JP7195021B2 - Data collection device, road condition evaluation support device, and program - Google Patents

Description

The present invention relates to, for example, a data collection device, a road condition evaluation support device, a program, and the like.

A laser ranging method is used to measure the amount of displacement such as the amount of subsidence of a road surface (Patent Document 1). In this laser distance measurement method, the displacement amount of the surface to be measured is calculated using laser distance measurement means having a function of setting the irradiation angle of the laser beam to a designated azimuth angle and/or vertical angle. A specific part on the measurement target surface obtained in the previous or previous survey is set as the displacement reference point, and the three-dimensional coordinates of the displacement reference point, or the distance from the surveying instrument to the displacement reference point and the sighting direction are stored. back. In this survey, the sighting direction of the displacement reference point or the three-dimensional coordinates of the displacement reference point were used from the memorized surveying instrument, and the point corresponding to the displacement reference point was sighted as the sighting point. Then, the point on the measurement target surface detected in the collimation direction is defined as the detection point, and the three-dimensional coordinates of this detection point or the distance from the surveying instrument to the detection point are obtained, and the detection point is determined with reference to the displacement reference point. Calculate the amount of displacement of Based on the detected amount of displacement, it is possible to predict when the road should be repaired.

JP 2011-7657 A

In order to measure the amount of displacement such as the amount of subsidence of a road surface using the laser ranging method, a laser ranging device must be installed in advance at the measurement location. By installing a laser ranging device in advance at a place where there is a high risk of subsidence, it is possible to measure the amount of subsidence of the road surface at that location. It is not possible to measure the amount of subsidence of the road surface.

An object of the present invention is, for example, to collect data that serves as a basis for determining whether or not roads or road accessories need to be repaired without installing a measuring device such as a laser ranging device in advance at the measurement location. It is to provide a data collection device etc. that can Another object of the present invention is, for example, to provide a road condition evaluation support device or the like for determining whether or not repair is necessary based on these collected data.

(1) It is mounted on a vehicle and used, and has a processing means for collecting determination basic data, which is data serving as a basis for determining the necessity of repairing roads or road appendages, wherein the determination basic data is the vehicle. The data collection device may include image data of the surroundings of the .

Based on the collected image data, it is possible to accurately determine whether the road or road appendages need to be repaired. It is preferable to have a function to display the collected judgment basic data, and it is particularly preferable to have a function to display an image of the collected image data. By doing so, it is possible to accurately determine whether or not the road or road appendages need to be repaired by looking at the displayed image.

Whether road repair is necessary (whether or not repair work is necessary) is based on, for example, the presence or absence of unevenness such as steps and dents on the road surface, rutting, cracks, repaired joints of expressways, subsidence of the road surface, etc. . As the determination basic data for determining the presence or absence of unevenness on the road surface, for example, acceleration data representing the acceleration applied to the vehicle when passing over the unevenness on the road surface, image data obtained by photographing the surroundings of the vehicle, and the like may be used. Image data obtained by photographing the front of the vehicle, for example, may be used as basic determination data for determining the presence or absence of rutting and cracking. Data indicating the inclination of the vehicle when passing through a subsidence point or the like may be used as the determination basic data for determining whether or not the road surface has subsidence.

Road attachments include, for example, fall prevention fences, separation fences between roadways and sidewalks, rows of trees on roads, road signs, road markings, road information display devices, vehicle monitoring devices, and utility tunnels. Data such as images of the surroundings of the vehicle may be used as basic determination data for determining whether repair is necessary.

The processing means preferably has a function of transferring the collected image data to an external device having a display function or a function of displaying the data on a device having a display function. A subject who determines whether or not repair is necessary may be, for example, a road administrator who has seen the image of the image data included in the determination basic data. For example, an image analysis program that analyzes image data included in the determination basic data and an artificial intelligence (AI) that performs determination processing based on the image analysis results may be used to determine whether repair is necessary.

The image data to be collected should preferably consist of a plurality of images acquired at a constant sampling cycle. This sampling period is preferably short enough to obtain images of the surroundings of the route traveled by the vehicle from the plurality of images included in the collected image data without interruption along the route. It is particularly preferable for the processing means to collect moving image data as this image data.

The processing means, for example, preferably has a function of recording the collected determination basic data in a recording device. A removable memory card, for example, may be used as the recording device. By doing so, the basic determination data can be transferred from the data collection device to other devices via the memory card.

For example, the determination basic data may include acceleration data obtained by quantifying the acceleration applied to the vehicle. The processing means preferably has a function of passing the acceleration data included in the determination basic data to an external device having a display function, or a function of causing the device having the display function to display the acceleration data. Acceleration data may be displayed, for example, as changes in acceleration on the time axis (time waveform). A subject who determines whether or not repair is necessary may be, for example, a road administrator who sees the time waveform of acceleration displayed on the screen of a personal computer. The subject that determines whether or not repair is necessary may be, for example, a determination program that performs determination based on the shape of the time waveform of acceleration.

(2) The determination basic data may include sensing data obtained by a sensor mounted on the vehicle and different from image data around the vehicle.

Sensing data includes, for example, position data indicating the current position of the vehicle, image data different from image data obtained by photographing the surroundings of the vehicle in (1) above, acceleration data indicating the magnitude of acceleration applied to the vehicle, and the like. Good to adopt.

A GPS receiver, for example, may be used as a sensor for acquiring position data. The processing means detects, for example, based on the position data that the vehicle has approached a point at which it should be determined whether or not the road or road appendages need to be repaired, or that the vehicle has entered an area where it should be determined whether the road or road appendages need to be repaired. It is preferable to have a function to detect the entry of It is preferable that the processing means has a function of collecting judgment basic data within a point or area where the necessity of repair of the road or road appendages is to be judged.

As the sensors for acquiring the image data obtained by photographing the surroundings of the vehicle in (1) above and the image data different from the image data, mutually different imaging devices such as a CMOS camera and a CCD camera may be used. For example, it is preferable that one image capturing device captures an image of the road surface and road attachments in front of the vehicle, and the other image capturing device captures an image of the road surface immediately below the vehicle. From these image data, the processing means can obtain information such as the condition of the road surface and the shape and surface condition of road appendages arranged around the road on which the vehicle travels.

As a sensor for obtaining acceleration data, for example, an acceleration sensor for detecting acceleration applied to the vehicle may be used. The processing means can detect the magnitude of the impact on the vehicle, for example from acceleration data. Based on the difference in the magnitude of the impact, the processing means can distinguish, for example, that the vehicle has received an impact due to a collision, that the vehicle has received an impact due to passing over an uneven road surface, and the like.

The processing means preferably has a function of associating the image data obtained by photographing the surroundings of the vehicle in (1) above with the sensing data in (2) above, creating a database, and recording the data. For example, the two may be associated with each other according to the date and time when the data was acquired. By doing so, it is possible to extract the corresponding data from one of the data. The processing means preferably has a function of transferring these image data and sensing data to an external device. The external device preferably has a function of associating the delivered image data with the sensing data, creating a database, and recording the data.

It is particularly preferable to use sensing data other than image data. The image data obtained by photographing the surroundings of the vehicle in (1) and the sensing data other than the image data in (2) are associated to more accurately determine the necessity of repairing the road or road appendages. be able to.

(3) the sensing data includes acceleration data representing the magnitude of acceleration applied to the vehicle;
Data having a function of recording, in a recording device, the image data and the acceleration data collected before and after the detection time when the processing means detects that the vehicle has collided based on the acceleration data. It may be a collecting device.

The data collection device having the function (1) above can be used as a general drive recorder that records images of the surroundings at the time the collision accident occurred (hereinafter referred to as event recording).

(4) When the processing means detects, based on the acceleration data, that the vehicle has passed an uneven road surface, the image data and the acceleration data collected before and after the detection time are stored in the recording device. It may be a data collection device for recording.

When it is difficult to determine whether or not road repair is necessary using only acceleration data, the image of the road surface represented by the image data can be used as information for determining whether or not repair is necessary.

For example, when the peak value of the measured acceleration exceeds the determination threshold, it may be determined that the vehicle has passed an uneven road surface. This determination threshold value is preferably determined by actually traveling on a road surface with various unevenness and measuring the acceleration applied to the vehicle. Road surface irregularities include, for example, pavement cracks, ruts, steps, potholes, and the like.

For general drive recorders that record events, the peak of the acceleration time waveform generated by the shock applied when the vehicle passes over uneven road surfaces is an obstacle to detecting the occurrence of a collision accident (such as debris). data). In general, the peak of the time waveform of acceleration that occurs when the road surface is uneven is smaller than the peak of the acceleration that occurs during a collision accident. Using this difference in peak magnitude, a typical drive recorder distinguishes between the occurrence of a collision accident and the passage of an uneven road surface. General drive recorders are equipped with a function to find (pick up) the point where unevenness occurs on the road surface by using the peak of the time waveform of relatively small acceleration, which has been treated as an obstacle, as a trigger (detection trigger). Good. By doing so, a general drive recorder can be easily diverted to a data collection device for collecting judgment basic data for judging the necessity of repairing a road or an adjunct to the road. Also, by providing both a function of detecting the occurrence of a collision accident and a function of detecting that the vehicle has passed over an uneven road surface, the drive recorder can be used in common with this data collection device.

(5) The processing means determines that a collision has occurred in the vehicle when the magnitude of the acceleration indicated by the acceleration data is equal to or greater than a first determination threshold, and the magnitude of the acceleration indicated by the acceleration data is The data collection device may determine that the vehicle has passed through an uneven road surface when the second determination threshold value is smaller than the first determination threshold value or more.

Collected acceleration data can be used to distinguish between the impact experienced by the vehicle as it passes over bumps in the road surface and the impact received during a crash. As a result, for example, a drive recorder that records events can also be used as a data collection device that collects determination basic data for determining the necessity of repairing roads and the like. For example, a typical drive recorder has a function of comparing the magnitude of acceleration with a first determination threshold. By adding the function of comparing the magnitude of acceleration and the second determination threshold to such a general drive recorder, the general drive recorder can be used as a judgment for judging the necessity of repairing roads, etc. It can be used as a data collection device for collecting basic data. When the acceleration is equal to or greater than the first determination threshold value, it is preferable to determine that the vehicle has collided and that the vehicle has passed through an uneven road surface. This makes it possible to correctly determine that the vehicle has passed through an uneven road surface when the vehicle has passed through an uneven road surface with a large difference in height that causes the vehicle to receive an impact as large as that in a collision.

(6) Further, a microphone may be provided, and the processing means may be a data collection device for detecting that the vehicle has passed over an uneven road surface by using information on sounds collected by the microphone.

By using sound information together, it is possible to determine the presence or absence of unevenness on the road surface with higher accuracy.

(7) The processing means analyzes the image data to determine whether or not the vehicle is traveling in a section where unevenness is caused by a factor other than deterioration of the road surface. It is preferable that the data collection device skips the process of detecting whether or not the vehicle has passed through an uneven road surface when it is determined that the vehicle is traveling in an uneven section.

Concavities and convexities due to factors other than deterioration that are not subject to repair can be excluded from detection targets. As a result, it is possible to suppress excessive detection of points where unevenness occurs. As a result, it becomes possible to easily detect the point where unevenness that should be considered as a repair target is occurring.

Sections where unevenness occurs due to factors other than deterioration of the road surface include, at least, sections where unevenness occurs due to, for example, construction work, and steps at seams where excavation work was performed. It is preferable to determine whether or not there is a section where there is a gap, a step due to the edge of a manhole, a step at the joint of a bridge, or the like. For example, when a signboard under construction is detected from an image of image data, it may be determined that the road on which the vehicle is currently traveling is under construction. Seams where excavation work has been performed, edges of manholes, seams of bridges, etc. may be detected by analyzing image data.

(8) The processing means analyzes the image data to determine the type of road surface on which the vehicle is traveling, and collects data that changes the determination criteria for determining that the vehicle has passed unevenness of the road surface according to the type of road surface. device.

The acceleration (impact) that the vehicle receives depends on the type of road surface on which the vehicle is running. By changing the above determination criteria according to the type of road surface, it is possible to make an appropriate determination according to the type of road surface.

Examples of road surface types include asphalt pavement, concrete pavement, and block pavement. The processing means preferably has a function of determining these types of road surfaces. On a concrete paved road surface, seams of about 1 cm are provided at intervals of, for example, 5 to 10 m. A unique pattern consisting of multiple blocks appears on the road surface of block pavement. No seams or unique patterns appear on the asphalt pavement. The processing means preferably analyzes the image data of the road surface and detects the presence or absence of joints and unique patterns to determine the type of road surface.

(9) The processing means detects intentionally provided stepped pavement on the road surface by analyzing the image data, and at the point where the stepped pavement is detected, whether or not the vehicle has passed through the unevenness of the road surface. It is preferable that the data collection device skips the process of detecting whether.

It is possible to prevent an intentionally provided point where the road surface is paved with steps from becoming a candidate for a point where there is a step to be repaired.

Examples of intentionally provided stepped pavement on a road surface include, for example, those intended to suppress the running speed and call attention to the driver of the vehicle by giving sound and vibration to the driver. Step pavement is performed, for example, by applying an aggregate such as ceramic to the pavement surface using a resin-based adhesive. The processing means preferably determines whether or not the road surface is intentionally provided with uneven pavement by detecting a pattern of aggregate such as ceramics from the image data of the road surface.

(10) The processing means has a function of acquiring current position data indicating a current position, and stores collected position data specifying a place where the basic determination data should be collected, and the current position data and the collected data are stored. determining whether or not to collect the basic determination data based on the position data; and collecting the basic determination data and recording it in the recording device when it is determined to collect the basic determination data. It may be a data collection device.

