JP2022143225A - Road surface abnormality detection system - Google Patents

Abstract

To provide a road surface abnormality detection system that can detect a road surface abnormality according to differences in road surface abnormality repair determination criteria for each road manager.SOLUTION: A road surface abnormality detection system is configured to collect travel data including a detection result of an on-vehicle sensor 8 provided in a vehicle 5 from the vehicle 5 that travels on a road, identify an abnormality level suggesting presence of a road surface abnormality on a road surface of the road on which the vehicle 5 has travelled, based on the collected travel data, set an abnormality level threshold value for detecting a road surface abnormality based on a history of road maintenance for road abnormalities performed in the past, and detect that a road surface abnormality has occurred at a spot where the abnormality level identified on the road surface of the road on which the vehicle 5 has travelled exceeds the threshold value.SELECTED DRAWING: Figure 2

Description

The present invention relates to a road surface abnormality detection system for detecting an abnormality occurring on a road surface.

Conventionally, as one of road maintenance and management, when road surface abnormalities such as asphalt peeling and unevenness occur on the road surface, a person who manages the road such as a local government or a road management company (hereinafter referred to as a road manager) Repairing those road surface abnormalities is being carried out by. In order to repair such road surface abnormalities, it is necessary for road administrators to grasp the location, current size, and degree of road surface abnormalities that have occurred on the road surface. 2. Description of the Related Art A road surface abnormality is detected based on sensor information or the like of a running vehicle.

For example, in Japanese Unexamined Patent Application Publication No. 2020-194450, it is detected that there is a road surface abnormality at the timing when the change in the acceleration in the longitudinal direction obtained by the vehicle from the sensor exceeds the threshold, and the road surface abnormality is detected for the length of the road. The number of times is calculated as the occurrence rate of road surface anomalies, and the administrator collects data on the occurrence rate of road anomalies calculated for each vehicle. have proposed a technique for grasping

JP 2020-194450 A (paragraph 0027-0035)

Here, roads all over the country are not managed by one road administrator, but are managed by a number of road administrators in units of areas or roads. In addition, the judgment criteria for road surface abnormality repair are not uniform and usually differ depending on the road administrator. Therefore, for example, when road surface abnormalities of the same size and degree exist on two different roads, road A and road B, road administrator A who manages road A judges that repair is necessary and repairs road B. The road administrator B who manages the road may decide that the repair is not necessary at the present time and put the repair on hold. That is, even if the road surface abnormality is of the same magnitude and degree, it is a road surface abnormality that should be detected by the road administrator A, while it is a road surface abnormality that does not need to be detected by the road administrator B at this time. In Patent Literature 1, since the threshold value for detecting the road surface abnormality is fixed, there is a problem that it is not possible to cope with the difference in judgment criteria for each road administrator.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned problems in the prior art. It is an object to provide a detection system.

In order to achieve the above object, the road surface abnormality detection system according to the present invention collects, from a vehicle traveling on a road to be managed, traveling data including the detection results of a sensor that detects the traveling state of the vehicle, which changes according to the road surface state. Travel data collection means for collecting; Abnormality degree level identification means for identifying an abnormality level indicating the presence of road surface abnormality on the road surface on which the vehicle travels based on the collected traveling data; Threshold setting means for setting a threshold of anomaly level for detecting a road surface anomaly based on the history of road maintenance against anomaly; and road surface abnormality detection means for detecting that a road surface abnormality has occurred.
In addition to the detection results of various sensors installed in the vehicle such as the vehicle speed sensor, acceleration sensor, gyro sensor, and yaw rate sensor, the "sensor detection results" include the image recognition results detected from the images captured by the in-vehicle camera. Also includes
In addition, "road surface anomaly" includes not only anomalies of the road surface itself such as potholes and cracks in the road surface, but also anomalies caused by road surfaces and other objects such as frozen road surfaces and obstacles that have entered the road surface. as a concept. That is, the road surface abnormality is a concept that includes various road surface abnormalities that affect the running of the vehicle.

According to the road surface abnormality detection system according to the present invention having the above configuration, the threshold value for road surface abnormality detection is set based on the history of road maintenance performed in the past. Considering the difference in judgment criteria, it becomes possible for the road administrator to detect only road surface abnormalities that should be detected.

1 is a schematic configuration diagram showing a road surface abnormality detection system according to an embodiment; FIG. 1 is a block diagram showing the configuration of a road surface abnormality detection system according to this embodiment; FIG. It is the figure which showed an example of the probe information memorize|stored in probe information DB. It is the figure which showed an example of the information regarding the threshold value memorize|stored in detection threshold value DB. It is the figure which showed an example of the information regarding the road surface abnormality memorize|stored in road surface abnormality detection DB. It is the figure which showed an example of the maintenance log|history of the road memorize|stored in repair log|history DB. 2 is a block diagram schematically showing a control system of the navigation device according to this embodiment; FIG. FIG. 4 is a diagram illustrating an example of behavior that occurs when a vehicle passes through a road surface abnormality; 5 is a flowchart of a threshold initial setting processing program according to the embodiment; 5 is a flowchart of a recommended threshold value calculation processing program according to the embodiment; It is a figure explaining the calculation method of a recommendation threshold value. 4 is a flowchart of a threshold correction processing program according to the embodiment; It is the figure which showed the threshold value setting screen displayed on the display of an operating terminal. It is the figure which showed the example which sets a threshold value using a threshold value setting screen. 4 is a flow chart of a road surface abnormality detection processing program according to the present embodiment; It is the figure which showed the example which guides a detected road surface abnormality to a road administrator.

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, a road surface abnormality detection system according to the present invention will be described in detail with reference to the drawings based on a specific embodiment. First, a schematic configuration of a road surface abnormality detection system 1 according to this embodiment will be described with reference to FIGS. 1 and 2. FIG. FIG. 1 is a schematic configuration diagram showing a road surface abnormality detection system 1 according to this embodiment. FIG. 2 is a block diagram showing the configuration of the road surface abnormality detection system 1 according to this embodiment. Roads all over the country are classified and managed by area or by road by local governments (for example, prefectures, municipalities) or by road management companies. of each municipality or each road management company. A local government or a road management company that manages roads using the road surface abnormality detection system 1 of the present embodiment is hereinafter referred to as a road manager.

As shown in FIG. 1, a road surface abnormality detection system 1 according to the present embodiment includes a server device (road surface abnormality detection device) 3 provided in an information management center 2 under the control of a road administrator, and a server device (road surface abnormality detection device) 3 operated by the road administrator. It basically has an operation terminal 4 that is connected to the vehicle and a vehicle 5 that travels on the road. The server device 3 , the operation terminal 4 and the vehicle 5 are configured to be able to transmit and receive electronic data to and from each other via a communication network 6 . In this embodiment, it is basically assumed that there are a plurality of vehicles 5 included in the road surface abnormality detection system 1, but implementation is possible even if there is only one vehicle. Also, the vehicles 5 may be limited to specific vehicles (for example, public vehicles, taxis, garbage trucks) under the control of the road administrator, or may include a wide range of general vehicles.

Here, the road surface abnormality detection system 1 according to this embodiment constitutes a so-called probe car system. Here, the probe car system is a system that collects information using the vehicle 5 as a sensor. Specifically, the vehicle 5 transmits speed data, the operation status of each system such as steering operation, shift position, etc. to the information management center 2 via a communication device pre-installed in the vehicle 5 together with GPS position information. , a system that reuses the collected data as various information on the center side.

