Title of invention: Optical fiber sensing system, road monitoring method, and optical fiber sensing device
Technical field
[0001]
This disclosure relates to an optical fiber sensing system, a road monitoring method, and an optical fiber sensing device.
Background technology
[0002]
In recent years, a system for monitoring road conditions has been proposed.
For example, in Patent Document 1, an impact sensor is fixed to a guard rail or the like on a road, and when the level of an electric signal output from the impact sensor is equal to or higher than a threshold level, an accident detection signal indicating that a traffic accident has occurred is generated. It is disclosed to do.
[0003]
Further, Patent Document 2 discloses that an optical fiber is laid on the surface of an underground power cable or the like to continuously detect whether or not a physical phenomenon has occurred in the optical fiber.
Prior art literature
Patent documents
[0004]
Patent Document 1: Japanese Unexamined Patent Publication No. 2000-22989
Patent Document 2: Japanese Patent Application Laid-Open No. 06-307896
Outline of the invention
Problems to be solved by the invention
[0005]
However, the technique described in Patent Document 1 can only detect whether or not a traffic accident has occurred on the road. Further, the technique described in Patent Document 2 can only detect whether or not a physical phenomenon has occurred.
Therefore, all of the technologies described in Patent Documents 1 and 2 have a problem that the situation of a traffic accident occurring on a road cannot be grasped.
[0006]
Therefore, an object of the present disclosure is to provide an optical fiber sensing system, a road monitoring method, and an optical fiber sensing device capable of solving the above-mentioned problems and grasping the situation of a traffic accident occurring on a road.
Means to solve problems
[0007]
The optical fiber sensing system according to one aspect is
An optical fiber installed along the road to detect vibration,
A detection unit that detects the vibration pattern of vibration caused by a traffic accident that occurred on the road from the optical signal received from the optical fiber.
Based on the vibration pattern, the estimation unit that estimates the situation of the traffic accident and
Equipped with.
[0008]
The road monitoring method according to one aspect is
The optical fiber installed along the road has a step to detect vibration,
A detection step that detects the vibration pattern of vibration caused by a traffic accident that occurred on the road from the optical signal received from the optical fiber.
The estimation step for estimating the situation of the traffic accident based on the vibration pattern,
including.
[0009]
The optical fiber sensing device according to one aspect is
A detection unit that detects the vibration pattern of vibration caused by a traffic accident that occurred on the road from an optical signal provided along the road and received from an optical fiber that detects vibration.
Based on the vibration pattern, the estimation unit that estimates the situation of the traffic accident and
Equipped with.
The invention's effect
[0010]
According to the above-described aspect, it is possible to provide an optical fiber sensing system, a road monitoring method, and an optical fiber sensing device that can grasp the situation of a traffic accident that has occurred on a road.
A brief description of the drawing
[0011]
FIG. 1 is a diagram showing a configuration example of an optical fiber sensing system according to a first embodiment.
FIG. 2 is a diagram showing an example of vibration data used by the estimation unit according to the first embodiment to estimate the situation of a traffic accident occurring on a road.
FIG. 3 is a diagram showing an example in which the estimation unit according to the first embodiment estimates the situation of a traffic accident occurring on a road by using pattern matching.
FIG. 4 is a diagram showing an example of vibration data used by the estimation unit according to the first embodiment to estimate the situation of a traffic accident occurring on a road.
FIG. 5 is a diagram showing an example of vibration data used by the estimation unit according to the first embodiment to estimate the situation of a traffic accident occurring on a road.
FIG. 6 is a diagram showing an example of vibration data used by the estimation unit according to the first embodiment to estimate the situation of a traffic accident occurring on a road.
FIG. 7 is a diagram showing an example of vibration data used by the estimation unit according to the first embodiment to estimate the situation of a traffic accident occurring on a road.
FIG. 8 is a diagram showing an example of a method in which the estimation unit according to the first embodiment estimates the situation of a traffic accident occurring on a road.
FIG. 9 is a flow chart showing an operation example of the optical fiber sensing system according to the first embodiment.
FIG. 10 is a diagram showing an example of vibration data used by the estimation unit according to the second embodiment to estimate the situation of a traffic accident occurring on a road and an example of a running state of a vehicle on the road.
FIG. 11 is a diagram showing an example of vibration data used by the estimation unit according to the second embodiment to estimate the situation of a traffic accident occurring on a road.
FIG. 12 is a flow chart showing an operation example of the optical fiber sensing system according to the second embodiment.
FIG. 13 is a diagram showing a configuration example of an optical fiber sensing system according to a third embodiment.
FIG. 14 is a diagram showing an example of a method in which the estimation unit according to the third embodiment estimates the situation of a traffic accident occurring on a road.
FIG. 15 is a flow chart showing an operation example of the optical fiber sensing system according to the third embodiment.
FIG. 16 is a diagram showing a configuration example of an optical fiber sensing system according to another embodiment.
FIG. 17 is a diagram showing a configuration example of an optical fiber sensing system according to another embodiment.
FIG. 18 is a diagram showing a configuration example of an optical fiber sensing system conceptually showing an embodiment.
FIG. 19 is a flow chart showing an operation example of the optical fiber sensing system shown in FIG.
FIG. 20 is a block diagram showing an example of a hardware configuration of a computer that realizes an optical fiber sensing device according to an embodiment.
Embodiment for carrying out the invention
[0012]
Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. The following descriptions and drawings have been omitted or simplified as appropriate for the sake of clarification of the explanation. Further, in each of the following drawings, the same elements are designated by the same reference numerals, and duplicate explanations are omitted as necessary.
[0013]

First, a configuration example of the optical fiber sensing system according to the first embodiment will be described with reference to FIG.
[0014]
As shown in FIG. 1, the optical fiber sensing system according to the first embodiment includes an optical fiber 10A (first optical fiber), an optical fiber 10B (second optical fiber), and an optical fiber sensing device 20. There is. Further, the optical fiber sensing device 20 includes a detection unit 21 and an estimation unit 22.
[0015]
The optical fibers 10A and 10B are laid on the road R. Specifically, the optical fiber 10A is buried in the vicinity of the road R, and the optical fiber 10B is overhead-wired along the road R. In FIG. 1, the optical fiber 10B is overhead-wired by a utility pole T, but may be overhead-wired by another means such as a steel tower. Further, the optical fibers 10A and 10B may be realized by existing unused optical fibers for communication (so-called dark fibers). Further, the optical fibers 10A and 10B can be realized by the existing communication optical fiber in use if a frequency different from the frequency used for communication in the existing communication optical fiber is used. May be done. Further, the optical fibers 10A and 10B may be laid on the road R in the form of an optical fiber cable configured by covering the optical fiber.
[0016]
The detection unit 21 incidents pulsed light (incident light) on the optical fiber 10A. Further, the detection unit 21 receives the reflected light or scattered light generated when the pulsed light is transmitted through the optical fiber 10A as return light (optical signal) via the optical fiber 10A. Similarly, the detection unit 21 incidents the pulsed light on the optical fiber 10B and receives the return light from the optical fiber 10B.
[0017]
When an impact is generated on the road R, the vibration is transmitted to the optical fiber 10A buried under the road R, affects the return light transmitted by the optical fiber 10A, and propagates through the air as sound. The light is transmitted to the optical fiber 10B which is overhead-wired along the road R, and affects the return light transmitted by the optical fiber 10B. Therefore, the optical fibers 10A and 10B can detect the vibration generated on the road R and the sound caused by the vibration.
[0018]
In this way, the impact generated on the road R propagates as vibration through the ground and sound through the air, but since the optical fiber 10A can easily detect the vibration propagating on the ground, the detection is performed centering on the vibration. Further, since the optical fiber 10B can easily detect the sound propagating in the air, the detection is performed centering on the sound.
