from traffic rules managed based on an address or latitude/longitude. Statistical information that is extracted, determines whether or not the target vehicle violates the traffic rules based on the extracted traffic rules and the travel information, and associates the presence or absence of a plurality of violations determined for the driver of the target vehicle with each location information. a control unit that creates dangerous driving risk information representing the driver's cognitive function score or driving level score based on the statistical information; an output unit that outputs the dangerous driving risk information; A dangerous driving risk information output system is provided.

According to such a configuration, the "dangerous driving risk information" is created based on the position information detected with high accuracy, so that the driver of the target vehicle, family members, etc. can notice the deterioration of cognitive function. We can expect the effect of reducing traffic accidents by encouraging the relatives of children to refrain from driving.

Further, when the cognitive function score is created as the dangerous driving risk information, the control unit determines whether the cognitive function score is on an upward trend, and determines that the cognitive function score is on an upward trend. If so, it is preferable that the output unit outputs the alert information as a part of the dangerous driving risk information.

According to such a configuration, it is possible to notice that the cognitive function is declining by the "alert information", so the effect of reducing traffic accidents can be expected.

In addition, it is preferable that the control unit calculates the cognitive function score based on at least one traffic rule violation among non-stop violations, non-stop violations at railroad crossings, one-way traffic violations, and right/left turn prohibition violations.

According to such a configuration, a highly reliable cognitive function score is created based on the traffic rules that tend to cause noticeable deterioration in cognitive function.

Further, it is preferable that the travel information includes distance information regarding the distance between the target vehicle and surrounding vehicles, and the control unit calculates the cognitive function score in consideration of the distance information as well.

According to such a configuration, problems such as inter-vehicle distance, which are not included in the traffic rules but are likely to lead to accidents, are taken into consideration, so that the effect of reducing traffic accidents can be expected.

Further, when the driving level scores of a plurality of drivers are created as the dangerous driving risk information, the control unit displays a list on the display unit of the receiving terminal in descending order of the excellent drivers with the highest driving level scores. It is preferable to issue a command to

As a result, for example, when the present invention is used for a shared ride, it is expected that unless the driver has a high driving level score, that is, an excellent driver based on compliance with the road traffic law, he or she will not be able to participate in the shared ride. It can contribute to preventing social problems caused by accidents in new business models in the future.

Further, when the driving level score is generated as the dangerous driving risk information, the control unit extracts the corresponding time of the drive recorder on the display unit of the receiving terminal when the driving level score exceeds a predetermined threshold. It is preferable to command the image to be displayed.

As a result, it is possible to specifically grasp what kind of danger and risk existed from the image.

Moreover, it is preferable that the accumulation unit creates the statistical information based on position information measured by a position information positioning system with an error of 1.5 m or less.

According to such a configuration, considering that the average lane width is about 3 m, the distance from the center of the vehicle to the boundary with the oncoming lane is about 1.5 m. Even with some degree of error, in most cases the vehicle stayed within the lane in which it actually traveled, creating "statistical information" that was erroneously determined to be traveling in the next lane or side road. is suppressed.

Moreover, it is preferable that the accumulation unit creates the statistical information based on sub-meter level position information.

According to such a configuration, creation of erroneously determined "statistical information" is further suppressed.

According to another aspect of the present invention, there is provided a program to be installed in a computer, comprising steps of acquiring travel information including location information of a target vehicle; Extract at least one or more traffic rules applied to the location information from among, determine whether or not the target vehicle violates based on the extracted traffic rules and the travel information, and determine the driver of the target vehicle creating and accumulating statistical information that associates the presence or absence of a plurality of said violations with each location information; and creating dangerous driving risk information representing the cognitive function score or driving level score of the driver based on the statistical information. and a step of outputting the dangerous driving risk information.

According to the dangerous driving risk information output system and the dangerous driving risk information output program of the present invention, road traffic law violations are detected with high accuracy based on vehicle position information, and dangerous driving risks are determined to prevent traffic accidents. It becomes possible to contribute to reduction.

1 is an overall diagram of a dangerous driving risk information output system according to an embodiment of the present invention; Explanatory drawing of the latitude and longitude of the traffic rule application position according to the embodiment of the present invention Flowchart until outputting "dangerous driving risk information" according to the embodiment of the present invention Explanatory diagram of error in position information according to the embodiment of the present invention

A dangerous driving risk information output system 1 according to an embodiment of the present invention will be described below with reference to FIGS. 1 to 4. FIG.

