Risk assessment device, risk assessment method, and risk assessment program

Abstract

This improves the reliability of acquired biometric information and enables accurate determination of risk levels for each predetermined interval using reliable biometric information. [Solution] The risk level determination device 100 includes a biometric information acquisition unit 101 that acquires biometric information of the passengers of the moving vehicle, and a determination unit 102 that determines the risk level of a predetermined section traveled by the moving vehicle before it arrives at the first point, based on the biometric information acquired by the biometric information acquisition unit 101 at a second point where the moving vehicle is traveling at a predetermined speed or less, and a set reference value. The set reference value is based on the biometric information acquired by the biometric information acquisition unit 101 at a second point where the moving vehicle is traveling at a predetermined speed or less, before it arrives at the first point.

Description

Technical Field

[0001] The present invention relates to a risk level determination device, a risk level determination method, and a risk level determination program for displaying the energy consumption of a moving object. However, the use of the present invention is not limited to the above-described risk level determination device, risk level determination method, and risk level determination program.

Background Art

[0002] With the spread of navigation devices, it is known to reflect information on dangerous locations on the road in navigation map information. Also, it is known that when the driver's heart rate suddenly increases during driving, it is presumed that a dangerous state called "a near miss" has occurred.

[0003] As a conventional technique, there is a technique for measuring biometric reaction data reflecting the mental state of a driver and operation data of the driver's vehicle, and determining that a dangerous reaction has occurred when these change significantly (see, for example, Patent Document 1 below). Also, as a method for acquiring biometric information, an electrocardiogram sensor that arranges electrodes on a seat and senses a weak signal from the heart is disclosed (see, for example, Patent Document 2 below).

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, with conventional methods for acquiring biometric information, when a vehicle is in motion, vibrations associated with driving and driving operations can cause changes in contact resistance between the human body and the sensor, generating noise and potentially preventing accurate acquisition of biometric information. This could also reduce the accuracy of determining dangerous situations. [Means for solving the problem]

[0006] To solve the above-mentioned problems and achieve the objective, the risk level determination device according to claim 1 comprises: a biometric information acquisition unit that acquires biometric information of a passenger of a moving body; and a determination unit that determines the risk level of a predetermined section traveled by the moving body before it arrives at the first point, based on the biometric information acquired by the biometric information acquisition unit at a first point where the moving body is below a predetermined speed, and a set reference value, wherein the set reference value is based on biometric information acquired by the biometric information acquisition unit at a second point where the moving body is below the predetermined speed before it arrives at the first point.

[0007] Furthermore, the risk level determination device according to claim 2 is characterized in that the set reference value is the biological information acquired by the biological information acquisition unit at the second point where the moving body is at or below the predetermined speed before the moving body arrives at the first point.

[0008] Furthermore, the risk level determination device according to claim 3 is characterized by comprising: a heart rate information acquisition unit that acquires heart rate information of a passenger of a moving vehicle; and a determination unit that determines the risk level of a predetermined section traveled by the moving vehicle until it arrives at the first point, based solely on the heart rate information acquired by the heart rate information acquisition unit at the first point where the moving vehicle is traveling at or below a predetermined speed, and a set reference value.

[0009] Furthermore, the risk level determination device according to claim 4 further comprises a movement information acquisition unit that acquires information regarding the movement of the moving body, and the determination unit is characterized in that it identifies the predetermined section based on the information acquired by the movement information acquisition unit.

[0010] Furthermore, the risk level determination device according to claim 5 is characterized in that it further comprises a storage unit that stores the risk level determined by the determination unit and the predetermined interval in association with each other.

[0011] Furthermore, the risk level determination device according to claim 6 is characterized in that it further comprises a display unit that displays the risk level determined by the determination unit and the predetermined section on map information.

[0012] Furthermore, the risk level determination device according to claim 7 is characterized in that it further comprises a route search unit that performs a route search based on the risk level determined by the determination unit and the predetermined section.

[0013] Furthermore, the risk assessment method according to claim 8 includes a biometric information acquisition step of acquiring biometric information of a passenger of a moving body, and a assessment step of determining the risk assessment of a predetermined section traveled by the moving body before it arrives at the first point, based on the biometric information acquired in the biometric information acquisition step at a first point where the moving body is traveling at or below a predetermined speed, and a set reference value, wherein the set reference value is based on biometric information acquired in the biometric information acquisition step at a second point where the moving body is traveling at or below the predetermined speed, before the moving body arrives at the first point.

