JP2021168144A - Data collection device, road status evaluation support device, and program - Google Patents

Abstract

To provide a data collection device capable of collecting data and the like forming a basis of determining whether or not a repair of roads or road accessories etc. is necessary without setting a measurement device such as a laser distance measurement device in advance at the measurement place.SOLUTION: A data collection device is installed on a vehicle and used. The data collection device has processing means for collecting basic determination data forming a basis of determining whether or not a repair of roads or road accessories is necessary. The basic determination data includes image data around the vehicle.SELECTED DRAWING: Figure 4

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 the road surface (Patent Document 1). In this laser ranging method, the displacement amount of the surface to be measured is calculated by using a laser ranging means having a function of setting the irradiation angle of the laser beam to a designated azimuth angle or a vertical angle. The displacement reference point is a specific part on the measurement target surface obtained in the previous or previous survey, and the three-dimensional coordinates of the displacement reference point or the distance and collimation direction from the surveyor to the displacement reference point are stored. back. In this survey, the collimation direction of the displacement reference point or the three-dimensional coordinates of the displacement reference point is used from the memorized surveying instrument to collimate the point corresponding to the displacement reference point as the collimation point. Then, a point on the measurement target surface detected in the collimation direction is set as a detection point, and the three-dimensional coordinates of this detection point or the distance from the surveying instrument to the detection point is obtained, and the detection point is based on the displacement reference point. Calculate the amount of displacement of. The repair time of the road surface can be predicted based on the detected displacement amount.

Japanese Unexamined Patent Publication No. 2011-7657

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

An object of the present invention is, for example, to collect basic data or the like for determining whether or not a road or a road accessory needs to be repaired without installing a measuring device such as a laser ranging device in advance at a measuring place. It is to provide a data collecting device or the like capable of performing. 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 the collected data.

(1) It has a processing means for collecting judgment basic data which is mounted on a vehicle and is used as a basis for judging whether or not repair of a road or a road accessory is necessary, and the judgment basic data is the vehicle. It is preferable to use a data collecting device that includes image data around the road.

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

Whether or not 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, repair points at highway joints, and subsidence of the road surface. .. As the basic determination 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 through the unevenness of the road surface, image data obtained by photographing the surroundings of the vehicle, or the like may be used. As the basic determination data for determining the presence or absence of rutting or cracking, for example, image data obtained by photographing the front of the vehicle may be used. As the basic judgment data for determining the presence or absence of subsidence of the road surface, it is preferable to use data showing the inclination of the vehicle when passing through the subsidence location.

Road accessories 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, utility tunnels, and the like. It is advisable to use data such as an image of the surroundings of the vehicle as the basic judgment data for determining the necessity of repair.

The processing means may have a function of delivering the collected image data to an external device having a display function, or a function of displaying the collected image data on the device having a display function. The main body that determines the necessity of repair may be, for example, a road manager who has seen the image of the image data included in the determination basic data. The main body that determines the necessity of repair may be, for example, an image analysis program that analyzes image data included in the determination basic data, and artificial intelligence (AI) that performs determination processing based on the image analysis result.

The collected image data may be composed of a plurality of images acquired at a fixed sampling cycle. The sampling cycle may be short enough to obtain an image of the surroundings of the route on which the vehicle has traveled without interruption along the route by means of a plurality of images included in the collected image data. It is particularly preferable that the processing means collects moving image data as this image data.

The processing means may have, for example, a function of recording the collected basic determination data in a recording device. As the recording device, for example, a detachable memory card may be used. By doing so, the determination basic data can be handed over from the data collection device to another device via the memory card.

For example, it is advisable to include the acceleration data in which the acceleration applied to the vehicle is quantified in the determination basic data. The processing means may have a function of delivering the acceleration data included in the determination basic data to an external device having a display function, or a function of displaying the acceleration data on the device having a display function. The acceleration data may be displayed as, for example, a time axis change (time waveform) of acceleration. The main body that determines the necessity of repair may be, for example, a road manager who has seen the time waveform of acceleration displayed on the screen of a personal computer. The main body that determines the necessity of repair may be, for example, a determination program that determines based on the shape of the time waveform of acceleration.

(2) It is preferable that the determination basic data is acquired by a sensor mounted on the vehicle and includes sensing data different from the image data around the vehicle.

As sensing data, for example, position data indicating the current position of the vehicle, image data different from the 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. It is good to adopt it.

As a sensor for acquiring position data, for example, a GPS receiver may be used. The processing means is, for example, that the vehicle has approached a point where the repair necessity of the road or the road accessory should be determined based on the position data, or the vehicle is within the area where the repair necessity of the road or the road accessory should be determined. It is preferable to have a function to detect that the vehicle has entered. The processing means may have a function of collecting basic determination data within a point or area where the necessity of repairing the road or road attachment should be determined.

As the image data obtained by photographing the surroundings of the vehicle in the above (1) and the sensor for acquiring the image data different from the image data, it is preferable to use different imaging devices such as a CMOS camera and a CCD camera. For example, one imaging device may be used to photograph the road surface or road attachment in front of the vehicle, and the other imaging device may be used to photograph the road surface directly below the vehicle. For example, the processing means can obtain information such as the state of the road surface, the shape of the road appendages arranged around the road on which the vehicle travels, and the surface state from these image data.

As a sensor for acquiring acceleration data, for example, an acceleration sensor for detecting the acceleration applied to the vehicle may be used. The processing means can detect the magnitude of the impact applied to the vehicle, for example, from the acceleration data. Depending on the difference in the magnitude of the impact, the processing means can distinguish, for example, that the vehicle has been impacted by a collision, that the vehicle has been impacted by passing through the unevenness of the road surface, and the like.

The processing means may have a function of associating the image data obtained by photographing the surroundings of the vehicle in the above (1) with the sensing data in the above (2) and recording them in a database. 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 data. The processing means may have a function of delivering these image data and sensing data to an external device. The external device may have a function of associating these delivered image data with the sensing data to create a database and recording the data.

It is particularly preferable that the sensing data is data other than image data. By associating the image data obtained by photographing the surroundings of the vehicle in (1) with the sensing data other than the image data in (2), it is more accurately determined whether or not the road or road accessories need to be repaired. be able to.

(3) The sensing data includes acceleration data representing the magnitude of acceleration applied to the vehicle.
When the processing means detects that a collision has occurred in the vehicle based on the acceleration data, the data having a function of recording the image data and the acceleration data collected in the period before and after the detection time in the recording device. It is good to use a collecting device.

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

(4) When the processing means detects that the vehicle has passed the unevenness of the road surface based on the acceleration data, the image data and the acceleration data collected in the period before and after the detection time are stored in the recording device. It is preferable to use a data collecting device for recording.

When it is difficult to determine the necessity of repairing the road only with the acceleration data, the image of the road surface indicated by the image data can be used as information for determining the necessity of repairing.

For example, when the measured peak value of acceleration exceeds the determination threshold value, it may be determined that the vehicle has passed the unevenness of the road surface. This determination threshold value may be determined by actually traveling on a road having various irregularities on the road surface and measuring the acceleration applied to the vehicle. The unevenness of the road surface includes, for example, cracks in the pavement, rutting, steps, potholes, and the like.

For a general drive recorder that records events, the peak of the time waveform of the acceleration generated by the impact applied by the vehicle passing through the unevenness of the road surface is an obstacle to detect the occurrence of a collision accident (dust). Data). Generally, the peak of the time waveform of the acceleration generated when passing through the unevenness of the road surface is smaller than the peak of the acceleration generated at the time of a collision accident. Taking advantage of this difference in peak magnitude, a typical drive recorder distinguishes between the occurrence of a collision and the passage of bumps on the road surface. A general drive recorder is equipped with a function to find (pick up) the point where the road surface is uneven by using the peak of the time waveform of relatively small acceleration, which was treated as an obstacle, as a trigger (detection trigger). It is good. By doing so, a general drive recorder can be easily diverted to a data collecting device that collects judgment basic data for determining the necessity of repairing a road or a road accessory. Further, the drive recorder can be shared with this data collecting device by having both a function of detecting the occurrence of a collision accident and a function of detecting that the vehicle has passed through unevenness of the road surface.

(5) When 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 the first determination threshold value, the magnitude of the acceleration indicated by the acceleration data is determined. When it is equal to or greater than the second determination threshold value, which is smaller than the first determination threshold value, the data collecting device may be used to determine that the vehicle has passed the unevenness of the road surface.

Using the collected acceleration data, it is possible to separate the impact received when the vehicle passes through the unevenness of the road surface and the impact received by the collision accident. As a result, for example, a drive recorder that records an event can also be used as a data collection device that collects basic determination data for determining the necessity of repairing a road or the like. For example, a general drive recorder has a function of comparing the magnitude of acceleration with the first determination threshold value. By adding a function to compare the magnitude of acceleration with the second determination threshold value to such a general drive recorder, it is possible to determine whether or not the general drive recorder needs to be repaired such as a road. It can be used as a data collection device that collects basic data. When the acceleration is equal to or higher than the first determination threshold value, it may be determined that the vehicle has collided and that the vehicle has passed the unevenness of the road surface. As a result, it can be correctly determined that the vehicle has passed through the unevenness of the road surface when it has passed through unevenness with a large height difference such that a large impact similar to that when a collision occurs is applied to the vehicle.

(6) Further, the processing means may be a data collecting device having a microphone and detecting that the vehicle has passed the unevenness of the road surface by using the sound information collected by the microphone together.

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

(7) By analyzing the image data, the processing means determines whether or not the vehicle is traveling in a section where unevenness is generated due to a factor other than deterioration of the road surface, and other than deterioration of the road surface. If it is determined that the vehicle is traveling in a section where unevenness is generated due to a factor, it is preferable to use a data collecting device that skips the process of detecting whether or not the vehicle has passed the unevenness of the road surface.

Unevenness caused by factors other than deterioration that are not the target of repair can be excluded from the detection target. As a result, it is possible to prevent the points where the unevenness is generated from being excessively detected. As a result, it becomes possible to easily detect the point where the unevenness that should be considered as the target of repair is generated.

As a section where unevenness is generated due to factors other than deterioration of the road surface, at least, a section where unevenness is generated due to construction work, and a step at the seam of the place where the excavation work is performed are generated. It is advisable to determine whether or not the section has a step, a step due to the edge of the manhole, a step at the joint of the 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 currently being driven is under construction. The seams of the places where the excavation work was performed, the edges of manholes, the seams of bridges, etc. should be detected by analyzing the image data.

(8) Data collection in which the processing means determines the type of the road surface on which the vehicle is traveling by analyzing the image data, and changes the determination criteria for determining that the vehicle has passed the unevenness of the road surface according to the type of the road surface. It should be a device.

