JP6050415B2 - Road surface smoothness evaluation method - Google Patents

Description

  The present invention relates to a method for diagnosing road surface smoothness, and more particularly, to a method for detecting and evaluating road surface smoothness such as steps and unevenness.

  Ideally, the road surface should be a smooth surface. However, there is no road that maintains perfect smoothness, and in reality there are countless steps and irregularities. Such steps and irregularities are inevitably generated from the time of completion of the road, and the degree thereof increases with the frequency of use. In particular, on highways, strict road surface management is possible because not only the steps and irregularities that occur on the road surface greatly affect comfort while driving, but it also causes noise and interferes with safe operation. is necessary.

  The technology for measuring the road surface condition is roughly divided into a profile method and a response method. The profile method is a method for actually measuring unevenness (profile) in the vertical direction of the road surface. The response method is a method of measuring the smoothness of the road surface based on a dynamic response (acceleration) received from the road surface. The most common method of measuring the road surface state by the response method is a method of measuring vertical acceleration and integrating the measured acceleration in the vertical direction. However, when such a measurement method is used, there is a problem in that high detection accuracy cannot always be obtained with respect to road level differences and unevenness. This is because the accelerometer detects the acceleration according to the level difference or unevenness of the road surface, but if the acceleration when the level difference or unevenness is relatively small and the acceleration when relatively large, the acceleration change is significant between the two This is because no occurs. That is, when the vehicle is actually traveled on the road, fine steps and irregularities are continuous on the road surface, so that the accelerometer mounted on the vehicle always detects acceleration. For this reason, even if a relatively large step or unevenness is overcome, a large acceleration change is unlikely to appear. As a result, high detection accuracy cannot be obtained for road surface steps and unevenness.

  In Japan, there is an MCI (Maintenance Control Index) developed by the Ministry of Construction (currently the Ministry of Land, Infrastructure, Transport and Tourism) as an index for evaluating the smoothness of the road surface. As an index with an emphasis on, IRI (International Roughness Index), which has realized ride comfort evaluation and reproducibility based on information calculated from road surface unevenness, has attracted attention. Although these are not classified, as a technique for measuring the road surface condition, for example, Patent Document 1 includes a laser range finder that measures the height to the road surface at three locations along the traveling direction of the automobile. A technique for measuring the shape of the road surface by fluctuation of one intermediate distance measurement value with respect to a reference line connecting two distance measurement values before and after the laser distance measurement device is disclosed. Patent Document 2 also collects measurement data using an accelerometer located on the axle side of the test vehicle, an accelerometer located on the vehicle body side supported by the suspension, and a GPS receiver for measuring the running speed of the test vehicle. A technique for calculating an IRI (International Roughness Index) is disclosed.

  On the other hand, the current road surface smoothness management is performed from the viewpoint of a road administrator on how to repair the structural destruction of the road, and does not necessarily reflect the position of the road user. In particular, since there are many complaints regarding articles affected by vibration and impact such as precision machinery accompanying truck transportation, a smoothness standard that considers the transported goods is necessary. In addition, the current criteria for determining smoothness abnormalities are for a small portion of a number of road surface shapes, and a number of abnormal locations remain in the repairs based on these criteria. And the smoothness management that the same force is applied to the force applied to the vehicle, the force applied to the load, the passenger car, the truck, the front part and the rear part of the vehicle is the actual situation.

JP 2012-173095 A JP 2010-066604 A

  The present invention has been made in view of the above-described conventional problems, and an object of the present invention is to experience the road surface condition of a road where a step or unevenness is generated using a load sensor mounted at a predetermined position of the vehicle. It is providing the road surface smoothness evaluation method evaluated along.