The server device 3 provided in the information management center 2 appropriately collects and accumulates probe information (material information) including the current time and travel information from each vehicle 5 traveling on the road managed by the road manager. At the same time, various types of support information (for example, traffic jam information, road conditions, accident information, travel time, etc.) are generated from the accumulated probe information, the generated support information is distributed to the navigation device 7, and the support information is used. It is an information management server that performs various types of processing. In particular, in the present embodiment, the server device 3 collects from each vehicle 5 information on the detection values of various sensors such as a vehicle speed sensor and an acceleration sensor provided in the vehicle 5 that detect the running state of the vehicle that changes according to the road surface condition. By statistically collecting the collected information, road surface anomalies existing on the road surface to be managed by the road administrator are detected. Then, the server device 3 provides information on the detected road surface abnormality to the operation terminal 4, and based on the information provided via the operation terminal 4, the road administrator checks the site as necessary. Determine whether to repair or suspend the road surface abnormality detected in . Incidentally, the "road surface anomaly" in the present embodiment means not only an abnormality of the road surface itself such as a pothole or cracks in the road surface, but also an abnormality of the road surface and other objects such as a frozen road surface or an obstacle that has entered the road surface. The concept also includes the abnormalities that occur. That is, the road surface abnormality is a concept that includes various road surface abnormalities that affect the running of the vehicle.

In this embodiment, the information management center 2 and the server device 3 are under the control of the road administrator. A system may be adopted in which information on the road surface abnormality detection result is transferred to the operation terminal 4 of the road administrator.

The operation terminal 4 corresponds to, for example, a personal computer, a tablet terminal, a smart phone, etc., and is a terminal that can be operated by the road administrator. The operation terminal 4 includes a control unit mainly composed of a CPU, ROM, RAM, etc., an input unit composed of a keyboard, a pointing device, etc., an output unit such as a display and a speaker, and an auxiliary unit composed of non-volatile storage means such as a hard disk. It is equipped with a storage unit and the like. The operation terminal 4 is equipped with Windows (registered trademark), Linux (registered trademark), MacOS (registered trademark), or the like as an OS (Operating System). The OS provides basic functions commonly used by applications, such as input/output functions such as keyboard input and screen output, and functions for accessing the memory as the main memory and the hard disk as the auxiliary memory. Since the various functions provided by each OS are known, detailed description thereof will be omitted here.

Furthermore, the operation terminal 4 is connected to a communication network 6 via communication equipment such as a modem, and is configured to be capable of two-way communication with the server device 3 . Then, the operation terminal 4 displays various information on the display based on the data acquired from the server device 3 . In particular, the operation terminal 4 according to the present embodiment displays a screen for setting a threshold value for detecting a road surface abnormality as described later, and accepts a user's operation to change the threshold value. In addition, information on the road surface abnormality detected by the server device 3 is acquired from the server device 3, and the detection point and status (magnitude and degree of abnormality) of the road surface abnormality are displayed on the display for the road administrator. invite.

On the other hand, the vehicle 5 is a means of transportation that travels on the road with a passenger on board, and includes a navigation device 7 that is a communication (guidance) terminal, and various on-vehicle sensors such as a GPS, a vehicle speed sensor, an acceleration sensor, and an on-vehicle camera. 8. The on-vehicle sensor 8 provided in the vehicle 5 is a sensor that detects the running state of the vehicle that changes according to the road surface condition, and the type is not particularly limited, and various sensors that can be mounted on the vehicle 5 can be used. Further, the number of in-vehicle sensors 8 provided in the vehicle 5 may be one or plural. The vehicle 5 may be a vehicle capable of traveling by automatic operation.

The navigation device 7 is mounted on the vehicle 5, and displays a map of the vehicle's surroundings based on the stored map data, displays the current position of the vehicle on the map image, and provides navigation along a set guidance route. It is an in-vehicle device that provides movement guidance. In addition, the navigation device 7 has a communication means for connecting to the communication network 6, acquires the current position, vehicle speed, acceleration, etc. of the vehicle using the GPS and the on-vehicle sensor 8, and acquires the current time along with the current time at predetermined time intervals. The information is transmitted to the server device 3 as probe information. Instead of the navigation device 7, for example, another vehicle-mounted device provided in the vehicle 5 or a vehicle control ECU that controls the vehicle 5 may be used as a subject that transmits the probe information.

The communication network 6 includes a large number of base stations located all over the country and communication companies that manage and control each base station. It is configured by connecting Here, the base station has a transceiver (transmitter/receiver) for communicating with the vehicle 5 and an antenna. While the base station performs wireless communication between communication companies, the base station serves as the terminal of the communication network 6 and relays the communication of the vehicle 5 within the radio wave range (cell) of the base station to the server device 3. have a role. It also has a role of relaying communication between the operation terminal 4 and the server device 3 .

Next, the configuration of the server device 3 included in the road surface abnormality detection system 1 will be described in more detail using FIG.

As shown in FIG. 2, the server device 3 includes a server control unit 11, a probe information DB 12 as information recording means connected to the server control unit 11, a detection threshold DB 13, a road surface abnormality detection DB 14, and a repair history DB 15. , a server-side map DB 16 and a center communication device 17 .

The server control unit 11 is a control unit (MCU, MPU, etc.) that controls the entire server device 3, and is used as a working memory when the CPU 21 as an arithmetic unit and a control unit and the CPU 21 performs various kinds of arithmetic processing. In addition to the RAM 22 and control programs, which will be described later, a threshold initial setting processing program (Fig. 9), a recommended threshold calculation processing program (Fig. 10), a threshold correction processing program (Fig. 12), a road surface abnormality detection processing program (Fig. 15) etc. are recorded, and an internal storage device such as a flash memory 24 for storing programs read from the ROM 23 is provided. The server control unit 11 has various means as processing algorithms together with control units of the operation terminal 4 and the navigation device 7 . For example, the traveling data collecting means collects traveling data including the detection results of the vehicle-mounted sensors 8 that detect the traveling conditions of the vehicles 5 that change according to the road surface conditions, from the five vehicles traveling on the road to be managed. The abnormality level identifying means identifies an abnormality level indicating the presence of a road surface abnormality on the road surface on which the vehicle travels, based on the collected travel data. The threshold setting means sets an abnormality level threshold for detecting a road surface abnormality based on a history of road maintenance performed in the past for road surface abnormalities. The road surface abnormality detection means detects that a road surface abnormality has occurred at a point where the identified abnormality degree level exceeds a threshold on the road surface on which the vehicle travels.

The probe information DB 12 is storage means for cumulatively storing probe information collected from each vehicle 5 traveling on a road managed by a road manager. In this embodiment, the probe information collected from the vehicle 5 includes (a) the date and time, (b) the position coordinates (latitude and longitude) of the vehicle 5 at that date and time, and (c) the traveling link on which the vehicle travels. , (d) includes detection values of the in-vehicle sensor 8 provided in the vehicle. The in-vehicle sensor 8 provided in the vehicle includes, for example, a vehicle speed sensor, a steering sensor, a yaw rate sensor, a gyro sensor, a longitudinal acceleration sensor, a vertical acceleration sensor, and an infrared sensor. A vehicle speed sensor and a longitudinal acceleration sensor are included as sensors for detecting changing running conditions of the vehicle.

That is, the probe information indicates the point where the vehicle 5 was located during past travel, the time when the vehicle was located at that point, and the detected value of the vehicle-mounted sensor 8 at that point, that is, the travel data (behavior) of the vehicle. . However, the probe information does not necessarily include all of the information related to (a) to (d) above, and may include information other than (a) to (d) (for example, brake operation amount, direction, etc.) good. Also, the probe information may include video information captured by an on-vehicle camera.

FIG. 3 is a diagram showing an example of probe information stored in the probe information DB 12. As shown in FIG. As shown in FIG. 3, the probe information includes a vehicle ID that identifies the vehicle that is the source of transmission, information related to the above (a) to (d), and the like. For example, the probe information shown in FIG. 3 stores that the vehicle 5 with ID "A" gradually decelerated and stopped while traveling on the link with ID "100001". On the other hand, it is stored that the vehicle 5 with the ID "B" traveled the link with the ID "100002" at about 55 km. Similarly, other probe information is also stored. In the example shown in FIG. 3, the probe information is collected from the vehicle at 200 msec intervals, but the probe information collection interval may be shorter or longer than the 200 msec interval.