[0014] Furthermore, the risk level determination program according to claim 9 is characterized by causing a computer to execute the risk level determination method described in claim 8. [Brief explanation of the drawing]

[0015] [Figure 1]FIG. 1 is a block diagram showing a functional configuration of a risk level determination device according to an embodiment. [Figure 2] FIG. 2 is a flowchart showing the processing contents of the risk level determination device according to the embodiment. [Figure 3] FIG. 3 is a block diagram showing the hardware configuration of a navigation device. [Figure 4] FIG. 4 is a flowchart showing a system processing example of risk level determination using a navigation device and a server. [Figure 5] FIG. 5 is a diagram showing a dangerous route on map data. [Figure 6] FIG. 6 is a diagram showing an example of assigning a near miss score to a link.

Embodiment for Carrying Out the Invention

[0016] Hereinafter, preferred embodiments of a risk level determination device, a risk level determination method, and a risk level determination program according to this invention will be described in detail with reference to the accompanying drawings.

[0017] (Embodiment) FIG. 1 is a block diagram showing a functional configuration of a risk level determination device according to the embodiment. The risk level determination device 100 includes a biological information acquisition unit 101, a determination unit 102, and a movement information acquisition unit 103. In addition, it may include a storage unit 104, a display unit 105, and a route search unit 106.

[0018] The biological information acquisition unit 101 acquires the biological information of the passengers of the moving body. Various methods of acquiring biological information are conceivable, and this biological information acquires information that changes with the running state of the moving body, such as the heart rate. For example, the heart rate of the passenger can be detected by a sensor.

[0019] The determination unit 102 determines the degree of danger in a predetermined section during the movement of the moving body. Based on the biological information acquired by the biological information acquisition unit 101 at the first point where the moving body has reached a predetermined speed or less and a preset reference value, the determination unit 102 determines the degree of danger of a predetermined section (the section between the second point where it stopped last time and the first point) that the moving body has traveled until it reaches the first point.

[0020] For example, if the biological information acquisition unit 101 is configured to detect the heart rate of the passenger by a sensor, when there is an increase in the heart rate, the determination unit 102 can determine that the degree of danger of the corresponding predetermined section is high (a dangerous driving state such as sudden braking or sudden steering has occurred). The predetermined section with a high degree of danger is likely to be a section where so-called "near misses" are likely to occur. Although details will be described later, by collecting information on the degree of danger of this predetermined section from a plurality of moving bodies (danger degree determination devices 100), the accuracy of the danger degree determination can be further improved.

[0021] The above "predetermined speed or less" is set corresponding to the speed of the moving body at which the biological information acquisition unit 101 can stably acquire biological information. For example, during the movement of the moving body, when traveling at a speed exceeding a predetermined speed, stable biological information cannot be acquired due to vibrations during traveling, etc. On the other hand, if it is set to be acquired when the moving body is at a predetermined speed or less, for example, when it stops, biological information can be stably acquired without being affected by vibrations associated with traveling or driving operations, etc.

[0022] For the above reference value, before the moving body reaches the first point, the biological information acquired by the biological information acquisition unit 101 at another point (the second point) where the moving body has reached a predetermined speed or less can be used.

[0023] The movement information acquisition unit 103 acquires information related to the movement of the moving body (speed, acceleration calculated from speed information, etc.). In this case, the determination unit 102 identifies the above-mentioned predetermined section based on the information acquired by the movement information acquisition unit 103.

[0024] The memory unit 104 stores the determination result determined by the determination unit 102 in association with the predetermined interval. The display unit 105 displays the degree of danger, which is the determination result of the determination unit 102. For example, the degree of danger can be displayed on a map using different display modes, such as different color levels.

[0025] The route search unit 106 searches for a driving route from the current location to the destination based on the destination setting input, and outputs it to the display unit 105, etc. This route search unit 106 can search for a route based on the judgment result (degree of danger) of the judgment unit 102. For example, it can search for a driving route that avoids predetermined sections with a high degree of danger.