[0019]
In the explanation in the previous term, the detection of vibration due to an impact such as an accident was described, but the optical fiber 10A is not limited to that, and it is also possible to detect the vibration generated when the vehicle normally travels on the road R.
[0020]
Here, the vibration generated on the road R has a unique vibration pattern in which the strength of the vibration, the vibration position, the transition of the fluctuation of the frequency, etc. differ depending on the event that caused the vibration. For example, the vibration pattern of vibration caused by a traffic accident occurring on the road R is a pattern peculiar to the traffic accident.
[0021]
Therefore, by analyzing the dynamic change of the vibration pattern of the vibration caused by the traffic accident that occurred on the road R, it is not only detected that the traffic accident occurred on the road R, but also the traffic accident that occurred on the road R. It is also possible to estimate the situation.
[0022]
For example, the following can be considered as the situation of a traffic accident.
・ Number of vehicles that have had a traffic accident
-Type of vehicle that caused a traffic accident (for example, automobile, motorcycle, etc.)
・ Types of traffic accidents (for example, spin accidents, rollover accidents, collision accidents, etc.)
・ Property damage (for example, damage to traffic lights)
[0023]
Therefore, the detection unit 21 detects the vibration pattern of the vibration caused by the traffic accident generated on the road R from the return light received from the optical fibers 10A and 10B. Here, the optical fiber 10A detects the vibration directly transmitted to the road R. Therefore, the detection unit 21 detects, for example, the vibration pattern of vibration caused by a traffic accident from the return light received from the optical fiber 10A. On the other hand, the optical fiber 10B detects vibration as a sound transmitted from the road R via air. Therefore, the detection unit 21 detects, for example, the vibration pattern of vibration caused by a traffic accident from the return light received from the optical fiber 10B.
[0024]
The estimation unit 22 estimates the situation of a traffic accident that occurred on the road R based on the vibration pattern of the vibration caused by the traffic accident detected by the detection unit 21. At this time, as described above, the vibration pattern of the vibration detected by the detection unit 21 is a pattern peculiar to a traffic accident. Therefore, the estimation unit 22 estimates the situation of a traffic accident by analyzing the dynamic change of the vibration pattern of the vibration detected by the detection unit 21.
[0025]
In the first embodiment, the return light received from the optical fibers 10A and 10B may be analyzed in real time to estimate the situation of a traffic accident, or the return light received from the optical fibers 10A and 10B may be estimated. The vibration data obtained by converting the light or its return light may be temporarily held, and then the return light or the vibration data may be read out and analyzed to estimate the situation of a traffic accident.
[0026]
Further, the estimation unit 22 estimates the time of occurrence of the traffic accident based on the time when the return light in which the vibration pattern caused by the traffic accident is detected from the optical fibers 10A and 10B is received by the detection unit 21. May be.
[0027]
Further, in the estimation unit 22, the time when the detection unit 21 incidents the pulsed light on the optical fibers 10A and 10B and the return light from which the vibration pattern caused by the traffic accident is detected from the optical fibers 10A and 10B are the detection units 21. The position where the traffic accident occurs (distance of the optical fibers 10A and 10B from the detection unit 21) may be estimated based on the time difference from the time received in. Specifically, the estimation unit 22 can measure the distances of the optical fibers 10A and 10B from the detection unit 21 to the position where the traffic accident occurs based on the above time difference. At this time, the estimation unit 22 uses the optical fibers 10A and 10 If a correspondence table in which the distance of B and the position (point) corresponding to the distance are associated with each other is held in advance, the position (point) where the traffic accident occurs can be estimated using the correspondence table. It will be possible.
[0028]
Subsequently, in the following, the estimation unit 22 will explain a specific method for estimating the situation of a traffic accident that occurred on the road R.
[0029]
(A) Method A
First, with reference to FIGS. 2 and 3, a method A for estimating the situation of a traffic accident occurring on the road R will be described.
[0030]
The detection unit 21 converts the return light received from the optical fiber 10B into vibration data as shown in FIG. 2, for example. The vibration data shown in FIG. 2 is vibration data of vibration detected by the optical fiber 10B at a certain position on the road R, and the horizontal axis indicates time and the vertical axis indicates sound intensity.
[0031]
The estimation unit 22 estimates the situation of a traffic accident based on the vibration data as shown in FIG. At this time, for example, the estimation unit 22 uses pattern matching. Specifically, the estimation unit 22 holds in advance vibration data according to the situation of a traffic accident as teacher data. The teacher data may be learned by the estimation unit 22 by machine learning or the like. Then, as shown in FIG. 3, the estimation unit 22 compares the vibration pattern of the vibration data converted by the detection unit 21 with the vibration pattern of the plurality of teacher data held in advance. When the estimation unit 22 matches the vibration pattern of any of the teacher data, the estimation unit 22 determines that the vibration data converted by the detection unit 21 is the vibration data generated in the traffic accident situation corresponding to the matched teacher data. do. In the example shown in FIG. 3, the vibration data converted by the detection unit 21 substantially matches the vibration data at the time of the collision accident and the vibration pattern. Therefore, the estimation unit 22 determines that a collision accident has occurred.
[0032]
(B) Method B
Subsequently, with reference to FIGS. 4 and 5, a method B for estimating the situation of a traffic accident occurring on the road R will be described.
The detection unit 21 converts the return light received from the optical fiber 10A into vibration data as shown in FIGS. 4 and 5, for example. The vibration data shown in FIGS. 4 and 5 are vibration data of vibration detected by the optical fiber 10A on the road R where two-way traffic is performed, and the horizontal axis is the distance of the optical fiber 10A from the detection unit 21 and the vertical axis is the vertical axis. However, it shows the passage of time. Further, the vertical axis becomes older data as it goes in the positive direction.
[0033]
In the vibration data shown in FIGS. 4 and 5, when the vibration of the vehicle traveling on the road R is detected by the optical fiber 10A, it is represented by a line that the vehicle is traveling. For example, the fact that one vehicle is traveling over time is represented by a single line diagonally. Here, the absolute value of the slope of the line represents the traveling speed of the vehicle. The smaller the absolute value of the slope of the line, the faster the traveling speed of the vehicle. The positive / negative of the slope of the line indicates the traveling direction of the vehicle. For example, when a positively inclined line represents a vehicle traveling in lane A, a negatively inclined line represents a vehicle traveling in lane B which is the opposite lane of lane A.
[0034]
The estimation unit 22 estimates the situation of a traffic accident based on the vibration data as shown in FIGS. 4 and 5.
[0035]
In the example of FIG. 4, the line L1 has a negative slope, while the line L2 has a positive slope. This means that the vehicle represented by the line L1 is traveling in the opposite lane to the lane in which the vehicle represented by the line L2 is traveling. At this time, both vehicles continue to travel even after passing the position P1 where the distances of the optical fibers 10A from the detection unit 21 are the same. Therefore, in the example of FIG. 4, the estimation unit 22 determines that a traffic accident such as a collision does not occur and the vehicles pass each other normally.
[0036]
On the other hand, in the example of FIG. 5, as in FIG. 4, the vehicle represented by the line L1 is traveling in the opposite lane to the lane in which the vehicle represented by the line L2 is traveling. However, both vehicles suddenly stop running without decelerating at the position P1 where the distances of the optical fibers 10A from the detection unit 21 are the same. Therefore, the estimation unit 22 determines that a head-on collision accident has occurred in the example of FIG.
[0037]
Also in this method B, the estimation unit 22 estimates the situation of a traffic accident based on the vibration data as shown in FIGS. 4 and 5 by using the same pattern matching as the above-mentioned method A. May be.
[0038]
(C) Method C
Subsequently, with reference to FIGS. 6 and 7, a method C for estimating the situation of a traffic accident occurring on the road R will be described.
The detection unit 21 converts the return light received from the optical fiber 10A into vibration data as shown in FIGS. 6 and 7, for example. The vibration data shown in FIGS. 6 and 7 focus on a specific vehicle traveling on the road R, and show the vibration data of the vehicle detected by the optical fiber 10A in chronological order.