As shown in FIG. 1, a dangerous driving risk information output system 1 is implemented between a target vehicle 2, a dangerous driving risk information output device 3, and a receiving terminal 4. 3 creates "statistical information" on traffic rule violations based on multiple pieces of position information acquired from the target vehicle 2, and then collects "dangerous driving risk information" for preventing traffic accidents of the target vehicle 2 into "statistical data". information” and output to the receiving terminal 4.

In this embodiment, the dangerous driving risk information output device 3 is installed in a communication center or the like, and communication between the target vehicle 2 and the receiving terminal 4 is performed wirelessly.

As shown in FIG. 1, the target vehicle 2 is equipped with a GPS device 21 capable of detecting its own position, and the position information about its own position is associated with the time information, which is the detection time, to generate dangerous driving risk information. It is configured to be able to transmit to the output device 3 . As the position information, point information composed of real-time latitudes and longitudes of the target vehicle 2, line information indicating a driving route composed of a plurality of latitudes and longitudes, and the like can be considered.

Positional information preferably has an error of 1 m or less. To achieve such accuracy, it is conceivable to use sub-meter class satellite signals from Michibiki (Quasi-Zenith Satellite System). In the case of one lane on one side, considering the case where the width of the road on one side is 3 m, the distance from the center of the vehicle to the boundary with the oncoming lane is about 1.5 m. If a GPS device is installed in the center of the vehicle, using a GPS device with an error of at least 1.5 m or less will clarify which lane the vehicle is traveling. In other words, it becomes possible to determine reverse running, which has become a problem in recent years. Any positioning information positioning system other than Michibiki may be used as long as it realizes this. Due to problems such as multipath, this accuracy may not be as high as the actual catalog spec. However, considering the time axis, for example, 18 points of position information can be obtained by sampling every 10 seconds while traveling for 3 minutes. If the standard deviation between the approximated curve and the plot is within 1.5m, it is possible to almost correctly determine which lane the vehicle is traveling in. can. Therefore, if the accuracy is within 1.5 m according to the catalog specifications, it can be applied to this system.

In addition, the target vehicle 2 further includes a vehicle-side transmission section 22 .

The vehicle-side transmission unit 22 can transmit travel information detected by a device other than the GPS device 21 to the dangerous driving risk information output device 3 . Driving information includes information from various sensors installed in moving vehicles that can determine driving conditions (e.g., information from acceleration sensors, right and left turn information from blinkers, inter-vehicle distances and signs detected by images and radar, etc.). distance, etc.). The vehicle-side transmission unit 22 also transmits the driver identifier of the driver of the target vehicle 2 .

It is preferable that the position information, the driving information, and the driver identifier described above are constantly transmitted at least while the target vehicle 2 is driving.

As shown in FIG. 1 , the dangerous driving risk information output device 3 includes an acquisition unit 31 , an accumulation unit 32 , a reception unit 33 , a control unit 34 and an output unit 35 . Although the acquisition unit 31 and the reception unit 33 are described as separate components for the sake of convenience, they may of course be realized with the same hardware configuration. It is a so-called general communication infrastructure. The hardware configuration of other components can also be arbitrarily configured.

The acquisition unit 31 can acquire the position information of the target vehicle 2 transmitted from the GPS device 21 and the travel information and driver identifier transmitted from the vehicle-side transmission unit 22 .

The storage unit 32 pre-stores traffic rules managed based on addresses or latitude/longitude, and extracts at least one or more traffic rules applied to the acquired position information from the traffic rules. , the presence or absence of violation of the target vehicle 2 is determined based on the extracted traffic rules and travel information. Then, "statistical information" that associates the presence or absence of a large number of violations obtained from the target vehicle 2 with each positional information is created and accumulated. It should be noted that not only the violation but near-miss information one step before the violation may be associated with each position information and accumulated as "statistical information". In other words, any information may be used as long as it is information for determining traffic risk.

Traffic rules pre-stored in the storage unit 32 include rules indicated by road signs (regulatory signs, direction signs, auxiliary signs), road signs (regulatory signs, direction signs), etc., and these rules are applied. The latitude and longitude of the rule application position described in the decision-making data issued by the public safety commission, police station, etc. can be used. If the data based on the public safety commission, police station, etc. is an address, the information obtained by converting the address into latitude and longitude is stored in the storage unit 32 . Data based on public safety commissions, police stations, etc. are often described in terms of addresses, and with only these addresses, the process of determining the traffic rules applied to the position of the vehicle becomes complicated. For this reason, it is preferable to convert the address into latitude and longitude and register it in the storage unit 32 in advance, thereby increasing the calculation speed of the system. For example, in the case of receiving information on the current driving position of the vehicle and determining traffic rules that apply almost in real time, it is important to store information as latitude and lightness because real time is important. is important.