[0026] Figure 2 is a flowchart showing the processing content of the risk level determination device according to the embodiment. The processing content performed by the risk level determination device 100 is described below. First, it is determined whether the speed of the moving object is below a predetermined speed (e.g., stopped) (step S201). If the speed is not below the predetermined speed, it waits (loop of step S201: No), and if it becomes below the predetermined speed (step S201: Yes), the biometric information acquisition unit 101 acquires biometric information (e.g., the driver's heart rate) of the occupant of the moving object (e.g., the driver) (step S202).

[0027] Next, the determination unit 102 determines whether the value of the biological information acquired in step S202 has changed from the value of the biological information acquired in the previous step (step S203). If there is no significant change from the value of the biological information acquired in the previous step (step S203: No), the process returns to step S201.

[0028] On the other hand, if there is a significant change from the value of the biometric information acquired last time (step S203: Yes), the determination unit 102 determines the degree of risk based on this change (step S204). This makes it possible to determine the degree of risk for a predetermined period from the time the biometric information was acquired last time until the time it was acquired this time.

[0029] For example, if the heart rate obtained this time has increased significantly compared to the heart rate obtained last time, the risk level for the predetermined interval is determined to be high. If the increase in the heart rate obtained this time is small compared to the heart rate obtained last time, the risk level for the predetermined interval is determined to be low. The determination unit 102 can also determine that the risk level for the predetermined interval is high if both the heart rate obtained last time and the heart rate obtained this time are high. Since heart rate varies from person to person, by setting multiple thresholds for the increase based on the normal heart rate, it becomes possible to determine the risk level in multiple stages, taking into account individual differences.

[0030] The above series of processes is executed each time the speed falls below a predetermined level (for example, each time the vehicle stops). This allows for the sequential determination of the level of risk for each predetermined section between the previous stop and the current stop while the vehicle is moving.

[0031] Furthermore, since biometric information is acquired whenever the moving object stops or falls below a predetermined speed, noise and other effects based on vibrations during the object's movement can be reduced, allowing for the acquisition of the most accurate values ​​possible. This improves the reliability of the acquired biometric information, enabling accurate determination of the risk level for each predetermined section using reliable biometric information.

[0032] Fluctuations in biometric information can be interpreted as a manifestation of driving stress (e.g., increased heart rate). By having a server collect heart rate variability distributions from many drivers using a risk assessment device and statistically processing them on map data, it becomes possible to identify the degree of risk on the map data and on the map display. On the other hand, it also becomes possible to find locations and routes with low risk and less driving stress, and to present drivers with routes that reduce driving stress. [Examples]

[0033] The following describes embodiments of the present invention. In this embodiment, a navigation device mounted on a vehicle and capable of communicating with a server is used as the risk level determination device 100, and an example of how the present invention can be applied is described. For example, the server can collect information from the navigation device 300, create a risk map showing the risk level on a map, and distribute it to the navigation device 300. A risk level determination system can be constructed using these servers and multiple navigation devices 300.

[0034] (Hardware configuration of the navigation system) Next, the hardware configuration of the navigation device will be described. Figure 3 is a block diagram showing the hardware configuration of the navigation device. In Figure 3, the navigation device 300 includes a CPU 301, ROM 302, RAM 303, magnetic disk drive 304, magnetic disk 305, optical disk drive 306, optical disk 307, audio interface 308, microphone 309, speaker 310, input device 311, video interface 312, display 313, camera 314, communication interface 315, GPS unit 316, and various sensors 317. Each component 301 to 317 is connected by a bus 320.

[0035] The CPU 301 controls the entire navigation device 300. The ROM 302 stores programs such as the boot program, data update program, map data display program, and the aforementioned risk level determination program. The RAM 303 is used as the work area for the CPU 301. In other words, the CPU 301 controls the entire navigation device 300 by executing various programs stored in the ROM 302 while using the RAM 303 as its work area.

[0036] The magnetic disk drive 304 controls the reading and writing of data to the magnetic disk 305 according to the control of the CPU 301. The magnetic disk 305 records the data written under the control of the magnetic disk drive 304. For example, the magnetic disk 305 can be an HD (hard disk) or an FD (flexible disk).