Further, the detection threshold DB 13 is storage means for storing a threshold for detecting a road surface abnormality currently set for each vehicle 5 . In this embodiment, as will be described later, based on the detection value of the vehicle-mounted sensor 8, an abnormality level indicating the presence of road surface abnormality on the road on which the vehicle is traveling (the higher the abnormality level, the more likely the road surface abnormality is present) is highly probable and suggests that a larger road surface abnormality exists at that point), and detection of the road surface abnormality is performed based on the identified abnormality degree level. The threshold stored in the detection threshold DB 13 is a threshold for detecting a road surface abnormality from the abnormality level. Also, the threshold is set for each vehicle 5 . Furthermore, three types of thresholds, a first threshold, a second threshold, and a third threshold, are set as the thresholds, and are defined as follows.
(1) First threshold: Threshold value for determining whether or not to detect a road surface abnormality detection target)
(2) Third threshold: Threshold value for determining whether or not the detected road surface abnormality should be a target for guidance by default (i.e., if the abnormality level is greater than or equal to the first threshold value and less than the third threshold value, it is detected as a road surface abnormality). However, if there is no request from the road administrator, it is basically not subject to guidance to the road administrator, and if the anomaly level is equal to or higher than the third threshold, it is unconditionally subject to guidance to the road administrator as a road surface abnormality)
(3) Second threshold: a threshold set between the first threshold and the third threshold for classifying the magnitude and degree of road surface abnormalities

FIG. 4 is a diagram showing an example of thresholds stored in the detection threshold DB 13. As shown in FIG. As shown in FIG. 4, the threshold is set in association with the vehicle ID that identifies the vehicle. is set to "118" and the third threshold is set to "160". The vehicle 5 with ID "B" has the first threshold set to "57", the second threshold set to "100", and the third threshold set to "143". The vehicle 5 with ID "C" has the first threshold set to "65", the second threshold set to "108", and the third threshold set to "156". The vehicle 5 with ID "D" has the first threshold set to "52", the second threshold set to "96", and the third threshold set to "133".

As will be described later, a unique initial value corresponding to each vehicle 5 is set in advance for the threshold value, and then the threshold value is appropriately corrected to a more appropriate value based on the history of road maintenance for road surface abnormalities. The Rukoto. Details of the threshold setting method will be described later.

On the other hand, the road surface abnormality detection DB 14 detects road surface abnormalities detected on the road surface to be managed by the road administrator based on the probe information stored in the probe information DB 12 and the threshold value stored in the detection threshold DB 13. It is a storage means for storing information about. In particular, in this embodiment, for each detected road surface abnormality, the position where the road surface abnormality was detected, the vehicle that detected the road surface abnormality (more precisely, the vehicle that transmitted the probe information used for detection), the road surface Information specifying the date and time when the abnormality was detected and the current status of the road surface abnormality are stored. Here, the "road surface abnormality status" indicates the magnitude and degree of the abnormality. The height, the difference between the highest point and the lowest point in the case of unevenness, and the angle of inclination in the case of an inclined shape are included. The status of the road surface abnormality is specified based on the first threshold, the second threshold, and the third threshold described above. is greater than or equal to the first threshold and less than the second threshold, it is determined that there is a "level 1 (small)" road surface abnormality at that point. Also, if there is a point where the degree of abnormality level is equal to or greater than the second threshold value and less than the third threshold value, it is determined that there is a "level 2 (medium)" road surface abnormality at that point. Also, if there is a point where the degree of abnormality level is equal to or higher than the third threshold, it is determined that there is a road surface abnormality of "level 3 (large)" at that point.

For example, FIG. 5 is a diagram showing an example of information about road surface anomalies stored in the road surface anomaly detection DB 14 . In the step identification information shown in FIG. 5, the level difference of "level 1" detected at 12:02 on March 2 by the vehicle 5 of ID "A" at the point (X1, Y1) of the link of ID "100001". It is stored that a road anomaly exists. Similarly, at the point (X2, Y2) of the link with ID "100011", the vehicle 5 with ID "F" detected a "level 2" road surface abnormality at 13:03 on March 11th. remembered. In addition, at the point (X3, Y3) of the link with ID "100022", the vehicle 5 with ID "H" detected a "level 3" road surface abnormality at 23:02 on March 14th. remembered. In addition, at the point (X4, Y4) of the link with ID "100033", there is a "level 1" road surface abnormality detected by vehicle 5 with ID "D" at 14:34 on March 21st. remembered. Information about road surface anomalies is stored for each road surface anomaly detected on a road managed by a road administrator. Information stored in the road surface abnormality detection DB 14 is appropriately updated based on probe information newly collected from the vehicle 5 . For example, when the shape of the road surface abnormality increases with the lapse of time and the status changes, the corresponding road surface abnormality information is also updated. On the other hand, when the road surface abnormality is repaired by the road administrator, the information on the repaired road surface abnormality is manually or automatically deleted from the road surface abnormality detection DB 14 . However, until a certain period of time has passed since the repair, the repaired flag may be added and the information may be left.

In addition, the server device 3 distributes the information on the road surface abnormality stored in the road surface abnormality detection DB 14 to the operation terminal 4 in response to a request from the operation terminal 4 . On the other hand, the operating terminal 4 to which the road surface abnormality information has been distributed displays the distributed road surface abnormality information on a display or the like to guide the road administrator. For example, it is possible to indicate the position and status of road anomalies detected on a map image. However, unless otherwise specified, only information about road surface abnormalities with a status of level 3 is subject to guidance, and information about road surface abnormalities with a status of level 1 or 2 is also provided if the road administrator specifically requests it. set to target. Then, the road administrator refers to the information on the road surface abnormality that has been guided, and further checks the site if necessary, and then decides whether to repair the detected road surface abnormality or suspend the repair.

On the other hand, the repair history DB 15 is a storage unit that stores the results of work done by road administrators in the past for road surface abnormalities, that is, the history of road maintenance for road surface abnormalities. In addition to the results of carrying out work to repair road surface abnormalities, the results of work include the results of confirming road surface abnormalities and deferring repairs (that is, not repairing at this time). There is also The repair history DB 15 also stores the date and time when the repair work was performed, and when the work was suspended, the date and time when the suspension was decided.

For example, FIG. 6 is a diagram showing an example of repair history information stored in the repair history DB 15. As shown in FIG. In the example shown in FIG. 6, it is stored that on March 12, repair work was performed for a "level 2 (medium)" road surface abnormality at point (X11, Y11) of the link with ID "102211". . Also, it is memorized that it was decided on March 14 to postpone the repair of the "level 1 (small)" road surface abnormality at the point (X12, Y12) of the link with the ID "100251". there is Also, it is stored that the road surface abnormality of "level 3 (large)" at the point (X13, Y13) of the link of ID "100002" was repaired on March 16th. Also, it is memorized that it was decided on March 17 to postpone the repair of the "level 1 (small)" road surface abnormality at the point (X14, Y14) of the link with the ID "120032". there is

On the other hand, the server-side map DB 16 is storage means for storing server-side map information, which is the latest version of map information registered based on input data or input operations from the outside. Here, the server-side map information is composed of various information necessary for route search, route guidance, and map display, including road networks. For example, network data including nodes and links indicating a road network, link data relating to roads (links), node data relating to node points, intersection data relating to each intersection, point data relating to points such as facilities, map display for displaying maps data, search data for searching for routes, search data for searching for points, and the like.

The center communication device 17 is a communication device for communicating with an external traffic information center such as the vehicle 5, the operation terminal 4, or a VICS (registered trademark: Vehicle Information and Communication System) center via the communication network 6. be. In this embodiment, probe information and distribution information (road surface abnormality information) are transmitted and received between each vehicle 5 and the operation terminal 4 via the center communication device 17 .

Next, a schematic configuration of the navigation device 7 mounted on the vehicle 5 will be described with reference to FIG. FIG. 7 is a block diagram showing the navigation device 7 according to this embodiment.