The acceleration (impact) received by the vehicle depends on the type of road surface on which the vehicle is traveling. By changing the above-mentioned 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 the type of road surface include asphalt pavement, concrete pavement, and block pavement. The processing means may have a function of determining the type of these road surfaces. On the road surface of concrete pavement, for example, seams of about 1 cm are provided at intervals of 5 to 10 m. On the road surface of the block pavement, a unique pattern consisting of multiple blocks spread out appears. No seams or unique patterns appear on the asphalt pavement. The processing means may determine the type of road surface by analyzing the image data of the road surface and detecting the presence or absence of seams and unique patterns.

(9) Whether or not the vehicle has passed the unevenness of the road surface at the point where the processing means detects the stepped pavement on the road surface intentionally provided by analyzing the image data and the stepped pavement is detected. It is preferable to use a data collecting device that skips the process of detecting the hump.

It is possible to prevent a point where a step paved road surface that is intentionally provided is raised as a candidate for a point where a step to be repaired occurs.

Examples of the intentionally provided stepped pavement on the road surface include those for suppressing the traveling speed and calling attention by giving sound and vibration to the driver of the traveling vehicle. 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 may determine whether or not the road surface is intentionally provided with a stepped pavement by detecting a pattern made of an aggregate such as ceramic from the image data of the road surface.

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

It is possible to collect the judgment basic data at the place where the judgment basic data should be collected, and not to collect the judgment basic data at other places. Compared to the case where the judgment basic data is collected at all the places where the vehicle has traveled, the amount of judgment basic data to be analyzed is smaller. Therefore, the amount of memory for recording the basic judgment data can be reduced, and the wasted time required for the process of analyzing unnecessary basic judgment data can be eliminated.

The current position data may be acquired by the GPS receiver. The GPS receiver may be built into the data collection device. Alternatively, the data collection device may receive the current position data from the GPS receiver mounted on the vehicle. It is preferable that the sensing data includes the 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 specify the position where the image data is collected and the position where the acceleration data is collected.

(11) The collection position data includes data for specifying a measurement point from which the determination basic data should be collected.
The processing means may be 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 is equal to or less than the reference distance.

The driver of the vehicle equipped with the data collection device can know that the vehicle is approaching the measurement point. As a result, preparations for collecting basic judgment data can be started.

The measurement points for which the basic judgment data should be collected may be selected from a plurality of points where unevenness or the like that does not need to be repaired immediately is detected by the analysis of the basic judgment data measured in the past. By continuously collecting the basic determination data of such measurement points at intervals of days, it is possible to determine the necessity of repair in consideration of the progress rate of deterioration of the road surface.

(12) The processing means stores a standard value of a traveling speed when passing through the measurement point, notifies the driver of the vehicle that the vehicle has approached the measurement point, and informs the driver of the vehicle. It is preferable to use a data collecting device having a function of encouraging the vehicle to travel at a standard traveling speed.

The driver of the vehicle equipped with the data collection device can notice that it is necessary to drive at the standard value before traveling at the measurement point. As a result, it is possible to suppress the occurrence of a situation in which the vehicle travels at the measurement point greatly deviating from the standard value and the collected basic judgment data cannot be effectively used. For example, it is advisable to output a voice to encourage the vehicle to travel at a standard traveling speed.

(13) It is preferable that the processing means is a data collecting device having a function of constantly recording the collected basic determination data in the recording device.

It is possible to collect basic judgment data for determining the necessity of repairing a road or a road accessory for all routes traveled by a vehicle equipped with a data collection device. As a result, basic judgment data is collected in a wider area. If the basic judgment data collected at the past time when no abnormality was found is accumulated at the point where the abnormality is found on the road or road attachment, the basic judgment data collected at the past time is used together. Then, it is possible to analyze the time and cause of the abnormality.

The period for constant recording may be, for example, the period from the time when the accessory key of the vehicle is turned on to the time when the accessory key of the vehicle is turned off. Further, the section in which the basic judgment data is collected may be determined in advance in the traveling route, and the data may be constantly recorded in the section in which the basic judgment 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 judgment basic data, starts collecting the judgment basic data when the current position of the vehicle matches the start point, and sets the end point. If they match, the collection of basic judgment data should be completed.

(14) It is preferable that the processing means is a data collecting device having a function of determining whether or not a road or a road accessory needs to be repaired by analyzing the image data.

It is possible to reduce the burden of checking the image of the image data by the road administrator. Further, even when an abnormal portion is overlooked by human visual inspection, the overlooking of the abnormality can be reduced by detecting the abnormality by the processing means.

By analyzing image data, cracks on the road surface, deterioration of road markings, poor drainage function of the road after rain, corrosion and deformation of road accessories such as road signs and guardrails, signs of landslides, harmful effects of roadside trees, etc. are detected. It would be nice to be able to do it.

(15) Further, it is preferable to use a data collecting device having a communication means and having a function of transmitting the determination basic data collected while the vehicle is running to an external device via the communication means. ..

When the vehicle equipped with the data collection device is a vehicle for road maintenance work that returns to the depot after departing from the depot and traveling on the target 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, basic judgment data can be collected not only from vehicles for road maintenance work but also from general vehicles equipped with a drive recorder. By collecting and accumulating more basic judgment data from drive recorders mounted on many general vehicles, it is possible to improve the accuracy of judgment of the necessity of repair.

(16) The image data around the vehicle collected by the data collection device mounted on the vehicle, the acceleration data indicating the magnitude of the acceleration applied to the vehicle, the position data of the vehicle, and the collection date and time data collected from the data are associated with each other. It is preferable to use a road condition evaluation support device having a processing means for displaying images of the image data acquired at a plurality of different dates and times at specific points on a display means in chronological order based on the accumulated database.

The road administrator can check the progress of deterioration of the road or road attachment by looking at the images displayed in chronological order. As a result, it is possible to determine whether or not repair is necessary and to predict when repair will be required. In addition, it is possible to determine whether or not it is necessary to continuously observe the deterioration state of the displayed point by looking at the displayed image. When it is determined that continuous observation is necessary, the images displayed in chronological order are useful information for determining the frequency of observation.

As a specific point for displaying the image on the display means, for example, a point where it is determined that the road surface is uneven based on the acceleration data, a point which is a target of continuous observation, or the like may be used.

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

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

The road administrator can identify the magnitude of the impact applied to the vehicle when passing the point by looking at the time waveform of the acceleration data. The magnitude of the impact can be used as information for identifying, for example, the height difference of the unevenness generated on the road surface. From the time waveform of the acceleration data displayed in time series, 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 a time waveform of the acceleration data showing a peak waveform on the display means 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 where the time waveforms of the plurality of acceleration data displayed in the time series are acquired. As a result, the impact generated due to the unevenness at the same point generated on the road surface can be evaluated in chronological order.

Acceleration data collected at a specific point can be found by referring to the position data associated with the acceleration data. This position data is acquired by, for example, a GPS receiver, and a position measurement error occurs due to various factors. For this reason, it is difficult to accurately match the acquired positions of each of the plurality of time waveforms of the traveling acceleration data collected at different dates and times from the position data alone. By detecting the peak of the time waveform of the acceleration data, it is possible to accurately match the acquired positions of each of the plurality of time waveforms of the acceleration data collected at different dates and times. As a result, the image data of a specific point can be accurately extracted based on the collection date and time of the acceleration data.

(19) The processing means obtains an evaluation value depending on the unevenness of the road surface at the specific point from each of the plurality of acceleration data collected at the specific points at a plurality of different dates and times, and the obtained said. It is preferable to use a road condition evaluation support device having a function of displaying the change with time of the evaluation value on the display means.

The degree of future deterioration can be estimated from the change over time in the evaluation value that depends on the unevenness of the road surface at a specific point. From the estimated degree of deterioration, it is possible to predict when repairs should be performed. As an evaluation value depending on the unevenness of the road surface, for example, the height of the peak appearing in the time waveform of the acceleration data may be used.

The processing means may display the evaluation values from the past to the present in a graph format. The road manager can visually recognize the speed of deterioration of the evaluation value by observing the change of the evaluation value in a graph format. The processing means predicts the change in the evaluation value in the future from the change in the evaluation value from the past to the present, and displays the change in the evaluation value from the past to the present and the predicted change in the future evaluation value in a graph format. It is good to let it. Predicted future changes in assessments can be used as useful information in determining when to repair a road or road appendage.
(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 the unevenness of the road surface from the time waveform of the acceleration data stored in the database. ..

Based on the acceleration data accumulated in the database, it is possible to extract points where unevenness is considered to exist on the road surface without human intervention. This makes it possible to process a huge amount of acceleration data. The time waveform that suggests that the vehicle has passed the unevenness can be extracted based on, for example, the peak height that appears in the time waveform of the acceleration data, the shape of the time waveform, and the magnitude relationship of the acceleration in the three directions of front, back, left, right, up, and down. can.

For example, when sudden braking is applied to the vehicle, a large acceleration is generated in the front-rear direction. When the driver suddenly operates the steering wheel, a large acceleration is generated in the left-right direction. On the other hand, when the vehicle passes through the unevenness of the road surface, a large acceleration is generated in the vertical direction. The processing means may use the difference in the direction of the generated acceleration to extract points where unevenness is considered to exist on the road surface. Further, the time waveform of the acceleration data corresponding to sudden braking, sudden steering, etc. changes more slowly than the time waveform of the acceleration data corresponding to the passage of the unevenness of the road surface. The processing means may use this difference in the shape of the time waveform to extract points where unevenness is considered to exist on the road surface.

It is particularly preferable that the processing means uses information other than the acceleration data in order to extract a time waveform suggesting that the vehicle has passed the unevenness of the road surface. As the processing means, for example, the traveling speed of the vehicle may be used as information other than the acceleration data. For example, a peak appears in the time waveform of the acceleration data when the door of the vehicle is opened and closed, but the traveling speed at this time is almost 0. By using the traveling speed data together with the determination of whether or not the vehicle has passed the unevenness of the road surface, the peak of the time waveform of the acceleration data generated by opening and closing the door can be excluded from the detection target.

(21) The database includes vehicle type data indicating the type of vehicle on which the data collection device was mounted 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 having different vehicle types. Here, "normalize based on vehicle type data" would have been obtained if the acceleration data actually collected by the data collection devices mounted on various vehicles was mounted on a standard vehicle. It means to convert to acceleration data. The acceleration data to be converted may be, for example, a feature amount that characterizes the time waveform of the acceleration data. As the feature amount that characterizes the time waveform of the acceleration data, for example, the height of the peak appearing in the time waveform, the distribution of the frequency component of the time waveform, and the like may be used.

(22) The database accumulates vehicle traveling speed data in association with the 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.