[0037] Furthermore, the optical disc drive 306 controls the reading and writing of data to the optical disc 307 according to the control of the CPU 301. The optical disc 307 is a removable recording medium from which data is read according to the control of the optical disc drive 306. The optical disc 307 can also use a writable recording medium. In addition to the optical disc 307, MO disks, memory cards, etc. can be used as removable recording media.

[0038] Examples of information recorded on the magnetic disk 305 and optical disk 307 include map data, vehicle information, road information, and driving history. Map data is used in car navigation systems to display information about the remaining driving distance and includes background data representing features such as buildings, rivers, and the ground surface, and road shape data representing the shape of roads using links and nodes. Here, vehicle information, road information, and driving history are road-related data used as variables in the estimation formula for calculating estimated energy consumption.

[0039] The audio interface 308 is connected to a microphone 309 for audio input and a speaker 310 for audio output. The audio received by the microphone 309 is converted from analog to digital within the audio interface 308. The microphone 309 can be installed, for example, on the dashboard of a vehicle, and there may be one or more of them. The speaker 310 outputs audio that has been converted from analog to digital within the audio interface 308, such as a predetermined audio signal for route guidance.

[0040] The input device 311 may include a remote control, keyboard, or touch panel equipped with multiple keys for inputting characters, numbers, and various instructions. The input device 311 may be implemented in any one form of a remote control, keyboard, or touch panel, but it can also be implemented in multiple forms.

[0041] The video interface 312 is connected to the display 313. Specifically, the video interface 312 consists of, for example, a graphics controller that controls the entire display 313, a buffer memory such as VRAM (Video RAM) that temporarily stores image information that can be displayed immediately, and a control IC that controls the display 313 based on the image data output from the graphics controller.

[0042] The display 313 displays various data such as icons, cursors, menus, windows, text, and images. For example, the display 313 can be a TFT liquid crystal display or an organic EL display.

[0043] Camera 314 captures images of the interior or exterior of the vehicle. The images can be either still images or videos. For example, camera 314 can capture images of the exterior of the vehicle, and the captured images can be analyzed by the CPU 301 or output to a recording medium such as a magnetic disk 305 or an optical disk 307 via the video interface 312.

[0044] The communication interface 315 is connected to wireless and wired networks and functions as an interface for the navigation device 300 and CPU 301. Communication networks that function as networks include public telephone networks, mobile phone networks, DSRC (Dedicated Short Range Communication), LAN, WAN, and CAN. Examples of communication interfaces 315 include network modules, public telephone network connection modules, ETC (Electronic Toll Collection) units, FM tuners, and VICS (Vehicle Information and Communication System: registered trademark) / beacon receivers.

[0045] The GPS unit 316 receives radio waves from GPS satellites and outputs information indicating the vehicle's current position. The output information from the GPS unit 316, along with the output values ​​from various sensors 317, is used by the CPU 301 to calculate the vehicle's current position. The information indicating the current position is, for example, information that identifies a specific point on map data, such as latitude, longitude, and altitude.

[0046] The various sensors 317, such as a vehicle speed sensor, acceleration sensor, angular velocity sensor, and tilt sensor, output information to determine the vehicle's position and behavior. The output values ​​of the various sensors 317 are used by the CPU 301 to calculate the vehicle's current position and the amount of change in speed and direction.

[0047] Each component of the risk level determination device 100 shown in Figure 1 functions by the CPU 301 executing a predetermined program using programs and data recorded in the ROM 302, RAM 303, magnetic disk 305, optical disk 307, etc., shown in Figure 3, thereby controlling each part of the navigation device 300. Furthermore, when a request for route search is received from a moving object, the navigation device 300 has a route search function that performs a route search based on information about the current position of the moving object and the destination, through the execution of a program by the CPU 301.

[0048] (Server hardware configuration) The server capable of communicating with the navigation device 300 also has the same configuration as shown in Figure 3. However, the GPS unit 316, various sensors 317, camera 314, etc., shown in Figure 3 are not required for this server.

[0049] Incidentally, the server may have the function related to determining the degree of danger of the danger determination device 100 shown in Figure 1. In this case, the server can receive biometric information of the occupant (e.g., driver) of the moving object from the navigation device 300 each time the moving object falls below a predetermined speed (e.g., stops), and then determine the degree of danger for the section up to that point based on the changes since the last reception.

