Road surface marking deterioration analysis device, method, and program

Abstract

Provided is a road marking deterioration analysis device capable of providing information useful for maintenance and management of roads to a user such as a road administrator. A road marking detection means (11) detects a road marking on a road on the basis of sensor information obtained by sensing the road. An interruption detection means (12) detects a location at which the road marking has been interrupted on the basis of the detection result of the road marking. A factor determination means (13) determines a cause for the interruption of the road marking for the location at which the interruption of the road marking is detected.

Description

Technical Field

[0001] The present disclosure relates to a road marking deterioration analysis apparatus, method, and computer-readable medium.

Background Art

[0002] As related art, Patent Document 1 discloses a road marking body deterioration detection apparatus. The road marking body deterioration detection apparatus acquires a camera image in which a crosswalk is photographed from an obliquely upper direction from a camera. The road marking body deterioration detection apparatus trims the area of the crosswalk from the acquired camera image. The road marking body deterioration detection apparatus corrects the image of the trimmed crosswalk area into an overhead view using a homography transformation. The road marking body deterioration detection apparatus calculates the peeling rate of the white line in the crosswalk from the corrected overhead view-like corrected image, and determines whether the white line area in the crosswalk is deteriorated.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In Patent Document 1, the peeling rate of the white line is calculated according to the ratio of "white" and "black" in the white line area, and when the peeling rate is high, it is determined that the white line is deteriorated. However, in Patent Document 1, even when the white line is not actually deteriorated, if the proportion of "black" in the image is large, it is determined that the white line is deteriorated. In this case, a user such as a road administrator may receive an incorrect determination result from the road marking body deterioration detection apparatus described in Patent Document 1, and may formulate a road maintenance plan or management plan based on the incorrect determination result.

[0005] In view of the above circumstances, an object of the present disclosure is to provide a road marking deterioration analysis device that can provide users such as road administrators with information useful for road maintenance and management.

Means for Solving the Problems

[0006] To achieve the above object, the present disclosure provides, as a first aspect, a road marking deterioration analysis device. The road marking deterioration analysis device includes a road marking detection means for detecting road markings on a road based on sensor information obtained by sensing the road, a break detection means for detecting a location where the road marking is broken based on the detection result of the road marking, and a cause determination means for determining a cause of the break of the road marking for a location where it is detected that the road marking is broken.

[0007] The present disclosure provides, as a second aspect, a road marking deterioration analysis method. The road marking deterioration analysis method includes detecting road markings on a road based on sensor information obtained by sensing the road, detecting a location where the road marking is broken based on the detection result of the road marking, and determining a cause of the break of the road marking for a location where it is detected that the road marking is broken.

[0008] The present disclosure provides, as a third aspect, a computer-readable medium. The computer-readable medium stores a program for causing a computer to execute a process including detecting road markings on a road based on sensor information obtained by sensing the road, detecting a location where the road marking is broken based on the detection result of the road marking, and determining a cause of the break of the road marking for a location where it is detected that the road marking is broken.

Effects of the Invention

[0009] The road marking deterioration analysis device, method, and computer-readable medium according to the present disclosure can provide users such as road administrators with information useful for road maintenance and management.

Brief Description of the Drawings

[0010]

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DETAILED DESCRIPTION OF THE INVENTION

[0011] Prior to the description of the embodiments of the present disclosure, an overview of the present disclosure will be described. FIG. 1 shows a schematic configuration of a road marking deterioration analysis device according to the present disclosure. The road marking deterioration analysis device 10 includes a road marking detection unit 11, a break detection unit 12, and a cause determination unit 13.

[0012] The road marking detection unit 11 detects road markings on the road based on sensor information obtained by sensing the road. The break detection unit 12 detects a location where the road marking is broken based on the detection result of the road marking. Here, that the road marking is broken refers to, for example, a location where the presence of the road marking (such as its paint) cannot be confirmed in the sensor information at a location where the road marking should originally be applied. The cause determination unit 13 determines the cause of the breakage of the road marking at the location where it is detected that the road marking is broken.

[0013] In the present disclosure, the road marking deterioration analysis device does not simply detect a location where the road marking is interrupted as a location where the road marking is deteriorated, but determines the cause thereof. A user such as a road administrator can refer to the cause of the interrupted road marking and formulate a plan for road maintenance and management according to the cause. Thus, the road marking deterioration analysis device according to the present disclosure can provide useful information for road maintenance and management to a user such as a road administrator.