It is possible to collect basic determination data at locations where basic determination data should be collected, and not to collect basic determination data at other locations. The amount of basic determination data to be analyzed is smaller than in the case where the basic determination data is collected at all locations where the vehicle travels. Therefore, it is possible to reduce the amount of memory in which the basic determination data should be recorded, and to eliminate unnecessary time required for the process of analyzing unnecessary basic determination data.

The current position data should be acquired by a GPS receiver. A GPS receiver may be built into the data collection device. Alternatively, the data collection device may receive the current location data from a GPS receiver mounted on the vehicle. The sensing data may include current position data indicating the current position. It is particularly preferable to record the current position data included in the sensing data in a database in association with image data, acceleration data, and the like. By doing so, it is possible to identify the position where the image data was collected and the position where the acceleration data was collected.

(11) the collection position data includes data specifying a measurement point at which the determination basic data should be collected;
Preferably, the processing means is a data collection device having a function of notifying that the vehicle has approached the measurement point when the distance between the current position of the vehicle and the measurement point becomes equal to or less than a reference distance.

A driver of a vehicle equipped with a data collection device can know when the vehicle approaches the measurement point. Thereby, preparation for collection of determination basic data can be started.

The measurement points at which the basic determination data should be collected should be selected from a plurality of points where irregularities, etc., that do not need to be immediately repaired at the present time have been detected by analyzing the basic determination data measured in the past. By continuously collecting the determination basic data of such measurement points every other day, it is possible to determine the necessity of repair in consideration of the progress speed of deterioration of the road surface.

(12) The processing means stores a standard value of traveling speed when passing the measurement point, notifies the vehicle that the vehicle has approached the measurement point, and informs the driver of the vehicle of the The data collection device should have a function to prompt the vehicle to run at a standard running speed.

A driver of a vehicle equipped with a data collection device can be made aware of the need to drive with standard values before driving a measurement point. As a result, it is possible to suppress the occurrence of a situation in which the collected determination basic data cannot be used effectively because the vehicle travels at a measurement point that greatly deviates from the standard value. For example, by outputting a voice, it is preferable to encourage the vehicle to run at the standard running speed.

(13) The processing means may be a data collection device having a function of constantly recording the collected judgment basic data in the recording device.

It is possible to collect basic judgment data for judging the necessity of repairing roads or road appendages for all routes traveled by vehicles equipped with data collection devices. As a result, judgment basic data is collected in a wider area. If there is accumulated basic judgment data collected in the past when an abnormality was found in the road or road appendages, the judgment basic data collected in the past will be used together. By doing so, it is possible to analyze the time and cause of occurrence of the abnormality.

The period of constant recording may be, for example, the period from when the accessory key of the vehicle is turned on to when it is turned off. Further, it is also possible to predetermine a section of the travel route for which the basic determination data is collected, and to constantly record in the section for which the basic determination data is collected. For example, the processing means stores the position data of the start point and the end point of the section for collecting the determination basic data, and starts collecting the determination basic data when the current position of the vehicle coincides with the start point, and moves to the end point. If they match, the collection of judgment basic data should be terminated.

(14) The processing means may be a data collection device having a function of determining whether or not the road or road appendages need to be repaired by analyzing the image data.

It is possible to reduce the burden on the road administrator for checking the images of the image data. In addition, even if an abnormal portion is overlooked by human visual observation, the processing means detects the abnormality, thereby reducing the possibility of overlooking the abnormality.

By analyzing image data, cracks in the road surface, deterioration of road markings, poor drainage of roads after rain, corrosion and deformation of road appendages such as road signs and guardrails, signs of landslides, and harmful effects caused by roadside trees can be detected. It should be possible to do so.

(15) Further, the data collection device preferably has communication means, and the processing means has a function of transmitting the determination basic data collected while the vehicle is running to an external device via the communication means. .

When a vehicle equipped with a data collection device is a vehicle for road maintenance work that departs from a depot and returns to the depot after traveling the intended route, the vehicle returns to the depot based on the collected judgment basic data. can be sent to an external device before. If this function is installed in a consumer drive recorder, it will be possible to collect basic judgment data not only from road maintenance vehicles but also from general vehicles equipped with drive recorders. By collecting and accumulating a larger amount of determination basic data from drive recorders installed in many general vehicles, it is possible to improve the accuracy of determining whether repair is necessary.

(16) Image data around the vehicle collected by a data collection device mounted on the vehicle, acceleration data representing the magnitude of acceleration applied to the vehicle, vehicle position data, and data collection date and time data are associated. It is preferable that the road condition evaluation support device has processing means for displaying, on a display means, images of the image data obtained at a specific point on a plurality of different dates and times in chronological order, based on a database accumulated in the above.

A road administrator can see the images displayed in chronological order to check the progress of deterioration of the road or road appendages. As a result, it is possible to determine whether or not repair is necessary, and to predict when the repair will be required. Also, by looking at the displayed image, it is possible to determine whether or not it is necessary to continue observing the deterioration state of the displayed point. When it is determined that continuous observation is necessary, the images displayed in chronological order serve as effective information for determining the frequency of observation.

The specific point at which the image is displayed on the display means may be, for example, a point where unevenness is determined to occur on the road surface based on the acceleration data, a point subject to continuous observation, or the like.

This database may be placed in the storage device of the road condition evaluation support device. It is also particularly advantageous if this database is located on a server connected to the data communication network. In this way, by connecting a plurality of road condition evaluation support devices to the data communication network, it becomes possible to access the database from a plurality of road condition evaluation support devices.

(17) The processing means may be a road condition evaluation support device that causes the display means to display the time waveform of the corresponding acceleration data together with the image of the image data.

By looking at the time waveform of the acceleration data, road administrators can identify the magnitude of the shock applied to the vehicle when it passed that point. The magnitude of the impact can be used as information for specifying, for example, the height difference of unevenness occurring on the road surface. From the temporal waveform of the acceleration data displayed in chronological order, it is possible to know the progress of deterioration such as unevenness occurring on the road surface.

(18) The processing means may be a road condition evaluation support device having a function of displaying, on the display means, a temporal waveform of the acceleration data indicating a peak waveform as the acceleration data collected at the specific point.

By detecting the peak of the time waveform of the acceleration data, it is possible to accurately match the points at which the time waveforms of the plurality of acceleration data displayed in time series were obtained. As a result, it is possible to evaluate the impact caused by the unevenness at the same point on the road surface in chronological order.

Acceleration data collected at a particular point can be found by reference to position data associated with the acceleration data. This position data is obtained, for example, by a GPS receiver, and position measurement errors occur due to various factors. Therefore, it is difficult to precisely match the positions at which the plurality of temporal waveforms of the acceleration data during running collected on different dates and times are acquired, based only on the position data. By detecting the peak of the time waveform of the acceleration data, it is possible to precisely match the positions at which the plurality of time waveforms of the acceleration data collected on different dates and times are acquired. As a result, it is possible to accurately extract image data of a specific spot based on the date and time when the acceleration data was collected.

(19) The processing means obtains an evaluation value dependent on the unevenness of the road surface at the specific point from each of the plurality of acceleration data collected at the specific point on a plurality of different dates and times; It is preferable that the road condition evaluation support device has a function of displaying the temporal change of the evaluation value on the display means.

It is possible to estimate the progress of future deterioration from changes over time in the evaluation value, which depends on the unevenness of the road surface at a specific point. From the estimated progress of deterioration, it is possible to predict when repairs should be made. As an evaluation value that depends on the unevenness of the road surface, for example, the peak height appearing in the time waveform of the acceleration data may be used.

The processing means preferably displays the evaluation values from the past to the present time in a graph format. A road administrator can visually recognize the speed of deterioration of evaluation values by viewing changes in evaluation values in the form of graphs. The processing means predicts changes in evaluation values in the future based on changes in evaluation values from the past to the present, and displays changes in the evaluation values from the past to the present and predicted future changes in evaluation values in a graph format. It is better to let Predicted future changes in evaluation values can be used as useful information for determining when to repair roads or road appendages.
(20) The processing means may be a road condition evaluation support device having a function of extracting a time waveform suggesting that the vehicle has passed over an uneven road surface from the time waveform of the acceleration data accumulated in the database. .

Based on the acceleration data accumulated in the database, it is possible to extract points where unevenness is thought to exist on the road surface without human intervention. This makes it possible to process enormous amounts of acceleration data. Extraction of the temporal waveform that suggests passing through unevenness can be performed, for example, based on the peak height appearing in the temporal waveform of the acceleration data, the shape of the temporal waveform, and the magnitude relationship of the acceleration in the three directions of front, back, left, right, up and down. can.

For example, when the vehicle is suddenly braked, a large acceleration is generated in the longitudinal direction. When the driver performs a sudden steering operation, a large lateral acceleration is generated. On the other hand, when the vehicle passes through unevenness of the road surface, a large acceleration occurs in the vertical direction. The processing means preferably extracts a point where unevenness is likely to exist on the road surface by using the difference in direction of the generated acceleration. Furthermore, the time waveform of the acceleration data corresponding to sudden braking, sharp steering, etc., changes more slowly than the time waveform of the acceleration data corresponding to passing over an uneven road surface. The processing means preferably uses the difference in the shape of the time waveform to extract points where unevenness is thought to exist on the road surface.

Particularly preferably, the processing means utilizes information other than acceleration data to extract a temporal waveform that suggests that the vehicle has passed over an uneven road surface. The processing means may use, for example, the running speed of the vehicle as information other than the acceleration data. For example, when a vehicle door is opened and closed, a peak appears in the temporal waveform of the acceleration data, but the running speed at this time is almost zero. By using travel speed data together to determine whether the vehicle has passed over an uneven road surface, peaks in the temporal waveform of the acceleration data generated by door opening/closing can be excluded from detection targets.

(21) the database includes vehicle type data indicating the type of vehicle in which the data collection device was installed when the acceleration data was collected;
The processing means may be a road condition evaluation support device having a function of normalizing the acceleration data based on vehicle type data.

By normalizing the acceleration data based on the vehicle type data, it becomes possible to compare the acceleration data collected by the data collection devices mounted on a plurality of vehicles of different vehicle types. Here, "normalize based on vehicle type data" means that acceleration data actually collected by data collection devices mounted on various vehicles would have been obtained if they were mounted on a standard vehicle. It means to convert to acceleration data. The acceleration data to be converted may be, for example, a feature quantity that characterizes the time waveform of the acceleration data. For example, the height of a peak appearing in the time waveform, the distribution of frequency components of the time waveform, and the like may be used as the feature quantity that characterizes the time waveform of the acceleration data.

(22) the database accumulates vehicle travel speed data in association with data collection date and time;
The processing means may be a road condition evaluation support device having a function of normalizing the acceleration data based on the traveling speed data.

Normalizing the acceleration data based on the running speed data allows comparison of the acceleration data collected at different running speeds. Here, "normalizing based on running speed data" means converting acceleration data actually collected at various different running speeds into acceleration data that would have been obtained if the vehicle had run at a standard speed. means to As the standard speed, for example, the legal speed of the route on which the vehicle is traveling or a speed slightly lower than the legal speed may be adopted. The acceleration data to be converted may be, for example, a feature quantity that characterizes the time waveform of the acceleration data. For example, the height of a peak appearing in the time waveform, the distribution of frequency components of the time waveform, and the like may be used as the feature quantity that characterizes the time waveform of the acceleration data.

(23) The processing means determines a degree of need for road surface repair based on the image data accumulated in the database, and outputs the determination result to the image data, the acceleration data, the position data, and the collected data. It is preferable that the road condition evaluation support device has a function of registering in the database in association with date and time data.

Since the degree of need for repair can be determined without human intervention, it is possible to deal with a huge amount of image data. The degree of need for road surface repair may be determined using, for example, artificial intelligence (AI).

(24) The processing means may be a road condition evaluation support device having a function of displaying information specifying points requiring repair on the road surface on the display means in such a manner that the degree of necessity of repair can be recognized.

A road administrator who sees the information displayed on the display means can easily find a point with a high degree of urgency from a plurality of points requiring repair. For example, the road names, addresses, and location information of points requiring repair may be rearranged according to the degree of repair required and displayed in a list format on the display means. Alternatively, a map may be displayed on the display means, and different icons may be displayed at points requiring repair depending on the degree of repair required. Alternatively, instead of icons, points on the road that require repair may be given different colors depending on the degree of repair required.

(25) Road condition evaluation support having a function in which the processing means causes the display means to display the position information of points requiring repair of the road surface in such a manner that the amount of reduction in the life cycle cost of the road due to the repair can be identified. device.

Road administrators can easily find repaired areas with a large reduction in life cycle cost. For example, road names, addresses, and location information of points requiring repair may be rearranged according to the degree of reduction in life cycle cost and displayed on the display means in the form of a list. also,
A map may be displayed on the display means, and an icon may be displayed at points requiring repair in accordance with the extent of reduction in the life cycle cost. Alternatively, instead of icons, points on the road that require repair may be colored according to the size of the reduction in life cycle cost.

(26) The processing means may analyze the image data accumulated in the database to determine the necessity of repairing road appendages.

It is possible to determine whether or not road appendages need to be repaired without human intervention. This makes it possible to process enormous amounts of image data. For example, we will take up the deterioration of road markings, poor drainage function of roads after rain, corrosion and deformation of road appendages such as road signs and guardrails, signs of landslides, and harmful effects of roadside trees, etc. Good.

(27) A road condition evaluation support device in which the processing means has a function of determining the necessity of repairing road appendages based on the difference between the plurality of image data collected at the same spot on different dates. should be

The progress speed of deterioration of road appendages can be recognized from the difference of the image data. By considering the progress speed of deterioration of the road appendages, it is possible to more appropriately determine whether or not the road appendages need to be repaired. For example, it is possible to more appropriately determine the need for repair based on the speed at which road markings fade, the speed at which roadside trees grow, and the like.