[0039]
The estimation unit 22 estimates the situation of a traffic accident based on the vibration data as shown in FIGS. 6 and 7.
[0040]
In both the examples of FIGS. 6 and 7, a large peak P1 peculiar to a traffic accident occurs in the vibration data.
However, in the example of FIG. 6, the vibration is converged only by the occurrence of one peak P1. From this, it is probable that the vehicle that caused the traffic accident collided with something and stopped. Therefore, the estimation unit 22 determines that a relatively simple form of accident has occurred.
[0041]
On the other hand, in the example of FIG. 7, after the peak P1 is generated, relatively large peaks P2 and P3 are continuously generated. From this, it is considered that the vehicle in which the traffic accident has occurred collides with another vehicle or the like or rolls over, and the vibration at that time is generated as peaks P2 and P3. Therefore, the estimation unit 22 determines that a complicated type of collision accident such as a collision or a rollover of a plurality of vehicles has occurred. The estimation unit 22 may determine the number of vehicles in which a collision accident has occurred based on the number of peaks in the vibration data. In the example of FIG. 7, since three peaks P1 to P3 have occurred, the estimation unit 22 determines that if the collision of the peaks P1 is a collision between vehicles, a collision accident by at least four vehicles has occurred. do.
[0042]
Also in this method C, the estimation unit 22 estimates the situation of a traffic accident based on the vibration data as shown in FIGS. 6 and 7 by using the same pattern matching as in the above method A. Is also good.
[0043]
Here, the above-mentioned methods A to C are examples of estimating the types of traffic accidents (for example, single accidents, multiple collision accidents, etc.), the number of vehicles in which a traffic accident has occurred, and the like. However, the present invention is not limited to these examples, and the estimation unit 22 analyzes the vibration pattern, and the type of vehicle in which the traffic accident has occurred (for example, automobile, motorcycle, etc.), property damage (for example, damage to the traffic light, etc.), etc. May be estimated.
[0044]
Further, the estimation unit 22 may estimate the situation of a traffic accident by using the above-mentioned methods A to C in combination with each other. Here, in the above-mentioned method B and method C, the vibration directly transmitted to the road R is detected, whereas in the above-mentioned method A, the vibration is also detected as the sound transmitted from the road R through the air. Therefore, for example, the estimation unit 22 analyzes the collision sound of the above-mentioned method A, determines that a dull collision sound other than the collision sound between metals is generated, and detects the time and position and the above-mentioned method C. If the impact and the sudden deceleration position of the vehicle match, it is judged that there is a possibility of a personal injury caused by the vehicle colliding with a person.
[0045]
(D) Method D
Subsequently, with reference to FIG. 8, the method D for estimating the situation of the traffic accident that occurred on the road R will be described.
[0046]
In FIG. 8, a neural network (NN: Neural Network) having vibration data representing a time change of amplitude as shown in FIGS. 6 and 7 is input to NN # 1, and the spectrum after the vibration data is subjected to Fourier conversion is shown. The input NN is NN # 2, the NN to be input is the spectrum after the vibration data is Wavelet-converted, and the NN representing the fusion weight of NN # 1 to NN # 3 is NN # 4.
The estimation unit 22 comprehensively determines the three types of information of NN # 1 to NN # 3 and estimates the presence or absence of a traffic accident.
[0047]
Subsequently, with reference to FIG. 9, an operation example of the optical fiber sensing system according to the first embodiment will be described.
As shown in FIG. 9, the optical fibers 10A and 10B detect the vibration generated on the road R (step S11). The vibration detected by the optical fibers 10A and 10B affects the return light transmitted through the optical fibers 10A and 10B.
[0048]
Subsequently, the detection unit 21 detects the vibration pattern of the vibration caused by the traffic accident generated on the road R from the return light received from the optical fibers 10A and 10B (step S12).
[0049]
Subsequently, the estimation unit 22 estimates the time of occurrence of the traffic accident based on the time when the return light in which the vibration pattern caused by the traffic accident is detected is received from the optical fibers 10A and 10B. Further, the estimation unit 22 has a time difference between the time when the pulsed light is incident on the optical fibers 10A and 10B and the time when the return light is received from the optical fibers 10A and 10B in which the vibration pattern caused by the traffic accident is detected. Based on the above, the position where the traffic accident occurs is estimated (step S13).
[0050]
After that, the estimation unit 22 determines the type of traffic accident (for example, as the situation of the traffic accident occurring on the road R) based on the vibration pattern of the vibration caused by the traffic accident occurring on the road R detected by the detection unit 21. , Single accident, multiple collision accident, etc.), the number of vehicles that have caused a traffic accident, etc. (step S14).
[0051]
As described above, according to the first embodiment, the optical fibers 10A and 10B detect the vibration generated on the road R. The detection unit 21 detects the vibration pattern of the vibration caused by the traffic accident generated on the road R from the return light received from the optical fibers 10A and 10B. The estimation unit 22 estimates the situation of a traffic accident that occurred on the road R based on the vibration pattern. As a result, it is possible not only to grasp whether or not a traffic accident has occurred on the road R, but also to grasp the situation of the traffic accident that has occurred on the road R.
[0052]
Also, for example, if a microphone or camera is placed at an intersection, there is a possibility that a traffic accident can be detected from the impact sound collected by the microphone or the camera image taken by the camera. However, traffic accidents can only be detected by this method at intersections where microphones and cameras are located.
[0053]
On the other hand, according to the first embodiment, the optical fibers 10A and 10B can detect vibration at any place where the optical fibers 10A and 10B are laid. Therefore, it is possible to detect the occurrence of a traffic accident and grasp the situation of the traffic accident at any of the places where the optical fibers 10A and 10B are laid.
[0054]
Further, according to the first embodiment, the optical fibers 10A and 10B may be realized by existing optical fibers for communication. In this case, since it is not necessary to newly install the optical fibers 10A and 10B, the optical fiber sensing system can be constructed at low cost.
[0055]
Further, according to the first embodiment, the estimation unit 22 causes the traffic accident based on the time when the return light in which the vibration pattern caused by the traffic accident is detected is received from the optical fibers 10A and 10B. You may estimate the time. In this case, since the exact time of occurrence of the traffic accident can be grasped, it is possible to specify the display status of the traffic light at the time of occurrence of the traffic accident. As a result, even if the party involved in the traffic accident perjuries the manifestation situation, it can be determined to be perjury.
[0056]
According to the first embodiment, the vibration data of the vibration detected by the optical fiber 10A and the vibration data of the vibration detected by the optical fiber 10B as sound in order to estimate the situation of the traffic accident occurring on the road R. And, but it is not limited to this. When there is a temperature change on the road R, the temperature change also affects the return light transmitted by the optical fibers 10A and 10B. Therefore, the optical fibers 10A and 10B can also detect the temperature of the road R. Therefore, the detection unit 21 may convert the return light received from the optical fibers 10A and 10B into temperature data, and the estimation unit 22 may further use the temperature data to estimate the situation of a traffic accident. By using the temperature data, the estimation unit 22 can determine, for example, that the road R is frozen. Further, the estimation unit 22 can determine, for example, that a fire or an explosion has occurred on the road R by using the temperature data in combination with the vibration data. Therefore, for example, when the estimation unit 22 estimates a collision accident using vibration data, the collision accident is caused by freezing of the road R, a fire or an explosion occurring on the road R, for example, by further using the temperature data. It can be judged that it occurred.
[0057]

The optical fiber sensing system according to the second embodiment has the same configuration itself as the first embodiment described above, but has expanded the functions of the detection unit 21 and the estimation unit 22.