[0014] Hereinafter, embodiments of the present disclosure will be described in detail. FIG. 2 shows a road marking deterioration analysis system including a road marking deterioration analysis device according to an embodiment of the present disclosure. The road marking deterioration analysis system 100 includes a road marking deterioration analysis device 110 and one or more moving bodies 200. The road marking deterioration analysis device 110 is connected to one or more moving bodies 200 via a network 150. The network 150 includes, for example, a wireless communication network using a communication line standard such as LTE (Long Term Evolution). The network 150 may include a wireless communication network such as WiFi (registered trademark) or a fifth-generation mobile communication system.

[0015] The moving body 200 is configured as a land vehicle that travels on a road, such as a car, a bus, a taxi, or a truck. The moving body 200 may be a vehicle such as a public vehicle, a garbage collection vehicle, or a police vehicle. The moving body 200 includes a peripheral monitoring sensor for monitoring the surrounding situation of the moving body. The peripheral monitoring sensor includes, for example, sensors such as a camera and LiDAR (Light Detection and Ranging). The moving body 200 may be configured to be capable of autonomous driving (self-driving) based on information from sensors mounted on the moving body.

[0016] The mobile body 200 is equipped with a communication device, and the communication device transmits sensor data (sensor information) of the peripheral monitoring sensor to the road marking degradation analysis device 110. For example, the mobile body 200 transmits a camera image captured by a camera, 3D point cloud data acquired by LiDAR, or both of them to the road marking degradation analysis device 110 as sensor data. Hereinafter, mainly, an example in which the mobile body 200 has a camera and transmits a camera image to the road marking degradation analysis device 110 will be described. Each mobile body 200 may include a plurality of cameras that capture the front, rear, right side, and left side of the vehicle.

[0017] The road marking degradation analysis device 110 analyzes the degradation of road markings on the road using the sensor data transmitted from the mobile body 200. FIG. 3 shows a configuration example of the road marking degradation analysis device 110. The road marking degradation analysis device 110 includes a data acquisition unit 111, a road marking detection unit 112, a break detection unit 113, and a factor determination unit 114. The road marking degradation analysis device 110 is configured as a computer device having, for example, one or more memories and one or more processors. At least a part of the functions of each unit in the road marking degradation analysis device 110 can be realized by the processor operating according to a program read from the memory. The road marking degradation analysis device 110 corresponds to the road marking degradation analysis device 10 shown in FIG. 1.

[0018] The data acquisition unit 111 acquires a camera image from the camera 210. The camera 210 is mounted on the mobile body 200 (see FIG. 2). In the present embodiment, the camera 210 may simply transmit a camera image of the road to the road marking degradation analysis device 110 and does not necessarily need to be mounted on the mobile body 200. The camera 210 may be installed in a traffic signal or a roadside unit. Instead of or in addition to the camera image, the data acquisition unit 111 may acquire 3D point cloud data (LiDAR image) including data of the road area from a 3D scanner such as LiDAR.

[0019] The road surface marking detection unit 112 detects road surface markings (their areas) on the road from the camera image of the camera 210. The road surface marking detection unit 112 detects, for example, the lane lines on the road. The lane lines can be detected by searching for areas painted with a predetermined color (for example, white) in the camera image. The road surface marking detection unit 112 corresponds to the road surface marking detection means 11 shown in FIG. 1.

[0020] The break detection unit 113 detects, based on the camera image, the locations where the lane lines detected by the road surface marking detection unit 112 are broken. In other words, the break detection unit 113 detects the locations where the lane lines apparently deteriorate. The break detection unit 113 detects, for example, the locations where the lane lines are broken in the camera image, that is, the locations where there are no lane lines at positions where there should originally be lane lines, as the deteriorated locations. The break detection unit 113 may determine the locations where the lane lines are broken by comparing with past data. Here, the past data means the data obtained before the time when the camera image was acquired. The past data includes, for example, at least one of the construction records of road works, the inspection data of the road, and the detection results of road surface markings in the past. The break detection unit 113 collates, for example, the lane lines detected by the road surface marking detection unit 112 with the construction ledger (construction record) of the works and the past inspection data, and determines the locations where the lane lines are broken. The construction ledger of the works and the past inspection data may be acquired from, for example, a database owned by the road administrator. The break detection unit 113 may also determine the locations where the lane lines are broken by collating the detection results of the lane lines in the road surface marking detection unit 112 with the detection results of the lane lines detected by the road surface marking detection unit 112 in the past. The locations where deterioration is detected by the break detection unit 113 may include the locations where actual deterioration has occurred in the road surface markings and the locations where deterioration appears to have occurred in the camera image but in fact no deterioration has occurred. The break detection unit 113 corresponds to the break detection means 12 shown in FIG. 1.