By normalizing the acceleration data based on the running speed data, it becomes possible to compare the acceleration data collected at different running speeds. Here, "normalize based on the running speed data" means converting the acceleration data actually collected at various different running speeds into the acceleration data that would have been obtained if the car had been running at the standard speed. Means to do. As the standard speed, for example, the legal speed of the traveling route or a speed slightly slower than the legal speed may be adopted. The acceleration data to be converted may be, for example, a feature amount that characterizes the time waveform of the acceleration data. As the feature amount that characterizes the time waveform of the acceleration data, for example, the height of the peak appearing in the time waveform, the distribution of the frequency component of the time waveform, and the like may be used.

(23) The processing means determines the degree to which the road surface needs to be repaired based on the image data stored in the database, and the determination result is the image data, the acceleration data, the position data, and the collection. It is preferable to use a road condition evaluation support device having a function of associating with date and time data and registering it in the database.

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

(24) The processing means may be a road condition evaluation support device having a function of displaying information for identifying a point where repair of the road surface is necessary on the display means so that the necessary degree of repair can be recognized.

A road administrator who sees the information displayed on the display means can easily find a highly urgent point from a plurality of points requiring repair. For example, the road name, address, and location information of the point where repair is required may be sorted according to the degree of need for repair and displayed in a list format on the display means. Further, a map may be displayed on the display means, and different icons may be displayed at points requiring repair depending on the degree of need for repair. Alternatively, instead of the icon, points on the road that need repair may be colored differently depending on the degree of need for repair.

(25) Road condition evaluation support having a function of displaying the position information of a point where the road surface needs to be repaired on the display means so that the magnitude of the decrease in the life cycle cost of the road due to the repair can be identified. It should be a device.

Road managers can easily find repair points where the life cycle cost is significantly reduced. For example, the road name, address, and location information of the points requiring repair may be sorted by the magnitude of the reduction in life cycle cost and displayed in a list format on the display means. again,
A map may be displayed as a display means, and an icon may be displayed at a point requiring repair according to the magnitude of the reduction in life cycle cost. Alternatively, instead of the icon, the points on the road that need repair may be colored according to the magnitude of the reduction in the life cycle cost.

(26) The processing means may be a road condition evaluation support device for determining the necessity of repairing road accessories by analyzing the image data stored in the database.

It is possible to determine the necessity of repairing road accessories without human intervention. This makes it possible to process a huge amount of image data. For example, deterioration of road markings, poor drainage function of roads after rain, corrosion and deformation of road accessories such as road signs and guardrails, signs of landslides, harmful effects of roadside trees, etc. are taken up as targets for repair of road accessories. It is good.

(27) A road condition evaluation support device in which the processing means has a function of determining the necessity of repairing road accessories based on the difference between a plurality of the image data collected at a plurality of different dates and times at the same point. It is good to say.

From the difference in the image data, the progress speed of deterioration of the road appendage can be recognized. By considering the progress rate of deterioration of road appendages, it is possible to more appropriately determine the necessity of repairing road appendages. For example, it becomes possible to more appropriately determine the necessity of repair based on the speed at which the color of the road markings fades, the speed at which the roadside trees grow, and the like.

(28) Further, the processing means has the communication means, and the image data, the acceleration data, the position data, the collection date and time data, and the data collected by the processing means by a plurality of data collection devices via the 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 these data with each other, 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. Further, since data is received from a plurality of data collection devices, a larger amount of data can be collected as compared with the case where data is obtained from one data collection device. For example, not only the work vehicle of the road management company but also the personally owned vehicle of the employee of the road management company may be equipped with a data collection device to obtain these data. It is even better to equip an unspecified general vehicle with a data collection device to obtain these data.

(29) It is preferable that the processing means is a road condition evaluation support device that stores the cumulative value of points by adding points according to the received image data and acceleration data for each data collection device.

Depending on the points, it becomes possible to provide benefits to the owner of the data collection device. Vehicle owners equipped with a data collection device will be motivated to send more data to the road condition assessment support device. For vehicle owners who do not have a data collection device, it is an incentive to install a data collection device. This makes it possible to obtain a larger amount of data. As a privilege, for example, a discount on toll road tolls, a discount when purchasing products at a roadside station, etc. may be used.

(30) The present specification discloses an invention of a program for realizing a function as a data collection device according to any one of (1) to (15) above in a mobile terminal.

(31) The present specification discloses an invention of a program for realizing a function as a road condition evaluation support device according to any one of (16) to (29) above in a computer.

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. The invention of the road condition evaluation support system is disclosed. Further, this specification describes 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. The invention of a device having both functions is disclosed. Such a device may be realized, for example, by a tablet terminal or the like that is detachably mounted on a vehicle.

For example, it is possible to collect data or the like that is the basis for determining whether or not a road or a road accessory needs to be repaired without installing a measuring device such as a laser ranging device in advance at the measurement location. For example, these collected data will be useful information for determining whether or not repair is necessary.

FIG. 1A is a perspective view of the data collection device according to the first embodiment as viewed obliquely from the rear, and FIG. 1B is a view showing a data collection device, a windshield, a dashboard, and the like 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 an example of the configuration of various sensing data other than the image data collected by the data collection device in a tabular format, and FIG. 3B is a diagram showing the configuration of the image data in a tabular format. FIG. 4 is a flowchart of the data recording process executed by the controller of the data collection device according to the first embodiment. FIG. 5 is a diagram showing an example of a time waveform of acceleration data, a first determination threshold value At1, a 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 the camera. FIG. 7A is a flowchart of processing executed by the controller of the data collection device according to the third modification of the first embodiment, and FIGS. 7B, 7C, and 7D are asphalt pavement, concrete pavement, and block, respectively. It is a figure which shows an example of the image acquired while traveling on the paved road surface. 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 traveling on a road surface paved with steps. It is a figure. 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 section, and FIG. 9C is a diagram showing data. 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 a route for recording basic determination data. FIG. 11A is a flowchart of the process executed by the controller of the data collection device according to the seventh modification of the first embodiment, and FIGS. 11B and 11C show that the controller needs to repair the road surface or road accessories. It is a drawing which shows the example of the image which was determined to be. 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 the change with time of the evaluation value 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 time waveform of the acceleration data and the date and time and the position where the time 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. 16B is a diagram shown on the display by the controller of the road condition evaluation support device according to the first modification of the second embodiment. It is a figure which shows an example of the image. FIG. 17A is a diagram showing an example of a data structure of judgment basic data accumulated in the road condition evaluation support device according to the second modification of the second embodiment, and FIG. 17B shows a vehicle type and a conversion coefficient. It is a figure which shows the correspondence relationship. FIG. 18 is a diagram showing an example of the correspondence relationship between the vehicle type, the traveling speed, and the conversion coefficient applied to the road condition evaluation support device 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 a point 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 a plurality of different dates and times at the same point. FIG. 23A is a schematic view of a system including a road condition evaluation support device according to a seventh modification of the second embodiment and a plurality of vehicles equipped with the data collection device 1, and FIG. 23B is a schematic view of each data collection device. It is a figure which shows an example of the cumulative value of the points given to.

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

FIG. 1A is a perspective view of the data collection device according to the first embodiment as viewed obliquely from the rear. A display 11 and a plurality of operation buttons 12 are arranged on a surface facing the rear (inside the vehicle interior) of the housing of the data collection device 1 mounted on the vehicle and used. The SD card insertion slot 10 is arranged on the side surface 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. The DC jack is arranged on the side surface not shown in FIG. 1A, and the speaker is arranged on the bottom surface.

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

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

FIG. 2 is a block diagram of the data collection device 1 according to the first embodiment. The controller 20 as a 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), a program for realizing various functions of the data collection device 1, and the like. By executing the program stored in the ROM 20b by the CPU 20a, various functions of the data collection device 1 are realized. The RAM 20c is used as a temporary storage area when the CPU 20a executes a program.

The speaker 16 and the display 11 function as notification means for notifying the user of various information. The controller 20 emits a sound or voice alarm or various information from the speaker 16. Further, the controller 20 causes the display 11 to display various information as images. The operation button 12 functions as an input means for the user to give various commands to the data collection device 1.

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

The GPS receiver 14 calculates position data indicating the current position of the vehicle based on the signal received from the GPS satellite. Further, the GPS receiver 14 calculates the current time based on the signal received from the GPS satellite. The controller 20 can obtain position data indicating the current position of the vehicle and date and time data indicating the current date and time from the GPS receiver 14. The controller 20 has an internal timer, and the current date and time can be acquired from the internal timer.

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

The acceleration sensor 17 measures acceleration in the front-rear direction (X-axis direction), left-right direction (Y-axis direction), and up-down direction (Z-axis direction) applied to the vehicle, and acquires acceleration data. The gyro sensor 18 has a three-axis direction of the vehicle, that is, a rotation direction (yowing direction) about the vertical direction, a rotation direction (pitching direction) about the left-right direction, and a rotation direction (rolling direction) about the front-rear direction. ) Is measured and the angular velocity data is acquired. The controller 20 captures the acceleration data and the angular velocity data at a constant sampling period, for example, a supplementing period of 10 ms.

The SD card 22 is mounted on the SD card reader 19 through the SD card insertion slot 10 (FIG. 1A). The SD card reader 19 executes a data writing process to the mounted SD card 22 or a data reading process from the SD card 22 based on the control from 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 compliant with a WiFi standard, a short-range wireless communication standard such as Bluetooth (registered trademark), a mobile communication system standard such as LTE or 4G, or the like may be used. The short-range wireless communication standard can be applied to communication with a device outside the vehicle, for example, when the vehicle is stopped. Alternatively, it can be applied to communication with a device in a vehicle, for example, a personal computer having a large-capacity storage. Standards for mobile communication systems can be applied, for example, to communication between vehicles moving within a wider area and external devices.

The data collecting 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 the image data collected by the data collection device 1 in a table format. The controller 20 collects date / time data, traveling speed data, position data, acceleration data, and angular velocity data at a constant sampling cycle. The date and time data includes date information and time information. The controller 20 can acquire date and time data from the GPS receiver 14 or the internal timer.

The traveling speed data represents the traveling speed of the vehicle. The controller 20 acquires traveling speed data from the electronic control unit (ECU) of the vehicle via the OBD connector. The position data is composed of latitude information and longitude information. The acceleration data represents acceleration on the X-axis (front-back direction), Y-axis (horizontal direction), and Z-axis (vertical direction). The angular velocity data represents the angular velocity in the rotation direction with the X-axis as the rotation axis, the angular velocity in the rotation direction with the Y-axis as the rotation axis, and the angular velocity in the rotation direction with the Z-axis as the rotation axis.

FIG. 3B is a diagram showing the structure of image data in a tabular format. The controller 20 uses, for example, H.A. 264, H. Compress according to a video compression standard such as 265. The image data is composed of a plurality of frames F, and some frame FIs include date and time data and position data at which the image was acquired. The acquisition date and time of the image of the frame F that does not include the date and time data can be calculated based on the date and time when 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, the acceleration data and the image data when the acceleration data is acquired are associated with each other via the date and time data.

The date and 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 or not the road needs to be repaired. In the present specification, these data are referred to as judgment basic data.