[0058]
The vibration pattern of the vibration generated on the road R also differs depending on the traveling state of the vehicle on the road R (for example, the traveling direction, the traveling speed, the number of traveling vehicles, the distance between vehicles, the presence or absence of traffic congestion, the presence or absence of dangerous driving, etc.). .. Vibration caused by the traveling state of the vehicle can be detected particularly by the optical fiber 10A embedded under the road R.
[0059]
In the second embodiment, the situation of the traffic accident is estimated by using not only the vibration pattern of the vibration caused by the traffic accident generated on the road R but also the vibration pattern of the vibration caused by the traveling state of the vehicle on the road R. It is something to do.
[0060]
As described above, the estimation unit 22 can specify the time and position of the traffic accident that occurred on the road R.
Therefore, the detection unit 21 is a vehicle near the position where the traffic accident occurs on the road R from the return light received from the optical fiber 10A at the time of the occurrence of the traffic accident or at least before or after the occurrence of the traffic accident. Further detect the vibration pattern of the vibration caused by the running condition.
[0061]
The estimation unit 22 is a road R at one of the vibration pattern of the vibration caused by the traffic accident that occurred on the road R detected by the detection unit 21 and the time, before, or after the occurrence of the traffic accident. The situation of the traffic accident that occurred on the road R is estimated based on the vibration pattern of the vibration caused by the running state of the vehicle near the position where the above traffic accident occurred. At this time, as described above, the vibration pattern of the vibration detected by the detection unit 21 includes a pattern peculiar to the traffic accident and also includes a peculiar pattern according to the traveling state of the vehicle on the road R. Therefore, the estimation unit 22 estimates the situation of a traffic accident by analyzing the dynamic change of the vibration pattern of the vibration detected by the detection unit 21.
[0062]
In the second embodiment, the return light received from the optical fibers 10A and 10B or the vibration data obtained by converting the return light is temporarily held, and then the return light or the vibration data is read out and analyzed to cause a traffic accident. The situation shall be estimated.
[0063]
Subsequently, with reference to FIGS. 10 and 11, a specific method for estimating the situation of a traffic accident occurring on the road R will be described in the estimation unit 22.
The upper figure of FIG. 10 shows the running state of the vehicle on the road R. Since the vibration caused by the traveling state of the vehicle is detected particularly by the optical fiber 10A, the illustration of the optical fiber 10B is omitted in the upper figure of FIG.
[0064]
The optical fiber 10A detects the vibration generated on the road R when the traveling state is as shown in the upper figure of FIG. 10, and the vibration affects the return light. The detection unit 21 receives the return light from the optical fiber 10A. The detection unit 21 converts the return light received from the optical fiber 10A into vibration data as shown in the lower figure of FIG. 10, for example.
[0065]
The estimation unit 22 estimates the situation of a traffic accident based on the vibration data as shown in the lower figure of FIG.
The horizontal axis and the vertical axis of the vibration data shown in the lower figure of FIG. 10 are the same as those shown in FIGS. 4 and 5. Therefore, even in the vibration data shown in the lower figure of FIG. 10, that one vehicle is traveling on the road R with the passage of time is represented by one diagonal line. Further, the absolute value of the slope of the line represents the traveling speed of the vehicle, and the positive / negative of the inclination of the line represents the traveling direction of the vehicle. Further, the distance G in the horizontal axis direction of the line represents the distance between vehicles, and the shorter the distance G, the shorter the distance between vehicles.
[0066]
In the vibration data shown in the lower figure of FIG. 10, in the vicinity of the center, the plurality of lines have a negative slope and a large absolute value, and the distance G between the lines is also short. This means that a plurality of vehicles are traveling in the same traveling direction, but the traveling speed is slow and the inter-vehicle distance is short. Therefore, it is considered that traffic congestion has occurred. On the other hand, it is considered that there is no congestion except near the center. In the example of the lower figure of FIG. 10, no traffic accident has occurred.
[0067]
Next, the vibration data of FIG. 11 converted by the same method as the lower figure of FIG. 10 will be described. The vibration data shown in FIG. 11 is vibration data of vibration detected by the optical fiber 10A on the road R where two-way traffic is performed.
[0068]
In the example of FIG. 11, the four vehicles represented by the lines L1 to L4 are traveling in the same traveling direction, but the traveling speed is slow and the inter-vehicle distance is short. Therefore, it is considered that traffic congestion has occurred. On the other hand, the vehicle represented by the line L5 is traveling in the opposite lane to the lane in which the four vehicles represented by the lines L1 to L4 are traveling. Further, the vehicle represented by the line L5 has stopped traveling at the position P1 where it is considered that the traffic jam has occurred. Therefore, in the example of FIG. 11, the estimation unit 22 determines that a traffic accident has occurred in which a vehicle head-on collides with a row of vehicles in a traffic jam from the opposite lane.
[0069]
In this method, the estimation unit 22 utilizes the same pattern matching as the method A described in the above-described first embodiment based on the vibration data as shown in the lower figure of FIG. 10 and FIG. , The situation of a traffic accident may be estimated.
[0070]
Here, in the above-mentioned method, it was estimated that the traffic jam occurred on the road R based on the vibration data as shown in the lower figure of FIG. 10 and FIG. However, the present invention is not limited to this example, and the estimation unit 22 has, for example, the presence or absence of a vehicle that is driving dangerously (for example, tilting driving, meandering driving, reverse driving, etc.), or the presence or absence of a vehicle that has been suddenly braked. May be estimated. For example, if there is a vehicle having a different traveling direction on the road R where one-sided traffic is performed, the estimation unit 22 can determine that the vehicle is driving in the reverse direction. Further, if there is a vehicle in which the distance between the vehicle and the vehicle in front of the vehicle continues to be short even though the estimation unit 22 is traveling at a traveling speed equal to or higher than the threshold value, the vehicle is driven in a tilted manner. It can be judged that there is. Further, the estimation unit 22 can determine that if there is a vehicle whose traveling speed has slowed down to the threshold value or more, that vehicle is suddenly braking.
[0071]
In addition, the estimation unit 22 estimates that traffic congestion has occurred after the occurrence of the traffic accident and that there is a vehicle that has escaped from the position where the traffic accident occurred by using the vibration data after the occurrence of the traffic accident. can do.
[0072]
Subsequently, with reference to FIG. 12, an operation example of the optical fiber sensing system according to the second embodiment will be described.
As shown in FIG. 12, the optical fibers 10A and 10B detect the vibration generated on the road R (step S21). The vibration detected by the optical fibers 10A and 10B affects the return light transmitted through the optical fibers 10A and 10B.
[0073]
Subsequently, the detection unit 21 detects the vibration pattern of the vibration caused by the traffic accident generated on the road R from the return light received from the optical fibers 10A and 10B (step S22).
Subsequently, the estimation unit 22 estimates the time of occurrence of the traffic accident based on the time when the return light in which the vibration pattern caused by the traffic accident is detected is received from the optical fibers 10A and 10B. Further, the estimation unit 22 has a time difference between the time when the pulsed light is incident on the optical fibers 10A and 10B and the time when the return light is received from the optical fibers 10A and 10B in which the vibration pattern caused by the traffic accident is detected. Based on the above, the position where the traffic accident occurs is estimated (step S23).
[0074]
Subsequently, the detection unit 21 is a vehicle near the position where the traffic accident occurred on the road R from the return light received from the optical fiber 10A at the time of the occurrence of the traffic accident or at least before or after the occurrence of the traffic accident. The vibration pattern of the vibration caused by the traveling state of the vehicle is detected (step S24).
[0075]
After that, the estimation unit 22 determines that the vibration pattern of the vibration caused by the traffic accident that occurred on the road R detected by the detection unit 21 and the vibration pattern at the time of occurrence of the traffic accident or at least before or after the occurrence of the traffic accident. The following is estimated based on the vibration pattern of the vibration caused by the traveling state of the vehicle near the position where the traffic accident occurs on the road R (step S25).
・ Driving conditions of vehicles near the location of the traffic accident on the road R (for example, whether there is a traffic jam, etc.)