[0021] The cause determination unit 114 determines the cause of the section where the road marking detected by the break detection unit 113 is broken. For example, the cause determination unit 114 determines whether the cause of the broken road marking is deterioration of the road marking or dirt on the road marking. For example, when the lane line cannot be seen in the camera image, the cause determination unit 114 determines the cause of the lane line not being visible. Specifically, the cause determination unit 114 determines whether the lane line is simply not visible in the camera image or is blurred and not visible. The cause determination unit 114 may determine the cause of the broken road marking based on, for example, the camera image.

[0022] The cause determination unit 114 outputs information indicating the section where the road marking is broken and the result of the determination at that section. For example, on the screen of the display device, the cause determination unit 114 displays the section where it is detected that the lane line is broken and the cause of the break at that section. The cause determination unit 114 corresponds to the cause determination means 13 shown in FIG. 1.

[0023] Various types of information can be used to determine the cause of the broken road marking. For example, the cause determination unit 114 may acquire cleaning information on the road and use the acquired cleaning information to determine the cause. The cleaning information includes, for example, information indicating when the road was cleaned, that is, information indicating the cleaning date. The cause determination unit 114 may compare the acquisition date of the camera image with the cleaning date and determine the cause of the break based on the comparison result. For example, the cause determination unit 114 determines the cause of the broken road marking according to the difference between the acquisition date of the camera image and the cleaning date, that is, the number of days elapsed since the most recent cleaning date.

[0024] For example, when the acquisition date of the camera image is immediately after the cleaning date, it is considered that there is a low possibility that fallen leaves or other attachments are attached to the lane lines. In that case, the factor determination unit 114 determines that, in the camera image, the lane line is interrupted and the interruption detection unit 113 detects that the lane line is interrupted because the lane line is actually faded or otherwise deteriorated. Conversely, when the number of days elapsed since the most recent cleaning date is a certain number of days or more, the road surface is contaminated with fallen leaves, garbage, etc., and it is considered that the lane line is interrupted in the camera image. In that case, the factor determination unit 114 determines that the interruption detection unit 113 detects that the lane line is interrupted because the lane line is covered with fallen leaves or garbage.

[0025] FIG. 4 shows an example of a camera image when the lane line is faded and deteriorated. In the example of FIG. 4, in a part of the lane line in the center of the road, the paint is faded. The interruption detection unit 113 detects, in the camera image, a location where the lane line is interrupted as a deteriorated location. The factor determination unit 114 determines that the lane line is actually deteriorated, for example, when the camera image is a camera image taken immediately after the cleaning date.

[0026] FIG. 5 shows an example of a camera image when the lane line is covered with fallen leaves. In the example of FIG. 5, in a part of the lane line in the center of the road, the paint is covered with fallen leaves. In this case, the interruption detection unit 113 detects, in the camera image, a location where the lane line is interrupted as a deteriorated location. The factor determination unit 114 determines that the lane line is not actually deteriorated and that the lane line is contaminated, for example, when the camera image is a camera image taken a predetermined number of days after the cleaning date.

[0027] The factor determination unit 114 may determine whether there are fallen leaves, garbage, etc. on the road based on the camera image, and if there are no fallen leaves or garbage on the road, determine that the lane line is actually deteriorated. The factor determination unit 114 may determine that the lane line is contaminated when there are fallen leaves or garbage on the road.

[0028] The cause determination unit 114 may acquire maintenance information indicating the maintenance status of the road surface markings on the road, and determine the cause of the road surface markings being interrupted using the acquired maintenance information. The maintenance information includes information indicating when the road surface markings were maintained. The maintenance information can be acquired, for example, from a database managed by a road administrator. The cause determination unit 114 compares the date when the camera image was acquired with the date when the road surface markings were maintained, and determines the cause based on the result of the comparison. For example, when the acquisition date of the camera image has passed a predetermined number of days or more since the date when the road surface markings were last maintained, the cause determination unit 114 determines that the road surface markings are deteriorated. When the acquisition date of the camera image has not passed a predetermined number of days or more since the date when the road surface markings were last maintained, the cause determination unit 114 determines that the road surface markings are dirty.