FIG. 4 is a flowchart of the data recording process executed by the controller 20. When the vehicle accessory key is turned on and power is supplied to the data collection device 1, the controller 20 starts the process 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, when the magnitude (absolute value) of the measured acceleration becomes equal to or greater than the first determination threshold value, the controller 20 determines that a collision has occurred. The acceleration data to be compared with the first judgment 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 becomes equal to or higher than the first judgment threshold, a collision occurs. It is good to judge that it has been done.

When the controller 20 determines that a collision has occurred, the controller 20 starts a process of recording the determination basic data collected in the period before and after the collision event in the recording area for the collision event of the SD card 22 (step ST03). The period for recording the data may be, for example, a sufficient period for analyzing the cause of the collision. For example, it may be a total period of 2 minutes having a time width of 1 minute before and after the time of the collision. The determination basic data before the time of collision occurs is read from the ring buffer by the controller 20 and recorded on the SD card 22.

If the occurrence of a collision is not detected in step ST01, the controller 20 determines whether or not the vehicle has passed the unevenness of the road surface (step ST02). For example, when the magnitude of the measured acceleration becomes equal to or greater than the second determination threshold value, which is smaller than the first determination threshold value, the controller 20 determines that the road surface has passed the unevenness. The acceleration data to be compared with the second determination threshold is, for example, three acceleration data of the X-axis, the Y-axis, and the Z-axis. It is good to judge that it has passed. Since acceleration in the vertical direction is mainly applied when passing through the unevenness, only the acceleration data of the Z axis may be compared with the second determination threshold value. The unevenness of the road surface includes, for example, cracks in the pavement, rutting, steps, potholes, and the like.

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

When the passage of the 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 supply of power from the vehicle to the data collection device 1 is stopped, the controller 20 ends the data collection process. The data collection device 1 has a built-in battery having a capacity capable of supplying power for executing the data collection stop processing even if the power supply from the vehicle is stopped, and the power supply from the vehicle is stopped. After that, the data collecting device 1 operates by the electric power from the built-in battery. When continuing the data collection, the controller 20 repeats the process from step ST01. In step ST01, the controller 20 determines the newly collected acceleration data.

Next, the recording process of the determination basic data in steps ST03 and ST04 will be described with reference to FIG.
FIG. 5 is a diagram showing an example of a time waveform of acceleration data, a first determination threshold value At1, a second determination threshold value At2, and image data to be recorded. The first determination threshold value At1 is set to a value larger than the maximum value of the acceleration received by the vehicle when passing through the unevenness of a normal road surface. The second determination threshold value At2 is set to a value larger than the maximum value of the acceleration received by the vehicle when traveling on a normal road surface having no unevenness.

When the vehicle passes through the unevenness of the road surface, a peak P1 larger than the second determination threshold value At2 appears in the time waveform of the acceleration data. When the controller 20 detects the peak P1, it records the image data 31 and the acceleration data acquired in the period T1 before and after the time when the peak P1 appears on the SD card 22.

When a collision accident occurs in a vehicle, a peak P2 larger than the first determination threshold value At1 is generated in the time waveform of the acceleration data. When the controller 20 detects the peak P2, the controller 20 records the image data 32, the acceleration data, and the like acquired in the period T2 before and after the time when the peak P2 appears on the SD card 22.

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 button 12 to input the date and time data or the position data obtained by acquiring the image to be displayed, the controller 20 causes the image of the image data associated with the input date and time data or the 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 the form of numbers or graphs. For example, when the user operates the operation button 12 to input the determination basic data (for example, acceleration data and date / time data) to be displayed, the controller 20 displays the input determination basic data on the display 11 in numerical or graph format. Let me.

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 on the SD card 22 and transmitting the determination basic data from the communication circuit 21 to another device via the data communication network 40. For example, when the user operates the operation button 12 to instruct the transmission of the determination basic data, the controller 20 starts the transmission of the determination basic data. The controller 20 may transmit the collected basic determination data to another device in real time.
@
Instead of recording the determination basic data on the SD card 22, the controller 20 may transfer the determination basic data to a device in the vehicle, for example, a personal computer having a large-capacity storage, via the communication circuit 21. After the judgment basic data is once stored in the device in the vehicle, the device in the vehicle can communicate over a long distance such as a mobile terminal, or the mobile communication system such as LTE or 4G of the data collection device 1. It is advisable to send the data to an external server, a management personal computer (for example, a road condition evaluation support device described later) or the like by using a communication function conforming to the standard. The wireless communication between the data collection device 1 and the device in the vehicle is more stable than the long-distance communication. Therefore, the device in the vehicle can be used as a large-capacity storage for buffering the determination basic data, similarly to the SD card 22.
@
Further, the basic determination data once recorded on the SD card 22 may be read from the SD card 22 and transferred to the device in the vehicle via the communication circuit 21. By doing so, even in a situation where communication with an external server, a management personal computer, or the like is not possible, a large amount of basic determination data can be accumulated without being restricted by the recording capacity of the SD card 22. When communication with an external server or the like becomes possible, it may be transmitted from a device in the vehicle to an external server or a management personal computer or the like via a device capable of long-distance communication such as a mobile terminal.

[Effect of the first embodiment]
Next, the excellent effect of the first embodiment will be described. The road administrator can see the image displayed on the display 11 and confirm the state of the road surface of the road included in the image, the shape of the road accessory, the surface state, and the like. Further, the SD card 22 can be attached to a personal computer or the like to check the image data and other basic determination data recorded on the SD card 22. The road manager can determine the necessity of repairing the road or road attachment based on these determination basic data.

Whether or not 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, repair points at highway joints, and subsidence of the road surface. 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 through the unevenness on the road surface, image data obtained by photographing the surroundings of the vehicle, and the like. The presence or absence of rutting or cracks 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, or the like. Whether or not the road surface has subsided may be determined by using data or the like indicating the inclination of the vehicle when passing through the subsidence location. The inclination of the vehicle may be obtained from the angular velocity of the vehicle.

Road accessories 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, utility tunnels, and the like. The necessity of these repairs may be determined based on data such as an image of the surroundings of the vehicle.

The image data collected by the data collection device 1 may be composed of a plurality of images acquired at a constant sampling cycle. The sampling cycle may be short enough to obtain an image of the surroundings of the route on which the vehicle has traveled without interruption along the route by means of a plurality of images included in the collected image data. By doing so, it is possible to obtain information on the deterioration state of the road and the road attachment in the entire area where the image data is acquired.

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

The data collecting device 1 according to the first embodiment uses the collected acceleration data to separate the impact received when the vehicle passes through the unevenness of the road surface and the impact received due to the collision accident. Thereby, for example, a drive recorder that records an image (event recording) at the time of a collision can also be used as a data collecting device that collects basic judgment data for determining the necessity of repairing a road or the like. For example, a general drive recorder has a function of comparing the magnitude of acceleration with a first determination threshold value for detecting a collision. By adding a function to compare the magnitude of acceleration with the second determination threshold value for detecting the unevenness of the road surface to such a general drive recorder, the general drive recorder can be used for repairing roads and the like. It can be used as a data collection device 1 that collects basic determination data for determining the necessity. When the acceleration is equal to or higher than the first determination threshold value, it may be determined that the vehicle has collided and that the vehicle has passed the unevenness of the road surface. As a result, it can be correctly determined that the vehicle has passed through the unevenness of the road surface when it has passed through unevenness with a large height difference such that a large impact similar to that when a collision occurs is applied to the vehicle.

In this way, by adding a simple function to a general consumer drive recorder, as a data collection device 1 for business use that collects judgment basic data for judging whether or not a road or road accessory needs to be repaired. It can be used. Therefore, it is possible to reduce the cost of the data collection device 1. On the contrary, the data collection device 1 according to the first embodiment can be used as a drive recorder.

For a general drive recorder that records events, the peak of the time waveform of the acceleration generated by the impact applied by the vehicle passing through the unevenness of the road surface is an obstacle to detect the occurrence of a collision accident (dust). Data). Generally, the peak of the time waveform of the acceleration generated when passing through the unevenness of the road surface is smaller than the peak of the acceleration generated at the time of a collision accident. Taking advantage of this difference in peak magnitude, a typical drive recorder distinguishes between the occurrence of a collision and the passage of bumps on the road surface. In the data collection device 1 according to the first embodiment, in order to find (pick up) the peak of the time waveform of relatively small acceleration, which was treated as an obstacle by the drive recorder, at 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, the determination basic data other than the image data and the image data are associated with each other via the date and time data indicating the date and time when the data was collected. Therefore, the corresponding image data can be extracted from the determination basic data other than the image data. For example, the corresponding image data can be extracted from the peak of the waveform of the acceleration data.

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

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

[First modification of the first embodiment]
Next, a first modification 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 using the acceleration data and the sound data collected by the microphone together to determine whether or not the vehicle has passed the unevenness of the road surface.

By using the acceleration data and the sound information together, it is possible to determine the presence or absence of unevenness on the road surface with higher accuracy. Furthermore, information on the shape and magnitude of the unevenness of the road surface can be obtained from the loudness and frequency (spectrum) of the sound.

[Second variant of the 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 the process executed by the controller 20 of the data collection device 1 according to the second modification of the first embodiment. Hereinafter, the difference from the flowchart of the process executed by the controller 20 of the data collection device 1 according to the first embodiment shown in FIG. 4 will be described.

In the second modification, by analyzing the collected image data between step ST01 and step ST02 of the first embodiment, the section in which the vehicle is traveling is uneven due to factors other than deterioration of the road surface. A process (step ST11) for determining whether or not the section in which is occurring is added. When the traveling section is not a section in which unevenness is generated due to a factor other than deterioration of the road surface, it is determined whether or not the passage of unevenness on the road surface is detected (step ST02). This determination process and the subsequent process are the same as the process according to the first embodiment.

When the traveling section is a section in which unevenness is generated due to a factor other than deterioration of the road surface, the controller 20 skips the process (step ST02) of determining whether or not the passage of unevenness on the road surface is detected. , Judgment 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 the camera 15 (FIG. 2). There is a "under construction" sign on the side of the road. When the controller 20 analyzes the acquired image data and detects a signboard under construction, it recognizes that the road ahead is under construction. Whether or not the section under construction has been passed can be determined from the condition of the road surface in the image data. 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 the section under construction is approached to the time when the section under construction is passed.