・ Driving conditions of a specific vehicle on the road R (for example, tilting driving, meandering driving, reverse driving, etc.)
-Status of traffic accidents that occurred on Road R (for example, the type of traffic accident, the number of vehicles that caused the traffic accident, etc.)
[0076]
As described above, according to the second embodiment, the detection unit 21 detects the vibration pattern of the vibration caused by the traffic accident generated on the road R from the return light received from the optical fibers 10A and 10B, and also detects the vibration pattern. Vibration caused by the running condition of the vehicle near the position where the traffic accident occurred on the road R from the return light received from the optical fiber 10A at the time of the occurrence of the traffic accident or at least before or after the occurrence of the traffic accident. Detect vibration patterns. The estimation unit 22 estimates the situation of a traffic accident that occurred on the road R based on those vibration patterns. This makes it possible to grasp the situation of the traffic accident that occurred on the road R in more detail. Other effects are the same as those in the first embodiment described above.
[0077]
In the second embodiment as well, the estimation unit 22 may further use the temperature data to estimate the situation of the traffic accident, as in the first embodiment described above.
[0078]

Subsequently, with reference to FIG. 13, a configuration example of the optical fiber sensing system according to the third embodiment will be described. In the following description, the third embodiment will be described as having a configuration in which a function is added to the first embodiment described above, but the third embodiment has a function in the second embodiment described above. Needless to say, the added configuration is also acceptable.
[0079]
As shown in FIG. 13, the optical fiber sensing system according to the third embodiment is different in that the camera 30 is added as compared with the first embodiment described above. Although only one camera 30 is provided in FIG. 13, a plurality of cameras 30 may be provided.
[0080] [0080]
The camera 30 is a camera that captures the road R, and is realized by, for example, a fixed camera, a PTZ (Pan Tilt Zoom) camera, or the like.
[0081]
The estimation unit 22 determines the installation position of the camera 30 (distance of the optical fibers 10A and 10B from the detection unit 21, latitude and longitude of the installation position of the camera 30, etc.), and a position (latitude and longitude, etc.) that defines the imageable area of ​​the camera 30. Holds camera information indicating such as. Further, as described above, the estimation unit 22 can estimate the occurrence time and the occurrence position (distance of the optical fibers 10A and 10B from the detection unit 21) of the traffic accident that occurred on the road R.
[0082]
Therefore, when a traffic accident occurs in the imageable area of ​​the camera 30 on the road R, the estimation unit 22 estimates the time and position of the traffic accident. Then, the estimation unit 22 acquires a camera image near the position where the traffic accident occurs at the time of the occurrence of the traffic accident or at least one before or after the occurrence of the traffic accident from the camera images taken by the camera 30. However, in order to acquire a camera image near the location where a traffic accident occurred, traffic Therefore, it is necessary to perform a process of converting the generated position to a position on the camera image. Therefore, for example, the estimation unit 22 holds in advance a correspondence table for associating the distances of the optical fibers 10A and 10B from the detection unit 21 with the camera coordinates, and even if the above-mentioned position conversion is performed using this correspondence table. good. Further, the estimation unit 22 may acquire the above-mentioned camera images from each of the plurality of cameras 30 as long as the vicinity of the position where the traffic accident occurs can be photographed by the plurality of cameras 30.
[0083]
Then, the estimation unit 22 determines the traffic generated on the road R based on the vibration pattern of the vibration caused by the traffic accident generated on the road R detected by the detection unit 21 and the camera image acquired above. Estimate the situation of the accident.
[0084]
For example, it is assumed that the estimation unit 22 estimates a collision accident or the like based on a vibration pattern of vibration caused by a traffic accident. In this case, the estimation unit 22 further identifies the number of the vehicle in which the collision accident or the like has occurred based on the camera image, or the occurrence of the traffic accident at the time of the occurrence of the traffic accident or at least one before or after the occurrence of the traffic accident. It is possible to estimate the situation of the position. The situation of the position where the traffic accident occurs estimated based on the camera image is, for example, a vehicle that is driving dangerously (for example, driving ignoring traffic signs such as tilting driving, meandering driving, reverse driving, and temporary stop). Whether or not there is a vehicle, whether or not there is a vehicle driving aside or dozing, and whether or not there is a traffic jam.
[0085]
In the third embodiment, the return light received from the optical fibers 10A and 10B or the vibration data obtained by converting the return light and the camera image taken by the camera 30 are temporarily held, and then returned. The light or vibration data and the camera image shall be read and analyzed to estimate the situation of the traffic accident.
[0086]
Further, in the third embodiment, the estimation unit 22 may estimate the situation of the traffic accident occurring on the road R by using the NN as in the method D of the first embodiment described above. This method will be described with reference to FIG.
[0087]
In FIG. 14, NN is NN # 1 for inputting vibration data representing the correlation between time and position of amplitude, which is vibration data of a specific vehicle traveling on the road R, and a camera image of the road R is input. Let NN # 2 be NN, and NN # 3 be NN representing the fusion weight of NN # 1 to NN # 2.
[0088]
The estimation unit 22 comprehensively determines two types of information, NN # 1 and NN # 2, and estimates whether or not a traffic accident has occurred. For example, even if the estimation unit 22 estimates that a traffic accident has occurred based on the information of NN # 1 detected by the optical fiber 10A, if the information of NN # 2 does not show the car in the camera image, it is determined to be an erroneous estimation. do. As described above, the camera image can also be used as auxiliary information for estimating the presence or absence of a traffic accident.
[0089]
Subsequently, with reference to FIG. 15, an operation example of the optical fiber sensing system according to the third embodiment will be described.
As shown in FIG. 15, the optical fibers 10A and 10B detect the vibration generated on the road R (step S31). The vibration detected by the optical fibers 10A and 10B affects the return light transmitted through the optical fibers 10A and 10B.
[0090]
Subsequently, the detection unit 21 detects the vibration pattern of the vibration caused by the traffic accident generated on the road R from the return light received from the optical fibers 10A and 10B (step S32).
Subsequently, the estimation unit 22 estimates the time of occurrence of the traffic accident based on the time when the return light in which the vibration pattern caused by the traffic accident is detected is received from the optical fibers 10A and 10B. Further, the estimation unit 22 has a time difference between the time when the pulsed light is incident on the optical fibers 10A and 10B and the time when the return light is received from the optical fibers 10A and 10B in which the vibration pattern caused by the traffic accident is detected. Based on the above, the position where the traffic accident occurs is estimated (step S33).
[0091]
Subsequently, the estimation unit 22 acquires a camera image near the position where the traffic accident occurred at the time of the occurrence of the traffic accident or at least one before or after the occurrence of the traffic accident from the camera images taken by the camera 30 (step). S34).
[0092]
After that, the estimation unit 22 determines the vibration pattern of the vibration caused by the traffic accident that occurred on the road R detected by the detection unit 21, and the traffic accident at the time of the occurrence of the traffic accident or at least one before or after the occurrence of the traffic accident. The situation of the traffic accident that occurred on the road R is estimated based on the camera image in the vicinity of the occurrence position of the road R (step S35).
[0093]
As described above, according to the third embodiment, the detection unit 21 detects the vibration pattern of the vibration caused by the traffic accident generated on the road R from the return light received from the optical fibers 10A and 10B. The estimation unit 22 acquires a camera image near the position where the traffic accident occurs at the time of the occurrence of the traffic accident, or at least one before or after the occurrence of the traffic accident, from the camera images taken by the camera 30. Then, the estimation unit 22 estimates the situation of the traffic accident that occurred on the road R based on those vibration patterns and the camera image. This makes it possible to grasp the situation of the traffic accident that occurred on the road R in more detail. Other effects are the same as those in the first embodiment described above.