(28) further comprising communication means, wherein said processing means includes said image data, said acceleration data, said position data, said collection date and time data, and data collected by a plurality of data collection devices via said communication means; It is preferable that the road condition evaluation support device has a function of receiving identification data for identifying the collection device, associating the data, and storing the data in the database.

Since the data is received via the communication means, it is possible to save the trouble of obtaining the data. Moreover, since data is received from a plurality of data collection devices, a larger amount of data can be collected than when data is obtained from a single data collection device. For example, it is preferable to install the data collecting device not only in the working vehicle of the road management company, but also in the personal vehicles of the employees of the road management company to obtain these data. It is even better to obtain these data by installing a data collection device in an unspecified general vehicle.

(29) The processing means may be a road condition evaluation support device that assigns points according to the received image data and acceleration data to each data collection device, and stores the cumulative value of the points.

Depending on the points, it becomes possible to provide benefits to the owner of the data collection device. Owners of vehicles equipped with data collection devices are motivated to send more data to the road condition evaluation support device. Owners of vehicles that do not have a data collection device will be motivated to install a data collection device. This makes it possible to obtain a larger amount of data. The privilege may be, for example, a discount on a toll road, a discount when purchasing a product at a roadside station, or the like.

(30) This specification discloses the invention of a program for making a mobile terminal realize the function as the data collection device according to any one of (1) to (15) above.

(31) This specification discloses the invention of a program for causing a computer to realize the function as the road condition evaluation support device according to any one of (16) to (29) above.

Further, the present specification includes the data collection device according to any one of (1) to (15) above and the road condition evaluation support device according to any one of (16) to (29) above. Disclosed is an invention of a road condition evaluation support system. Furthermore, the present specification provides the function of the data collection device according to any one of (1) to (15) above and the road condition evaluation support device according to any one of (16) to (29) above. Discloses the invention of a device that has both functions. Such a device may be implemented by, for example, a tablet terminal or the like that is detachably mounted on the vehicle.

For example, without installing a measuring device such as a laser distance measuring device in advance at the measurement location, it is possible to collect data and the like that serve as a basis for determining the necessity of repairing roads or road appendages. For example, these collected data are useful information for determining whether repair is necessary or not.

FIG. 1A is a perspective view of the data collection device according to the first embodiment as seen obliquely from behind, and FIG. 1B is a diagram showing the data collection device, windshield, dashboard, etc. mounted on a vehicle. . FIG. 2 is a block diagram of the data collection device 1 according to the first embodiment. FIG. 3A is a diagram showing, in tabular form, an example of the structure of various sensing data other than image data collected by the data collecting device, and FIG. 3B is a diagram showing, in tabular form, the structure of the image data. FIG. 4 is a flowchart of data recording processing executed by the controller of the data collection device according to the first embodiment. FIG. 5 is a diagram showing an example of the temporal waveform of acceleration data, the first determination threshold value At1, the second determination threshold value At2, and image data to be recorded. FIG. 6A is a flowchart of processing executed by the controller of the data collection device according to the second modification of the first embodiment, and FIG. 6B is a diagram showing an example of an image acquired by a camera. FIG. 7A is a flow chart of processing executed by the controller of the data collection device according to the third modification of the first embodiment, and FIGS. It is a figure which shows an example of the image acquired during driving|running|working on the road surface of a pavement. FIG. 8A is a flowchart of processing executed by the controller of the data collection device according to the fourth modification of the first embodiment, and FIG. 8B shows an example of an image when driving on a stepped road surface. It is a diagram. FIG. 9A is a flowchart of processing executed by the controller of the data collection device according to the fifth modification of the first embodiment; FIG. 9B is a diagram showing an example of a data collection interval; It is a figure which shows an example of a collection point. FIG. 10A is a flowchart of processing executed by the controller of the data collection device according to the sixth modification of the first embodiment, and FIG. 10B is a diagram showing an example of paths for recording determination basic data. FIG. 11A is a flow chart of processing executed by the controller of the data collection device according to the seventh modification of the first embodiment, and FIGS. It is drawing which shows the example of the image determined as. FIG. 12 is a block diagram of the road condition evaluation support device according to the second embodiment. FIG. 13 is a diagram showing an example of an image displayed on the display of the road condition evaluation support device according to the second embodiment. FIG. 14 is a diagram showing an example of an image of temporal changes in evaluation values displayed on the display of the road condition evaluation support device according to the second embodiment. FIG. 15 is a diagram showing the relationship between the temporal waveform of acceleration data and the date and time when the temporal waveform was acquired. FIG. 16A is a diagram showing an example of a main menu screen displayed on the display by the controller, and FIG. FIG. 10 is a diagram showing an example of an image obtained from the image; FIG. 17A is a diagram showing an example of the data structure of determination basic data accumulated in the road condition evaluation support device according to the second modification of the second embodiment, and FIG. It is a figure which shows correspondence. FIG. 18 is a diagram showing an example of correspondence relationships among vehicle types, traveling speeds, and conversion factors applied in the road condition evaluation support system according to the third modification of the second embodiment. FIG. 19A is a diagram showing an example of an image displayed on the display of the road condition evaluation support device according to the fourth modification of the second embodiment; FIG. 20 is a diagram showing another example of an image displaying points determined to require repair. FIG. 21 is a diagram showing an example of an image displayed on the display of the road condition evaluation support device according to the fifth modification of the second embodiment. 22A to 22C are diagrams showing examples of image data collected at the same spot on different dates. FIG. 23A is a schematic diagram of a system including a plurality of vehicles equipped with a road condition evaluation support device and a data collection device 1 according to a seventh modification of the second embodiment, and FIG. is a diagram showing an example of the cumulative value of points given to .

[First embodiment]
A data collection device according to a first embodiment will be described with reference to FIGS. 1A to 5. FIG.

FIG. 1A is a perspective view of the data acquisition device according to the first embodiment, viewed obliquely from behind. A display 11 and a plurality of operation buttons 12 are arranged on the surface facing the rear (inside the vehicle interior) of the housing of the data collection device 1 mounted on and used in the vehicle. An SD card slot 10 is arranged on the side of the housing of the data collection device 1 . A joint rail 13 is provided on the upper surface of the housing. Although not shown in FIG. 1A, a camera lens is attached to the front of the housing. A DC jack is located on the side not appearing in FIG. 1A, and a speaker is located on the bottom.

A camera including a lens photographs, for example, the front of the vehicle. The DC jack is connected to the vehicle's DC power supply via a power cable. A user such as a driver inserts an SD card into the data collection device 1 through the SD card slot 10 . The speaker outputs sound or voice. A joint for mounting the data collection device 1 on the vehicle is attached to the joint rail 13 . A display 11 displays various images. The user operates the operation buttons 12 to input various commands to the data collection device 1 .

FIG. 1B is a diagram showing the data collection device 1, the windshield 3, the dashboard, etc. mounted on the vehicle. The data collection device 1 is attached to a position on the front passenger seat side adjacent to the rearview mirror 4 near the center in the left-right direction on the upper part of the windshield 3 of the vehicle. The data collection device 1 is attached and fixed to the windshield 3 with an attachment member such as double-sided tape. A DC jack of the data collection device 1 is connected to the cigar socket 5 via the power cable 6 . When the accessory power source of the vehicle is turned on, power is supplied from the cigar socket 5 to the data collection device 1 . When the vehicle passes through unevenness of the road surface and acceleration (or impact) is applied to the vehicle, the same acceleration (or impact) is applied to the data collection device 1 as well.

FIG. 2 is a block diagram of the data collection device 1 according to the first embodiment. A controller 20 as processing means includes a central processing unit (CPU) 20a, a read only memory (ROM) 20b, a random access memory (RAM) 20c, and the like. The ROM 20b stores an operating system (OS), programs for realizing various functions of the data collection device 1, and the like. Various functions of the data collection device 1 are realized by the CPU 20a executing programs stored in the ROM 20b. The RAM 20c is used as a temporary storage area when the CPU 20a executes programs.

The speaker 16 and display 11 function as notification means for informing the user of various information. The controller 20 causes the speaker 16 to issue warnings and various information by sound or voice. Further, the controller 20 causes the display 11 to display various information as images. The operation button 12 functions as input means for the user to give various instructions to the data collection device 1 .

Sensing data obtained by various sensors are input to the controller 20 . A GPS receiver 14, a camera 15, an acceleration sensor 17, and a gyro sensor 18 are prepared as sensors.

The GPS receiver 14 calculates position data indicating the current position of the vehicle based on signals received from GPS satellites. Furthermore, the GPS receiver 14 calculates the current time based on signals received from GPS satellites. The controller 20 can obtain position data indicating the current position of the vehicle and date/time data indicating the current date and time from the GPS receiver 14 . Note that the controller 20 has an internal timer, and can acquire the current date and time from the internal timer.

The camera 15 photographs the surroundings of the vehicle and acquires surrounding image data. For example, the camera 15 may take an image in front of the vehicle. As the camera 15, for example, an imaging device such as a CMOS camera or a CCD camera may be used.

The acceleration sensor 17 measures acceleration applied to the vehicle in the longitudinal direction (X-axis direction), the lateral direction (Y-axis direction), and the vertical direction (Z-axis direction) to obtain acceleration data. The gyro sensor 18 detects the three axial directions of the vehicle, that is, the rotational direction (yawing direction) about the vertical direction, the rotational direction (pitching direction) about the horizontal direction, and the rotational direction (rolling direction) about the front-rear direction. ) to obtain angular velocity data. The controller 20 takes in acceleration data and angular velocity data at a constant sampling period, for example, a sampling period of 10 ms.

An SD card 22 is inserted into the SD card reader 19 through the SD card slot 10 (FIG. 1A). The SD card reader 19 writes data to the attached SD card 22 or reads data from the SD card 22 under the control of the controller 20 . Instead of the SD card 22, another removable recording medium may be used, and instead of the SD card reader 19, a card reader that reads and writes data to and from the removable recording medium may be used.

The communication circuit 21 performs data communication with other devices via the data communication network 40 under the control of the controller 20 . As the communication circuit 21, for example, a communication circuit conforming to a WiFi standard, a short-range wireless communication standard such as Bluetooth (registered trademark), a mobile communication system standard such as LTE, 4G, or the like may be used. The short-range wireless communication standard can be applied to communication with devices outside the vehicle, for example, when the vehicle is stopped. Alternatively, it can be applied to communication with a device in the vehicle, such as a personal computer having a large-capacity storage. Mobile communication system standards can be applied, for example, to communication between vehicles moving within a wider area and external devices.

The data collection device 1 has a function of recording sensing data such as position data, image data, acceleration data, and angular velocity data acquired by the GPS receiver 14, the camera 15, the acceleration sensor 17, and the gyro sensor 18 on the SD card 22. have.

Next, the data recording function of the data collection device 1 will be described.
FIG. 3A is a diagram showing an example of the configuration of various sensing data other than image data collected by the data collection device 1 in tabular form. The controller 20 collects date and time data, traveling speed data, position data, acceleration data, and angular velocity data at regular sampling intervals. The date and time data includes date information and time information. The controller 20 can obtain date and time data from the GPS receiver 14 or an internal timer.

The travel speed data represents the travel speed of the vehicle. The controller 20 acquires travel speed data from the vehicle's electronic control unit (ECU) through the OBD connector. Position data consists of latitude information and longitude information. The acceleration data represents acceleration along the X-axis (longitudinal direction), Y-axis (horizontal direction), and Z-axis (vertical direction). The angular velocity data represents the angular velocity in the direction of rotation about the X axis, the angular velocity in the direction of rotation about the Y axis, and the angular velocity in the direction of rotation about the Z axis.

FIG. 3B is a diagram showing the configuration of image data in tabular form. The controller 20 converts the image data input from the camera 15 into H.264, for example. 264, H. 265 or other video compression standards. The image data is composed of a plurality of frames F, and some of the frames FI contain date and time data and position data when the image was acquired. The acquisition date and time of the image of the frame F that does not include date and time data can be calculated based on the date and time at which the frame FI was acquired, the number of frames from the frame FI, and the frame rate.

Image data and other sensing data are associated with each other based on date and time data. For example, acceleration data and image data when the acceleration data is acquired are associated via date and time data.

The date/time data, traveling speed data, position data, acceleration data, angular acceleration data, and image data shown in FIGS. 3A and 3B are the basis for determining whether road repair is necessary. In this specification, these data are referred to as determination basic data.

FIG. 4 is a flow chart of data recording processing executed by the controller 20 . When the accessory key of the vehicle is turned on and power is supplied to the data collection device 1, the controller 20 starts the processing shown in FIG. When the process is started, the controller 20 starts the process of constantly recording the determination basic data in the ring buffer secured in the RAM 20c.

The controller 20 acquires acceleration data from the acceleration sensor 17 and determines whether or not a collision has occurred based on the acceleration data (step ST01). For example, the controller 20 determines that a collision has occurred when the magnitude (absolute value) of the measured acceleration is greater than or equal to the first determination threshold. The acceleration data to be compared with the first determination threshold is, for example, three acceleration data of the X-axis, the Y-axis, and the Z-axis, and when the acceleration data of any one axis exceeds the first determination threshold, a collision occurs. It should be judged that

When the controller 20 determines that a collision has occurred, the controller 20 starts the process of recording the determination basic data collected before and after the time of the collision in the collision event recording area of the SD card 22 (step ST03). The period during which the data is recorded should be sufficient, for example, to analyze the cause of the collision. For example, the period may be two minutes in total with time widths of one minute before and after the time of occurrence of the collision. The controller 20 reads out from the ring buffer and records in the SD card 22 the determination basic data before the time of collision occurrence.