These rule-applied positions need not be displayed like a map because they can be handled in terms of data. become something. In FIG. 2, the latitudes and longitudes of a plurality of rule-applied positions to which a predetermined speed limit is applied form a point set range A, and the latitudes and longitudes of a plurality of rule-applied positions to which a pause is applied form a point set range B , and the latitude and longitude of a plurality of rule application positions to which parking prohibition is applied form a point set range C.

In the present embodiment, not only the latitude/longitude that exactly matches the latitude/longitude of the rule application position to which the predetermined traffic rule is applied, but also all the latitude/longitude included in each point set range are subject to the predetermined traffic rule. is regarded as the rule application position to which is applied.

As a method of determining whether there is a violation, for example, if it is a speed violation, it is determined as a violation when the speed limit section (point set A in the case of FIG. 2) exceeds a predetermined speed, and even if it is a temporary stop violation For example, it is conceivable to determine as a violation if the vehicle does not stop for a predetermined time several meters before and after the temporary stop position (point set B in the case of FIG. 2).

In addition, the storage unit 32 stores the driver identifier of the registered driver (target vehicle 2) and the output destination identifier of the receiving terminal 4, which is the output destination of the "dangerous driving risk information" of the driver, in association with each other. It is

The receiving unit 33 can receive a request for "dangerous driving risk information" transmitted from the receiving terminal 4, which will be described later.

Based on the “statistical information” accumulated in the accumulation unit 32 , the control unit 34 creates “dangerous driving risk information” representing the cognitive function score or driving level score of the driver of the target vehicle 2 .

"Dangerous driving risk information" represents a cognitive function score or a driving level score, and can be calculated, for example, based on the type and frequency of traffic violations, but does not indicate the risk of dangerous driving for each driver. If so, other methods may be used for calculation. For example, it may be calculated using an acceleration sensor or other information included in the travel information. For example, when an acceleration sensor detects an acceleration equal to or greater than a predetermined value, it may be regarded as dangerous driving and added to the cognitive function score or the driving level score. Alternatively, it may be judged by a combination of various sensors, such as when acceleration to turn a curve is applied before a predetermined time has passed since the blinker is turned on, it is regarded as dangerous driving.

The Cognitive Function Score is based on the assumption that sign recognition and traffic law violations are proportional, and is calculated for each driver independently of other drivers. On the other hand, the driving level score is a relative index compared to other drivers.

In the present embodiment, the cognitive function score is calculated based on at least one traffic rule violation among non-stop violations, non-stop violations at railroad crossings, one-way traffic violations, and right/left turn prohibition violations.

The cognitive function score is calculated by, for example, sigma (weighting for each type×violation rank)/distance traveled. Regarding the violation rank, for example, if speeding is over 10km, violation rank is "1", over 30km is violation rank "3", if there is no stoppage, violation rank is "1", and if stopping correctly, violation rank is "1". Ranking such as "0" is conceivable. As an example of weighting, it is conceivable to set the weight of speeding to "1" and the weight of non-stopping to "5", because non-stopping is more important for judging cognitive function. . If the above 10 km over, 30 km over, and non-stop occurred once each in the running distance of 3 km, the cognitive function score is calculated as (1 × 1 + 3 × 1 + 1 × 5) / 3 It will be done. However, this calculation method is an example, and any other calculation method may be employed.

In addition, the control unit 34 determines whether or not the cognitive function score is on an upward trend when creating the cognitive function score as the “dangerous driving risk information”.

Determination of whether the cognitive function score is on an upward trend can be made, for example, by monitoring changes in the cognitive function score. In this case, on each date, the distribution of cognitive function scores for several days before and after is linearly approximated to obtain the slope, which is used as the slope value for that day. When the slope is viewed over a period of several weeks or several months, for example, when the slope is a positive number, 2/3 of the cognitive function scores tend to increase. It can be judged that there is a decrease in

It is preferable that the control unit 34 further considers the distance to surrounding vehicles to calculate the cognitive function score.