As shown in FIG. 7, the navigation device 7 according to the present embodiment includes a current position detection section 31 for detecting the current position of the vehicle 5 on which the navigation device 7 is mounted, and a data recording section 32 for recording various data. , a navigation ECU 33 that performs various arithmetic processing based on the input information, an operation unit 34 that receives operations from the user, a liquid crystal display 35 that displays a map of the vehicle surroundings, traffic information, etc. to the user, It has a speaker 36 for outputting voice guidance regarding route guidance, a DVD drive 37 for reading a DVD as a storage medium, and a communication module 38 for communicating with information centers such as the information management center 2 and the VICS center. The navigation device 7 is also connected to various onboard sensors 8 mounted on the vehicle 5 via an onboard network such as CAN.

Each component of the navigation device 7 will be described in order below.
The current position detection unit 31 includes a GPS 42 and the like, and is capable of detecting the current position, direction, and the like of the vehicle. Further, by acquiring the detection results of the vehicle speed sensor, acceleration sensor, and other vehicle-mounted sensors 8 installed in the vehicle, it is possible to detect the current vehicle position, direction, etc. with higher accuracy.

The data recording unit 32 reads a hard disk (not shown) as an external storage device and a recording medium, a map information DB 45, a travel history DB 46, and predetermined programs recorded in the hard disk, and stores predetermined data in the hard disk. and a recording head (not shown) which is a driver for writing. Note that the data recording unit 32 may be configured by a flash memory, a memory card, or an optical disk such as a CD or DVD instead of the hard disk. Further, the map information DB 45 and the travel history DB 46 may be stored in an external server, and the navigation device 7 may acquire them through communication.

Here, the map information DB 45 includes, for example, link data related to roads (links), node data related to node points, search data used for processing related to search and change of routes, facility data related to facilities, maps for displaying maps, and so on. This is storage means for storing display data, intersection data for each intersection, search data for searching for points, and the like.

Further, the travel history DB 46 is storage means that accumulates and stores travel information (vehicle behavior) of the vehicle 5 . In this embodiment, the travel information stored in the travel history DB 46 particularly includes the history of the current position of the vehicle and the detection results of the in-vehicle sensor 8 . The travel information stored in the travel history DB 46 is transmitted as needed to the server device 3 as probe information.

On the other hand, a navigation ECU (electronic control unit) 33 is an electronic control unit that controls the entire navigation device 7, and includes a CPU 51 as an arithmetic device and a control device, and a working memory when the CPU 51 performs various arithmetic processing. A RAM 52 that stores route data and the like when a route is searched, a ROM 53 that stores a program for control, a road surface abnormality detection processing program (see FIG. 15), etc., which will be described later. It has an internal storage device such as a flash memory 54 for storing the read program.

The operation unit 34 is operated when inputting a departure point as a travel start point and a destination as a travel end point, and is composed of a plurality of operation switches (not shown) such as various keys and buttons. Then, the navigation ECU 33 performs control to execute various corresponding operations based on switch signals output by pressing of each switch or the like. The operation unit 34 can also be configured by a touch panel provided on the front surface of the liquid crystal display 35 . It can also be composed of a microphone and a voice recognition device.

In addition, the liquid crystal display 35 displays a map image including roads, traffic information, operation guidance, operation menu, key guidance, guidance information along the guidance route (planned driving route), news, weather forecast, time, mail, TV Programs, etc. are displayed. A HUD or HMD may be used instead of the liquid crystal display 35 .

In addition, the speaker 36 outputs voice guidance for driving along a guidance route (planned driving route) and traffic information guidance based on instructions from the navigation ECU 33 .

Also, the DVD drive 37 is a drive capable of reading data recorded on recording media such as DVDs and CDs. Then, based on the read data, music and video are reproduced, the map information DB 45 is updated, and so on. A card slot for reading and writing a memory card may be provided instead of the DVD drive 37 .

Also, the communication module 38 is a communication device for receiving traffic information and the like transmitted from the information management center 2, the VICS center, and other external centers, and corresponds to, for example, a mobile phone or a DCM. It also includes a vehicle-to-vehicle communication device that communicates between vehicles and a road-to-vehicle communication device that communicates with a roadside unit. It is also used to transmit and receive probe information to and from the server device 3 .

Here, as described above, in the road surface abnormality detection system 1 of the present embodiment, the server device 3 detects a road surface abnormality occurring on the road based on the detection value of the in-vehicle sensor 8 transmitted as probe information from the vehicle 5. To detect. The type of road surface abnormality detected based on the detection value of the in-vehicle sensor 8 is not particularly limited, but for example, there is a pothole. Potholes are, for example, irregularities formed on the surface of a road, holes in the road, peeling of asphalt, and the like.

As the in-vehicle sensor 8 for detecting potholes, for example, a vehicle speed sensor and a longitudinal acceleration sensor can be employed. The server device 3 detects the presence of a pothole, that is, the presence of a road surface abnormality, based on the vehicle speed collected from the vehicle and the acceleration generated in the longitudinal direction. For example, as shown in FIG. 8, when the wheels pass through potholes 55 formed in the road surface having a concave shape, the wheels move away from the edge 55A of the road surface and the vehicle 5 accelerates momentarily. As a result, the longitudinal acceleration sensor provided in the vehicle 5 receives acceleration backward due to inertia. After that, when the wheels hit the edge 55B of the road surface, the vehicle 5 decelerates momentarily. As a result, the longitudinal acceleration sensor provided in the vehicle 5 receives forward acceleration due to inertia. Therefore, it can be estimated that the vehicle 5 has passed through the road surface abnormality from the variation in the vehicle speed of the vehicle 5 and the variation in the acceleration occurring in the longitudinal direction. It should be noted that it is also possible to estimate that the road surface abnormality has been passed only from the variation in acceleration occurring in the longitudinal direction.

Furthermore, when the speed of the vehicle 5 is the same, variation in vehicle speed and acceleration tends to increase as the width and depth of the pothole 55 increase. Furthermore, when passing through the pothole 55 of the same width and depth, the faster the vehicle speed, the greater the variation in vehicle speed and acceleration. Therefore, the server device 3 can specify an anomaly level indicating the presence of an anomaly on the road surface based on the vehicle speed of the vehicle and the amount of variation in the acceleration occurring in the longitudinal direction. For example, the abnormality level is specified between 0 and 200. Targeting the point where the vehicle 5 is estimated to have passed the road surface abnormality, if the vehicle speed is the same, the variation amount of the vehicle speed and the variation amount of the longitudinal acceleration A larger value identifies a higher anomaly level. A point with a higher degree of anomaly level indicates a higher possibility of the presence of a road surface anomaly, and suggests that a larger road anomaly exists at that point. Furthermore, the server device 3 compares the threshold set for each vehicle 5 with the specified abnormality degree level, as described above, to finally determine the position and status (magnitude and degree of abnormality) of the road surface abnormality present on the road. ).

The in-vehicle sensor 8 for detecting road surface abnormalities is not limited to a vehicle speed sensor or a longitudinal acceleration sensor. For example, as the in-vehicle sensor 8, a vertical acceleration sensor that detects vertical acceleration acting on the wheels of the vehicle 5 may be employed. Then, the server device 3 may calculate the degree of abnormality level, for example, based on the variation in the vertical acceleration detected by the vertical acceleration sensor. Alternatively, for example, a suspension sensor that detects the amount of expansion and contraction of the suspension device of the wheel (the amount of displacement of the suspension arm) and a vehicle height sensor that detects the amount of displacement of the vehicle height are used as the in-vehicle sensor 8, and the suspension arm is similarly detected. The abnormality level may be calculated from the difference between the amount of displacement and the amount of displacement of the vehicle height.