If the occurrence of a collision is not detected in step ST01, the controller 20 determines whether or not the vehicle has passed through an uneven road surface (step ST02). For example, when the magnitude of the measured acceleration reaches or exceeds a second determination threshold that is smaller than the first determination threshold, the controller 20 determines that the unevenness of the road surface has been passed. The acceleration data to be compared with the second determination threshold is, for example, three acceleration data on the X-axis, the Y-axis, and the Z-axis. It should be determined that the It should be noted that since acceleration in the vertical direction is applied mainly when passing through unevenness, only acceleration data on the Z-axis may be compared with the second determination threshold value. Road surface irregularities include, for example, pavement cracks, ruts, steps, potholes, and the like.

When the controller 20 determines that the vehicle has passed through the unevenness of the road surface, the controller 20 records the determination basic data collected before and after the time of passing the unevenness in the road condition evaluation recording area of the SD card 22 (step ST04). The period for recording data may be set to a period sufficient for recording an image of unevenness of a road surface, for example. For example, the period may be 40 seconds in total, with a time width of 20 seconds before and after the time when the passage of unevenness is detected.

When the passage of unevenness is not detected in step ST02, or when the recording of the determination basic data is completed in steps ST03 and ST04, the controller 20 determines whether or not to end the data collection process (step ST05). . For example, when the power supply from the vehicle to the data collection device 1 is stopped, the controller 20 terminates the data collection process. The data collection device 1 incorporates a battery with a capacity capable of supplying power for executing data collection stop processing even when the power supply from the vehicle is stopped, and the power supply from the vehicle is stopped. After that, the data collection device 1 operates with power from the built-in battery. When continuing data collection, the controller 20 repeats the process from step ST01. In step ST01, the acceleration data newly collected by the controller 20 is determined.

Next, referring to FIG. 5, the process of recording the determination basic data in steps ST03 and ST04 will be described.
FIG. 5 is a diagram showing an example of the temporal waveform of acceleration data, the first determination threshold value At1, the second determination threshold value At2, and image data to be recorded. The first determination threshold value At1 is set to a value that is larger than the maximum value of acceleration that the vehicle receives when it passes through an uneven road surface. The second determination threshold value At2 is set to a value larger than the maximum acceleration that the vehicle receives while traveling on a normal road surface without unevenness.

When the vehicle passes over an uneven road surface, a peak P1 larger than the second determination threshold value At2 appears in the temporal waveform of the acceleration data. When the peak P1 is detected, the controller 20 records in the SD card 22 the image data 31 and the acceleration data acquired during the period T1 before and after the peak P1 appears.

When a vehicle collision accident occurs, a peak P2 larger than the first determination threshold value At1 occurs in the temporal waveform of the acceleration data. When the controller 20 detects this peak P2, the controller 20 records the image data 32, the acceleration data, etc. acquired in the period T2 before and after the peak P2 appears in the SD card 22. FIG.

Next, the image display function of the data collection device 1 will be described. The controller 20 has a function of displaying an image of image data recorded on the SD card 22 on the display 11 . For example, when the user operates the operation buttons 12 to input date/time data or position data for obtaining an image to be displayed, the controller 20 displays an image of the image data associated with the input date/time data or position data. is displayed on the display 11.

Further, the controller 20 has a function of displaying the determination basic data other than the image data recorded on the SD card 22 on the display 11 in numerical or graphical form. For example, when the user operates the operation button 12 to input basic determination data to be displayed (e.g., acceleration data and date/time data), the controller 20 displays the input basic determination data in numerical or graphical form on the display 11. Let

Next, the data transmission function of the data collection device 1 will be described. The controller 20 has a function of reading the determination basic data recorded in the SD card 22 and transmitting it from the communication circuit 21 to other devices via the data communication network 40 . For example, when the user operates the operation button 12 to instruct transmission of basic determination data, the controller 20 starts transmitting the basic determination data. The controller 20 may transmit the collected determination basic data to other devices in real time.
@
Instead of recording the determination basic data in the SD card 22, the controller 20 may transfer the data to an in-vehicle device such as a personal computer having a large-capacity storage via the communication circuit 21. FIG. After the determination basic data is temporarily accumulated in the equipment in the vehicle, it is transmitted from the equipment in the vehicle via a device capable of long-distance communication such as a mobile terminal, or the data collection device 1 of a mobile communication system such as LTE, 4G. It is preferable to transmit to an external server or a management personal computer (for example, a road condition evaluation support device to be described later) using a communication function conforming to the standard. Wireless communication between the data collection device 1 and devices in the vehicle is more stable than long-distance communication. Therefore, the device in the vehicle can be used as a large-capacity storage for buffering the determination basic data, like the SD card 22 .
@
Further, the determination basic data once recorded in the SD card 22 may be read out from the SD card 22 and transferred to equipment in the vehicle via the communication circuit 21 . By doing so, even under conditions where communication with an external server, a personal computer for management, etc. cannot be performed, a large amount of determination basic data can be accumulated without being restricted by the recording capacity of the SD card 22.例文帳に追加When communication with an external server or the like becomes possible, the information may be sent from the device in the vehicle to the external server or management personal computer via a device capable of long-distance communication such as a mobile terminal.

[Effect of the first embodiment]
Next, the excellent effects of the first embodiment will be described. A road administrator can see the image displayed on the display 11 and can confirm the condition of the road surface and the shape and surface condition of road appendages included in the image. Furthermore, by attaching the SD card 22 to a personal computer or the like, it is possible to check the image data and other determination basic data recorded in the SD card 22 . The road administrator can determine whether or not the road or road appendages need to be repaired based on these determination basic data.

Whether road repair is necessary (whether or not repair work is necessary) is based on, for example, the presence or absence of unevenness such as steps and dents on the road surface, rutting, cracks, repaired joints of expressways, subsidence of the road surface, etc. good. The presence or absence of unevenness on the road surface may be determined based on, for example, acceleration data representing the acceleration applied to the vehicle when passing over the unevenness on the road surface, image data obtained by photographing the surroundings of the vehicle, or the like. The presence or absence of rutting and cracking may be determined based on, for example, image data obtained by photographing the front of the vehicle, image data obtained by photographing the road surface, and the like. The presence or absence of subsidence of the road surface may be determined using data or the like indicating the inclination of the vehicle when passing through the subsidence point. The tilt of the vehicle may be obtained from the angular velocity of the vehicle.

Road attachments include, for example, fall prevention fences, separation fences between roadways and sidewalks, rows of trees on roads, road signs, road markings, road information display devices, vehicle monitoring devices, and utility tunnels. It is preferable to determine whether or not these repairs are necessary based on data such as images of the surroundings of the vehicle.

The image data collected by the data collection device 1 is preferably composed of a plurality of images acquired at a constant sampling cycle. This sampling period is preferably short enough to obtain images of the surroundings of the route traveled by the vehicle from the plurality of images included in the collected image data without interruption along the route. By doing so, it is possible to obtain information about the deterioration state of the road and road appendages in the entire section where the image data is acquired.

In the first embodiment, image data and data other than the image data, such as acceleration data, are obtained as the information regarding the unevenness of the road surface. By using together two or more types of data with different properties, it is possible to more accurately determine whether road repair is necessary.

The data collection device 1 according to the first embodiment uses the collected acceleration data to distinguish between the impact received when the vehicle passes over uneven road surfaces and the impact received due to a collision accident. As a result, for example, a drive recorder that records images (event records) at the time of a collision can also be used as a data collection device that collects determination basic data for determining the necessity of repairing roads and the like. For example, a typical drive recorder has a function of comparing the magnitude of acceleration with a first determination threshold for detecting a collision. By adding to such a general drive recorder a function of comparing the magnitude of acceleration with a second determination threshold value for detecting road surface unevenness, the general drive recorder can be used for repairing roads, etc. It can be used as a data collection device 1 that collects determination basic data for determining necessity. When the acceleration is equal to or greater than the first determination threshold value, it is preferable to determine that the vehicle has collided and that the vehicle has passed through an uneven road surface. This makes it possible to correctly determine that the vehicle has passed through an uneven road surface when the vehicle has passed through an uneven road surface with a large difference in height that causes the vehicle to receive an impact as large as that in a collision.

In this way, by adding a simple function to a general consumer drive recorder, a data collection device 1 for business use that collects judgment basic data for judging the need for repair of roads or road appendages. can be used. Therefore, it is possible to reduce the cost of the data collection device 1 . Conversely, it is possible to use the data collecting device 1 according to the first embodiment as a drive recorder.

For general drive recorders that record events, the peak of the acceleration time waveform generated by the shock applied when the vehicle passes over uneven road surfaces is an obstacle to detecting the occurrence of a collision accident (such as debris). data). In general, the peak of the time waveform of acceleration that occurs when the road surface is uneven is smaller than the peak of the acceleration that occurs during a collision accident. Using this difference in peak magnitude, a typical drive recorder distinguishes between the occurrence of a collision accident and the passage of an uneven road surface. In the data collecting device 1 according to the first embodiment, the peak of the time waveform of relatively small acceleration, which was treated as an obstacle in the drive recorder, is used to find (pick up) the point where the unevenness of the road surface occurs. can be treated as useful information.

In the first embodiment, as shown in FIG. 3, image data and determination basic data other than image data are associated via date/time data indicating the date/time when the data was collected. Therefore, it is possible to extract the image data corresponding to the determination basic data other than the image data. For example, the corresponding image data can be extracted from the peak of the acceleration data waveform.

The controller 20 can transmit the determination basic data recorded in the SD card 22 to the external device from the communication circuit 21 while the vehicle is running. By equipping a consumer drive recorder with a function for collecting basic judgment data, it is possible to collect basic judgment data not only from road maintenance vehicles but also from general vehicles equipped with drive recorders. By collecting and accumulating a larger amount of determination basic data from drive recorders installed in many general vehicles, it is possible to improve the accuracy of determining whether repair is necessary.

When the vehicle speed is remarkably slow, even if the vehicle passes through unevenness, a large acceleration peak that exceeds the second determination threshold value At2 does not occur. Therefore, when the vehicle speed is extremely slow, it is not possible to obtain effective acceleration data for determining the presence or absence of unevenness. In order to determine the presence or absence of unevenness based on valid acceleration data, the process of detecting unevenness (step ST02) in FIG. 4 should be executed after the vehicle speed exceeds a predetermined threshold value.

[First Modification of First Embodiment]
Next, a first modified example of the first embodiment will be described.
The data collection device 1 according to the first modification of the first embodiment further has a microphone as a sensor for collecting determination basic data. The controller 20 has a function of determining whether or not the vehicle has passed over an uneven road surface by using both the acceleration data and the sound data collected by the microphone.

By using both the acceleration data and the sound information, it is possible to determine the presence or absence of unevenness on the road surface with higher accuracy. Furthermore, it is possible to obtain information about the shape and size of unevenness on the road surface from the volume and frequency (spectrum) of the sound.

[Second Modification of First Embodiment]
Next, a second modification of the first embodiment will be described with reference to FIGS. 6A and 6B.
FIG. 6A is a flowchart of processing executed by the controller 20 of the data collection device 1 according to the second modification of the first embodiment. Differences from the flowchart of the processing executed by the controller 20 of the data collection device 1 according to the first embodiment shown in FIG. 4 will be described below.

In the second modified example, by analyzing the image data collected between steps ST01 and ST02 of the first embodiment, it is possible to determine whether the section in which the vehicle is traveling is uneven due to factors other than deterioration of the road surface. is added (step ST11). If the section in which the vehicle is traveling is not a section in which irregularities have occurred due to factors other than deterioration of the road surface, it is determined whether passage of the irregularities in the road surface has been detected (step ST02). This determination process and subsequent processes are the same as those in the first embodiment.

If the section in which the vehicle is traveling is a section in which unevenness has occurred due to a factor other than deterioration of the road surface, the controller 20 skips the process (step ST02) of determining whether passage of the unevenness of the road surface has been detected. , a determination as to whether or not the processing is completed (step (ST05) is performed.

FIG. 6B is a diagram showing an example of an image acquired by camera 15 (FIG. 2). There is a "under construction" sign on the side of the road. When the controller 20 detects a signboard under construction by analyzing the acquired image data, it recognizes that the road ahead is under construction. It can be determined from the condition of the road surface in the image data whether or not the road has passed through the section under construction. The controller 20
It is determined that the vehicle is traveling in a section where unevenness is generated due to factors other than deterioration of the road surface from the time when it approaches the section under construction to the time when it exits the section under construction.

Next, the excellent effects of the data collection device 1 according to the second modification of the first embodiment will be described.

In a section of a road under construction, the road surface is uneven because, for example, the surface layer of the road is cut and the underlying roadbed is exposed. This unevenness is caused by factors other than deterioration of the road surface, and even if the data collection device 1 detects this unevenness, it is not necessary to determine whether repair is necessary. In the second modification, excessive detection of unevenness can be suppressed by excluding unevenness that does not need to be repaired from the detection target. As a result, consumption of the recording capacity of the SD card 22 by unnecessary determination basic data can be suppressed. Since the total amount of data to be recorded is reduced, the amount of data to be analyzed when determining unevenness to be repaired based on the recorded data is reduced. As a result, the processing time required for analysis can be shortened.

As shown in FIG. 6B, the section where unevenness occurs due to factors other than deterioration of the road surface may be, for example, a section where unevenness occurs due to construction work. In addition, it may include a section where there is a step at the joint where excavation work is performed, a section where there is a step at the edge of a manhole, a section where there is a step at the joint of a bridge, and the like. Seams where excavation work has been performed, edges of manholes, seams of bridges, etc. may be detected by analyzing image data.