[0094]
Note that the estimation unit 22 may acquire a camera image near the position where the traffic accident occurred after the occurrence of the traffic accident as follows. For example, when a traffic accident occurs, the estimation unit 22 controls the angle (azimuth angle, elevation angle), zoom magnification, etc. of the camera 30 so as to take a picture near the position where the traffic accident occurs, and then takes a picture with the camera 30. Get the camera image. At this time, a process of converting the position where the traffic accident occurs to the position on the camera image is required, and this position conversion may be performed by the method using the corresponding table described above.
[0095]
Further, in the above description, the present embodiment 3 has been described as having a configuration in which a function is added to the above-mentioned embodiment 1, but as described above, the present embodiment 3 has the above-mentioned embodiment. A configuration in which a function is added to the second form may be used. In this case, the estimation unit 22 has the vibration pattern of the vibration caused by the traffic accident generated on the road R detected by the detection unit 21, and the road at the time of the occurrence of the traffic accident or at least one before or after the occurrence of the traffic accident. The situation of the traffic accident may be estimated based on the vibration pattern of the vibration caused by the running state of the vehicle near the position where the traffic accident occurs on R and the above-mentioned camera image.
[0096]

The optical fiber sensing device 20 may further include a prediction unit 23 as shown in FIG.
The prediction unit 23 analyzes the running state of the vehicle on the road R and predicts the occurrence of a traffic accident. For example, when the prediction unit 23 detects a vehicle that is driving in a tilted manner, a vehicle whose traveling speed is faster than a threshold value, or a vehicle whose traveling speed is slower than a threshold value, it may predict that a traffic accident will occur.
[0097]
Further, the prediction unit 23 may analyze statistical data of the traveling state of the vehicle on the road R to identify a place where a traffic accident is likely to occur. For example, the prediction unit 23 may specify a place where the vehicle often applies a sudden brake as a place where a traffic accident is likely to occur.
[0098]
Further, the optical fiber sensing device 20 may further include a notification unit 24 as shown in FIG.
When a traffic accident occurs on the road R, the notification unit 24 notifies that the traffic accident has occurred and also notifies the status of the traffic accident estimated by the estimation unit 22. For example, if the road R is a general road, the notification unit 24 notifies the police and the fire department, and if the road R is a highway, the notification unit 24 notifies the highway management company. Further, this notification may be an acoustic output of the corresponding message or a display output.
[0099]
Further, the notification unit 24 may determine the urgency according to the situation of the traffic accident, and may change the notification destination and the notification content according to the determined urgency. For example, the notification unit 24 may increase the degree of urgency when a person is screaming or when the number of vehicles in which a traffic accident has occurred is large. Further, as shown in Table 1, the notification unit 24 holds in advance a correspondence table in which the urgency is associated with the notification destination and the notification content, and uses the correspondence table to respond to the urgency. You may specify the notification destination and notification content. In the example of Table 1, the larger the value, the higher the urgency, and when the urgency becomes higher, the police are requested to increase the number of police cars.
[table 1]

[0100]
Further, the optical fiber sensing device 20 may be configured to include both the prediction unit 23 shown in FIG. 16 and the notification unit 24 shown in FIG. Further, the optical fiber sensing device 20 may be configured to be connected to the camera 30 shown in FIG.
[0101]
Further, in the examples of FIGS. 1, 13, 16 and 17, the optical fiber sensing device 20 is provided with a plurality of components (detection unit 21, estimation unit 22, prediction unit 23, and notification unit 24). However, it is not limited to this. The components provided in the optical fiber sensing device 20 are not limited to being provided in one device, and may be distributed in a plurality of devices.
[0102]

Subsequently, with reference to FIG. 18, the configuration of the optical fiber sensing system conceptually showing the above-described embodiment will be described.
[0103]
The optical fiber sensing system shown in FIG. 18 includes an optical fiber 10 and an optical fiber sensing device 20. Further, the optical fiber sensing device 20 includes a detection unit 21 and an estimation unit 22.
[0104]
The optical fiber 10 is provided along the road R and detects vibration. For example, the optical fiber 10 may be provided in the vicinity of the road R or may be laid on the road R. Further, the optical fiber 10 may be buried under the road R or may be overhead-wired.
[0105]
The detection unit 21 incidents pulsed light on the optical fiber 10 and receives reflected light or scattered light generated by the pulsed light being transmitted through the optical fiber 10 as return light via the optical fiber 10. .. Further, the detection unit 21 detects the vibration pattern of the vibration caused by the traffic accident generated on the road R from the optical signal received from the optical fiber 10.
[0106]
The estimation unit 22 estimates the situation of a traffic accident that occurred on the road R based on the vibration pattern of the vibration caused by the traffic accident detected by the detection unit 21.
[0107]
Subsequently, an operation example of the optical fiber sensing system shown in FIG. 18 will be described with reference to FIG.
As shown in FIG. 19, the optical fiber 10 detects the vibration generated on the road R (step S41). The vibration detected in the optical fiber 10 affects the return light transmitted through the optical fiber 10.
[0108]
Subsequently, the detection unit 21 detects the vibration pattern of the vibration caused by the traffic accident generated on the road R from the return light received from the optical fiber 10 (step S42).
After that, the estimation unit 22 estimates the state of the traffic accident that occurred on the road R based on the vibration pattern of the vibration caused by the traffic accident that occurred on the road R, which was detected by the detection unit 21 (step S43).
[0109]
By the above operation, it is possible not only to grasp whether or not a traffic accident has occurred on the road R, but also to grasp the situation of the traffic accident that has occurred on the road R.
[0110]

Subsequently, with reference to FIG. 20, a hardware configuration example of the computer 40 that realizes the optical fiber sensing device 20 will be described. Here, a case where the optical fiber sensing device 20 having the configuration of the first embodiment described above is realized will be described as an example.
[0111]
As shown in FIG. 20, the computer 40 includes a processor 401, a memory 402, a storage 403, an input / output interface (input / output I / F) 404, a communication interface (communication I / F) 405, and the like. The processor 401, the memory 402, the storage 403, the input / output interface 404, and the communication interface 405 are mutually configured.It is connected by a data transmission line for transmitting and receiving data.
[0112]
The processor 401 is, for example, an arithmetic processing unit such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit). The memory 402 is, for example, a memory such as a RAM (Random Access Memory) or a ROM (Read Only Memory). The storage 403 is, for example, a storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), or a memory card. Further, the storage 403 may be a memory such as a RAM or a ROM.
[0113]
The storage 403 stores a program that realizes the functions of the components (detection unit 21 and estimation unit 22) included in the optical fiber sensing device 20. By executing each of these programs, the processor 401 realizes the functions of the components included in the optical fiber sensing device 20. Here, when the processor 401 executes each of the above programs, these programs may be read on the memory 402 and then executed, or may be executed without being read on the memory 402. Further, the memory 402 and the storage 403 also play a role of storing information and data held by the components included in the optical fiber sensing device 20.
[0114]
Further, the above-mentioned program is stored by using various types of non-transitory computer readable medium and can be supplied to a computer (including a computer 40). Non-temporary computer-readable media include various types of tangible storage media. Examples of non-temporary computer readable media include magnetic recording media (eg, flexible disks, magnetic tapes, hard disk drives), optomagnetic recording media (eg, optomagnetic disks), CD-ROMs (Compact Disc-ROMs), CDs. -R (CD-Recordable), CD-R / W (CD-ReWritable), semiconductor memory (for example, mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, RAM. , May be supplied to the computer by various types of transient computer readable media. Examples of transient computer readable media include electrical signals, optical signals, and electromagnetic waves. The computer-readable medium can supply the program to the computer via a wired communication path such as an electric wire and an optical fiber, or a wireless communication path.