[0050] (Example of system processing for determining the degree of risk) Figure 4 is a flowchart illustrating an example of a system process for determining the degree of risk using a navigation device and a server. The processing on the navigation device 300 side and the processing on the server side are shown separately.

[0051] The navigation device 300 first determines whether the speed of the moving object is below a predetermined speed (in this example, stopped) (step S401). If the moving object is not stopped, it waits (loop of step S401: No), and if it is stopped (step S401: Yes), it acquires the heart rate as biometric information of the occupant of the moving object (e.g., the driver) and detects the position (latitude and longitude) of the moving object (step S402).

[0052] Next, the navigation device 300 determines whether the value of the biometric information (heart rate) acquired in step S402 has changed from the value of the biometric information (heart rate) acquired in the previous step (step S403). If there is no significant change in the value of the biometric information acquired in the previous step (step S403: No), the process returns to step S401.

[0053] On the other hand, if there is a significant change in the value of the biometric information (heart rate) acquired last time (step S403: Yes), the navigation device 300 determines a dangerous route based on this change (step S404). This dangerous route is determined to be a high-risk route for a predetermined interval from the time the biometric information was acquired last time until the time it was acquired this time.

[0054] After this, the navigation device 300 transmits information about the dangerous route to the server (step S405), and terminates the processing during the mobile body's single stop.

[0055] The server-side processing involves collecting data on dangerous routes transmitted from the navigation device 300 each time the mobile vehicle stops (step S411). This data can be collected from the navigation devices 300 of multiple different mobile vehicles.

[0056] The server then overlays the received hazardous routes onto the map data and estimates the hazardous area from these hazardous routes (step S412). The hazardous area is defined as the range that includes routes with a large number of overlaps when the hazardous routes transmitted from multiple mobile devices (navigation devices 300) are overlaid onto the map data (for example, routes that become darker in color when overlaid).

[0057] This creates a hazard map showing the extent of dangerous areas on the map data (step S413). For example, dangerous routes and dangerous areas on the hazard map can be displayed using easily visible colors such as red. The created hazard map can be distributed to multiple mobile devices (navigation devices 300) connected to the server, as well as to PCs, smartphones, etc. By referring to the distributed hazard map, users can easily identify dangerous routes and dangerous areas where "near misses" frequently occur when actually driving a mobile device.

[0058] The navigation system 300 can use the information provided by the distributed hazard map to search for routes and notify the driver. This allows the navigation system 300 to search for planned routes that avoid hazardous routes and areas when searching for a route to a destination, enabling fuel-efficient driving and reducing accidents.

[0059] In the above process, the navigation device 300 is configured to determine the dangerous route, but the server may also determine the dangerous route. In this case, in step S405, the heart rate and position (latitude and longitude) of the moving object acquired and detected in step S402 are sent to the server. The server processes the change in heart rate for each stop of the moving object (step S403), and if there is a significant change in heart rate, it determines the dangerous route based on this change. The dangerous route is determined based on the previous and current positions (latitude and longitude) of the moving object on the map data.

[0060] Furthermore, the transmission (uploading) of dangerous route information from the navigation device 300 to the server may be performed at any time, periodically, or at various other times, such as when the driver performs an upload operation, not limited to when the moving vehicle is stopped.

[0061] Furthermore, when the server distributes (downloads) dangerous routes and dangerous areas to the navigation device 300, it can also calculate the current location and destination of the moving object obtained from the navigation device 300, calculate the dangerous route, search for a planned route to the destination that avoids the dangerous route, and distribute it to the navigation device 300.

[0062] Furthermore, in the information aggregation process performed by the server, driver attributes (male, female, age, driving experience (beginner, etc.), transportation company, etc.) and vehicle attributes (light vehicle, regular passenger vehicle, taxi, large truck, small truck, delivery truck, bus, etc.) may also be added to the aggregation process along with the various types of information mentioned above. This allows dangerous routes and dangerous areas suitable for the vehicle's attributes to be distributed to the vehicle's navigation device 300. In addition, it is possible to notify drivers of dangerous routes and dangerous areas suitable for their attributes and the time of day.