Further, the type of road surface abnormality is not limited to potholes. For example, cracks in the road, bumps in the road, freezing of the road surface, etc. may be used. For example, the server device 3 may collect image data captured by an in-vehicle camera from the vehicle and determine cracks in the road. In this case, the server device 3 can calculate the length of the crack estimated by recognizing the image data, the ratio of crack occurrence locations per unit area, etc., as the abnormality level.

Further, the identification of the abnormality degree level based on the detection value of the vehicle-mounted sensor 8 may be performed by the navigation device 7 instead of the server device 3 . In that case, the identified abnormality level is transmitted to the server device 3 as probe information. If the navigation device 7 acquires the threshold value from the server device 3, it is possible for the navigation device 7 to detect a road surface abnormality existing on the road.

Next, a threshold initial setting processing program executed in the server device 3 constituting the road surface abnormality detection system 1 having the above configuration will be described with reference to FIG. FIG. 9 is a flowchart of a threshold initial setting processing program according to this embodiment. Here, the threshold initial setting processing program is executed at the timing of newly registering the vehicle 5 from which the probe information is to be collected in the road surface abnormality detection system 1, and the initial value of the threshold for detecting the road surface abnormality is set to the vehicle 5. It is a program to set for. 9, 10 and 12 are stored in the RAM 22, ROM 23, etc. of the server device 3, and are executed by the CPU 21. FIG.

The processing of the following steps (hereinafter abbreviated as S) 1 and S2 is executed for each vehicle 5 newly registered as a target for collecting probe information in the road surface abnormality detection system 1, and for all target vehicles 5 It is executed repeatedly until the process ends.

First, in S1, the CPU 21 causes the vehicle 5 to be processed to pass over a road surface abnormality sample prepared in advance by the road administrator, and acquires the detection value of the in-vehicle sensor 8 of the vehicle 5 when passing. For example, in this embodiment, detection values of the vehicle speed sensor and the longitudinal acceleration sensor are obtained. The road surface abnormality samples are, for example, potholes artificially created on the test course, and the following three types of road surface abnormality samples with different degrees of abnormality (size and depth) are prepared in advance.
(1) A road surface abnormality with the lowest degree of abnormality (hereinafter referred to as a first sample) among the road surface abnormalities that the road administrator wishes to include in the detection targets.
(2) A road surface abnormality with the lowest degree of abnormality (hereinafter referred to as a second sample) among the road surface abnormalities that the road administrator unconditionally wishes to include in the guidance target.
(3) A road surface abnormality intermediate between the first sample and the second sample (hereinafter referred to as the third sample).

As described above, when the wheels pass through potholes 55 formed in the road surface as shown in FIG. 8, the wheels move away from the edge 55A of the road surface and the vehicle 5 momentarily accelerates. As a result, the longitudinal acceleration sensor provided in the vehicle 5 receives acceleration backward due to inertia. After that, when the wheels hit the edge 55B of the road surface, the vehicle 5 decelerates momentarily. As a result, the longitudinal acceleration sensor provided in the vehicle 5 receives forward acceleration due to inertia. In S1, the variation in vehicle speed and the variation in acceleration occurring in the longitudinal direction of the vehicle 5 are obtained.

Next, in S2, the CPU 21 uses a previously prepared arithmetic expression based on the vehicle speed of the vehicle 5 detected when the vehicle 5 to be processed passes the first sample and the amount of variation in the acceleration occurring in the longitudinal direction. An anomaly level corresponding to passage of the first sample is calculated. The abnormality level is calculated, for example, between 0 and 200. If the vehicle speed of the vehicle 5 is the same, the higher the abnormality level is calculated, the greater the variation in vehicle speed and the variation in longitudinal acceleration. Then, the calculated abnormality degree level is set as the initial value of the first threshold of the vehicle 5 to be processed. The first threshold is a threshold for determining whether or not to detect a road surface abnormality (that is, if the abnormality level is less than the first threshold, it is not detected, and if the abnormality level is equal to or higher than the first threshold, it is detected. target).

In addition, the CPU 21 similarly detects an abnormality corresponding to the passage of the second sample based on the amount of variation in the vehicle speed of the vehicle 5 detected when the vehicle 5 to be processed passes the second sample and the amount of acceleration generated in the longitudinal direction. degree level is calculated, and the calculated abnormality degree level is set as the initial value of the third threshold value of the vehicle 5 to be processed. The third threshold is a threshold for determining whether or not the detected road surface abnormality is to be a target for guidance by default (that is, if the abnormality level is greater than or equal to the first threshold and less than the third threshold, it is detected as a road surface abnormality, but the road Basically, if there is no request from the administrator, it is not subject to guidance to the road administrator, and if the abnormality level is equal to or higher than the third threshold, it is unconditionally subject to guidance to the road administrator as a road surface abnormality). .

Further, the CPU 21 similarly detects an abnormality corresponding to the passage of the third sample based on the amount of variation in the vehicle speed of the vehicle 5 detected when the vehicle 5 to be processed passes the third sample and the amount of variation in acceleration occurring in the longitudinal direction. degree level is calculated, and the calculated abnormality degree level is set as the initial value of the second threshold value of the vehicle 5 to be processed. The second threshold is set between the first threshold and the third threshold, and is a threshold for classifying the magnitude and degree of road surface abnormality.

After that, the CPU 21 sets the initial values of the thresholds for all the target vehicles 5, and then terminates the threshold initial setting processing program. The initial value of the threshold set by the threshold initial setting processing program is stored in the detection threshold DB 13 ( FIG. 4 ) in association with the vehicle ID that identifies the vehicle 5 .

Next, a recommended threshold value calculation processing program executed by the server device 3 constituting the road surface abnormality detection system 1 will be described with reference to FIG. 10 . FIG. 10 is a flowchart of a recommended threshold value calculation processing program according to this embodiment. Here, the recommended threshold value calculation processing program is a program that is executed every predetermined period (for example, every 24 hours) and derives a recommended threshold value for detecting road surface anomalies based on the history of road maintenance.

First, in S11, the CPU 21 determines whether the road administrator has responded to the road surface abnormality within the period after the previous program was executed (that is, the most recent 24 hours if the recommended threshold value calculation processing program is executed every 24 hours). The result of newly performed work, that is, the history of road maintenance for the road surface abnormality is acquired from the repair history DB 15 . As shown in FIG. 6, when road maintenance work is performed by a road administrator, the repair history DB 15 stores the work result and the date and time when the work was performed. In addition, as work results, "the result of carrying out the work to repair the road surface abnormality" and "a decision was made to suspend the repair after confirming the road surface abnormality (i.e., not to repair at this time). result”.

Next, in S12, the CPU 21 sends the maintenance history read in S11 to the vehicle that detected the road surface abnormality (more precisely, the vehicle that transmitted the probe information used for detection) for which the work was performed for each work result. Link and classify.

The following processing of S13 to S16 is executed for each vehicle 5 registered as a target for collecting probe information in the road surface abnormality detection system 1 and for each work result linked in S12, and all the target vehicles 5 And the work result is repeatedly executed until the process is completed.

In S13, the CPU 21 determines whether or not the work result to be processed is "the result of performing the work for repairing the road surface abnormality".

Then, when it is determined that the work result to be processed is "the result of performing the work for repairing the road surface abnormality" (S13: YES), the process proceeds to S15. On the other hand, if it is determined that the work result to be processed is "the result of confirming the road surface abnormality and then deferring the repair" (S13: NO), the process proceeds to S14. do.

In S14, the CPU 21 determines that the road surface abnormality detected in the past by the vehicle 5 to be processed was not a road surface abnormality of a level that should be repaired by the road administrator. should be set higher (limited to those with higher anomaly levels). Then, the CPU 21 adds +1 to the recommended threshold, which is the recommended value of the threshold. The initial value of the recommended threshold value is the same as the initial value of the threshold value set by the threshold initial setting processing program (FIG. 9). Then, the recommended threshold value is increased or decreased from the initial value as shown in FIG. 11 by S14 or S16 which will be described later. For example, in the example shown in FIG. 11, the initial value of the threshold is 100, and the recommended threshold is increased or decreased with 100 as the initial value. However, when the recommended threshold value is decreased as described later, the range within ±5% of the currently set threshold value is set as the adjustment region, and the adjustment region is not exceeded.