In the third modification shown in FIG. 6A, when the controller 20 determines that the road surface is uneven due to factors other than deterioration of the road surface, the unevenness detection process is skipped. The process of executing the unevenness detection process and recording the determination basic data (step ST04) may be skipped.

[Third Modification of First Embodiment]
Next, a third modification of the first embodiment will be described with reference to FIGS. 7A to 7D.
FIG. 7A is a flowchart of processing executed by the controller 20 of the data collection device 1 according to the third modification of the first embodiment. When power is supplied to the data collection device 1, the controller 20 analyzes the image data acquired by the camera 15 (FIG. 2) to determine the type of road surface on which the vehicle is currently running (step ST21). The controller 20 changes the second determination threshold value At2 (FIG. 5) for detecting unevenness of the road surface according to the type of road surface.

Road surface types include, for example, asphalt pavement, concrete pavement, and block pavement. When the controller 20 determines that the road surface type is asphalt pavement, the controller 20 sets the second determination threshold value At2 to a value for asphalt pavement (step ST22), and determines that the road surface type is concrete pavement. In this case, the second determination threshold value At2 is set to a value for concrete pavement (step ST23), and when it is determined that the road surface type is block pavement, the second determination threshold value At2 is set to a value for block pavement. A value is set (step ST24).

After setting the second determination threshold value At2, the controller 20 determines whether or not to end the process (step ST25). For example, when the power supply to the data collection device 1 is stopped, the controller 20 stops processing. When continuing the processing, the controller 20 repeats the processing from step ST21. This repetitive process may be executed, for example, at a constant cycle, for example, a cycle of 1 second.

FIG. 7B, FIG. 7C, and FIG. 7D are diagrams showing examples of images acquired while driving on asphalt pavement, concrete pavement, and block pavement road surfaces, respectively. As shown in FIG. 7C, a concrete paved road surface has seams having a width of about 1 cm at intervals of, for example, 5 m to 10 m. On the road surface of block pavement, a unique pattern consisting of, for example, a plurality of blocks appears, as shown in FIG. 7D. No seams or unique patterns appear on the asphalt pavement, as shown in FIG. 7B. The controller 20 can determine the type of road surface by detecting the presence or absence of joints and unique patterns through image analysis.

Next, an excellent effect of the third modification of the first embodiment will be described.
The acceleration (impact) that the vehicle receives depends on the type of road surface on which the vehicle is running. By changing the second determination threshold value At2 according to the type of road surface, it is possible to appropriately determine the presence or absence of unevenness according to the type of road surface. For example, while driving on a paved road surface, the vehicle is continuously impacted by the unique pattern of the blocks. It is preferable to set the second determination threshold value At2 so as to exclude the magnitude of the impact due to this unique pattern from the object of unevenness detection. When the road surface is concrete pavement, the second determination threshold value At2 may be set so as to exclude the magnitude of the impact applied to the vehicle by the joint from the unevenness detection target. By setting the second determination threshold value At2 in this manner, it is possible to prevent excessive detection of irregularities that are not to be repaired.

In the third modification of the first embodiment, the second determination threshold value At2 is varied depending on the type of road surface. can be different. By doing so, it is possible to more appropriately determine the presence or absence of unevenness on general roads and expressways. Also, it is preferable to collect basic judgment data when the traveling speed of the vehicle exceeds a threshold depending on the type of road on which the vehicle is traveling.

Instead of the method of determining the type of road surface by image analysis, the type of road surface for each road may be stored in the SD card 22 or the like in advance. The controller 20 can identify the type of road surface on which the vehicle is currently traveling from the relationship between the current position of the vehicle and the type of road surface for each road stored in advance.

[Fourth Modification of First Embodiment]
Next, a fourth modification of the first embodiment will be described with reference to FIGS. 8A and 8B.
FIG. 8A is a flowchart of processing executed by the controller 20 of the data collection device 1 according to the fourth modification of the first embodiment. Differences from the flowchart of the processing executed by the controller 20 of the data collection device 1 according to the first embodiment shown in FIG. 4 will be described below.

In the fourth modification, between steps ST01 and ST02, the controller 20 analyzes the image data acquired by the camera 15 (FIG. 2), so that stepped pavement intentionally provided on the road surface is detected. It is determined whether or not this has been done (step ST31). When determining that the road surface is paved with steps, the controller 20 skips the unevenness detection processing (step ST02) and determines whether or not the processing is finished (step ST05). When determining that the road surface is not paved with steps, the controller 20 executes the process of detecting unevenness (step ST02).

FIG. 8B is a diagram showing an example of an image when driving on a road surface paved with steps. Examples of stepped pavement that are intentionally provided include those intended to suppress the running speed and alert the driver of the vehicle by giving sound and vibration to the driver of the vehicle. Step pavement is performed, for example, by applying an aggregate such as ceramic to the pavement surface using a resin-based adhesive. As shown in FIG. 8B, regions 94 coated with aggregate are periodically arranged in the traveling direction. The controller 20 can determine whether stepped pavement is intentionally provided on the road surface by detecting the area 94 to which the aggregate is applied from the image data.

In the third modification, it is possible to prevent a point where stepped pavement is intentionally provided from becoming a candidate for a point where a step to be repaired occurs.

Information specifying a point where stepped pavement is intentionally provided may be registered in the SD card 22 or the like in advance. The controller 20 may skip the unevenness detection process (step ST02) when the vehicle passes through a previously registered point where stepped pavement is intentionally provided.

It is preferable to display an image of image data on an external device such as a personal computer so that the user can designate a section for skipping unevenness detection processing (step ST02) while viewing the image. For example, a pointing device may be used to specify the start point and end point of a section for which the unevenness detection process (step ST02) is to be skipped.

[Fifth Modification of First Embodiment]
Next, a fifth modification of the first embodiment will be described with reference to FIGS. 9A to 9C.
In the fifth modified example of the first embodiment, the controller 20 stores collection position data specifying a place to collect judgment basic data serving as a basis for judging the need for repair of roads or road appendages. there is The collected position data may be obtained, for example, by the controller 20 receiving it from an external device via the communication circuit 21 (FIG. 2). Alternatively, the controller 20 may obtain the collection position data by reading the collected position data recorded on the SD card 22 . The controller 20 stores the obtained collected position data in the RAM 20c (FIG. 2).

Collected position data is data in a format that specifies the points where basic judgment data should be collected (data collection points), and data in a format that specifies the start and end points of sections where basic judgment data should be collected (data collection sections). including at least one of The controller 20 periodically determines whether the current position of the vehicle is in the vicinity of the data collection point and whether it is within the data collection section. If the current position of the vehicle is in the vicinity of the data collection point or within the data collection section, the controller 20 sets a flag (data collection flag) indicating that the current position is where the basic data for determination should be collected. If the current position of the vehicle is neither near the data collection point nor within the data collection section, the controller 20 resets the data collection flag.

FIG. 9A is a flowchart of processing executed by the controller 20 of the data collection device 1 according to the fifth modification of the first embodiment. Differences from the flowchart of the processing executed by the controller 20 of the data collection device 1 according to the first embodiment shown in FIG. 4 will be described below.

In the fifth modification, instead of the process of step ST02 in FIG. 4, the controller 20 determines whether or not the current position of the vehicle is a place where basic determination data should be collected (step ST41). For example, when the data collection flag is set, the controller 20 determines that the current position of the vehicle is the location where the determination base data should be collected, and when the data collection flag is reset, the vehicle It is determined that the current position of is not the place where the determination basic data should be collected.

When the current position of the vehicle is determined to be the place where the basic determination data should be collected, the controller 20 records the basic determination data in the road condition evaluation recording area of the SD card 22 (step ST42). After that, it is determined whether or not to end the process (step ST05).
. When it is determined that the current position of the vehicle is not the place where the basic determination data should be collected, the controller 20 skips the process of recording the basic determination data and determines whether or not to end the process (step ST05).

FIG. 9B is a diagram illustrating an example of a data collection section; In FIG. 9B, the data collection section 80 is indicated by a thick solid line. A vehicle departs from a vehicle depot 83, travels a route including a predetermined data collection section 80, and then returns to the vehicle depot. When the vehicle reaches the start point 81 of the data collection section 80, the controller 20 sets the data collection flag, and when it reaches the end point 82, it resets the data collection flag. As a result, the determination basic data is constantly recorded in the SD card 22 while the vehicle is traveling in the data collection section 80 .

FIG. 9C is a diagram showing an example of data collection points. At least one data collection point 85 is preset. The vehicle leaves the depot 83 and returns to the depot 83 after passing the data collection point 85 . When the vehicle is positioned in the vicinity area 86 of the data collection point 85 (the portion indicated by the thick solid line in FIG. 9C), the controller 20 sets the data collection flag. Therefore, the controller 20 records the determination basic data in the SD card 22 in the vicinity area 86 of the data collection point 85 .

Next, the excellent effects of the fifth modification of the first embodiment will be described.
In the fifth modification of the first embodiment, the basic determination data is recorded in the SD card 22 regardless of whether there is a peak in the acceleration data at the location where the basic determination data should be collected. Therefore, when the road surface has deteriorated such that no noticeable peak appears in the acceleration data, it is possible to record the image data of the point where the deterioration has occurred. Determination of the presence or absence of deterioration of the road surface may be made by displaying the image data on the screen and visually inspecting the image by the road administrator. Further, the presence or absence of deterioration of the road surface may be automatically determined by performing image analysis using image analysis software. Further, the presence or absence of unevenness on the road surface may be determined based on the magnitude of the acceleration data.

Also, the basic judgment data is recorded on the SD card 22 at the place where the basic judgment data should be collected, and the basic judgment data is not recorded on the SD card 22 at other places. Therefore, compared to the case where the determination basic data is recorded on the SD card 22 for all routes traveled by the vehicle, the memory space consumption of the SD card 22 can be reduced. Furthermore, when analyzing the collected determination basic data, the data amount of the determination basic data to be analyzed is reduced, so the time required for analysis processing can be shortened.

As the data collection point 85 (FIG. 9C), it is preferable to register a point where deterioration of the road surface is observed, but the road surface does not require immediate repair. By periodically collecting the determination basic data at this point, the progress of deterioration can be continuously observed.

The neighborhood 86 of the data collection point 85 (FIG. 9C) takes into account the error in the position determined by the GPS receiver 14 (FIG. 2) and the difference between the current position of the vehicle and the position of the road taken by the camera 15. It is preferable to define such that the road surface at the data collection point 85 can be photographed.

The controller 20 preferably has a function of notifying the driver that the vehicle has approached the data collection point 85 when the distance between the current position of the vehicle and the data collection point 85 becomes equal to or less than the reference distance. The driver of the vehicle can know when the vehicle is approaching the data collection point 85 . Thereby, preparation for collection of determination basic data can be started.

Further, the controller 20 stores the standard value of the traveling speed when passing the data collection point 85, notifies the vehicle that the vehicle is approaching the data collection point 85, and informs the driver of the vehicle of the standard value. It is preferable to have a function to prompt the vehicle to run at the running speed. The driver of the vehicle
Before running the data collection point 85, it can be found that the standard values need to be run. As a result, it is possible to suppress the occurrence of a situation in which the vehicle travels at the data collection point 85 with a value greatly deviating from the standard value, and the collected determination basic data cannot be used effectively.

The fact that the vehicle has approached the data collection point 85 and the standard value of the running speed may be output by, for example, sound from the speaker 16 . This allows the driver to notice the notified information without looking away.

[Sixth Modification of First Embodiment]
Next, a sixth modification of the first embodiment will be described with reference to FIGS. 10A and 10B.

In the first embodiment, the data collection device 1 recorded the determination basic data in the SD card 22 with the detection of the unevenness of the road surface as a trigger (step ST04 in FIG. 4). In the fifth modification of the first embodiment, the basic determination data is recorded in the SD card 22 only at the locations where the basic determination data should be collected (step ST42 in FIG. 9). In the sixth modification, the data collection device 1 has a function of constantly recording the basic determination data.

A mode in which the basic determination data is constantly recorded is called a "constant recording mode", and a mode in which the basic determination data is recorded when an unevenness is detected is called an "event recording mode". The controller 20 stores one of the constant recording mode and the event recording mode as a default mode. If the user does not perform a mode switching operation, the data collection device 1 operates in the prescribed mode. When the user operates the operation button 12 (FIGS. 1 and 2) to select a mode different from the default mode, the data collection device 1 operates in the mode selected by the user.

FIG. 10A is a flowchart of processing executed by the controller 20 of the data collection device 1 according to the sixth modification of the first embodiment. Differences from the processing executed by the controller 20 of the data collection device 1 according to the first embodiment shown in FIG. 4 will be described below.

In the sixth modification, the controller 20 determines the current mode between steps ST01 and ST02 (step ST51). If the current mode is the constant recording mode, the controller 20 records the determination basic data in the road condition evaluation recording area of the SD card 22 (step ST04). If the current mode is the event recording mode, the controller 20 executes unevenness detection processing (step ST02).

FIG. 10B is a diagram showing an example of a route for recording determination basic data. After the vehicle leaves the depot 83 and travels along the route 87, it returns to the depot 83. In the sixth modification, when the constant recording mode is selected, the determination basic data is recorded in all sections of the route traveled from the departure from the depot 83 to the return.

Next, the excellent effect of the sixth modified example will be described. By setting the data collection device 1 to the constant recording mode, it is possible to collect basic judgment data for judging the necessity of repairing roads or road appendages for all routes traveled by the vehicle. As a result, judgment basic data is collected in a wider area. If there is accumulated basic judgment data collected in the past when an abnormality was found in the road or road appendages, the judgment basic data collected in the past will be used together. By doing so, it is possible to analyze the time and cause of occurrence of the abnormality.

The period of constant recording may be, for example, the period from when the accessory key of the vehicle is turned on to when it is turned off.