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

In the section under construction of the road, the road surface is uneven due to, for example, the surface layer of the road being cut to expose the lower roadbed. This unevenness is caused by a factor other than deterioration of the road surface, and even if the data collecting device 1 detects this unevenness, it is not necessary to determine whether or not repair is necessary. In the second modification, by excluding the unevenness that does not need to be repaired from the detection target, it is possible to suppress excessive detection of the unevenness. As a result, it is possible to suppress the consumption of the recording capacity of the SD card 22 due to unnecessary basic determination data. Since the total amount of recorded data is reduced, the amount of data to be analyzed when determining the 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, as a section in which unevenness is generated due to a factor other than deterioration of the road surface, for example, a section in which unevenness is generated due to construction work may be used. In addition, a section in which a step is generated at the joint portion of the place where the excavation work is performed, a step due to the edge of the manhole, a section in which a step is present at the joint portion of the bridge, etc. may be included. The seams of the places where the excavation work was performed, the edges of manholes, the seams of bridges, etc. should be detected by analyzing the image data.

In the third modification shown in FIG. 6A, when it is determined that the controller 20 is traveling in a section where unevenness is generated due to a factor 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 variant of the 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 the process 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 determines the type of road surface currently being traveled by analyzing the image data acquired by the camera 15 (FIG. 2) (step ST21). The controller 20 changes the second determination threshold value At2 (FIG. 5) for detecting the unevenness of the road surface according to the type of the 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 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 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 At2 is set for block pavement. Set to a value (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 supply of power to the data collection device 1 is stopped, the controller 20 stops the process. When continuing the process, the controller 20 repeats the process from step ST21. This iterative process may be executed, for example, in a fixed cycle, for example, in a 1-second cycle.

7B, 7C, and 7D are diagrams showing an example of images acquired while traveling on the road surfaces of asphalt pavement, concrete pavement, and block pavement, respectively. As shown in FIG. 7C, on the road surface of the concrete pavement, there are seams having a width of about 1 cm at intervals of, for example, 5 m to 10 m. On the road surface of the block pavement, as shown in FIG. 7D, for example, a unique pattern consisting of a plurality of paved blocks appears. 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 a seam or a unique pattern by image analysis.

Next, the excellent effect of the third modification of the first embodiment will be described.
The acceleration (impact) received by the vehicle depends on the type of road surface on which the vehicle is traveling. By changing the second determination threshold value At2 according to the type of the road surface, it is possible to appropriately determine the presence or absence of unevenness according to the type of the road surface. For example, while traveling on a block paved road surface, the impact of the unique pattern of the blocks is continuously applied to the vehicle. A second determination threshold value At2 may be set so as to exclude the magnitude of the impact due to this unique pattern from the target of unevenness detection. When the road surface is concrete pavement, it is preferable to set a second determination threshold value At2 so that the magnitude of the impact applied to the vehicle due to the seam is excluded from the target of unevenness detection. By setting the second determination threshold value At2 in this way, it is possible to prevent excessive detection of unevenness that is not the target of repair.

In the third modification of the first embodiment, the second determination threshold value At2 is different depending on the type of road surface, but in addition, the second determination threshold value At2 is set depending on the road type, for example, a general road and an expressway. It may be different. By doing so, it becomes possible to more appropriately determine the presence or absence of unevenness on general roads and expressways. In addition, depending on the type of road on which the vehicle is traveling, it is advisable to collect basic determination data when the traveling speed of the vehicle exceeds the threshold value.

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

[Fourth variant of the first embodiment]
Next, a fourth modification of the first embodiment will be described with reference to FIGS. 8A to 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. Hereinafter, the difference from the flowchart of the process executed by the controller 20 of the data collection device 1 according to the first embodiment shown in FIG. 4 will be described.

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

FIG. 8B is a diagram showing an example of an image when traveling on a road surface paved with steps. As an example of intentionally provided stepped pavement, there is one for suppressing the traveling speed and calling attention by giving a sound or vibration to the driver of the traveling 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, the regions 94 coated with the aggregate are periodically arranged in the traveling direction. By detecting the region 94 to which the aggregate is applied from the image data, the controller 20 can determine whether or not the step pavement intentionally provided on the road surface is formed.

In the third modification, it is possible to prevent a point where the step paving that is intentionally provided is made as a candidate for a point where a step to be repaired is generated.

Information that identifies a point where a stepped pavement that 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 pre-registered intentionally provided stepped pavement point.

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

[Fifth variant of the first embodiment]
Next, a fifth modification of the first embodiment will be described with reference to FIGS. 9A to 9C.
In the fifth modification of the first embodiment, the controller 20 stores the collection position data that specifies the place where the determination basic data that is the basis for determining whether or not the road or the road accessory needs to be repaired should be collected. There is. The collected position data may be acquired, for example, by the controller 20 receiving from an external device via the communication circuit 21 (FIG. 2). Alternatively, the controller 20 may acquire the data by reading the collection position data recorded on the SD card 22. The controller 20 stores the acquired collection position data in the RAM 20c (FIG. 2).

The collection position data is data in the format of specifying the point (data collection point) where the basic judgment data should be collected, and the data in the format of specifying the start point and end point of the section (data collection section) where the basic judgment data should be collected. Includes at least one of. The controller 20 periodically determines whether or not the current position of the vehicle is near the data collection point and whether or not it is within the data collection section. When the current position of the vehicle is near 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 the place where the determination basic data 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 the process executed by the controller 20 of the data collection device 1 according to the fifth modification of the first embodiment. Hereinafter, the difference from the flowchart of the process executed by the controller 20 of the data collection device 1 according to the first embodiment shown in FIG. 4 will be described.

In the fifth modification, instead of the process of step ST02 of FIG. 4, the controller 20 determines whether or not the current position of the vehicle is the place where the determination basic 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 place where the determination basic data should be collected, and when the data collection flag is reset, the vehicle Judge that the current position of is not the place where the judgment basic data should be collected.

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

FIG. 9B is a diagram showing an example of a data collection section. In FIG. 9B, the data collection section 80 is shown by a thick solid line. The vehicle departs from the depot 83, travels on a route including a predetermined data collection section 80, and then returns to the 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 the vehicle reaches the end point 82, the data collection flag is reset. As a result, the determination basic data is constantly recorded on the SD card 22 during the period in which the vehicle is traveling in the data collection section 80.

FIG. 9C is a diagram showing an example of a data collection point. At least one data collection point 85 is preset. The vehicle departs from the depot 83, passes the data collection point 85, and then returns to the depot 83. When the vehicle is located in the vicinity region 86 (the portion shown by the thick solid line in FIG. 9C) of the data collection point 85, the controller 20 sets the data collection flag. Therefore, the controller 20 records the determination basic data on the SD card 22 in the vicinity region 86 of the data collection point 85.

Next, the excellent effect of the fifth modification of the first embodiment will be described.
In the fifth modification of the first embodiment, the determination basic data is recorded on the SD card 22 at the place where the determination basic data should be collected, regardless of the presence or absence of the peak of the acceleration data. Therefore, when the road surface is deteriorated so that a remarkable peak does not appear in the acceleration data, the image data of the deteriorated point can be recorded. The presence or absence of deterioration of the road surface may be determined 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.

Further, 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, the amount of consumption of the memory space of the SD card 22 can be reduced as compared with the case where the determination basic data is recorded on the SD card 22 on all the routes traveled by the vehicle. Further, when analyzing the collected basic judgment data, the amount of basic judgment data to be analyzed is reduced, so that the time required for the analysis process can be shortened.

As the data collection point 85 (Fig. 9C), it is advisable to register a point where deterioration of the road surface is observed but repair is not immediately necessary. By regularly collecting the basic judgment data at this point, the progress of deterioration can be continuously observed.

The vicinity region 86 of the data collection point 85 (FIG. 9C) takes into consideration the position error obtained by the GPS receiver 14 (FIG. 2) and the difference between the current position of the vehicle and the position of the road surface photographed by the camera 15. Therefore, it may be defined so that the road surface of the data collection point 85 can be photographed.

The controller 20 may have 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 is equal to or less than the reference distance. The driver of the vehicle can know that the vehicle is approaching the data collection point 85. As a result, preparations for collecting basic judgment data can be started.

Further, the controller 20 stores the standard value of the traveling speed when passing through the data collection point 85, notifies that the vehicle is approaching the data collection point 85, and informs the driver of the vehicle of the standard value. It is good to have a function to encourage the vehicle to run at the running speed. The driver of the vehicle
It can be noticed that it is necessary to drive at the standard value before traveling at the data collection point 85. As a result, it is possible to suppress the occurrence of a situation in which the data collection point 85 deviates significantly from the standard value and the collected basic determination data cannot be effectively used.

For the vehicle approaching the data collection point 85 and the standard value of the traveling speed, for example, it is preferable to output sound from the speaker 16. As a result, the driver can notice the notified information without diverting his / her line of sight.

[Sixth variant of the 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 records the determination basic data on 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 determination basic data is recorded on the SD card 22 only at the place where the determination basic 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 determination basic data.

The mode for constantly recording the basic judgment data is referred to as the "constant recording mode", and the mode for recording the basic judgment data when the unevenness is detected is referred to as the "event recording mode". The controller 20 stores one of the constant recording mode and the event recording mode as the default mode. When the user does not perform the mode switching operation, the data collection device 1 operates in the specified mode. When the user operates the operation buttons 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. Hereinafter, 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.

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

FIG. 10B is a diagram showing an example of a route for recording basic determination data. After the vehicle departs from the depot 83 and travels on 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 the sections of the route traveled from the departure of the depot 83 to the return.

Next, the excellent effect of the sixth modification will be described. By setting the data collection device 1 to the constant recording mode, it is possible to collect basic determination data for determining the necessity of repairing the road or road accessories for all the routes traveled by the vehicle. As a result, basic judgment data is collected in a wider area. If the basic judgment data collected at the past time when no abnormality was found is accumulated at the point where the abnormality is found on the road or road attachment, the basic judgment data collected at the past time is used together. Then, it is possible to analyze the time and cause of the abnormality.

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

[7th modification of the 1st 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 process is executed, for example, between each of step ST02, step ST03, and step ST04 of the first embodiment shown in FIG. 4 and step ST05. In the seventh modification, after step ST02, step ST03, and step 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, the state of the road surface in the image data is analyzed, and the state of the road appendage in the image data is analyzed. The controller 20 determines whether or not the road surface and road accessories need repair based on the analysis result (step ST62). For example, the controller 20 detects cracks in the road surface, deterioration of road markings, poor drainage function of the road after rain, corrosion and deformation of road accessories such as road signs and guardrails, signs of landslides, and harmful effects of roadside trees. do.

When the controller 20 determines that the road surface or the road accessory needs to be repaired, the controller 20 records the image data and other determination basic data on the SD card 22 (step ST63). After recording the determination basic data, step ST05 of the flowchart shown in FIG. 4 is executed. When the controller 20 determines that the repair of the road surface or the road accessory is not necessary, the controller 20 executes step ST05 of the flowchart shown in FIG. 4 without recording the determination basic data on the SD card 22.

11B and 11C are drawings showing an example of an image in which the controller 20 determines that the road surface or road attachment needs to be repaired. In the example shown in FIG. 11B, a fractured portion 90 is confirmed in a part of the guardrail. In the example shown in FIG. 11C, a part of the road sign 91 is hidden by the roadside tree 92 so that the driver cannot see it.