[0063] Furthermore, while the above processing example uses heart rate as biometric information, the average heart rate or the rate of change in heart rate may also be calculated. In addition, vehicle information other than acceleration calculated from speed information (such as lateral acceleration of the moving body from a G-sensor, longitudinal acceleration, brake operation amount, steering operation amount, etc.) may be acquired simultaneously along with heart rate. This allows, for example, to determine that a point with a large change in acceleration is a point where sudden braking or sudden steering occurred, enabling a more accurate assessment of the degree of danger.

[0064] Furthermore, even on the same road, driving conditions differ depending on whether the vehicle is going straight, turning right, or turning left. For this reason, along with biometric information, the location, route, time information, vehicle speed, and acceleration information of the moving object may be acquired together with road shape information such as intersections, and vehicle operations such as going straight, turning right, or turning left, as well as vehicle progress, and the data may be separated into cases of going straight, turning right, or turning left. This will allow for the assessment of the degree of danger separately for cases of going straight, turning right, or turning left. In addition, the various types of acquired information may be added to link information and node information on map data.

[0065] (Regarding the determination of dangerous routes) Let's explain in detail the example of determining the degree of risk using heart rate as described above. To extract the "near miss" events mentioned above, we use instantaneous heart rate, which is calculated by converting each beat into heartbeats per minute, and determine the degree of risk based on the increase in instantaneous heart rate.

[0066] Specifically, the average of the instantaneous heart rate over 30 beats prior to the "near-miss" event, where the heart rate increased, is calculated as the average instantaneous heart rate before the event, H1. Similarly, the average of the instantaneous heart rate over 30 beats after the "near-miss" event is calculated as the average instantaneous heart rate after the event, H2. Then, the rate of increase in heart rate is calculated as (H2-H1) / (H1+H2). This rate of increase in heart rate represents the risk level, and will be referred to as the near-miss score below.

[0067] Here, we will explain the criteria for detecting changes in biological information (heart rate). The reference value for judging a change in state using biological information such as heart rate is set based on a certain statistical value, such as the average value in the world. When the heart rate increases above the reference value, it is judged that a "near miss" event has occurred. In addition, the average of measurements when there is no change in the measured value may be used as the reference value.

[0068] Furthermore, a value obtained by multiplying these average values ​​by a certain percentage may be used as a judgment value to determine the change. Also, the reference value and judgment value may always be constant, or they may be updated sequentially, for example, by using the previous measurement as the criterion for the next judgment. In addition, the reference value and judgment value may be updated regularly or irregularly depending on the situation. They may also be changed for each location or route, such as links or nodes. They may also be changed according to time information such as the date and time.

[0069] Figure 5 shows a diagram of a dangerous route on map data. By assigning the aforementioned risk level (near-miss score) to the corresponding link information or node information on the road data, the dangerous route 501 can be displayed.

[0070] As shown in Figure 5, if the dangerous path 501 between two stopping positions (nodes A and B) of a moving object spans multiple links (n1 to n4) on the map data, near-miss scores may be assigned to each link or node.

[0071] The memory unit 104 of the navigation device 300 (risk level determination device 100) stores map data and risky routes 501. The map data basically consists of a set of nodes corresponding to intersections and road links corresponding to roads connecting two intersections (nodes), and is used for displaying maps or calculating routes to destinations. In the example in Figure 5, if heart rate is detected at node A and node B respectively, a near-miss score is assigned to the link connecting nodes A and B.

[0072] (Example of assigning near-miss scores to multiple links) Figure 6 shows an example of assigning near-miss scores to links. Near-miss scores are divided and assigned to links 1-3 between the stopped nodes A and B, as shown in the figure.

[0073] The near-miss score assigned to a link in a single travel section (between nodes A and B) may be set by assigning a fixed number of points to each link, or by changing the point value in response to changes in biometric information. It may also be changed using information such as location, time, acceleration changes, brake operation amount, steering operation amount, and vehicle acceleration, or it may be changed in addition to considering changes in biometric information. For example, if a single travel section consists of multiple links, the points assigned to each link may be a fixed value, such as by dividing the points by the number of links, or it may be changed according to the distance and speed of each link. Furthermore, if a particular link or route has many near-misses, the point assignment for that route or link may be increased based on statistical processing of a large amount of data using a server or the like.

[0074] In example 1, if the near-miss score for the interval (between nodes A and B) is 1, the three links 1 to 3 are evenly allocated 0.33 points each. In example 2, if the near-miss score for the interval (between nodes A and B) is 2, the points are allocated according to the distance between the three links 1 to 3, with 0.7 points for link 1, 0.5 points for link 2, and 0.8 points for link 3.