[0029] The cause determination unit 114 may acquire road surface condition information indicating the road surface condition (road surface status) of the road, and determine the cause of the road surface markings being interrupted using the acquired road surface condition information. The road surface condition information can be acquired, for example, from a database managed by a road administrator. The road surface condition information includes information indicating, for example, the presence or absence of cracks on the road surface or the presence or absence of potholes. The cause determination unit 114 determines the cause of the road markings being interrupted based on, for example, the road surface condition within a predetermined distance range from the location where the camera image was acquired. The cause determination unit 114 determines, for example, whether there are many deteriorated portions of the road surface at the location where the camera image was taken and within a range within a predetermined distance from that location. When the cause determination unit 114 determines that there are many deteriorated portions of the road surface, it may determine that the lane lines are actually deteriorated. When the cause determination unit 114 determines that there are few deteriorated portions of the road surface, it may determine that the lane lines are dirty.

[0030] The cause determination unit 114 may consider the date when the camera image was acquired and determine the cause of the road surface markings being interrupted. For example, the cause determination unit 114 determines the season from the date when the camera image was acquired. When the season is a season with a lot of fallen leaves, for example, autumn, the cause determination unit 114 may determine that the lane lines are dirty.

[0031] In addition, the cause determination unit 114 may acquire information related to the garbage collection date and determine the cause of the interrupted road markings using the acquired information related to the garbage collection date. The cause determination unit 114 acquires, for example, the date and time of garbage collection. Information related to the garbage collection date can be acquired, for example, from the local government that conducts the garbage collection. The cause determination unit 114 determines whether the camera image is a camera image before garbage collection or a camera image after garbage collection. The cause determination unit 114 determines whether the date when the camera image was acquired is the same day as the garbage collection date and whether the time when the camera image was acquired is before or after the garbage collection. If the camera image is taken on the garbage collection date and before the garbage collection, there is a possibility that crows or the like have ransacked the garbage collection location and garbage is scattered on the road. When the camera image is an image taken on the garbage collection date and before the garbage collection, the cause determination unit 114 may determine that the lane markings are dirty. When the camera image is not taken on the garbage collection date or is an image taken after the garbage collection, the cause determination unit 114 may determine that the lane markings are deteriorated.

[0032] When the LiDAR image (3D point cloud data) is acquired in the data acquisition unit 111, the cause determination unit 114 may determine the cause of the interrupted road markings using the 3D point cloud data. For example, the cause determination unit 114 detects the thickness of the white line portion on the road surface. When the thickness of the white line portion is thinner than a predetermined value, the cause determination unit 114 determines that the road markings are deteriorated and blurred. The cause determination unit 114 may detect deposits adhering to the road markings based on the 3D point cloud data. For example, the cause determination unit 114 detects a location that bulges by the amount of the deposit from the road surface. When there is a deposit at a location where the road markings are interrupted, the cause determination unit 114 determines that the road markings are dirty.

[0033] The operation procedure will be described below. FIG. 6 shows the operation procedure (road marking deterioration analysis method) in the road marking deterioration analysis apparatus 110. The data acquisition unit 111 acquires sensor information (camera image) from the camera 210 (step S1). The road marking detection unit 112 detects road markings from the camera image (step S2). In step S2, the road marking detection unit 112 detects, for example, the lane lines on the road.

[0034] The break detection unit 113 detects the locations where the road markings are broken (step S3). The cause determination unit 114 determines whether the road markings are broken (step S4). When the cause determination unit 114 determines that the road markings are broken, it determines the cause of the road markings being broken (step S5). In step S5, the cause determination unit 114 determines, for example, for the locations where the lane lines are broken, whether the lane lines are deteriorated or dirty. The cause determination unit 114 may determine the cause of the lane lines being broken using a plurality of pieces of information. The cause determination unit 114 may determine the cause of the lane lines being broken based on, for example, a combination of two or more pieces of information among the camera image, the LiDAR image, the road cleaning information, the maintenance information of the road markings, the road surface condition information, and the information regarding the garbage collection date.

[0035] In the present embodiment, the break detection unit 113 detects the locations where the road markings are broken from the camera image. The cause determination unit 114 determines the cause of the road markings being broken for the locations where the road markings are broken. For example, when the road markings are broken because the road markings are deteriorated, it is considered necessary to repair the road markings. On the other hand, when the road markings are dirty, it is only necessary to clean the road, and there is no need to repair the road markings. It is considered important in road management to determine whether the road markings are actually deteriorated due to fading or are only dirty. In the present embodiment, when a break in the road markings is detected, the cause of the road markings being broken is determined. Therefore, the road marking deterioration analysis apparatus 110 according to the present embodiment can provide useful information for road management to a user such as a road administrator.