[Seventh Modification of First Embodiment]
Next, a seventh modification of the first embodiment will be described with reference to FIGS. 11A to 11C.

FIG. 11A is a flowchart of processing executed by the controller 20 of the data collection device 1 according to the seventh modification of the first embodiment. This processing is executed, for example, between each of steps ST02, ST03, and ST04 of the first embodiment shown in FIG. 4 and step ST05. In the seventh modification, after steps ST02, ST03, and ST04 of the first embodiment shown in FIG. 4, the controller 20 analyzes the image data acquired by the camera 15 (FIG. 2) (step ST61). For example, it analyzes the state of the road surface in the image data and analyzes the state of the road appendages in the image data. The controller 20 determines whether or not the road surface and road accessories need repair based on the analysis results (step ST62). For example, the controller 20 detects cracks in the road surface, deterioration of road markings, poor drainage of roads after rain, corrosion and deformation of road appendages such as road signs and guardrails, signs of landslides, and harmful effects caused by roadside trees. do.

When the controller 20 determines that the road surface or road appendages need to be repaired, it records the image data and other determination basic data in the SD card 22 (step ST63). After recording the determination basic data, step ST05 of the flow chart shown in FIG. 4 is executed. When the controller 20 determines that the road surface or road appendages need not be repaired, it executes step ST05 of the flowchart shown in FIG.

11B and 11C are drawings showing examples of images in which the controller 20 has determined that the road surface or road appendages need to be repaired. In the example shown in FIG. 11B, a broken portion 90 is confirmed in a part of the guardrail. In the example shown in FIG. 11C, a portion of the road sign 91 is hidden by the roadside trees 92 and cannot be visually recognized by the driver.

Next, the excellent effects of the seventh modification of the first embodiment will be described. In the seventh modification of the first embodiment, the amount of images that the road administrator should see compared to the case where the road administrator looks at all the images acquired while driving and finds the parts that need repair. less For this reason, it is possible to reduce the burden on the road administrator for image checking work. Also, even if an abnormal portion is overlooked by human visual inspection, the controller 20 detects the portion requiring repair, thereby reducing the overlooked portion requiring repair.

[Eighth modification of the first embodiment]
Next, an eighth modified example of the first embodiment will be described.
In the first embodiment, the data collection device 1 is equipped with one camera 15 (FIG. 2). In the eighth modification, in addition to the camera 15, a second camera is mounted. The second camera captures a direction different from the direction captured by the first camera 15 . For example, the first camera 15 captures the front of the vehicle, and the second camera captures the road surface directly below the vehicle.

In steps ST03 and ST04 (FIG. 4) of the first embodiment, the controller 20 stores the image data acquired by the second camera in addition to the image data acquired by the first camera 15 in the SD card. 22.

Next, the excellent effects of the eighth modification of the first embodiment will be described. In the eighth embodiment, it is possible to photograph not only the road surface in front of the vehicle but also the road surface immediately below the vehicle. Based on the image data of the road surface directly under the vehicle recorded in the SD card 22, it becomes possible to observe the road surface condition in more detail.

A second camera may be used to photograph the rear of the vehicle. In this way, images of road appendages viewed from different directions can be obtained by the first camera 15 and the second camera. As a result, it is possible to improve the accuracy of determining the necessity of repairing road appendages.

[Second embodiment]
Next, a road condition evaluation support device 50 according to a second embodiment will be described with reference to FIGS. 12 to 15. FIG.

FIG. 12 is a block diagram of the road condition evaluation support device 50 according to the second embodiment. The road condition evaluation support device 50 includes a controller 60 , a display 61 , an input device 62 , an SD card reader 63 , a communication device 64 , a database 65 and an external storage device 66 . A controller 60 as processing means includes a central processing unit (CPU) 60a, a random access memory (RAM) 60c, and the like. Various programs such as an operating system (OS) and application programs are stored in the external storage device 66 . Various functions of the road condition evaluation support device 50 are realized by the CPU 60a transferring the programs stored in the external storage device 66 to the RAM 60c and executing the programs. Furthermore, the RAM 60c is used as a temporary storage area when the CPU 60a executes the program.

An SD card reader 63 is loaded with the SD card 22 in which the basic data for determination collected by the data collection device 1 (FIGS. 1 and 2) is recorded. The controller 60 has a function of reading the judgment basic data recorded on the SD card 22 and storing it in the database 65 . Further, the controller 60 has a function of accumulating in the database 65 the judgment basic data collected by the data collection device 1 and received by the communication device 64 through the data communication network 40 . In the database 65, date data, running speed data, position data, acceleration data, angular velocity data, and image data shown in FIG. 3A are associated with each other and accumulated.

The controller 60 causes the display 61 to display a dialog prompting the user to enter a command. A user of the road condition evaluation support device 50 , for example, a road administrator sees the dialog displayed on the display 61 and operates the input device 62 to give various commands to the controller 60 . The controller 60 executes processing in response to commands given by the user and causes the display 61 to display processing results.

Next, processing executed by the road condition evaluation support device 50 will be described.
When the user performs an operation to display acceleration data and image data at a specific point, the controller 60 causes the display 61 to display images of the image data acquired at the specific point on a plurality of different dates and times in chronological order.

FIG. 13 is a diagram showing an example of an image displayed on the display 61. As shown in FIG. The controller 60 extracts image data of a specific point designated by the user from the database 65, and converts an image 70 of the image data acquired by the camera 15 (FIG. 2) at a plurality of dates and times into information indicating the date and time of acquisition. 71 are displayed on the display 61 in chronological order. The vertical direction of the displayed figure corresponds to the time series. In FIG. 13, as an example, 10:00:7 on July 5, 2016, 11:12:47 on 30th of the same month, 10:15:33 on August 26 of the same year, and 10:00 on October 8 of the same year An example of displaying an image 70 of the same point acquired at 43 minutes and 9 seconds is shown.

Further, the controller 60 extracts acceleration data associated with the displayed image data from the database 65, and causes the display 61 to display the time waveform 72 of the extracted acceleration data so that the correspondence with the image 70 can be identified. For example, a temporal waveform 72 of acceleration data is displayed beside the image 70 . As the time waveform of the acceleration data to be displayed, for example, acceleration data in the vertical direction of the vehicle may be used. In addition, time waveforms of the acceleration data in the vertical direction, the longitudinal direction, and the lateral direction of the vehicle may be displayed in different colors and superimposed. An identification mark 73 is displayed at a position on the time axis of the time waveform 72 corresponding to the time when the displayed image 70 was obtained. As the identification mark 73, for example, a dashed line extending in the vertical direction may be used.

When the road administrator moves the identification sign 73 in the direction of the time axis, the controller 60 switches the displayed image to an image corresponding to the time specified by the identification sign 73 .

The controller 60 further causes the display 61 to display an evaluation value button 75 . When the user selects the evaluation value button 75, the controller 60 obtains an evaluation value that depends on the unevenness of the road surface at the specific point from each of the plurality of acceleration data collected at the specific point on a plurality of different dates and times. Further, the display 61 is caused to display the change over time of the obtained evaluation value.

As the evaluation value, for example, the maximum height of the peak appearing in the time waveform of the acceleration data may be used. For example, the maximum amplitude (peak-to-peak) of the time waveform may be used as the evaluation value. Also, as the evaluation value, for example, an average value of waveforms of acceleration exceeding a certain threshold may be used.

FIG. 14 is a diagram showing an example of an image of temporal changes in evaluation values displayed on the display 61. As shown in FIG. The controller 60 causes the display 61 to display the change in the evaluation value over time in the form of a graph. The horizontal axis of the graph represents the date and time, and the vertical axis represents the evaluation value. The solid line indicates the evaluation value from the past to the present time, and the dashed line indicates the predicted fluctuation of the future evaluation value. TE is the evaluation value when the height difference of the unevenness reaches the size to be repaired. The controller 60 displays a dashed line at a position where the evaluation value is TE so that the position where the evaluation value is TE can be recognized, for example. In the example shown in FIG. 14, the evaluation value increases over time. This means that the unevenness of the road surface is increasing with the passage of time. The controller 20 predicts future evaluation value fluctuations based on the gradient of past evaluation value fluctuations.

Next, the process of displaying the image 70 and the time waveform 72 of the acceleration data shown in FIG. 13 will be described with reference to FIG.

FIG. 15 is a diagram showing the relationship between the temporal waveform of acceleration data and the date and time when the temporal waveform was acquired. When the user inputs the position data of the point L0 to be displayed, the controller 60 extracts the acceleration data acquired at the input specific point L0 or points in the vicinity thereof from the position data accumulated in the database 65. do. The date and time when the specific point L0 is passed is t0. A peak P is detected from the time waveform A of the extracted acceleration data. Image data (for example, one frame F of a moving image) corresponding to the date and time t1 when the acceleration peak P was detected is extracted from the database 65, and the image 70 of the image data and the acceleration peak P corresponding to the date and time t1 are extracted. The display 61 is caused to display the time waveform 72 of the period before and after including. The point L1 where the peak P appears does not necessarily match the point L0 input by the user due to errors in calculation of the position data by the GPS receiver 14 or the like.

The frame F at the date and time t1 when the peak P appeared corresponds to the image in front of the uneven point that caused the peak P. FIG. It is preferable to extract a frame slightly before the date and time t1 as the frame F so that the image 70 displayed on the display 61 includes the unevenness that caused the peak P.

[Effect of Second Embodiment]
The road administrator can see the time-series displayed images 70 (FIG. 13) to confirm the progress of deterioration of the road or road appendages. As a result, it is possible to determine whether or not repair is necessary, and to predict when the repair will be required. Also, by looking at the displayed image 70, it is possible to determine whether or not it is necessary to continue observing the deterioration state of the displayed point. When it is determined that continuous observation is necessary, the images 70 displayed in chronological order serve as effective information for determining the frequency of observation.

The road administrator selects specific points for which an image is to be displayed on the display 61, such as a point determined to have unevenness on the road surface based on acceleration data, a point subject to continuous observation, and various other points. It is preferable to input a point or the like where it is predicted that repair may be necessary depending on the factor.

A road administrator can see the time waveform of the acceleration data displayed on the display 61 and identify the magnitude of the impact applied to the vehicle when the vehicle passed that point. The magnitude of the impact can be used as information for identifying the height difference of unevenness occurring on the road surface. From the temporal waveform of the acceleration data displayed in chronological order, it is possible to know the progress of deterioration such as unevenness occurring on the road surface.

Acceleration data collected at specific points designated by road authorities can be found by reference to the location data associated with the acceleration data. This position data is acquired by the GPS receiver 14, for example, and position measurement errors occur due to various factors. Therefore, it is difficult to precisely match the positions at which the plurality of temporal waveforms of the acceleration data during running collected on different dates and times are acquired, based only on the position data.

In the second embodiment, the controller 60 detects the peak P (FIG. 15) of the temporal waveform of the acceleration data, and the position at which each of the plurality of temporal waveforms of the acceleration data collected on different dates and times is obtained is They can be matched with high accuracy. As a result, it is possible to evaluate in chronological order the impact caused by unevenness at the same point, and to accurately extract image data at a specific point based on the date and time when the acceleration data was collected.

The progress of future deterioration can be estimated from the temporal change in the evaluation value (FIG. 14) that depends on the unevenness of the road surface at a specific point. From the estimated progress of deterioration, it is possible to predict when repairs should be made.

Since the change over time of the evaluation value is displayed in the form of a graph (FIG. 14), the road administrator can visually recognize the speed of deterioration of the evaluation value. Changes in future evaluation values shown in the graph of FIG. 14 can be used as useful information for determining when to repair roads or road appendages.

The controller 60 may have a function of predicting when repairs are likely to be required at a plurality of repair candidate locations, averaging the repair work times so as not to concentrate them, and displaying the recommended repair work times on the display 61. . At this time, the controller 60 may determine the recommended time for repair work so that the life cycle cost of the road is minimized as a whole.

The controller 60 may receive the determination basic data from the data collection device 1 in real time. The controller 60 analyzes the determination basic data received in real time, and if it determines that recollection is necessary, it is preferable to transmit a signal prompting recollection to the data collection device 1 . For example, if the travel speed at a point determined to have unevenness is outside the prescribed speed range, a signal prompting the driver of the vehicle equipped with the data collection device 1 to travel again at the prescribed speed. should be sent.

[First Modification of Second Embodiment]
Next, a road condition evaluation support device 50 according to a first modification of the second embodiment will be described with reference to FIGS. 16A and 16B.

In the second embodiment, the road administrator designates a specific spot where the image data should be displayed. have.

FIG. 16A is a diagram showing an example of a main menu screen displayed on the display 61 (FIG. 12) by the controller 60. FIG. An uneven spot extraction button 76 is displayed in the menu screen for instructing the extraction of uneven spots. The road administrator selects the bumpy spot extraction button 76 to cause the controller 60 to execute processing for extracting bumpy spots.

When the uneven point extraction button 76 (FIG. 16A) is selected, the controller 60 extracts from the time waveforms of the acceleration data accumulated in the database 65 time waveforms suggesting that the vehicle has passed over an uneven road surface. For example, the peak value of the temporal waveform of acceleration data may be compared with a judgment threshold, and the temporal waveform including a peak value exceeding the judgment threshold may be extracted as a temporal waveform suggesting that the vehicle has passed over an uneven road surface.

FIG. 16B is a diagram showing an example of an image displayed on the display 61 by the controller 60. As shown in FIG. Time waveforms suggesting that the vehicle has passed unevenness are extracted at different times and positions, and the time waveforms of the extracted acceleration and date and time data and position data corresponding to the peaks of the time waveforms are displayed. . Further, a chronological display button 77A for instructing chronological display, and a detailed inspection registration button 77B for registering as continuous observation target points are displayed.