Further, when the threshold value is changed in the threshold correction processing program (FIG. 12) described later, the changed threshold value is newly set as the initial value of the recommended threshold value. A recommended threshold may be provided only for the first threshold, or recommended thresholds may be provided for all of the first, second, and third thresholds. If recommended thresholds are provided for all of the first, second, and third thresholds, +1 is added to each recommended threshold. Further, the current recommended threshold values are classified for each vehicle 5 and stored in the flash memory 24 or the like.

On the other hand, in S15, the CPU 21 reads out the current recommended threshold associated with the vehicle 5 to be processed, and determines whether or not the current recommended threshold is included in the adjustment area. Note that the adjustment area is within ±5% of the currently set threshold value. For example, if the currently set first threshold is 100 as shown in FIG. 11, it is determined whether the recommended threshold for the first threshold is included in the range from 95 to 105.

Then, when it is determined that the current recommended threshold is included in the adjustment area (S15: YES), the process proceeds to S16. On the other hand, if it is determined that the current recommended threshold is not included in the adjustment area (S15: NO), the process ends without increasing or decreasing the recommended threshold.

In S16, the CPU 21 estimates that the current threshold is an appropriate threshold because the road surface abnormality detected in the past by the vehicle 5 to be processed was a road surface abnormality that should be repaired by the road administrator. On the other hand, the possibility that the threshold of the degree of abnormality level for detecting road surface abnormality is too high (it is better to widen the threshold to include those with a lower degree of abnormality) is also considered. As a result, the CPU 21 subtracts -1 from the recommended threshold, which is the recommended value of the threshold. If recommended thresholds are provided for all of the first, second, and third thresholds, -1 is subtracted from each recommended threshold. Further, the current recommended threshold values are classified for each vehicle 5 and stored in the flash memory 24 or the like.

The processing of S13 to S16 is performed for each vehicle 5 registered as a target for collecting probe information in the road surface abnormality detection system 1, based on the work results for the road surface abnormality detected by the vehicle 5 in the past. Then, a recommended threshold value corresponding to the road administrator's criteria for repairing the road surface abnormality is derived as the recommended threshold value.

Next, a threshold correction processing program executed in the server device 3 that constitutes the road surface abnormality detection system 1 will be described with reference to FIG. 12 . FIG. 12 is a flow chart of a threshold correction processing program according to this embodiment. Here, the threshold correction processing program is executed at the timing when the server device 3 receives a request signal for threshold correction from the operation terminal 4 owned by the road administrator, and corrects the threshold for detecting road surface abnormalities.

First, in S21, the CPU 21 reads out the current threshold stored in the detection threshold DB 13 and transmits it to the operation terminal 4 which is the transmission source of the request signal. The threshold is set for each vehicle 5 in association with the vehicle ID as shown in FIG. Send the threshold that is set. In addition, the recommended threshold value derived by the recommended threshold value calculation processing program (FIG. 10) described above is similarly transmitted to all the vehicles 5 at the present time.

After that, in the operation terminal 4 that has received the information about the threshold and the recommended threshold from the server device 3 in S21, the threshold setting screen is displayed on the display. Here, FIG. 13 is a diagram showing a threshold setting screen 61 displayed on the display of the operation terminal 4. As shown in FIG.

As shown in FIG. 13 , the threshold value setting screen 61 is classified for each vehicle 5 registered together and indicates the threshold value and recommended threshold value currently set for each vehicle 5 . Specifically, a number line indicating the range of 0 to 200 of the abnormality degree level is displayed, an icon 62 indicating the numerical value of the first threshold on the number line, an icon 63 indicating the numerical value of the second threshold, An icon 64 indicating the numerical value of the third threshold is displayed. Also displayed are an icon 65 indicating the recommended numerical value of the first threshold, an icon 66 indicating the recommended numerical value of the second threshold, and an icon 67 indicating the recommended numerical value of the third threshold. By visually recognizing the threshold setting screen 61 displayed on the display of the operation terminal 4, the road administrator can see the threshold currently set for each vehicle and the threshold derived in the above-mentioned recommended threshold calculation processing program (FIG. 10). It is possible to grasp the recommended threshold value, which is the recommended value of the threshold value.

Further, the road administrator (operator) can move the icons 62 to 65 displayed on the threshold value setting screen 61 left and right by operating the operation terminal 4 . Then, in S22, the CPU 21 determines whether or not an operation to move the icons 62 to 65 has been received on the operation terminal 4. If it is determined that an operation to move the icons 62 to 65 has been received (S22: YES), , the threshold is changed to the abnormal level value corresponding to the positions of the icons 62 to 65 after movement on the number line (S23). Specifically, among the thresholds stored in the detection threshold DB 13, the corresponding threshold is updated to the changed value. When changing the threshold, it is possible to change to the recommended threshold indicated by the icons 65 to 56, or to a value other than the recommended threshold. However, it is also possible to allow only the change to the recommended threshold value (that is, to select from two choices of no change or change to the recommended threshold value).

For example, FIG. 14 shows a case where the icon 62 indicating the first threshold for the vehicle ID “A” is moved to the position of the recommended threshold on the threshold setting screen 61 . When the operation shown in FIG. 14 is performed, the first threshold is changed to the same value as the recommended threshold (for example, 60).

Note that the threshold correction processing program described above can change the threshold to the recommended threshold based on the operation by the road administrator. You can do it. For example, when the road surface abnormality detection system 1 is provided with a mode that permits automatic correction of the threshold value, and the mode is set to permit automatic correction, the recommended threshold value is derived in the recommended threshold value calculation processing program (FIG. 10) described above. Then, the CPU 21 may automatically correct the current threshold to the derived recommended threshold. Further, the reliability of the recommended threshold value may be calculated in consideration of the surrounding weather and the like when the vehicle 5 acquires the detection value of the in-vehicle sensor 8, and automatic correction may be performed only when the reliability is high.

Next, a road surface abnormality detection processing program executed by the server device 3 and the navigation device 7 constituting the road surface abnormality detection system 1 will be described with reference to FIG. FIG. 15 is a flowchart of a road surface abnormality detection processing program according to this embodiment. Here, the road surface abnormality detection processing program is repeatedly executed at predetermined time intervals (for example, 200 msec intervals) after the ACC power supply (accessory power supply) of the vehicle is turned on. The server device 3 collects the current position of the vehicle and the detection values of the in-vehicle sensor 8 as probe information, and detects road surface abnormalities on the road surface on which the vehicle 5 travels based on the collected probe information. 15 below is stored in the RAM 22 and ROM 23 provided in the server device 3 or the RAM 52 and ROM 53 provided in the navigation device 7, and is executed by the CPU 21 or CPU 51.

First, the road surface abnormality detection processing program executed in the navigation device 7 will be described.
In S31, the CPU 51 acquires the detection result of the in-vehicle sensor 8 via CAN or the like together with the detection result of the GPS 42 . The in-vehicle sensor 8 provided in the vehicle includes, for example, a vehicle speed sensor, a steering sensor, a yaw rate sensor, a gyro sensor, a longitudinal acceleration sensor, a vertical acceleration sensor, and an infrared sensor. A sensor for detecting the changing running state of the vehicle 5 includes a vehicle speed sensor and a longitudinal acceleration sensor. Therefore, in S31, at least the "current position coordinates of the vehicle 5", the "current vehicle speed of the vehicle 5", and the "acceleration generated in the longitudinal direction with respect to the vehicle 5" are acquired. The acquisition of the information in S31 is repeated at intervals of 200 msec while the ACC power is ON.