[0036] In the present disclosure, the road surface marking deterioration analysis device 110 can be configured as a computer device (server device). FIG. 7 shows a configuration example of a computer device that can be used as the road surface marking deterioration analysis device 110. The computer device 500 includes a control unit (CPU: Central Processing Unit) 510, a storage unit 520, a ROM (Read Only Memory) 530, a RAM (Random Access Memory) 540, a communication interface (IF: Interface) 550, and a user interface 560.

[0037] The communication interface 550 is an interface for connecting the computer device 500 to a communication network via wired communication means, wireless communication means, or the like. The user interface 560 includes a display unit such as a display, for example. Further, the user interface 560 includes an input unit such as a keyboard, a mouse, and a touch panel.

[0038] The storage unit 520 is an auxiliary storage device that can hold various data. The storage unit 520 does not necessarily have to be a part of the computer device 500, and may be an external storage device or a cloud storage connected to the computer device 500 via a network.

[0039] The ROM 530 is a non-volatile storage device. A semiconductor storage device such as a flash memory with a relatively small capacity, for example, is used for the ROM 530. The program executed by the CPU 510 can be stored in the storage unit 520 or the ROM 530. The storage unit 520 or the ROM 530 stores various programs for realizing the functions of each part in the road surface marking deterioration analysis device 110, for example.

[0040] When the program is loaded into a computer, it includes a set of instructions (or software code) for causing the computer to perform one or more of the functions described in the embodiments. The program may be stored in a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, the computer-readable medium or tangible storage medium includes random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technologies, Compact Disc (CD), digital versatile disc (DVD), Blu-ray (registered trademark) disc or other optical disc storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices. The program may be transmitted on a transitory computer-readable medium or a communication medium. By way of example and not limitation, the transitory computer-readable medium or communication medium includes electrical, optical, acoustic, or other forms of propagated signals.

[0041] RAM540 is a volatile memory device. Various semiconductor memory devices such as DRAM (Dynamic Random Access Memory) or SRAM (Static Random Access Memory) are used for RAM540. RAM540 can be used as an internal buffer for temporarily storing data and the like. The CPU510 expands and executes the program stored in the storage unit 520 or the ROM530 in the RAM540. By the CPU510 executing the program, the functions of each part within the road marking deterioration analysis device 110 can be realized. The CPU510 may have an internal buffer capable of temporarily storing data and the like.

[0042] As described above, the embodiments of the present disclosure have been described in detail. However, the present disclosure is not limited to the above-described embodiments, and those obtained by making changes or modifications to the above embodiments without departing from the spirit of the present disclosure are also included in the present disclosure.

[0043] For example, some or all of the above embodiments may be described as follows in the appended claims, but are not limited thereto.

[0044] [Appendix 1] A road marking detection means for detecting road markings on a road based on sensor information obtained by sensing the road, A break detection means for detecting a location where the road marking is broken based on the detection result of the road marking, A road marking deterioration analysis device comprising a factor determination means for determining a factor for which the road marking is broken at a location where it is detected that the road marking is broken.

[0045] [Appendix 2] The factor determination means determines whether the factor for which the road marking is broken is deterioration of the road marking or dirt on the road marking, in the road marking deterioration analysis device according to Appendix 1.

[0046] [Appendix 3] The factor determination means determines the factor based on the sensor information, in the road marking deterioration analysis device according to Appendix 1 or 2.

[0047] [Appendix 4] The factor determination means determines the factor using at least one of the road cleaning information and the maintenance information of the road marking on the road, in the road marking deterioration analysis device according to any one of Appendices 1 to 3.

[0048] [Appendix 5] The factor determination means determines the factor using the road cleaning information, The factor determination means compares the date on which the sensor information was acquired with the date on which the road was cleaned, and determines the factor based on the result of the comparison, in the road marking deterioration analysis device according to Appendix 4.

[0049] [Appendix 6] The factor determination means determines the factor using the maintenance information of the road marking, The cause determination means compares the date on which the sensor information was acquired with the date on which the road markings were maintained, and determines the cause based on the result of the comparison. The road marking deterioration analysis device according to appended note 4 or 5.

[0050] [Appended note 7] The cause determination means determines the cause using road surface condition information indicating the road surface condition of the road. The road marking deterioration analysis device according to any one of appended notes 1 to 6.