In this case, a threshold for the distance between the target vehicle 2 and the surrounding vehicles (inter-vehicle distance, etc.) is set in advance for each speed of the target vehicle 2, and the distance information regarding the distance between the target vehicle 2 and the surrounding vehicles included in the traveling information is calculated. If the distance is less than the threshold, it is regarded as dangerous driving equivalent to violating traffic rules and is added to the cognitive function score. A weight is also set for the distance, which is multiplied by the violation rank and added to the cognitive function score.

Distance measurement may be performed using distance measurement technology of a monocular camera based on video information from a drive recorder, or general technology such as millimeter wave radar.

The driving level score can be calculated in the same way as the cognitive function score, but in order to clarify the relative position with other drivers, the driving level score is calculated based on all registered drivers or among predetermined drivers. It may be calculated as a deviation value.

The output unit 35 outputs the “dangerous driving risk information” created by the control unit 34 . At this time, since the "dangerous driving risk information" is created in association with the driver identifier of the target vehicle 2, it is output to the receiving terminal 4 having the output destination identifier associated with the driver identifier. Become. The output destination identifier is, for example, an e-mail address.

Further, when the control unit 34 determines that the cognitive function score tends to increase, the output unit 35 outputs the "alert information" as part of the "dangerous driving risk information".

The receiving terminal 4 includes a terminal-side transmitting section 41 , a terminal-side receiving section 42 and a display section 43 . As the receiving terminal 4, a smart phone, a personal computer owned by the driver of the target vehicle 2, a family member, an administrator, etc., an information terminal such as a car navigation system mounted on the target vehicle 2 can be considered. With the aging of society in recent years, more and more elderly people live alone, and especially when their children live far away, it is important to check whether their parents have declining cognitive functions or are not driving in ways that are likely to cause accidents. How do you worry? It is of great social significance for children to know their parents' driving situations from "dangerous driving risk information" or to notice them from "alert information." This is because, in the case of dementia, early treatment can slow down the progression of the disease, or it may be possible to treat it in the future. .

The terminal-side transmission unit 41 can transmit a request for “dangerous driving risk information” to the dangerous driving risk information output device 3 .

The terminal-side receiving unit 42 can receive the “dangerous driving risk information” output from the dangerous driving risk information output device 3 .

The display unit 43 can display the received "dangerous driving risk information". Various methods such as numerical values and graphs are conceivable as display methods. Instead, it is conceivable to visualize and display changes in time series. This makes it easier for the driver of the target vehicle 2, family members, administrators, and the like to notice the possibility of dementia, and is expected to have the effect of prompting a medical examination at a hospital.

Next, the flow up to the output of "dangerous driving risk information" according to the present embodiment will be described using the flowchart of FIG.

First, position information (driving information) is acquired from the target vehicle 2 (S1).

Subsequently, at least one or more traffic rules applied to the position information are extracted (S2), and based on the extracted traffic rules and position information (driving information), it is determined whether or not the target vehicle 2 violates (S3), The presence or absence of violation is associated with location information (S4).

By performing the processing of S1-S4 on the location information and travel information that are transmitted from the target vehicle 2 every moment, and by associating the presence or absence of a large number of violations obtained from them with each location information, "statistical information" will be created.

Subsequently, when "statistical information" is created based on a predetermined number or more of position information (S5: YES), the control unit 34 calculates the cognitive function score or driving level of the driver of the target vehicle 2 based on the "statistical information." "Dangerous driving risk information" representing the score is created (S6).

After that, the processing from S1 to S6 is repeated to keep updating the “statistical information” and the “dangerous driving risk information”.

Then, when the receiving unit 33 receives the request for the “dangerous driving risk information” from the receiving terminal 4 (S7: YES), the output unit 35 outputs the latest “dangerous driving risk information” created at that time. (S8), and the process ends.

The output “dangerous driving risk information” is received by the receiving terminal 4 .

As described above, in the dangerous driving risk information output system 1 according to the present embodiment, "statistical information" is created by associating the presence or absence of a violation of the target vehicle 2 with each position information, and based on the "statistical information", "statistical information" is generated. Dangerous driving risk information” is created and output.

According to such a configuration, the "dangerous driving risk information" is created based on the position information detected with high accuracy, so that the driver of the target vehicle 2, family members, etc. can notice a decline in cognitive function. It is expected that traffic accidents will be reduced by encouraging elderly relatives to refrain from driving.

Further, in the dangerous driving risk information output system 1 according to the present embodiment, when it is determined that the cognitive function score is on an upward trend, the "alert information" is output as part of the "dangerous driving risk information".

According to such a configuration, it is possible to notice that the cognitive function is declining by the "alert information", so the effect of reducing traffic accidents can be expected.