Next, in S32, the CPU 51 transmits each piece of information acquired in S31 to the server device 3 as probe information together with a "vehicle ID" that identifies the vehicle of the transmission source. Based on the received probe information, the server device 3 detects a road surface abnormality as described later. The transmission of the probe information in S32 is performed, for example, at intervals of 1 second, and the new information obtained in S31 up to the present time after the previous transmission of the probe information is to be transmitted. However, the timing of transmitting the probe information does not necessarily have to be every one second, and can be changed as appropriate.

In the present embodiment, the processing of S31 and S32 is performed by the navigation device 7, but may be performed by another vehicle-mounted device provided in the vehicle 5 or by a vehicle control ECU.

Next, a road surface abnormality detection processing program executed by the server device 3 will be described.
First, in S<b>41 , the CPU 21 determines whether probe information is transmitted from each vehicle 5 registered as a target for collecting probe information in the road surface abnormality detection system 1 .

And when it determines with probe information transmission (S41:YES), the transmitted probe information is received (S42). Then, the CPU 21 cumulatively stores the received probe information in the probe information DB 12 (S43).

On the other hand, if it is determined that the probe information has not been transmitted (S41: NO), the road surface abnormality detection processing program is ended. It should be noted that the probe information received in S42 is travel data including the detection result of the vehicle-mounted sensor 8 that detects the travel condition of the vehicle 5 that changes according to the road surface condition. ”, “date and time”, “vehicle position coordinates”, and “detected values of on-vehicle sensors 8 provided in the vehicle”.

The following processing of S44 to S46 is executed for each vehicle 5 registered as a target for collecting probe information in the road surface abnormality detection system 1 and for each point where it is suspected that the vehicle 5 has passed a road surface abnormality. It is repeatedly executed until the processing is completed for all the vehicles 5 and the points.

As described above, when the wheels pass through the concave potholes 55 formed in the road surface, the wheels move away from the edge 55A of the road surface and the vehicle 5 momentarily accelerates as shown in FIG. As a result, the longitudinal acceleration sensor provided in the vehicle 5 receives acceleration backward due to inertia. After that, when the wheels hit the edge 55B of the road surface, the vehicle 5 decelerates momentarily. As a result, the longitudinal acceleration sensor provided in the vehicle 5 receives forward acceleration due to inertia. Therefore, the server device 3 can estimate that the vehicle 5 has passed through the road surface abnormality based on the variation in the vehicle speed of the vehicle 5 and the variation in the acceleration occurring in the longitudinal direction. The processing is executed for the point where the passage is suspected.

First, in S44, the CPU 21 prepares in advance based on the vehicle speed of the vehicle 5 detected when the vehicle 5 to be processed passes a point suspected of passing through a road surface abnormality and the amount of variation in the acceleration occurring in the longitudinal direction. The anomaly level is calculated by the arithmetic expression. The abnormality level is calculated, for example, between 0 and 200. If the vehicle speed of the vehicle 5 is the same, the higher the abnormality level is calculated, the greater the variation in vehicle speed and the variation in longitudinal acceleration.

Next, in S45, the CPU 21 reads the threshold currently set for the vehicle 5 to be processed from the detection threshold DB 13 . As the threshold, there are a first threshold, a second threshold and a third threshold, which are stored in the detection threshold DB 13 in association with each vehicle (FIG. 4). The threshold value is set as an initial value by the threshold initial setting processing program (FIG. 9), and is appropriately corrected by the threshold correction processing program (FIG. 12).

Subsequently, in S46, the CPU 21 compares the abnormality degree level specified in S44 with the threshold value read in S45, and when the abnormality degree level is equal to or higher than the first threshold value, the passage of the road surface abnormality is detected. Detect road anomalies to suspected points. Furthermore, based on the comparison with the second threshold value and the third threshold value, the current status (magnitude and degree of abnormality) of the detected road surface abnormality is also specified. Specifically, when the abnormality level is greater than or equal to the first threshold value and less than the second threshold value, it is determined that there is a "level 1 (small)" road surface abnormality. Further, when the degree of abnormality level is greater than or equal to the second threshold value and less than the third threshold value, it is determined that there is a "level 2 (medium)" road surface abnormality. Further, when the degree of abnormality level is equal to or higher than the third threshold, it is determined that there is a road surface abnormality of "level 3 (large)".

After that, in S47, the CPU 21 updates the road surface abnormality detection DB 14 based on the detection result of S46. For example, when a new road surface abnormality is detected, for each newly detected road surface abnormality, the position where the road surface abnormality was detected and the vehicle that detected the road surface abnormality (more precisely, the probe information used for detection) are sent. (transmission source vehicle), the date and time when the road surface abnormality was detected, and the current status of the road surface abnormality (magnitude and degree of abnormality) are stored. On the other hand, for example, when the shape of an existing road surface abnormality increases with the passage of time and the status changes, the status portion of the corresponding road surface abnormality information is updated. Further, when the road surface abnormality is repaired by the road administrator, the information on the repaired road surface abnormality is manually or automatically deleted from the road surface abnormality detection DB 14 . As a result, it becomes possible for the server device 3 to manage road surface abnormalities that occur on roads to be managed by the road administrator.

Further, the information on the road surface abnormality detected by the road surface abnormality detection processing program and stored in the road surface abnormality detection DB 14 is distributed to the operation terminal 4 in response to a request from the operation terminal 4 . The operation terminal 4 to which the information on the road surface abnormality is distributed displays the distributed information on the road surface abnormality on a display or the like, and guides the road administrator.

For example, FIG. 16 is a diagram showing a road surface abnormality management screen 71 displayed on the display of the operation terminal 4 when providing information on the road surface abnormality to the road administrator. As shown in FIG. 16, on the road surface abnormality management screen 71, a map image 72 is displayed, and a road surface abnormality mark 73 indicating the existence of the road surface abnormality is displayed at the position where the road surface abnormality is detected on the map image 72. . Further, when the user selects the road surface abnormality mark 73 displayed on the road surface abnormality management screen 71, an information window 74 is displayed that displays more detailed information about the road surface abnormality corresponding to the selected road surface abnormality mark 73.

The information window 74 displays, for example, a management number for managing the road surface abnormality, the date and time when the road surface abnormality was detected, and the current status of the road surface abnormality (magnitude and degree of abnormality). Further, when a photograph of the road surface abnormality can be obtained from a vehicle that has passed through the road surface abnormality, the corresponding photograph is obtained from the vehicle 5 and displayed. Furthermore, the information window 74 may display information other than the above as information on the road surface abnormality. For example, the type of road surface abnormality, prediction of future changes in the status of the road surface abnormality, and the like may be displayed. Unless otherwise specified, the road surface abnormality management screen 71 provides guidance only for road surface abnormality information with a status of level 3 (large). ) and level 2 (medium) road surface abnormalities are also subject to guidance. Then, the road administrator refers to the information on the road surface abnormality that has been guided, and further checks the site if necessary, and then decides whether to repair the detected road surface abnormality or suspend the repair.