[0051] [Appended note 8] The cause determination means determines the cause based on the road surface condition within a predetermined distance range from the point where the sensor information was acquired. The road marking deterioration analysis device according to appended note 7.

[0052] [Appended note 9] The cause determination means determines the cause using at least one of information regarding the garbage collection date and the season. The road marking deterioration analysis device according to any one of appended notes 1 to 8.

[0053] [Appended note 10] The sensor information includes at least one of a camera image that captures the road and three-dimensional point cloud data of the road. The road marking deterioration analysis device according to any one of appended notes 1 to 9.

[0054] [Appended note 11] The break detection means compares the detection result of the road markings with at least one of the construction records of the roadworks on the road, the inspection data of the road, and the past detection results of the road markings to detect the locations where the road markings are broken. The road marking deterioration analysis device according to any one of appended notes 1 to 10.

[0055] [Appended note 12] Based on sensor information obtained by sensing the road, detect road markings on the road. Based on the detection result of the road markings, detect the locations where the road markings are broken. A road surface marking deterioration analysis method that includes determining the cause of the interruption of the road surface marking at a location where it is detected that the road surface marking is interrupted.

[0056] [Appendix 13] Based on sensor information obtained by sensing a road, detect road surface markings on the road, Based on the detection result of the road surface marking, detect a location where the road surface marking is interrupted, A non-transitory computer-readable medium that stores a program for causing a computer to execute a process including determining the cause of the interruption of the road surface marking at a location where it is detected that the road surface marking is interrupted.

Explanation of Signs

[0057] 10: Road surface marking deterioration analysis device 11: Road surface marking detection means 12: Interruption detection means 13: Cause determination means 100: Road surface marking deterioration analysis system 110: Road surface marking deterioration analysis device 111: Data acquisition unit 112: Road surface marking detection unit 113: Interruption detection unit 114: Cause determination unit 150: Network 200: Moving body 210: Camera 500: Computer device 510: CPU 520: Storage unit 530: ROM 540: RAM 550: Communication interface 560: User interface

Claims

1. Road surface marking detection means for detecting road surface markings on a road based on sensor information obtained by sensing the road, Discontinuity detection means for detecting a location where the road surface marking is discontinuous based on the detection result of the road surface marking, A road surface marking deterioration analysis apparatus comprising factor determination means for determining a factor causing the road surface marking to be discontinuous using at least one of cleaning information of the road and maintenance information including information indicating when the road surface marking was maintained at a location where it has been detected that the road surface marking is discontinuous.

2. The road surface marking deterioration analysis apparatus according to claim 1, wherein the factor determination means determines whether the factor causing the road surface marking to be discontinuous is deterioration of the road surface marking or dirt on the road surface marking.

3. The road surface marking deterioration analysis apparatus according to claim 1 or 2, wherein the factor determination means determines the factor based on the sensor information.

4. The factor determination means determines the factor using the cleaning information of the road, The factor determination means compares a date when the sensor information was acquired with a date when the road was cleaned, and determines the factor based on a result of the comparison. The road surface marking deterioration analysis apparatus according to any one of claims 1 to 3.

5. The factor determination means determines the factor using the maintenance information of the road surface marking, The factor determination means compares a date when the sensor information was acquired with a date when the road surface marking was maintained, and determines the factor based on a result of the comparison. The road surface marking deterioration analysis apparatus according to any one of claims 1 to 4.

6. The road surface marking deterioration analysis apparatus according to any one of claims 1 to 5, wherein the factor determination means determines the factor using road surface condition information indicating a road surface condition of the road.

7. The road surface marking deterioration analysis apparatus according to any one of claims 1 to 6, wherein the factor determination means determines the factor using at least one of information regarding a garbage collection date and a season.

8. Detecting road surface markings on a road based on sensor information obtained by sensing the road, Detecting a location where the road surface marking is discontinuous based on the detection result of the road surface marking, A road surface marking deterioration analysis method including determining a factor causing the road surface marking to be discontinuous using at least one of cleaning information of the road and maintenance information including information indicating when the road surface marking was maintained at a location where it has been detected that the road surface marking is discontinuous.

9. Detect road markings on a road based on sensor information obtained by sensing the road, detect a location where the road marking is interrupted based on the detection result of the road marking, For a location where it is detected that the road marking is interrupted, use at least one of the cleaning information of the road and the maintenance information including information indicating when the road marking was maintained on the road to determine the cause of the interruption of the road marking. A program for causing a computer to execute a process including this.

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