Further, in the dangerous driving risk information output system 1 according to the present embodiment, the cognitive function is based on at least one traffic rule violation among non-stop violations, non-stop violations at railroad crossings, one-way traffic violations, and right/left turn prohibition violations. Calculate the score.

According to such a configuration, a highly reliable cognitive function score is created based on the traffic rules that tend to cause noticeable deterioration in cognitive function.

Further, in the dangerous driving risk information output system 1 according to the present embodiment, the cognitive function score is calculated in consideration of the distance between the target vehicle 2 and surrounding vehicles.

According to such a configuration, problems such as inter-vehicle distance, which are not included in the traffic rules but are likely to lead to accidents, are taken into consideration, so that the effect of reducing traffic accidents can be expected.

Further, in the dangerous driving risk information output system 1 according to the present embodiment, "statistical information" is created based on sub-meter level position information.

According to such a configuration, considering that the average lane width is about 3 m, even if there is an error of about 1 m, as shown in FIG. This prevents the creation of "statistical information" that is erroneously determined to be "running in the next lane or side road". In addition, it is preferable that at least the error is within 1.5 m.

In this way, when conventional GPS information is used, the error is in increments of 10m. Therefore, for example, traffic rules such as no stoppages and no stoppages at railroad crossings can be accurately determined as causing an error of 10m. Although there are cases where it is not possible, the dangerous driving risk information output system 1 according to the present embodiment uses Michibiki (Quasi-Zenith Satellite System) to detect road traffic law violations with high accuracy, so road traffic law violations can be accurately detected. It becomes possible to With an error range of about 1 m, it is possible to determine whether or not the vehicle has stopped at least several meters before or after the stop line.

The dangerous driving risk information output system of the present invention is not limited to the above-described embodiment, and various modifications and improvements are possible within the scope of the claims.

For example, in the above-described embodiment, the dangerous driving risk information output device 3 is installed in a place different from the target vehicle 2 and the receiving terminal 4, but the dangerous driving risk information output device 3 is installed in the target vehicle 2 or the receiving terminal 4. may be integrated with In that case, when it is mounted on the target vehicle 2, it can be incorporated in the GPS device 21 or a portable information terminal such as a driver's smart phone.

Further, in the above embodiment, the output "dangerous driving risk information" is handled on the receiving terminal 4 side, but the dangerous driving risk information output system of the present invention may output "dangerous driving risk information". The output "dangerous driving risk information" may be used by the driver of the target vehicle 2, family members, administrators, etc. according to the purpose. In that case, the dangerous driving risk information output device 3 corresponds to the dangerous driving risk information output system of the present invention.

In the above embodiment, decision-making data issued by a public safety commission, a police station, or the like is used as the "latitude and longitude of a rule application position to which a predetermined traffic rule is applied" of the present invention. You may use the data acquired from.

The present invention can also be used for shared rides. A shared ride is a mechanism that saves on transportation costs by utilizing vacant seats in a third party's vehicle and sharing the cost of gasoline with the third party. In this case, it is conceivable that the reception terminal 4 receives the driving level score for each driver registered for the shared ride and displays it for each driver. By making it possible to compare and display the driving level scores of each driver, users of the shared ride service can select drivers who drive safely. For example, on the screen of a smartphone or personal computer, which is the receiving terminal 4, a list of drivers near the user is displayed, and based on each driver's driving level score, the list is displayed in order of the drivers who drive safely. . This allows users to select safe drivers nearby.

As a result, it is expected that only excellent drivers with a high driving level score, that is, those who do not comply with road traffic laws, will be able to participate in shared rides. You can help prevent it from happening.

Moreover, the present invention can also be used for an operation management system. In this case, the driving level score is the degree of traffic violation (for example, whether it is over 20km or over 30km on a 60km road), and when the driving level score exceeds a predetermined threshold, the image of the corresponding time on the drive recorder is displayed. A configuration for extracting and displaying on the display unit 43 of the receiving terminal 4 is conceivable. As a result, it is possible to specifically grasp what kind of danger and risk existed from the image.

Also, when used in an operation management system, a driving level score may be calculated and ranking information compared with other people's driving level scores may be output.

In addition, the present invention is used in conjunction with a car navigation system or smartphone navigation application to output "dangerous driving risk information" when the speed limit is exceeded while driving, and to change the color of the car navigation system or smartphone panel. can also

In addition, the GPS device 21 used in the present invention is equipped with a rechargeable battery, which is charged while driving and driven by its own battery when the vehicle is stopped. By setting a long transmission interval, it is possible to save battery consumption. In this case, since the position of the target vehicle 2 can be known even when the vehicle is stopped, it is possible to find the parking position of the parking lot.