As described in detail above, in the road surface abnormality detection system 1, the server device 3, and the computer program executed by the server device 3 according to the present embodiment, the vehicle 5 traveling on the road to be managed receives the Traveling data including the detection results of the in-vehicle sensor 8 that detects the changing traveling state of the vehicle 5 is collected (S42), and based on the collected traveling data, the presence of a road surface abnormality is suggested on the road surface on which the vehicle 5 travels. While identifying the abnormality level (S44), based on the history of road maintenance for past road surface abnormalities, the threshold of the abnormality level for detecting road surface abnormalities is set (S11 to S16, S21 to S23 ), it is detected that a road surface abnormality has occurred at a point where the abnormality level specified on the road surface on which the vehicle 5 has traveled exceeds a threshold value (S46). Considering the difference in judgment criteria, it becomes possible for the road administrator to detect only road surface abnormalities that should be detected.
In addition, since the history of road maintenance is a history indicating whether the road surface abnormality detected in the past has been repaired or is on hold, it is possible to determine whether the road administrator has actually repaired the road surface abnormality. By referring to whether the road is being repaired or not repaired, it becomes possible for the road administrator to set a threshold value so that only road surface abnormalities that should be detected can be detected.
Also, when setting the threshold of the degree of abnormality level for detecting road surface abnormalities, if repairs are performed for road surface abnormalities detected in the past, the threshold is corrected so that it becomes a lower degree of abnormality level, If repairs are pending for road surface anomalies detected in the past, the threshold is corrected to a higher anomaly level. By correcting as appropriate, road surface anomalies at anomaly levels at which road administrators repair road surface anomalies are included in the detection targets, while road surface anomalies at anomaly levels at which road administrators withhold repair of road anomalies can be excluded from detection targets.
In addition, since the running condition of the vehicle, which changes according to the road surface condition, includes changes in the acceleration occurring in the longitudinal direction with respect to the vehicle, by collecting the detection results of the sensors of the vehicle 5, it is possible to determine whether the vehicle has passed through the road surface abnormality. It is possible to accurately detect that.
In addition, traveling data is collected for a plurality of vehicles 5, and a threshold value is set based on the history of road maintenance for road surface abnormalities detected from the traveling data of the vehicle 5 for each vehicle 5 whose traveling data is to be collected. Since the threshold values are set (S11 to S16, S21 to S23), it is possible to set the threshold values in consideration of the characteristics of each vehicle from which traveling data is collected. Therefore, it is possible to detect a road surface abnormality based on travel data collected from vehicles of various types.
Further, based on the history of road maintenance for road surface abnormalities performed within the most recent predetermined period for each predetermined period, a recommended value for the threshold of the degree of abnormality level for detecting road surface abnormalities is specified (S11 to S16), and the current A screen showing the set threshold value and the recommended value of the threshold value is displayed on the display device (S21), and the currently set threshold value is corrected based on the operation of the operator viewing the display device (S23). Therefore, it is possible to specify the recommended threshold value based on the road surface abnormality repair judgment criteria of each road administrator, and to modify the threshold value to the recommended value based on the final intention of the road administrator. Become.
Further, based on the history of road maintenance for road surface abnormalities performed within the most recent predetermined period for each predetermined period, a recommended value for the threshold of the degree of abnormality level for detecting road surface abnormalities is specified (S11 to S16), and the current Since the set threshold is corrected to the recommended threshold value, the recommended threshold value is specified based on the judgment criteria for road surface abnormality repair for each road administrator, and the threshold value is corrected to the recommended value. It is possible for the administrator to detect only road surface abnormalities that should be detected.

It should be noted that the present invention is not limited to the above-described embodiments, and of course various improvements and modifications are possible without departing from the gist of the present invention.
For example, in the present embodiment, a probe car system using probe information is used to collect traveling data from a plurality of vehicles traveling on roads managed by a road administrator, but the probe car system is not essential. For example, it is possible to detect a road surface abnormality based on travel data acquired from one vehicle.

In this embodiment, the server device 3 collects detection values of the in-vehicle sensor 8 from the vehicle 5, and the server device 3 side detects an abnormality in the road surface that the vehicle has passed (S44 to S46). It is also possible to detect an abnormality in the road surface through which the own vehicle passes based on the detection value of the vehicle-mounted sensor 8 of the own vehicle. In that case, information about the threshold is distributed from the server device 3 to each vehicle 5, each vehicle 5 detects a road surface abnormality using the distributed threshold, and the detection result is sent to the server device 3 as probe information. to send.

Further, in the present embodiment, the server device 3 executes the recommended threshold value calculation processing program shown in FIG.

Also, in the present embodiment, three thresholds, ie, a first threshold, a second threshold, and a third threshold, are provided as thresholds for detecting a road surface abnormality, but only the first threshold may be used.

In this embodiment, the road surface abnormality status is divided into three levels, level 1 (small), level 2 (medium), and level 3 (large), in descending order of the degree of abnormality. ) may be specified. Level 0 is a road surface abnormality that has been repaired by a road administrator in the past, and the abnormality level is less than the first threshold.

In the present embodiment, the vehicle speed and the acceleration in the longitudinal direction of the vehicle are used to detect that the vehicle has passed through a road surface abnormality (S44 to S46). Other methods may be used as the detection method. For example, there are a method of detecting acceleration generated in the vertical direction with respect to the vehicle, a method of detecting the operation of the suspension, and a method of detecting based on an image captured by an external camera.

Further, in the present embodiment, when calculating the recommended threshold value, it is referred to whether the road surface abnormality has been repaired or is on hold as the history of road maintenance (S13). In some cases, the recommended threshold may be calculated based on the reason for suspension. Further, when repair is being performed, the recommended threshold may be calculated based on the number of days from the detection of the road surface abnormality to the repair.

In this embodiment, the road surface abnormality detection system 1 exists for each local government or road management company that manages roads, but it may be a system that is shared by a plurality of local governments and road management companies. However, in that case, the probe information DB 12, the detection threshold DB 13, the road surface abnormality detection DB 14, and the repair history DB 15 are classified and managed for each local government or each road management company.

DESCRIPTION OF SYMBOLS 1... Road surface abnormality detection system 2... Information management center 3... Server apparatus 4... Operation terminal 5... Vehicle 7... Navigation apparatus 8... In-vehicle sensor 12... Probe information DB 13... Detection threshold DB 14 Road surface abnormality detection DB 15 Repair history DB 21 CPU 22 RAM 23 ROM 24 Flash memory 33 Navigation ECU 55 Pothole 61 Threshold setting screen

Claims (7)

a traveling data collection means for collecting traveling data including detection results of sensors for detecting the traveling state of the vehicle, which changes according to the road surface state, from the vehicle traveling on the road to be managed;
Abnormality level identification means for identifying an abnormality level suggesting the presence of a road surface abnormality on the road surface on which the vehicle travels based on the collected travel data;
Threshold setting means for setting a threshold of an abnormality degree level for detecting a road surface abnormality based on the history of road maintenance for past road surface abnormalities;
A road surface abnormality detection system, comprising road surface abnormality detection means for detecting that a road surface abnormality has occurred at a point where the abnormality degree level specified on the road surface on which the vehicle travels exceeds the threshold value. 2. The road surface abnormality detection system according to claim 1, wherein the history of road maintenance is a history indicating whether the road surface abnormality detected by the road surface abnormality detection means in the past has been repaired or is pending repair. . The threshold setting means is
When the road surface abnormality detected by the road surface abnormality detection means has been repaired in the past, the threshold is corrected to a lower abnormality degree level,
3. The road surface abnormality detection system according to claim 2, wherein when the road surface abnormality detected by said road surface abnormality detection means in the past is pending repair, the threshold value is corrected to a higher degree of abnormality level. 4. The road surface abnormality detection system according to any one of claims 1 to 3, wherein the running condition of the vehicle that changes according to the road surface condition includes changes in acceleration occurring in the longitudinal direction with respect to the vehicle. The traveling data collection means collects the traveling data for a plurality of vehicles,
5. The threshold value setting means sets the threshold value for each vehicle for which the travel data is collected, based on a history of road maintenance for road surface abnormalities detected from the travel data of the vehicle. Road surface abnormality detection system according to any one of. The threshold setting means is
Based on the history of road maintenance for road surface abnormalities performed within the most recent predetermined period for each predetermined period, a recommended value for the threshold of the degree of abnormality level for detecting road surface abnormalities is specified,
displaying a screen showing the currently set threshold value and the recommended value of the threshold value on the display device;
6. The road surface abnormality detection system according to any one of claims 1 to 5, wherein a currently set threshold value is corrected based on an operation of an operator who visually recognizes said display device. The threshold setting means is
Based on the history of road maintenance for road surface abnormalities performed within the most recent predetermined period for each predetermined period, a recommended value for the threshold of the degree of abnormality level for detecting road surface abnormalities is specified,
6. The road surface abnormality detection system according to any one of claims 1 to 5, wherein a currently set threshold value is corrected to a recommended value of said threshold value.

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