[0115]
The input / output interface 404 is connected to a display device 4041, an input device 4042, a sound output device 4043, and the like. The display device 4041 is a device that displays a screen corresponding to drawing data processed by the processor 401, such as an LCD (Liquid Crystal Display), a CRT (Cathode Ray Tube) display, and a monitor. The input device 4042 is a device that receives an operator's operation input, and is, for example, a keyboard, a mouse, a touch sensor, and the like. The display device 4041 and the input device 4042 may be integrated and realized as a touch panel. The sound output device 4043 is a device such as a speaker that acoustically outputs sound corresponding to acoustic data processed by the processor 401.
[0116]
The communication interface 405 sends and receives data to and from an external device. For example, the communication interface 405 communicates with an external device via a wired communication path or a wireless communication path.
[0117]
Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various changes that can be understood by those skilled in the art can be made to the structure and details of the present disclosure within the scope of the present disclosure.
For example, the above-described embodiment may be used in combination in part or in whole.
[0118]
Further, a part or all of the above embodiments may be described as in the following appendix, but the present invention is not limited to the following.
(Appendix 1)
An optical fiber installed along the road to detect vibration,
A detection unit that detects the vibration pattern of vibration caused by a traffic accident that occurred on the road from the optical signal received from the optical fiber.
Based on the vibration pattern, the estimation unit that estimates the situation of the traffic accident and
An optical fiber sensing system equipped with.
(Appendix 2)
The estimation unit estimates the time of occurrence of the traffic accident based on the time when the optical signal in which the vibration pattern is detected is received from the optical fiber.
The optical fiber sensing system described in Appendix 1.
(Appendix 3)
The detection unit receives the optical signal for the incident light incident on the optical fiber, and receives the optical signal.
The estimation unit determines the traffic accident based on the time difference between the time when the incident light is incident on the optical fiber and the time when the optical signal in which the vibration pattern is detected is received from the optical fiber. Estimate the position of occurrence of
The optical fiber sensing system described in Appendix 2.
(Appendix 4)
The vibration pattern further includes a vibration pattern of vibration caused by a running state of a vehicle near the position where the traffic accident occurs on the road at the time of occurrence or before the occurrence of the traffic accident.
The estimation unit estimates the situation of the traffic accident based on the vibration pattern.
The optical fiber sensing system described in Appendix 3.
(Appendix 5)
The vibration pattern further includes a vibration pattern of vibration caused by a running state of a vehicle near the position where the traffic accident occurs on the road after the occurrence of the traffic accident.
The estimation unit estimates the situation of the traffic accident based on the vibration pattern.
The optical fiber sensing system according to Appendix 3 or 4.
(Appendix 6)
Equipped with a camera to shoot the road,
The estimation unit is
From the camera images taken by the camera, a camera image near the position where the traffic accident occurred on the road at the time of the occurrence of the traffic accident, or at least one before or after the occurrence of the traffic accident is acquired. ,
The situation of the traffic accident is estimated based on the vibration pattern and the acquired camera image.
The optical fiber sensing system described in Appendix 3.
(Appendix 7)
Equipped with a camera to shoot the road,
The estimation unit is
From the camera images taken by the camera, a camera image near the position where the traffic accident occurred on the road at the time of the occurrence of the traffic accident, or at least one before or after the occurrence of the traffic accident is acquired. ,
The situation of the traffic accident is estimated based on the vibration pattern and the acquired camera image.
The optical fiber sensing system according to Appendix 4 or 5.
(Appendix 8)
The optical fiber is
The first optical fiber buried under the road and
The second optical fiber that is overhead wired along the road,
The optical fiber sensing system according to any one of Supplementary note 1 to 7, including.
(Appendix 9)
It is a road monitoring method using an optical fiber sensing system.
The optical fiber installed along the road has a step to detect vibration,
A detection step that detects the vibration pattern of vibration caused by a traffic accident that occurred on the road from the optical signal received from the optical fiber.
The estimation step for estimating the situation of the traffic accident based on the vibration pattern,
Road monitoring method including.
(Appendix 10)
In the estimation step, the time of occurrence of the traffic accident is estimated based on the time when the optical signal in which the vibration pattern is detected is received from the optical fiber.
The road monitoring method described in Appendix 9.
(Appendix 11)
In the detection step, the optical signal for the incident light incident on the optical fiber is received, and the optical signal is received.
In the estimation step, the traffic accident is based on the time difference between the time when the incident light is incident on the optical fiber and the time when the optical signal in which the vibration pattern is detected is received from the optical fiber. Estimate the position of occurrence of
The road monitoring method described in Appendix 10.
(Appendix 12)
The vibration pattern further includes a vibration pattern of vibration caused by a running state of a vehicle near the position where the traffic accident occurs on the road at the time of occurrence or before the occurrence of the traffic accident.
In the estimation step, the situation of the traffic accident is estimated based on the vibration pattern.
The road monitoring method described in Appendix 11.
(Appendix 13)
The vibration pattern further includes a vibration pattern of vibration caused by a running state of a vehicle near the position where the traffic accident occurs on the road after the occurrence of the traffic accident.
In the estimation step, the situation of the traffic accident is estimated based on the vibration pattern.
The road monitoring method described in Appendix 11 or 12.
(Appendix 14)
In the estimation step,
From the camera images taken by the camera that captures the road, a camera near the position where the traffic accident occurred on the road at least one at the time of the occurrence of the traffic accident, before, or after the occurrence of the traffic accident. Get the image,
The situation of the traffic accident is estimated based on the vibration pattern and the acquired camera image.
The road monitoring method described in Appendix 11.
(Appendix 15)
In the estimation step,
From the camera images taken by the camera that captures the road, a camera near the position where the traffic accident occurred on the road at least one at the time of the occurrence of the traffic accident, before, or after the occurrence of the traffic accident. Get the image,
The situation of the traffic accident is estimated based on the vibration pattern and the acquired camera image.
The road monitoring method described in Appendix 12 or 13.
(Appendix 16)
The optical fiber is
The first optical fiber buried under the road and
The second optical fiber that is overhead wired along the road,
The road monitoring method according to any one of Supplementary note 9 to 15, including.
(Appendix 17)
A detection unit that detects the vibration pattern of vibration caused by a traffic accident that occurred on the road from an optical signal provided along the road and received from an optical fiber that detects vibration.
Based on the vibration pattern, the estimation unit that estimates the situation of the traffic accident and
An optical fiber sensing device equipped with.
(Appendix 18)
The estimation unit estimates the time of occurrence of the traffic accident based on the time when the optical signal in which the vibration pattern is detected is received from the optical fiber.
The optical fiber sensing device described in Appendix 17.
(Appendix 19)
The detection unit receives the optical signal for the incident light incident on the optical fiber, and receives the optical signal.
The estimation unit determines the traffic accident based on the time difference between the time when the incident light is incident on the optical fiber and the time when the optical signal in which the vibration pattern is detected is received from the optical fiber. Estimate the position of occurrence of
The optical fiber sensing device according to Appendix 18.
(Appendix 20)
The vibration pattern further includes a vibration pattern of vibration caused by a running state of a vehicle near the position where the traffic accident occurs on the road at the time of occurrence or before the occurrence of the traffic accident.
The estimation unit estimates the situation of the traffic accident based on the vibration pattern.
The optical fiber sensing device described in Appendix 19.
(Appendix 21)
The vibration pattern further includes a vibration pattern of vibration caused by a running state of a vehicle near the position where the traffic accident occurs on the road after the occurrence of the traffic accident.
The estimation unit estimates the situation of the traffic accident based on the vibration pattern.
The optical fiber sensing device according to Appendix 19 or 20.
((Appendix 22)
The estimation unit is
From the camera images taken by the camera that captures the road, a camera near the position where the traffic accident occurred on the road at least one at the time of the occurrence of the traffic accident, before, or after the occurrence of the traffic accident. Get the image,
The situation of the traffic accident is estimated based on the vibration pattern and the acquired camera image.
The optical fiber sensing device described in Appendix 19.