The present invention is also applied to a program corresponding to processing performed by the dangerous driving risk information output system 1, the target vehicle 2, the dangerous driving risk information output device 3, or the receiving terminal 4, and a recording medium storing the program. It is possible. In the case of a recording medium, the program is installed in a computer or the like. Here, the recording medium storing the program may be a non-transitory recording medium. A CD-ROM or the like can be considered as a non-transitory recording medium, but it is not limited to this.

A computer is composed of a CPU, a memory, and a hard disk, and the program is recorded on the hard disk, loaded into the memory when executed, and processed by performing arithmetic processing on the CPU. Note that the CPU of the computer may be capable of parallel processing, or the computer itself may be of a form capable of distributed processing. The results of processing can be displayed on any display via the network.

1 Dangerous driving risk information output system 2 Target vehicle 3 Dangerous driving risk information output device 4 Receiving terminal 21 GPS device 22 Vehicle-side transmitting unit 31 Acquiring unit 32 Accumulating unit 33 Receiving unit 34 Control unit 35 Outputting unit 41 Terminal-side transmitting unit 42 Terminal Side receiving unit 43 Display unit

Claims (9)

an acquisition unit that acquires travel information including position information of the target vehicle;
At least one or more traffic rules applied to the location information are extracted from the traffic rules managed based on the address or latitude/longitude, and the violation of the target vehicle is detected based on the extracted traffic rules and the travel information. an accumulation unit that determines the presence or absence of a driver of the target vehicle and creates and accumulates statistical information that associates the presence or absence of a plurality of violations determined for the driver of the target vehicle with each position information;
a control unit that creates dangerous driving risk information representing the cognitive function score of the driver based on the statistical information;
an output unit that outputs the dangerous driving risk information;
with
In calculating the cognitive function score, a violation rank is set according to the degree or presence of the violation for each type of violation, and a weight is set for each type of violation for judging cognitive function. and the cognitive function score is obtained by determining the violation rank according to the degree or presence or absence of the violation for each of the determined violations, weighting them with the weights corresponding to each, and summing them. Dangerous driving risk information output system. 2. The dangerous driving risk information output system according to claim 1, wherein the weight is set higher for the non-stop type than for the overspeeding type. 2. The dangerous driving risk information output system according to claim 1, wherein said dangerous driving risk information is transmitted to a receiving terminal owned by a family member of said target vehicle or an administrator. The control unit, when creating the cognitive function score as the dangerous driving risk information, determines whether the cognitive function score is on an upward trend,
2. The dangerous driving risk information output according to claim 1, wherein when it is determined that the cognitive function score is on an upward trend, the output unit outputs alert information as part of the dangerous driving risk information. system. 3. The control unit calculates the cognitive function score based on at least one violation of traffic rules among non-stop violations, non-stop violations at railroad crossings, one-way traffic violations, and right/left turn prohibition violations. 2. The dangerous driving risk information output system according to 1 . The travel information also includes distance information relating to the distance between the target vehicle and surrounding vehicles,
2. The dangerous driving risk information output system according to claim 1 , wherein the control unit calculates the cognitive function score in consideration of the distance information. 2. The dangerous driving risk information output system according to claim 1 , wherein the accumulation unit creates the statistical information based on position information measured by a position information positioning system with an error of 1.5 m or less. 2. The dangerous driving risk information output system according to claim 1 , wherein said accumulation unit creates said statistical information based on sub-meter level position information. A program installed on a computer that
a step of acquiring travel information including location information of the target vehicle;
At least one or more traffic rules applied to the location information are extracted from the traffic rules managed based on the address or latitude/longitude, and the violation of the target vehicle is detected based on the extracted traffic rules and the travel information. creating and accumulating statistical information that associates the presence or absence of a plurality of violations determined for the driver of the target vehicle with each location information;
creating dangerous driving risk information representing the driver's cognitive function score based on the statistical information;
a step of outputting the dangerous driving risk information;
with
A violation rank is set according to the degree or presence or absence of the violation for each type of violation, and a weight is set for each type of violation for judgment of cognitive function, and the cognitive function score is , a dangerous driving risk information output program characterized by determining a violation rank according to the degree or presence or absence of the violation for each of the judged violations, weighting them with the weights corresponding to each, and summing them. .

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