Next, the excellent effect 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 manager should see as compared to the case where the road manager looks at all the images acquired while driving and finds out the part that needs repair. Is less. Therefore, it is possible to reduce the burden on the road manager for checking the image. Further, even when an abnormal portion is overlooked by human eyes, the controller 20 can detect the repair-required portion to reduce the oversight of the repair-required portion.

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

The controller 20 uses the SD card to obtain the image data acquired by the second camera in addition to the image data acquired by the first camera 15 in steps ST03 and ST04 (FIG. 4) of the first embodiment. Record at 22.

Next, the excellent effect of the eighth modification of the first embodiment will be described. In the eighth embodiment, not only the front of the vehicle but also the road surface directly under the vehicle can be photographed. Based on the image data of the road surface directly under the vehicle recorded on the SD card 22, the state of the road surface can be observed in more detail.

A second camera may be used to photograph the rear of the vehicle. In this way, the first camera 15 and the second camera can obtain images of the road appendages viewed from different directions. As a result, it is possible to improve the accuracy of determining whether or not the road attachment needs to be repaired.

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

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. The controller 60 as a 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 an application program are stored in the external storage device 66. The CPU 60a transfers the program stored in the external storage device 66 to the RAM 60c and executes it, thereby realizing various functions of the road condition evaluation support device 50. Further, the RAM 60c is used as a temporary storage area when the CPU 60a executes a program.

The SD card 22 on which the basic determination data collected by the data collection device 1 (FIGS. 1 and 2) is recorded is attached to the SD card reader 63. The controller 60 has a function of reading the determination basic data recorded on the SD card 22 and storing it in the database 65. Further, the controller 60 has a function of accumulating the determination 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. In the database 65, the date and time data, the traveling speed data, the position data, the acceleration data, the angular velocity data, and the image data shown in FIG. 3A are stored in association with each other.

The controller 60 causes the display 61 to display a dialog prompting the user to input a command. The user of the road condition evaluation support device 50, for example, the 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 a process for a command given by the user, and displays the process result on the display 61.

Next, the process 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 image data acquired at a plurality of different dates and times at the specific point in chronological order.

FIG. 13 is a diagram showing an example of an image displayed on the display 61. The controller 60 extracts the image data of a specific point designated by the user from the database 65, and displays the image 70 of the image data acquired by the camera 15 (FIG. 2) at a plurality of dates and times as information indicating the acquired date and time. It is displayed on the display 61 in chronological order together with the 71. The vertical direction of the displayed figure corresponds to the time series. In FIG. 13, as an example, July 5, 2016, 10:00:07, July 30, 2016, 11:12:47, August 26, 2016, 10:15:33, and October 8, 2016, 10:00. An example of displaying the image 70 of the same point acquired at 43 minutes and 9 seconds is shown.

Further, the controller 60 extracts the acceleration data associated with the displayed image data from the database 65, and displays the time waveform 72 of the extracted acceleration data on the display 61 so that the correspondence with the image 70 can be identified. For example, the time waveform 72 of the acceleration data is displayed next to the image 70. As the time waveform of the acceleration data to be displayed, for example, the acceleration data in the vertical direction of the vehicle may be adopted. Further, the time waveforms of the acceleration data in the vertical direction, the front-rear direction, and the left-right direction of the vehicle may be color-coded and displayed in an overlapping manner. The 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 is acquired. As the identification mark 73, for example, a broken line extending in the vertical direction may be used.

When the road manager moves the identification mark 73 in the time axis direction, the controller 60 switches the displayed image to the image corresponding to the time specified by the identification mark 73.

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

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

FIG. 14 is a diagram showing an example of an image of the evaluation value displayed on the display 61 over time. The controller 60 causes the display 61 to display the change with time of the evaluation value in a graph format. The horizontal axis of the graph represents the date and time, and the vertical axis represents the evaluation value. The evaluation values from the past to the present are displayed with solid lines, and the fluctuation prediction of future evaluation values is displayed with broken lines. The value of the evaluation value when the height difference of the unevenness reaches the size to be repaired is expressed as TE. The controller 60 can recognize the position where the evaluation value is TE, for example, displays a broken line at the position where the evaluation value is TE. In the example shown in FIG. 14, the evaluation value increases with the passage of time. This means that the height difference of the unevenness of the road surface increases with the passage of time. The controller 20 predicts future fluctuations in the evaluation value based on the slope of the fluctuation in the past evaluation value.

Next, with reference to FIG. 15, a process of displaying the time waveform 72 of the image 70 and the acceleration data shown in FIG. 13 will be described.

FIG. 15 is a diagram showing the relationship between the time waveform of the acceleration data and the date and time and the position where the time 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 a point in the vicinity thereof from the position data stored in the database 65. do. The date and time when the specific point L0 is passed is t0. The peak P is detected from the time waveform A of the extracted acceleration data. Image data corresponding to the date and time t1 when the acceleration peak P is detected (for example, one frame F of the moving image) is extracted from the database 65, and the image 70 of the image data corresponding to the date and time t1 and the acceleration peak P are obtained. The time waveform 72 of the period before and after the inclusion is displayed on the display 61. The point L1 where the peak P appears does not always match the point L0 input by the user due to an error in calculating the position data by the GPS receiver 14.

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

[Effect of the second embodiment]
The road administrator can check the progress of deterioration of the road or road attachment by looking at the image 70 (FIG. 13) displayed in chronological order. As a result, it is possible to determine whether or not repair is necessary and to predict when repair will be required. Further, by looking at the displayed image 70, it is possible to determine whether or not it is necessary to continuously observe the deterioration state of the displayed point. When it is determined that continuous observation is necessary, the image 70 displayed in time series becomes effective information for determining the frequency of observation.

The road administrator has various specific points for displaying an image on the display 61, for example, a point where it is determined that the road surface has irregularities based on acceleration data, a point where continuous observation is performed, and various other points. It is advisable to enter points that are predicted to need repair due to factors.

The road administrator can identify the magnitude of the impact applied to the vehicle when passing through the point by looking at the time waveform of the acceleration data displayed on the display 61. The magnitude of the impact can be used as information for identifying the height difference of the unevenness generated on the road surface. From the time waveform of the acceleration data displayed in time series, it is possible to know the progress of deterioration such as unevenness occurring on the road surface.

Acceleration data collected at a specific point designated by the road administrator can be found by referring to the position data associated with the acceleration data. This position data is acquired by, for example, the GPS receiver 14, and a position measurement error occurs due to various factors. For this reason, it is difficult to accurately match the acquired positions of each of the plurality of time waveforms of the traveling acceleration data collected at different dates and times from the position data alone.

In the second embodiment, the controller 60 detects the peak P (FIG. 15) of the time waveform of the acceleration data, so that the position where each of the plurality of time waveforms of the acceleration data collected at different dates and times is acquired is set. It can be matched accurately. As a result, the impact generated due to the unevenness at the same point can be evaluated in chronological order, and the image data at a specific point can be accurately extracted based on the collection date and time of the acceleration data.

The degree of future deterioration can be estimated from the change over time (FIG. 14) of the evaluation value depending on the unevenness of the road surface at a specific point. From the estimated degree of deterioration, it is possible to predict when repairs should be performed.

Since the change with time of the evaluation value is displayed in a graph format (FIG. 14), the road manager can visually recognize the speed of deterioration of the evaluation value. Changes in future assessments shown in the graph of FIG. 14 can be used as useful information for determining when to repair a road or road appendage.

The controller 60 may have a function of predicting when repairs are likely to be required at a plurality of candidate repair locations, averaging the repair work timings so that they are not concentrated, and displaying the recommended repair work time 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 when it is determined that recollection is necessary, the controller 60 may transmit a signal prompting recollection to the data collection device 1. For example, when the traveling speed at a point determined to have unevenness is outside the specified speed range, a signal prompting the driver of the vehicle equipped with the data collection device 1 to drive again at the specified speed. It is good to send.

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

In the second embodiment, the road administrator specifies a specific point where the image data should be displayed, but in the first modification of the second embodiment, the controller 60 has a function of extracting the unevenness occurrence point. 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. In the menu screen, the uneven point extraction button 76 for instructing the extraction of the uneven point is displayed. By selecting the uneven point extraction button 76, the road administrator causes the controller 60 to execute the process of extracting the uneven points.

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

FIG. 16B is a diagram showing an example of an image displayed on the display 61 by the controller 60. Time waveforms suggesting that the waveform has passed through the unevenness are extracted at different dates and times, and the time waveforms of the extracted accelerations and the date and time data and position data corresponding to the peaks of the time waveforms are displayed. .. Further, a time-series display button 77A for instructing the time-series display and a detailed inspection registration button 77B for registering as a continuous observation target point are displayed.

When the road administrator specifies one of the time waveforms of the plurality of accelerations and selects the time series display button 77A, the controller 60 determines the other date and time at the point where the peak of the specified time waveform is detected. The time waveform of the acceleration data acquired in the above, the image data, and the like are displayed on the display 61 in chronological order. The image to be displayed is, for example, the same as the image shown in FIG.

When the road administrator specifies one of the time waveforms of the plurality of accelerations and selects the detailed inspection registration button 77B, the controller 60 performs a detailed inspection at the point where the peak of the specified time waveform appears. Register as a target point. The controller 60 stores, for example, information indicating a point registered as a detailed inspection target point in an external storage device 66.

When the road administrator operates the input device 62 to input a command for displaying 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 determines the date and time data information, the image of the image data, and the acceleration data shown in FIG. 13 for the selected detailed inspection target point. The time waveform is displayed on the display 61 in chronological order.

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

The data collection device 1 that has acquired the information for specifying the detailed inspection target point may have a function of notifying the driver that the vehicle has approached the detailed inspection target point when the vehicle approaches the detailed inspection target point. For example, it is advisable to output a voice message from the speaker 16 (Fig. 2), "1 km away, the point to be inspected in detail. Please carry out the detailed inspection."

Next, the excellent effect of the first modification of the second embodiment will be described.
In the first modification of the second embodiment, based on the acceleration data accumulated in the database 65, it is possible to extract the points where the road surface is considered to have irregularities without human intervention. This makes it possible to process a huge amount of acceleration data.

In the first modification of the second embodiment, the unevenness was detected based on the peak value of the time waveform of the acceleration data, but the shape of the time waveform, the magnitude relationship of the acceleration in the three directions of front, back, left, right, up and down, etc. Based on this, a time waveform suggesting that the vehicle has passed the unevenness of the road surface may be extracted. For example, when sudden braking is applied to the vehicle, a large acceleration is generated in the front-rear direction. When the driver suddenly operates the steering wheel, a large acceleration is generated in the left-right direction. On the other hand, when the vehicle passes through the unevenness of the road surface, a large acceleration is generated in the vertical direction. The controller 60 may use the difference in the direction of the generated acceleration to extract points where unevenness is considered to exist on the road surface. Further, the time waveform of the acceleration data corresponding to sudden braking, sudden steering, etc. changes more slowly than the time waveform of the acceleration data corresponding to the passage of the unevenness of the road surface. The controller 60 may use this difference in the shape of the time waveform to extract points where unevenness is considered to exist on the road surface.