[0075] Furthermore, when assigning near-miss scores to multiple nodes in a single driving section, it is sufficient to assign them to one of the nodes at either end of the link.

[0076] By assigning near-miss scores to such links or nodes, the navigation device 300 transmits the risk level (near-miss score) for each node or link as a hazardous route 501 to the server. This allows the server to aggregate hazardous routes acquired from multiple mobile devices (navigation devices 300) on a node or link basis, and to determine the risk level on a node or link basis. Furthermore, the server can distribute hazardous routes on a node or link basis to the navigation device 300.

[0077] The above-mentioned dangerous routes and areas can be used for business purposes, such as providing information to truck dispatch managers and suggesting routes to dispatch managers and drivers. For general drivers, it can be used for notifying them of dangerous locations and suggesting alternative routes that avoid high-risk areas. For autonomous vehicles, it can be used to suggest safer routes that avoid dangerous routes, utilizing information on high-risk locations and routes. Furthermore, for administrative services, it can be used to provide information that facility managers can use for facility improvements, and information that police and other authorities can use for safety improvements (e.g., indicating high-risk locations, information for considering signals and signs, warnings, etc.).

[0078] The risk assessment method described in this embodiment can be implemented by executing a pre-prepared program on a computer such as a personal computer or workstation. This program is recorded on a computer-readable recording medium such as a hard disk, flexible disk, CD-ROM, MO, or DVD, and is executed when read from the recording medium by the computer. This program may also be transmitted via a network such as the Internet. [Explanation of symbols]

[0079] 100 Risk Level Assessment Device 101 Biological Information Acquisition Unit 102 Judgment section 103 Movement information acquisition unit 104 Storage section 105 Display section 106 Route Search Unit 300 Navigation System

Claims

1. A biometric information acquisition unit that acquires biometric information of the passengers of the mobile vehicle, A determination unit determines the degree of danger of a predetermined section traveled by the moving body until it arrives at the first point, based on the biological information acquired by the biological information acquisition unit at the first point where the moving body is traveling at or below a predetermined speed, and a set reference value. Equipped with, The risk level determination device is characterized in that the set reference value is based on biological information acquired by the biological information acquisition unit at a second point where the moving body is below the predetermined speed before the moving body arrives at the first point.

2. The risk level determination device according to claim 1, characterized in that the set reference value is biological information acquired by the biological information acquisition unit at a second point where the moving body is at or below the predetermined speed before the moving body arrives at the first point.

3. A heart rate information acquisition unit that acquires heart rate information of the passengers of a moving vehicle, A determination unit determines the degree of danger of a predetermined section traveled by the moving body until it arrives at the first point, based solely on the heart rate information acquired by the heart rate information acquisition unit at the first point where the moving body is traveling at or below a predetermined speed, and a set reference value. A risk level determination device characterized by being equipped with [a specific feature].

4. The system further includes a movement information acquisition unit that acquires information regarding the movement of the aforementioned moving object, The determination unit identifies the predetermined section based on the information acquired by the movement information acquisition unit. A risk level determination device according to any one of features 1 to 3.

5. The system further includes a storage unit that stores the degree of risk determined by the determination unit in association with the predetermined interval. A risk level determination device according to any one of features 1 to 4.

6. The system further includes a display unit that displays the degree of danger determined by the determination unit and the predetermined section on the map information. A risk level determination device according to any one of features 1 to 5.

7. The system further includes a route search unit that performs route searching based on the degree of risk determined by the determination unit and the predetermined section. A risk level determination device according to any one of features 1 to 6.

8. A biometric information acquisition process that acquires the biometric information of the passengers of a mobile vehicle, A determination step that determines the degree of danger of a predetermined section traveled by the moving body until it arrives at the first point, based on the biological information acquired in the biological information acquisition step at the first point where the moving body is traveling at or below a predetermined speed, and a set reference value. Includes, The risk level determination method is characterized in that the set reference value is based on biological information acquired in the biological information acquisition step at a second point where the moving body reaches a predetermined speed or less before arriving at the first point.

9. A risk level determination program characterized by causing a computer to execute the risk level determination method described in claim 8.

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