When the road administrator designates one time waveform among a plurality of time waveforms of acceleration and selects the time-series display button 77A, the controller 60 displays another date and time at the point where the peak of the designated time waveform is detected. The time waveform of the acceleration data, image data, and the like acquired in 1 are displayed on the display 61 in chronological order. The displayed image is the same as the image shown in FIG. 13, for example.

When the road administrator designates one time waveform out of a plurality of time waveforms of acceleration and selects the detailed inspection registration button 77B, the controller 60 registers the point where the peak of the designated time waveform appears for detailed inspection. Register as a target point. The controller 60 causes the external storage device 66, for example, to store information indicating the points registered as detailed inspection target points.

When the road administrator operates the input device 62 to input a command to display a list of detailed inspection target points, the controller 60 causes the display 61 to display information on the detailed inspection target points in a list format. When the road administrator selects one point from the displayed detailed inspection target points, the controller 60 displays date and time data information, image data images, and acceleration data shown in FIG. 13 for the selected detailed inspection target points. The time waveform is displayed on the display 61 in chronological order.

Further, the controller 60 has a function of transferring information specifying the detailed inspection target point, such as position data, to the data collecting device 1 (FIGS. 1 and 2). Delivery of the information specifying the detailed inspection target point may be performed via the SD card 22, for example. Alternatively, it may be done via the data communication network 40 (FIG. 12).

The data collection device 1 that has acquired the information specifying the detailed inspection point may have a function of notifying the driver that the vehicle has approached the detailed inspection point when the vehicle approaches the detailed inspection point. For example, it is preferable to output a voice message from the speaker 16 (FIG. 2), saying, "1km ahead, detailed inspection target point. Please carry out detailed inspection."

Next, the excellent effects of the first modification of the second embodiment will be described.
In the first modified example of the second embodiment, it is possible to extract points where unevenness is thought to exist on the road surface based on the acceleration data accumulated in the database 65 without human intervention. This makes it possible to process enormous amounts of acceleration data.

In the first modification of the second embodiment, unevenness is detected based on the peak value of the temporal waveform of the acceleration data. Based on this, a temporal waveform that suggests that the vehicle has passed over the unevenness of the road surface may be extracted. For example, when the vehicle is suddenly braked, a large acceleration is generated in the longitudinal direction. When the driver performs a sudden steering operation, a large lateral acceleration is generated. On the other hand, when the vehicle passes through unevenness of the road surface, a large acceleration occurs in the vertical direction. The controller 60 may use the difference in the direction of the generated acceleration to extract points where unevenness is likely to exist on the road surface. Furthermore, the time waveform of the acceleration data corresponding to sudden braking, sharp steering, etc., changes more slowly than the time waveform of the acceleration data corresponding to passing over an uneven road surface. The controller 60 may use the difference in the shape of the time waveform to extract points where unevenness is thought to exist on the road surface.

Controller 60 is particularly good at using information other than acceleration data to extract time waveforms that suggest that the vehicle has passed over road surface irregularities. The controller 60 may use, for example, the running speed of the vehicle as information other than the acceleration data. For example, a peak appears in the temporal waveform of the acceleration data due to the impact when opening and closing the door of the vehicle, but the running speed at this time is almost zero. By using travel speed data together to determine whether the vehicle has passed over an uneven road surface, peaks in the temporal waveform of the acceleration data generated by door opening/closing can be excluded from detection targets.

When the controller 60 detects a point where unevenness is thought to exist, if no peak of the waveform of the acceleration data is detected at the same point before and after that point, it is preferable not to extract that point as the unevenness occurrence point. . This is because such a point is considered to be a place where unevenness has temporarily occurred due to a small obstacle such as a pebble.

The controller 60 preferably has a function of obtaining the tilt of the vehicle based on the angular velocity data and detecting the point where the road surface is abnormally tilted. It is preferable to determine the point for analyzing the angular velocity data based on the underground condition of the road. For example, during construction of a subway, it is preferable to determine a point for analyzing angular velocity data based on information such as the presence of a large underground cavity. In this way, the amount of angular velocity data to be analyzed can be reduced by performing the process of detecting the occurrence of an abnormal slope of the road surface in consideration of the underground state of the road.

The controller 60 may display, in the image shown in FIG. 13, the date and time information of an event such as road cleaning, snow removal, etc., which is estimated to cause a large change in the image. There is a large difference in the collected images before and after road cleaning, or between before and after snow removal. If the road administrator observes the images without knowing whether cleaning or snow removal work is being performed, there is a concern that the difference between the two images may lead to an erroneous determination of whether or not repairs are necessary. By making the road manager aware of the display of information such as the date and time of cleaning the road and the date and time of snow removal work, it is possible to prevent erroneous determination of the presence or absence of repairs.

[Second Modification of Second Embodiment]
Next, a road condition evaluation support device 50 according to a second modification of the second embodiment will be described with reference to FIGS. 17A and 17B.

In the second embodiment, determination basic data acquired from a single data collection device 1 (FIGS. 1A, 1B, and 2) mounted on a specific vehicle, for example, a work vehicle of a road management company was handled. , in the second modification, basic determination data is obtained from the data collection devices 1 mounted on each of a plurality of vehicles.

FIG. 17A is a diagram showing an example of the data structure of determination basic data. Date and time data, traveling speed data, position data, acceleration data, and angular velocity data are stored in the database 65 in association with vehicle type data. Furthermore, the image data shown in FIG. 3B is also associated with the vehicle type data.

FIG. 17B is a diagram showing a correspondence relationship between vehicle types and conversion factors. This correspondence relationship is stored in the external storage device 66 in advance, for example. In the example shown in FIG. 17B, conversion factors x1, x2, and x3 are associated with vehicle types A01, A02, and B01, respectively.

Even if the shape and depth of the unevenness of the road surface are the same, the magnitude of the acceleration measured by the data collection device 1 will also differ if the vehicle equipped with the data collection device 1 is different. In a second modification of the second embodiment, the controller 60 has a function of normalizing acceleration data based on vehicle type data. "Normalization" means converting the acceleration data actually collected by the data collection device 1 mounted on various vehicles into the acceleration data that would have been obtained if it had been mounted on a standard vehicle. . The acceleration data to be converted may be, for example, a feature amount that characterizes the time waveform of the acceleration data. For example, the height of a peak appearing in the time waveform, the distribution of frequency components of the time waveform, and the like may be used as the feature quantity that characterizes the time waveform of the acceleration data. For example, the controller 60 multiplies the feature amount of the time waveform of the actually measured acceleration data by a conversion factor for the vehicle type of the vehicle in which the data collection device 1 that acquired the acceleration data is mounted, thereby obtaining the feature amount. is normalized based on the vehicle type data.

By normalizing the acceleration data acquired by the data collection device 1 mounted on various vehicles based on the vehicle type data, the data acquired by the data collection device 1 mounted on each of a plurality of vehicles of different vehicle types Acceleration data can be compared with each other.

The conversion factor can be calculated in advance by mounting the data collection device 1 on various vehicles, passing through irregularities, and collecting acceleration data.

The magnitude of the acceleration data acquired when passing through unevenness may be affected by the weather. For example, tire temperatures and suspension temperatures differ between summer and winter, and these parameters are thought to affect the acceleration data. For example, the acquired acceleration data may be normalized based on the air temperature at the time of data acquisition. By doing so, it becomes possible to compare acceleration data acquired in summer and acceleration data acquired in winter.

[Third Modification of Second Embodiment]
Next, a road condition evaluation support device 50 according to a third modification of the second embodiment will be described with reference to FIG. In the second modification of the second embodiment, conversion factors are set for each vehicle type as shown in FIG. 17B. On the other hand, in the third modification of the second embodiment, a conversion factor is set for each vehicle type and each traveling speed. The controller 60 has a function of normalizing the acceleration data based on the vehicle type and running speed. "Normalization" means converting the acceleration data actually collected at different running speeds into the acceleration data that would have been obtained had the vehicle been running at a standard speed. As the standard speed, for example, the legal speed of the route on which the vehicle is traveling or a speed slightly lower than the legal speed may be adopted.

FIG. 18 is a diagram showing an example of correspondence relationships among vehicle types, traveling speeds, and conversion factors. For example, vehicle type A01 and running speed v1 are associated with conversion factor x11. The controller 60 mounts the data collection device 1 on a vehicle of the vehicle type A01, and multiplies the feature quantity of the time waveform of the acceleration data acquired when the vehicle is traveling at the traveling speed v1 by the conversion factor x11, thereby normalizing the acceleration data. become

Even if the shape and depth of the unevenness of the road surface are the same, the magnitude of the acceleration measured by the data collection device 1 will also differ if the traveling speed of the vehicle on which the data collection device 1 is mounted differs. The controller 60 normalizes the acceleration data based on vehicle type and travel speed, allowing comparison of acceleration data collected at different travel speeds.

The conversion factor can be calculated in advance by mounting the data collection device 1 on a vehicle and collecting acceleration data while passing through unevenness at various running speeds.

Determining an appropriate conversion factor can be difficult if the actual travel speed deviates significantly from the standard speed. Such running speeds are not associated with conversion factors in the list of correspondence relationships shown in FIG. The controller 60 preferably excludes acceleration data obtained at a running speed to which a relevant coefficient is not associated from the determination of the presence or absence of unevenness.

[Fourth Modification of Second Embodiment]
Next, a road condition evaluation support device 50 according to a fourth modification of the second embodiment will be described with reference to FIGS. 19A to 20. FIG.

In the fourth modification of the second embodiment, the controller 60 determines the degree of road surface repair required based on the image data accumulated in the database 65, and the determination result is stored in the image data, the acceleration data, the position It has a function of registering in the database 65 in association with data, date and time data, and the like. When the road administrator operates the input device 62 (FIG. 12) and instructs to execute the process of determining the degree of need for repair, the controller 60 analyzes the image data accumulated in the database 65. By doing so, the degree of need for repair is calculated at various points. Artificial intelligence technology based on deep learning, for example, may be used to calculate the degree of need for repair.

The controller 60 causes the display 61 (FIG. 12) to display the position data of the point determined to require repair so that the degree of repair necessity can be recognized.

FIG. 19A is a diagram showing an example of an image displayed on the display 61. FIG. Information specifying points determined to require repair and the degree of necessity of repair are arranged and displayed on the display 61 in the form of a list. As the information for identifying the point determined to require repair, for example, the road name, address, and latitude/longitude information may be displayed. Furthermore, an image display button 78 is displayed corresponding to each point. FIG. 19A shows an example in which an abnormality with a degree of need for repair of 10 has occurred at XX streets △△△, for example. When the road administrator selects the image display button 78 corresponding to this point, the controller 60 displays the image of the point △△△ on 〇〇 streets.

FIG. 19B is a diagram showing an example of an image of XX street △△△ points. From this image, unevenness 93 is confirmed on the road surface.

FIG. 20 is a diagram showing another example of an image displaying points determined to require repair. The controller 60 displays a map including a plurality of points determined to require repair, and displays an icon at the point determined to require repair on the map so that the degree of repair required can be recognized. Circled numbers, for example, may be used as icons. Numbers born in the past in a circle represent the degree of need for repair. Spots in need of repair may be colored differently according to the degree of need for repair.

Next, the excellent effects of the fourth modification of the second embodiment will be described.
In the fourth modification of the second embodiment, it is possible to determine the degree of necessity of repairing roads and road appendages without human intervention, so that it is possible to deal with a huge amount of image data. be possible. A road administrator who sees the information displayed on the display 61 can easily find a point with a high degree of urgency from a plurality of points requiring repair.

By using the data of the road maintenance management plan, it is preferable to exclude the points where the renewal time (repair time) of the road itself is near from the candidates that need to be repaired.

[Fifth Modification of Second Embodiment]
Next, a road condition evaluation support device 50 according to a fifth modification of the second embodiment will be described with reference to FIG.

In the fourth modified example of the second embodiment, the controller 60 causes the display 61 to display the location information of the point requiring repair so that the degree of repair required at that point can be recognized. In a modified example, the controller 60 causes the display 61 to display points requiring repair in such a manner that the amount of reduction in the life cycle cost of the road due to the repair is identifiable.

FIG. 21 is a diagram showing an example of an image displayed on the display 61. As shown in FIG. The information specifying points determined to require repair is associated with the amount of reduction in the life cycle cost of the road due to the repair, and the list is displayed on the display 61 after being sorted by the size of the amount of reduction in the life cycle cost. is displayed. As the information for identifying the point determined to require repair, for example, the road name, address, and latitude/longitude information may be displayed. Furthermore, an image display button 79 is displayed corresponding to each point. In FIG. 21, for example, it is shown that the decrease in the life cycle cost of the road due to the repair at the point of XX street △△△ is 20,000,000 yen. When the road administrator selects the image display button 79 corresponding to this point, the controller 60 causes the display 61 to display the image of this point.

Next, the excellent effects of the fifth modification of the second embodiment will be described. By looking at the image displayed on the display 61, the road administrator can easily find out repaired areas with a large reduction in life cycle cost. By performing repairs in order of decreasing extent of reduction in the life cycle cost of the road due to repair, it is possible to suppress an increase in the life cycle cost of the road as a whole.

For example, it is preferable to detect that the degree of damage has started to increase rapidly from the transition of the degree of damage to road appendages. By repairing while the degree of damage is low, an increase in repair costs can be suppressed.

FIG. 21 shows an example in which points determined to require repair are displayed in a table format along with the degree of decrease in life cycle cost. However, as shown in FIG. An icon corresponding to the degree of reduction in the life cycle cost may be displayed at a point requiring repair. Alternatively, instead of icons, points on the road that require repair may be colored according to the size of the reduction in life cycle cost.