It is particularly preferable that the controller 60 uses information other than the acceleration data in order to extract a time waveform suggesting that the vehicle has passed the unevenness of the road surface. The controller 60 may use, for example, the traveling speed of the vehicle as information other than the acceleration data. For example, due to the impact when opening and closing the door of the vehicle, a peak appears in the time waveform of the acceleration data, but the traveling speed at this time is almost 0. By using the traveling speed data together with the determination of whether or not the vehicle has passed the unevenness of the road surface, the peak of the time waveform of the acceleration data generated by opening and closing the door can be excluded from the detection target.

When the controller 60 detects a point where unevenness is considered to exist, and if the peak of the waveform of the acceleration data is not detected at the same point before and after that point, it is preferable not to extract that point as the unevenness generation point. .. This is because such a point is considered to be a place where unevenness is temporarily generated due to a small obstacle such as a pebble.

The controller 60 may have a function of obtaining the inclination of the vehicle based on the angular velocity data and detecting a point where an abnormal inclination occurs on the road surface. It is advisable to find the point where the angular velocity data is analyzed based on the underground condition of the road. For example, it is advisable to determine the point at which the angular velocity data is analyzed based on the information that a large cavity exists underground during subway construction. 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 inclination of the road surface in consideration of the underground state of the road.

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

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

In the second embodiment, the judgment basic data acquired from one data collection device 1 (FIGS. 1A, 1B, 2) mounted on a specific vehicle, for example, a work vehicle of a road management company, is dealt with. In the second modification, the determination basic data is acquired from the data collection device 1 mounted on each of the plurality of vehicles.

FIG. 17A is a diagram showing an example of a 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. Further, 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 the vehicle type and the conversion coefficient. This correspondence is stored in the external storage device 66 in advance, for example. In the example shown in FIG. 17B, the conversion coefficients x1, x2, and x3 are associated with the 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 differs depending on the vehicle on which the data collection device 1 is mounted. In the second modification of the second embodiment, the controller 60 has a function of normalizing the acceleration data based on the 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. As the feature amount that characterizes the time waveform of the acceleration data, for example, the height of the peak appearing in the time waveform, the distribution of the frequency component of the time waveform, and the like may be used. The controller 60, for example, multiplies the feature amount of the time waveform of the actually measured acceleration data by the conversion coefficient of the vehicle type of the vehicle on which the data collection device 1 that has acquired the acceleration data is mounted. 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, it was acquired by the data collection device 1 mounted on each of a plurality of vehicles having different vehicle types. It becomes possible to compare acceleration data with each other.

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

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

[Third variant of the second embodiment]
Next, with reference to FIG. 18, the road condition evaluation support device 50 according to the third modification of the second embodiment will be described. In the second modification of the second embodiment, the conversion coefficient is set for each vehicle type as shown in FIG. 17B. On the other hand, in the third modification of the second embodiment, the conversion coefficient is set for each vehicle type and for each traveling speed. The controller 60 has a function of normalizing the acceleration data based on the vehicle type and the traveling speed. "Normalization" means converting acceleration data actually collected at various different running speeds into acceleration data that would have been obtained if running at standard speeds. As the standard speed, for example, the legal speed of the traveling route or a speed slightly slower than the legal speed may be adopted.

FIG. 18 is a diagram showing an example of the correspondence between the vehicle type, the traveling speed, and the conversion coefficient. For example, the conversion coefficient x11 is associated with the vehicle type A01 and the traveling speed v1. The controller 60 mounts the data collection device 1 on the vehicle of vehicle type A01, and multiplies the characteristic amount of the time waveform of the acceleration data acquired when traveling at the traveling speed v1 by the conversion coefficient x11 to normalize the acceleration data. To become.

Even if the shape and depth of the unevenness of the road surface are the same, if the traveling speed of the vehicle equipped with the data collection device 1 is different, the magnitude of the acceleration measured by the data collection device 1 is also different. The controller 60 normalizes the acceleration data based on the vehicle type and the traveling speed, so that the acceleration data collected at different traveling speeds can be compared with each other.

The conversion coefficient can be calculated in advance by mounting the data collecting device 1 on the vehicle and collecting acceleration data by passing through the unevenness at various traveling speeds.

If the actual running speed deviates significantly from the standard speed, it may be difficult to determine an appropriate conversion factor. A conversion coefficient is not associated with such a traveling speed in the correspondence list shown in FIG. The controller 60 may exclude acceleration data obtained at a traveling speed to which a coefficient related to z is not associated with the determination target of the presence or absence of unevenness.

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

In the fourth modification of the second embodiment, the controller 60 determines the degree to which the road surface needs to be repaired based on the image data stored in the database 65, and determines the determination result as image data, acceleration data, and 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 instructs the input device 62 (FIG. 12) to execute a process of determining the degree of need for repair, the controller 60 analyzes the image data stored in the database 65. By doing so, the degree of need for repair at various points is calculated. For example, artificial intelligence technology by deep learning may be used to calculate the degree of need for repair.

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

FIG. 19A is a diagram showing an example of an image displayed on the display 61. Information for identifying a point determined to be repaired and the degree to which repair is required are displayed side by side on the display 61 in a list format. As information for identifying the point where repair is determined to be necessary, for example, road name, address, latitude / longitude information, etc. may be displayed. Further, an image display button 78 is displayed corresponding to each point. FIG. 19A shows an example in which an abnormality having a degree of need for repair of 10 occurs at a point of Δ△△ in XX streets, for example. When the road administrator selects the image display button 78 corresponding to this point, the controller 60 displays an image of the point of XX streets △△△.

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

FIG. 20 is a diagram showing another example of an image displaying a point determined to require repair. The controller 60 displays a map including a plurality of points determined to require repair, and displays an icon on the map at the points determined to require repair so that the degree of need for repair can be recognized. For example, a circled number may be used as the icon. The numbers created in the past in circles indicate the degree to which repairs are needed. The points that need repair may be colored differently depending on the degree of need for repair.

Next, the excellent effect of the fourth modification of the second embodiment will be described.
In the fourth modification of the second embodiment, the degree to which the road and road accessories need to be repaired can be determined without human intervention, so that it is possible to deal with a huge amount of image data. It will be possible. The road administrator who sees the information displayed on the display 61 can easily find a point having a high degree of urgency from a plurality of points requiring repair.

Using the data of the road maintenance management plan, it is advisable to exclude the points where the renewal time (repair time) of the road itself is near from the candidates that need repair.

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

In the fourth modification of the second embodiment, the controller 60 displays the position information of the point requiring repair on the display 61 so that the degree of need for repair at that point can be recognized. In the modified example, the controller 60 causes the display 61 to display the point where the repair is necessary so that the magnitude of the reduction in the life cycle cost of the road due to the repair can be identified.

FIG. 21 is a diagram showing an example of an image displayed on the display 61. The information that identifies the point where repair is determined to be necessary is associated with the amount of decrease in the life cycle cost of the road due to the repair, and the display 61 is sorted by the amount of decrease in the life cycle cost and displayed in a list format. It is displayed. As information for identifying the point where repair is determined to be necessary, for example, road name, address, latitude / longitude information, etc. may be displayed. Further, an image display button 79 is displayed corresponding to each point. FIG. 21 shows that, for example, the reduction in the life cycle cost of the road due to the repair of the points of XX streets is 20,000,000 yen. When the road administrator selects the image display button 79 corresponding to this point, the controller 60 displays the image of this point on the display 61.

Next, the excellent effect of the fifth modification of the second embodiment will be described. The road administrator can easily find the repaired part where the life cycle cost is greatly reduced by looking at the image displayed on the display 61. By repairing in order from the place where the decrease in the life cycle cost of the road due to the repair is large, it is possible to suppress the increase in the life cycle cost of the road as a whole.

For example, it is advisable to detect that the degree of damage has begun to increase rapidly from the transition of the degree of damage to road attachments. By repairing while the degree of damage is low, it is possible to suppress an increase in repair costs.

FIG. 21 shows an example in which the points determined to be repaired are displayed in a list format together with the reduction in the life cycle cost. However, as shown in FIG. 20, a map is displayed on the display 61. An icon may be displayed at a point requiring repair according to the magnitude of the decrease in life cycle cost. Alternatively, instead of the icon, the points on the road that need repair may be colored according to the magnitude of the reduction in the life cycle cost.

[Sixth variant of the second embodiment]
Next, the road condition evaluation support device 50 according to the 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 determining the necessity of repairing the road appendage by analyzing the image data stored in the database 65. When the road administrator instructs the input device 62 (FIG. 12) to execute the process of determining the necessity of repairing the road attachment, the controller 60 receives the image data stored in the database 65. By performing the analysis, it is determined whether or not the road attachments at various points need to be repaired. The controller 60 is displayed on the display 61. Further, the controller 60 registers the determination result in the database 65 in association with the image data, the acceleration data, the position data, the date and time data, and the like.

For example, deterioration of road markings, poor drainage function of roads after rain, corrosion and deformation of road accessories such as road signs and guardrails, signs of landslides, harmful effects of roadside trees, etc. are taken up as targets for repair of road accessories. It is good. For example, artificial intelligence technology by deep learning may be used to determine the necessity of repair. If the color of a part of the guardrail is different from the surrounding color, for example, if a part of the white guardrail is discolored to brown, it can be determined that there is a high possibility that corrosion has occurred in that part. In this way, it is possible to determine whether or not the road attachment needs to be repaired based on the spatial color change.

Road inspections include initial inspections performed when roads are opened, daily inspections performed as normal work, regular inspections performed about once a year, and emergency inspections performed after a disaster occurs. The controller 60 may perform inspections on daily inspection items based on, for example, basic determination data stored in the database 65.

Further, the controller 60 has a function of determining the necessity of repairing road accessories based on the difference between a plurality of image data collected at a plurality of different dates and times at the same point.

22A to 22C are diagrams showing examples of image data collected at a plurality of different dates and times at the same point. In the example shown in FIG. 22A, the maximum speed limit sign 95 is visually recognized without being hidden by the roadside trees. In the example shown in FIG. 22B, since the roadside tree 96 has grown from the time of FIG. 22A, a part of the maximum speed regulation sign 95 is hidden by the roadside tree 96, but it can be confirmed that the maximum speed is 40 km / h. be. In the example shown in FIG. 22C, since the roadside tree 96 has grown further, most of the maximum speed regulation sign 95 is hidden by the roadside tree 96, and it cannot be confirmed that the maximum speed is 40 km / h.