(Appendix 23)
The estimation unit is
From the camera images taken by the camera that captures the road, a camera near the position where the traffic accident occurred on the road at least one at the time of the occurrence of the traffic accident, before, or after the occurrence of the traffic accident. Get the image,
The situation of the traffic accident is estimated based on the vibration pattern and the acquired camera image.
The optical fiber sensing device according to Appendix 20 or 21.
Code description
[0119]
10,10A, 10B optical fiber
20 Optical fiber sensing equipment
21 Detection unit
22 Estimator
23 Prediction department
24 Notification section
30 camera
40 computer
401 processor
402 memory
403 storage
404 I / O interface
4041 Display device
4042 input device
4043 Sound output device
405 communication interface
R road
T utility pole
The scope of the claims
[Claim 1]
An optical fiber installed along the road to detect vibration,
A detection unit that detects the vibration pattern of vibration caused by a traffic accident that occurred on the road from the optical signal received from the optical fiber.
Based on the vibration pattern, the estimation unit that estimates the situation of the traffic accident and
An optical fiber sensing system equipped with.
[Claim 2]
The estimation unit estimates the time of occurrence of the traffic accident based on the time when the optical signal in which the vibration pattern is detected is received from the optical fiber.
The optical fiber sensing system according to claim 1.
[Claim 3]
The detection unit receives the optical signal for the incident light incident on the optical fiber, and receives the optical signal.
The estimation unit determines the traffic accident based on the time difference between the time when the incident light is incident on the optical fiber and the time when the optical signal in which the vibration pattern is detected is received from the optical fiber. Estimate the position of occurrence of
The optical fiber sensing system according to claim 2.
[Claim 4]
The vibration pattern further includes a vibration pattern of vibration caused by a running state of a vehicle near the position where the traffic accident occurs on the road at the time of occurrence or before the occurrence of the traffic accident.
The estimation unit estimates the situation of the traffic accident based on the vibration pattern.
The optical fiber sensing system according to claim 3.
[Claim 5]
The vibration pattern further includes a vibration pattern of vibration caused by a running state of a vehicle near the position where the traffic accident occurs on the road after the occurrence of the traffic accident.
The estimation unit estimates the situation of the traffic accident based on the vibration pattern.
The optical fiber sensing system according to claim 3 or 4.
[Claim 6]
Equipped with a camera to shoot the road,
The estimation unit is
From the camera images taken by the camera, a camera image near the position where the traffic accident occurred on the road at the time of the occurrence of the traffic accident, or at least one before or after the occurrence of the traffic accident is acquired. ,
The situation of the traffic accident is estimated based on the vibration pattern and the acquired camera image.
The optical fiber sensing system according to claim 3.
[Claim 7]
Equipped with a camera to shoot the road,
The estimation unit is
From the camera images taken by the camera, a camera image near the position where the traffic accident occurred on the road at the time of the occurrence of the traffic accident, or at least one before or after the occurrence of the traffic accident is acquired. ,
The situation of the traffic accident is estimated based on the vibration pattern and the acquired camera image.
The optical fiber sensing system according to claim 4 or 5.
[Claim 8]
The optical fiber is
The first optical fiber buried under the road and
The second optical fiber that is overhead wired along the road,
The optical fiber sensing system according to any one of claims 1 to 7, including.
[Claim 9]
It is a road monitoring method using an optical fiber sensing system.
The optical fiber installed along the road has a step to detect vibration,
A detection step that detects the vibration pattern of vibration caused by a traffic accident that occurred on the road from the optical signal received from the optical fiber.
The estimation step for estimating the situation of the traffic accident based on the vibration pattern,
Road monitoring method including.
[Claim 10]
In the estimation step, the time of occurrence of the traffic accident is estimated based on the time when the optical signal in which the vibration pattern is detected is received from the optical fiber.
The road monitoring method according to claim 9.
[Claim 11]
In the detection step, the optical signal for the incident light incident on the optical fiber is received, and the optical signal is received.
In the estimation step, the traffic accident is based on the time difference between the time when the incident light is incident on the optical fiber and the time when the optical signal in which the vibration pattern is detected is received from the optical fiber. Estimate the position of occurrence of
The road monitoring method according to claim 10.
[Claim 12]
The vibration pattern further includes a vibration pattern of vibration caused by a running state of a vehicle near the position where the traffic accident occurs on the road at the time of occurrence or before the occurrence of the traffic accident.
In the estimation step, the situation of the traffic accident is estimated based on the vibration pattern.
The road monitoring method according to claim 11.
[Claim 13]
The vibration pattern further includes a vibration pattern of vibration caused by a running state of a vehicle near the position where the traffic accident occurs on the road after the occurrence of the traffic accident.
In the estimation step, the situation of the traffic accident is estimated based on the vibration pattern.
The road monitoring method according to claim 11 or 12.
[Claim 14]
In the estimation step,
From the camera images taken by the camera that captures the road, a camera near the position where the traffic accident occurred on the road at least one at the time of the occurrence of the traffic accident, before, or after the occurrence of the traffic accident. Get the image,
The situation of the traffic accident is estimated based on the vibration pattern and the acquired camera image.
The road monitoring method according to claim 11.
[Claim 15]
In the estimation step,
From the camera images taken by the camera that captures the road, a camera near the position where the traffic accident occurred on the road at least one at the time of the occurrence of the traffic accident, before, or after the occurrence of the traffic accident. Get the image,
The situation of the traffic accident is estimated based on the vibration pattern and the acquired camera image.
The road monitoring method according to claim 12 or 13.
[Claim 16]
The optical fiber is
The first optical fiber buried under the road and
The second optical fiber that is overhead wired along the road,
The road monitoring method according to any one of claims 9 to 15, including.
[Claim 17]
A detection unit that detects the vibration pattern of vibration caused by a traffic accident that occurred on the road from an optical signal provided along the road and received from an optical fiber that detects vibration.
Based on the vibration pattern, the estimation unit that estimates the situation of the traffic accident and
An optical fiber sensing device equipped with.
[Claim 18]
The estimation unit estimates the time of occurrence of the traffic accident based on the time when the optical signal in which the vibration pattern is detected is received from the optical fiber.
The optical fiber sensing device according to claim 17.
[Claim 19]
The detection unit receives the optical signal for the incident light incident on the optical fiber, and receives the optical signal.
The estimation unit determines the traffic accident based on the time difference between the time when the incident light is incident on the optical fiber and the time when the optical signal in which the vibration pattern is detected is received from the optical fiber. Estimate the position of occurrence of
The optical fiber sensing device according to claim 18.
[Claim 20]
The vibration pattern further includes a vibration pattern of vibration caused by a running state of a vehicle near the position where the traffic accident occurs on the road at the time of occurrence or before the occurrence of the traffic accident.
The estimation unit estimates the situation of the traffic accident based on the vibration pattern.
The optical fiber sensing device according to claim 19.
[Claim 21]
The vibration pattern further includes a vibration pattern of vibration caused by a running state of a vehicle near the position where the traffic accident occurs on the road after the occurrence of the traffic accident.
The estimation unit estimates the situation of the traffic accident based on the vibration pattern.
The optical fiber sensing device according to claim 19 or 20.
[Claim 22]
The estimation unit is
From the camera images taken by the camera that captures the road, a camera near the position where the traffic accident occurred on the road at least one at the time of the occurrence of the traffic accident, before, or after the occurrence of the traffic accident. Get the image,
The situation of the traffic accident is estimated based on the vibration pattern and the acquired camera image.
The optical fiber sensing device according to claim 19.
[Claim 23]
The estimation unit is
From the camera images taken by the camera that captures the road, a camera near the position where the traffic accident occurred on the road at least one at the time of the occurrence of the traffic accident, before, or after the occurrence of the traffic accident. Get the image,
The situation of the traffic accident is estimated based on the vibration pattern and the acquired camera image.
The optical fiber sensing device according to claim 20 or 21.