[Sixth Modification of Second Embodiment]
Next, a road condition evaluation support device 50 according to a sixth modification of the second embodiment will be described with reference to FIGS. 22A to 22C.

In the sixth modification of the second embodiment, the controller 60 has a function of analyzing the image data accumulated in the database 65 to determine whether road appendages need to be repaired. When the road administrator operates the input device 62 (FIG. 12) and instructs to execute the process of determining the necessity of repairing the road appendages, the controller 60 converts the image data accumulated in the database 65. An analysis is performed to determine if road appendage repairs at various points are required. The controller 60 causes the display 61 to display. Further, the controller 60 registers the determination result in the database 65 in association with image data, acceleration data, position data, date and time data, and the like.

For example, we will take up the deterioration of road markings, poor drainage function of roads after rain, corrosion and deformation of road appendages such as road signs and guardrails, signs of landslides, and harmful effects of roadside trees, etc. Good. Artificial intelligence technology based on deep learning, for example, may be used to determine whether repair is necessary. If the color of a portion of the guardrail differs from the surrounding color, for example, if a portion of the guardrail that is white is discolored to brown, it can be determined that there is a high possibility that corrosion has occurred in that portion. Thus, based on spatial color variations, it can be determined whether road appendage repair is required.

Road inspections include initial inspections performed when roads are opened to traffic, daily inspections performed as normal work, periodic inspections performed about once a year, and emergency inspections performed after a disaster. The controller 60 may, for example, check the daily check items based on the determination basic data accumulated in the database 65 .

Further, the controller 60 has a function of determining whether or not road appendages need to be repaired based on the difference between a plurality of image data collected at the same point on a plurality of different dates.

22A to 22C are diagrams showing examples of image data collected at the same spot on different dates. In the example shown in FIG. 22A, the speed limit sign 95 is visible without being hidden by roadside trees. In the example shown in FIG. 22B, since the roadside trees 96 have grown since the time of FIG. 22A, a part of the speed limit sign 95 is hidden by the roadside trees 96, but it is possible to confirm that the maximum speed is 40 km/h. be. In the example shown in FIG. 22C, since the roadside trees 96 have grown further, most of the speed limit sign 95 is hidden by the roadside trees 96, and it cannot be confirmed that the maximum speed is 40 km/h.

The controller 60 detects how the roadside trees 96 grow and how the speed limit sign 95 is hidden by the roadside trees 96 by obtaining the difference between the images in FIGS. 22A, 22B, and 22C. can be done.

In addition, it is possible to recognize how a small scratch on the road attachment grows larger over time. In this manner, it is possible to determine whether or not road appendages need to be repaired based on changes in the image over time.

Next, the excellent effects of the sixth modification of the second embodiment will be described. In the sixth modified example of the second embodiment, it is possible to determine whether or not road attachments need to be repaired without human intervention. This makes it possible to process enormous amounts of image data.

The controller 60 can recognize the progress speed of deterioration of road appendages from the difference in the image data. By considering the progress speed of deterioration of the road appendages, it is possible to more appropriately determine whether or not the road appendages need to be repaired. For example, it is possible to more appropriately determine whether repairs are necessary based on the speed at which the color of road markings fades, the speed at which scratches on road appendages grow larger, and the speed at which roadside trees grow. be possible.

Regarding road appendages, it is preferable to preliminarily determine locations to be analyzed intensively in order to determine whether or not repair is necessary. For example, guardrails, guard cables, guardrail column foundations and anchors, guardrail bolts and nuts, etc., may be registered as important analysis points. For example, artificial intelligence using deep learning technology may be allowed to analyze images of important analysis points intensively and determine whether or not repair is necessary.

By analyzing the image data acquired after it rains, it is possible to easily detect the failure of the drainage function of the road, the occurrence of rutting, and the like. Whether it is raining or not can be determined by the operation of the wipers reflected in the image data. For example, when the state in which the wipers are operating changes to the state in which the wipers are stopped, it may be determined that the rain is over.

After a torrential downpour, rainwater on the road surface may not be drained even if the drainage function is normal. Therefore, after a torrential downpour, it may not be determined whether or not the drainage function is normal. Whether or not it is a torrential downpour can be determined based on the operating speed of the wipers, the degree of smoke in the distant scenery, and the like.

Image data, date/time data, and position data collected from many data collection devices 1 are preferably saved as big data. Based on this big data, it is possible to know the time period and area where it rained.

It is preferable to register locations where disasters such as landslides are likely to occur in the past as data collection locations 85 (FIG. 9C). As a result, it is possible to continuously accumulate images of locations where disasters are likely to occur. By observing these images in chronological order, it is possible to detect signs of disasters such as landslides in advance.

In addition, by evaluating images in chronological order, it is possible to detect the presence or absence of liquefaction due to an earthquake. When liquefaction occurs, a phenomenon occurs in which objects with relatively low specific gravity float and objects with relatively high specific gravity sink. The controller 60 has a function of determining whether or not there is a possibility that liquefaction has occurred by comparing the current image with the past image and detecting floating and sinking objects. good. In particular, it is preferable to determine the presence or absence of liquefaction by comparing the pre-earthquake image and the post-earthquake image.

In particular, from information such as the Advanced Land Observing Satellite "DAICHI", an area with a high possibility of liquefaction occurrence is determined, and this area is registered as an image data collection target (data collection point 85 in Fig. 9C). good. In addition to the information from the Advanced Land Observing Satellite, an area with a high possibility of occurrence of liquefaction may be obtained based on the height map of the groundwater level.

Furthermore, based on the information from the Advanced Land Observing Satellite, etc., it is advisable to register areas where there is a high possibility of landslides occurring as targets for image data collection.

[Seventh Modification of Second Embodiment]
Next, a road condition evaluation support device 50 according to a seventh modification of the second embodiment will be described with reference to FIGS. 23A and 23B.

In the seventh modification of the second embodiment, the road condition evaluation support device 50 determines whether or not the road or road appendages need to be repaired from a plurality of data collection devices 1 via the communication device 64 (FIG. 12). It receives the basic data for determination and the identification data for identifying the data collection device 1 .

FIG. 23A is a schematic diagram of a system including a road condition evaluation support device 50 according to the seventh modification of the second embodiment and a plurality of vehicles 51 equipped with the data collection device 1. FIG. A road condition evaluation support device 50 performs data communication with a data collection device 1 mounted on each of a plurality of vehicles 51 via a data communication network 40 and a radio base station 55 . Each of the data collection devices 1 transmits the collected determination basic data and identification data for identifying the data collection device to the road condition evaluation support device 50 . The controller 60 of the road condition evaluation support device 50 receives the determination basic data and identification data from each of the data collection devices 1 , associates these data, and stores them in the database 65 .

Further, the controller 60 assigns points according to the received determination basic data to each data collection device 1, and stores the accumulated points in the external storage device 66, for example.

FIG. 23B is a diagram showing an example of accumulated points given to each data collection device 1. As shown in FIG. For example, 1,000 points are given to the data collection device 1 whose identification data is ABC00001.

Next, the excellent effects of the seventh modification of the second embodiment will be described. In the seventh modification of the second embodiment, the controller 60 receives data via the communication device 64 (FIG. 12), thus saving the trouble of obtaining the data. Moreover, since data is received from a plurality of data collecting apparatuses 1, a larger amount of data can be collected than when data is obtained from one data collecting apparatus 1. FIG. For example, the data collection device 1 may be mounted not only on work vehicles of the road management company, but also on vehicles owned by employees of the road management company to obtain these data. It is even better to install the data collection device 1 in an unspecified general vehicle to obtain these data.

Furthermore, in the seventh modification of the second embodiment, it is possible to provide benefits to the owner of the data collection device 1 according to the points given to each data collection device 1 . The owner of the vehicle equipped with the data collection device 1 is motivated to transmit more data to the road condition evaluation support device 50 . For the owner of a vehicle in which the data collecting device 1 is not installed, it is a motivation to install the data collecting device 1 . This makes it possible to store a larger amount of data in the road condition evaluation support device 50 . The privilege may be, for example, a discount on a toll road, a discount when purchasing a product at a roadside station, or the like.

Points may be assigned to groups of general citizens such as neighborhood associations and residents' associations. Organizations that accumulate the most points should be rewarded for providing information.

The controller 60 preferably has a function of transmitting information specifying an area requiring emergency inspection due to the occurrence of a disaster (urgent inspection required area) to the plurality of data collection devices 1 . The emergency inspection required area may be input by operating the input device 62 by the road administrator.

The data collection device 1 that has received the information specifying the urgent inspection required area has a function of collecting image data and transmitting it to the road condition evaluation support device 50 in real time when the vehicle is located in the urgent inspection required area. The road condition evaluation support device 50 has a function of accumulating the image data received from the data collection device 1 in the database 65 and displaying it on the display 61 in response to a command from the road administrator.

When a vehicle equipped with the data collection device 1 exists in the urgent inspection required area, the road administrator can obtain the image of the urgent inspection required area without going to the urgent inspection required area. This enables rapid response to disasters.

More preferably, the data collection device 1 is mounted on a flight device such as a multicopter operated by a general user, and an aerial image of the emergency inspection required area is transmitted to the road condition evaluation support device 50 .

The data transmitted from the data collection device 1 to the road condition evaluation support device 50 may include data (vehicle classification data) indicating vehicle classifications such as standard-sized vehicles, medium-sized vehicles, and large-sized vehicles. It is said that the impact of large vehicles on pavement is about 10,000 times greater than the impact of small vehicles on pavement. If the ratio of vehicle classifications of vehicles passing on the road differs, the progress of deterioration of the road surface also differs. When almost all vehicles in Japan are equipped with the data collection device 1, the number of passing vehicles on each road can be calculated for each vehicle classification based on the data acquired from the data collection device 1.

When estimating the impact of passing vehicles on the road surface, it is preferable to reflect the number of vehicles for each vehicle classification. For example, the traffic of one large vehicle may be converted into the traffic of 10,000 standard-size vehicles to estimate the impact on the road surface. The impact on the road surface reflecting the tolls for each vehicle class provides useful information for predicting when road repairs are required.

Various aspects of the present invention have been described above using examples and modifications, but the description of these examples and modifications is not intended to limit the technical scope of the present invention. It should be noted that it is provided to facilitate understanding of the present invention. The scope of the invention is not limited to the configurations expressly described herein, and the specification contemplates other inventions that may be obtained by combining various aspects of the invention described. Disclose. Applicant of the present application has identified the features of the invention which are claimed to be patentable in the appended claims, but are not presently identified in the claims and It is our intention that inventions that include at least one element disclosed herein will also be claimed in the future.

The present invention is not limited to the configuration described in the "Mode for Carrying Out the Invention" above. A new invention may be constructed by arbitrarily selecting and combining the constituent elements included in the above-described embodiments and modifications. In addition, any constituent element of each embodiment or modification, and any constituent element described in "Means for Solving the Problem" or any constituent element described in "Means for Solving the Problem" A new invention can be made by arbitrarily combining the components described above. The applicant of the present application intends to acquire the rights to these new inventions as well, in amendments or divisional applications of the present application.

For example, this specification discloses the invention of a program for making a portable terminal realize the function of the data collection device 1 according to the first embodiment and various modifications of the first embodiment. Furthermore, this specification discloses the invention of a program for causing a computer to realize the functions of the road condition evaluation support device 50 according to the second embodiment and various modifications of the second embodiment.

Furthermore, the present specification describes the data collection device 1 according to the first embodiment and various modifications of the first embodiment and the road data collection device 1 according to the second embodiment and various modifications of the second embodiment. An invention of a road condition evaluation support system including a condition evaluation support device 50 is disclosed. Furthermore, this specification describes the functions of the data collection device 1 according to the first embodiment and various modifications of the first embodiment, and the second embodiment and various modifications of the second embodiment. Discloses the invention of a device having both the function of the road condition evaluation support device 50 by. Such a device may be implemented by, for example, a tablet terminal or the like that is detachably mounted on the vehicle.

1 Data collection device 3 Windshield 4 Room mirror 5 Cigar socket 6 Power cable 10 SD card slot 11 Display 12 Operation button 13 Joint rail 14 GPS receiver 15 Camera 16 Speaker 17 Acceleration sensor 18 Gyro sensor 19 SD card reader 20 Controller 20a CPU
20b ROM
20c RAM
21 communication circuit 22 SD card 31, 32 image data 40 data communication network 50 road condition evaluation support device 51 vehicle 60 controller 60a CPU
60c RAM
61 display 62 input device 63 SD card reader 64 communication device 65 database 66 external storage device 70 image 71 information indicating the date and time when the image was acquired 72 time waveform of acceleration data 73 identification mark 75 indicating the acquisition time of the displayed image evaluation Value button 76 Uneven point extraction button 77A Time-series display button 77B Detailed inspection registration buttons 78, 79 Image display button 80 Data collection section 81 Start point 82 End point 83 of data collection section Depot 85 Data collection point 86 Data collection point Neighboring area 87 Route 90 Guardrail broken point 91 Road sign 92 Roadside tree 93 Road surface unevenness 94 Aggregate applied area 95 Maximum speed limit sign 96 Roadside tree

Claims (2)

Image data of the surroundings of the vehicle collected by a data collection device mounted on the vehicle, acceleration data representing the magnitude of acceleration applied to the vehicle, vehicle position data, and data collection date and time data are associated and accumulated. A road condition evaluation support device having processing means for displaying, on a display means, in chronological order, images of the image data acquired at a specific point on a plurality of different dates and times based on a database obtained from the database ,
The processing means has a function of displaying, on the display means, the position information of points requiring repair of the road surface in such a manner that the degree of decrease in the life cycle cost of the road due to the repair can be identified. A program for causing a computer to implement the functions of the road condition evaluation support device according to claim 1 .

Images