The controller 60 detects the growth of the roadside tree 96 and the state where the maximum speed limit sign 95 is hidden by the roadside tree 96 by obtaining the difference between the images of FIGS. 22A, 22B, and 22C. Can be done.

In addition, it is possible to recognize how small scratches generated on the road attachment grow larger with the passage of time. In this way, it is possible to determine whether or not the road attachment needs to be repaired based on the change in the image over time.

Next, the excellent effect of the sixth modification of the second embodiment will be described. In the sixth modification of the second embodiment, it is possible to determine whether or not the road attachment needs to be repaired without human intervention. This makes it possible to process a huge amount of image data.

The controller 60 can recognize the progress speed of deterioration of the road appendage by the difference of the image data. By considering the progress rate of deterioration of road appendages, it is possible to more appropriately determine the necessity of repairing road appendages. For example, it is possible to more appropriately determine the necessity of repair based on the speed at which the color of road markings fades, the speed at which scratches on road attachments grow, and the speed at which roadside trees grow. It will be possible.

Regarding road accessories, it is advisable to determine in advance the points to be analyzed with priority in order to determine the necessity of repair. For example, guardrails, guard cables, guardrail support foundations and anchors, guardrail bolts and nuts, etc. may be registered as priority analysis points. For example, it is advisable to have artificial intelligence using deep learning technology analyze the image of the priority analysis part with priority and determine the necessity of repair.

By analyzing the image data acquired after the rain, it is possible to easily detect the failure of the drainage function of the road and the occurrence of rutting. Whether or not it is raining can be determined by the operation of the wiper transferred to the image data. For example, when the wiper shifts from the operating state to the stopped state, it may be determined that it is raining.

After a guerrilla rainstorm, rainwater on the road surface may not be drained even if the drainage function is normal. Therefore, after the guerrilla rainstorm, it may not be possible to determine whether or not the drainage function is normal. Whether or not it is a guerrilla rainstorm can be determined based on the operating speed of the wiper, the degree of smoke in a distant landscape, and the like.

Image data, date / time data, and position data collected from many data collection devices 1 may be stored as big data. Based on this big data, it is possible to know the time zone and area where it rained.

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

In addition, by evaluating the 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 a relatively light object floats and a heavy object sinks. The controller 60 has a function of comparing the current image with the past image and detecting whether the image is floating or sinking to determine whether or not liquefaction may have occurred. good. In particular, it is advisable to determine the presence or absence of liquefaction by comparing the image before the earthquake with the image after the earthquake.

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

Furthermore, it is advisable to register areas where landslides are likely to occur as targets for image data collection, based on information from land observation technology satellites.

[7th modification of the 2nd embodiment]
Next, the road condition evaluation support device 50 according to the 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 attachment needs to be repaired from the plurality of data collection devices 1 via the communication device 64 (FIG. 12). Receives basic determination data to be performed and identification data for identifying the data collection device 1.

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

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

FIG. 23B is a diagram showing an example of the cumulative value of points given to each data collection device 1. For example, 1,000 points are given to the data collecting device 1 whose identification data is identified by ABC00001.

Next, the excellent effect of the seventh modification of the second embodiment will be described. In the seventh modification of the second embodiment, since the controller 60 receives the data via the communication device 64 (FIG. 12), it is possible to save the trouble of obtaining the data. Further, since data is received from a plurality of data collection devices 1, a larger amount of data can be collected as compared with the case where data is obtained from one data collection device 1. For example, it is preferable to mount the data collection device 1 not only on the work vehicle of the road management company but also on the personally owned vehicle of the employee of the road management company to obtain these data. It is even better to mount the data collection device 1 on an unspecified general vehicle to obtain these data.

Further, 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 that does not have the data collection device 1, it is a motivation to install the data collection device 1. This makes it possible to accumulate a larger amount of data in the road condition evaluation support device 50. As a privilege, for example, a discount on toll road tolls, a discount when purchasing products at a roadside station, etc. may be used.

Points may be given to each general citizen's group such as neighborhood associations and residents' associations. It is advisable to give rewards for providing information to organizations that have accumulated a lot of points.

The controller 60 may have a function of transmitting information for identifying an area requiring an emergency inspection (area requiring an emergency inspection) to a plurality of data collecting devices 1 due to a disaster or the like. The area requiring emergency inspection may be input by the road administrator by operating the input device 62.

The data collecting device 1 that has received the information for identifying the area requiring emergency inspection 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 area requiring emergency inspection. The road condition evaluation support device 50 has a function of accumulating 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 area requiring emergency inspection, the road administrator can obtain an image of the area requiring emergency inspection without going to the area requiring emergency inspection. This enables a quick response to a disaster.

It is further preferable to mount the data collecting device 1 on a flying device such as a multicopter operated by a general user so as to transmit an aerial image of an area requiring emergency inspection 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 ordinary vehicles, medium-sized vehicles, and large vehicles. The impact of large vehicles on pavement is said to be about 10,000 times that of small vehicles on pavement. If the ratio of vehicle classification of vehicles passing through the road is different, the degree of progress of deterioration of the road surface is also different. When the data collection device 1 is installed in almost all vehicles in Japan, the number of passing vehicles for each road can be calculated for each vehicle category based on the data acquired from the data collection device 1.

When estimating the impact of passing vehicles on the road surface, it is advisable to reflect the number of vehicles for each vehicle category. For example, it is advisable to convert the traffic of one large vehicle into the traffic volume of 10,000 ordinary vehicles and estimate the effect on the road surface. The impact on the road surface, which reflects tolls for each vehicle category, provides useful information for predicting when road repairs will be needed.

Although various aspects of the present invention have been described above with reference to Examples and Modifications, the description of these Examples and Modifications has not been made for the purpose of limiting the technical scope of the present invention. It should be added that it is provided to contribute to the understanding of the present invention. The technical scope of the present invention is not limited to the configurations expressly described herein, and the present specification also includes other inventions obtained by combining various aspects of the invention described. Disclose. The applicant of the present application has specified the constitution of the invention for which a patent is sought in the present invention in the appended claims, but the present invention has not been specified in the claims and the present specification. The invention including at least one component disclosed in the document is also intended to be included in the claims in the future.

The invention of the present application is not limited to the configuration described in the above-mentioned "mode for carrying out the invention". A new invention may be constructed by arbitrarily selecting and combining the components included in the above-described examples and modifications. In addition, any component of each embodiment or modification, and any component described in "Means for Solving the Problem" or any component described in "Means for Solving the Problem" are embodied. It is possible to make a new invention by arbitrarily combining the above-mentioned components. The applicant of the present application also intends to acquire the rights to these new inventions in the amendment or divisional application of the present application.

For example, the present specification discloses an invention of a program for realizing a function as a data collection device 1 according to a first embodiment and various modifications of the first embodiment in a mobile terminal. Further, the present specification discloses an invention of a program for realizing a function as a road condition evaluation support device 50 according to a second embodiment and various modifications of the second embodiment on a computer.

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

1 Data collection device 3 Front glass 4 Room mirror 5 Cigar socket 6 Power cable 10 SD card insertion slot 11 Display 12 Operation button 13 Joint rail 14 GPS receiver 15 Camera 16 Speaker 17 Accelerometer 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 75 Evaluation Value button 76 Concavo-convex point extraction button 77A Time series display button 77B Detailed inspection registration button 78, 79 Image display button 80 Data collection section 81 Data collection section start point 82 Data collection section end point 83 Vehicle base 85 Data collection point 86 Data collection point Areas near 87 Route 90 Guard rail breaks 91 Road signs 92 Road trees 93 Road surface irregularities 94 Areas coated with aggregate 95 Maximum speed regulation signs 96 Road trees

Claims (15)

Image data around the vehicle collected by the data collection device mounted on the vehicle, acceleration data indicating the magnitude of the acceleration applied to the vehicle, vehicle position data, and collection date and time data for which the data was collected are accumulated in association with each other. A road condition evaluation support device having a processing means for displaying images of the image data acquired at a plurality of different dates and times at specific points on a display means in chronological order based on the database. The road condition evaluation support device according to claim 1, wherein the processing means displays the time waveform of the corresponding acceleration data together with the image of the image data on the display means. The road condition evaluation support according to claim 1 or 2, wherein the processing means has a function of displaying a time waveform of the acceleration data showing a peak waveform as the acceleration data collected at the specific point on the display means. Device. The processing means obtains an evaluation value depending on the unevenness of the road surface at the specific point from each of the plurality of acceleration data collected at the specific point at a plurality of different dates and times, and obtains the evaluation value of the obtained evaluation value. The road condition evaluation support device according to any one of claims 1 to 3, which has a function of displaying a change with time on the display means. The processing means according to any one of claims 1 to 4, which has a function of extracting a time waveform suggesting that the vehicle has passed the unevenness of the road surface from the time waveform of the acceleration data stored in the database. Road condition evaluation support device. The database includes vehicle type data indicating the type of vehicle on which the data collection device was installed when the acceleration data was collected.
The road condition evaluation support device according to any one of claims 1 to 5, wherein the processing means has a function of normalizing the acceleration data based on vehicle type data. The database accumulates vehicle traveling speed data in association with the data collection date and time.
The road condition evaluation support device according to any one of claims 1 to 6, wherein the processing means has a function of normalizing the acceleration data based on the traveling speed data. The processing means determines the degree to which the road surface needs to be repaired based on the image data stored in the database, and the determination result is the image data, the acceleration data, the position data, and the collection date / time data. The road condition evaluation support device according to any one of claims 1 to 7, which has a function of being associated and registered in the database. The road condition evaluation according to any one of claims 1 to 8, wherein the processing means has a function of displaying information for identifying a point where repair of the road surface is necessary on the display means so that the necessary degree of repair can be recognized. Support device. Any of claims 1 to 9, wherein the processing means has a function of displaying the position information of a point where the road surface needs to be repaired on the display means so that the magnitude of the reduction in the life cycle cost of the road due to the repair can be identified. Road condition evaluation support device described in Crab. The road condition evaluation support according to any one of claims 1 to 10, wherein the processing means analyzes the image data stored in the database to determine the necessity of repairing road accessories. Device. One of claims 1 to 11, wherein the processing means has a function of determining whether or not repair of road accessories is necessary based on a difference between a plurality of the image data collected at a plurality of different dates and times at the same point. Road condition evaluation support device described in. Further, it has a communication means, and the processing means includes the image data, the acceleration data, the position data, the collection date / time data, and the data collection device collected by a plurality of data collection devices via the communication means. The road condition evaluation support device according to any one of claims 1 to 12, which has a function of receiving identification data to be identified, associating the data with each other, and storing the data in the database. The road condition evaluation according to any one of claims 1 to 13, wherein the processing means attaches points to each data collecting device according to the received image data and acceleration data, and stores the cumulative value of the points. Support device. A program for realizing the function of the road condition evaluation support device according to any one of claims 1 to 14 on a computer.

Images