  The road surface smoothness evaluation method according to one aspect of the present invention made to achieve the above object is to run a vehicle equipped with a load sensor that measures a vertical load by applying a gravitational load with a weight of a predetermined weight. A method for evaluating the smoothness of a road surface, the step of recording the output of a load sensor when the vehicle is stopped when the gravity load is applied as a stationary load, and the output of the load sensor while the vehicle is applied with the gravity load. Recording as a dynamic load at predetermined sampling time intervals, recording position information during traveling of the vehicle corresponding to the recording time of the output of the load sensor during traveling of the vehicle, and based on the position information Determining a segment section of the road surface corresponding to a predetermined segment time interval, determining a rate of change of the dynamic load value during traveling of the vehicle with respect to the static load value, and during traveling of the vehicle Obtaining a maximum rate of change for each predetermined segment time interval from the rate of change, and a predetermined value set corresponding to any one or more of a vehicle type, a load sensor mounting position, and an evaluation target Setting a segment segment of the road surface corresponding to a segment time interval having a specific maximum rate of change value among the maximum rate of change for each segment time interval as a specific evaluation interval based on a reference value; Visualizing the evaluation interval by a graph or a list.

The reference value for setting the specific evaluation section can be set as a value corresponding to the maximum change rate when the evaluation value determined based on the sensation of a plurality of persons is equal to or higher than a predetermined determination ratio.
The step of setting the segment section of the road surface as a specific evaluation section includes a road surface corresponding to a segment time interval having a maximum change rate value exceeding a predetermined first reference value among the maximum change rates for each segment time interval. The segment interval is set as a first evaluation interval, and the segment time interval having a maximum rate of change exceeding a predetermined second reference value greater than the first reference value among the maximum rate of change for each segment time interval Setting a corresponding road segment segment as a second evaluation segment.
The road surface smoothness evaluation method may further include a step of recording a rate of change of the dynamic load value with respect to the static load value in association with the position information.
The road surface smoothness evaluation method further includes visualizing the first evaluation section and the second evaluation section in association with the recorded position information, and visualizing the first evaluation section and the second evaluation section. Can be displayed on a map showing segment segments of the road surface including the recorded position information.
The road surface smoothness evaluation method further includes the step of visualizing a value of a rate of change in a predetermined section of the value of the dynamic load with respect to the value of the static load in association with a sampling time for each sampling time interval, Visualization of the change rate of the load value can be performed by a two-dimensional graph having an axis indicating the sampling time and an axis of the change rate value at the sampling time.
The road surface smoothness evaluation method further includes visualizing the value of the maximum rate of change for each segment time interval in association with the rank of the value of the maximum rate of change for each segment time interval, wherein the visualization of the maximum rate of change is And a two-dimensional graph having an axis indicating the rank of the maximum rate of change value for each segment time interval and an axis of the maximum rate of change value for each segment time interval.
The road surface smoothness evaluation method further includes a step of recording a peripheral image specifying a segment section of the road surface corresponding to at least the segment time interval in association with position information during vehicle travel, and the visualization includes the segment of the road surface This may be performed together with the peripheral image display that specifies the section.

  According to the road surface smoothness evaluation method of the present invention, a dynamic force applied to a 60 kg heavy object of the same weight as that of the body weight is measured according to the level difference or unevenness of the road surface, and the determination by a plurality of judges By adopting the evaluation criteria based on the correlation, the smoothness of the road surface along the bodily sensation can be evaluated.

It is a schematic diagram which shows the vehicle for implementing the road surface smoothness evaluation method by one form of this invention. It is a disassembled perspective view of the sensing apparatus by one Embodiment. It is sectional drawing of the sensing apparatus shown in FIG. It is a schematic block diagram of the road surface state measuring apparatus by one Embodiment. It is a block diagram which shows the structure of the personal computer (PC) shown in FIG. 4 and a peripheral device. It is a figure which shows the output of the load sensor unit explaining the relationship between the static load fs, the dynamic load fd, and the impact force Pimp. It is a figure which shows an example of the content of the database after the analysis produced | generated based on the collection data of a road surface state measuring apparatus. It is a figure for demonstrating the dynamic load fd measured by the road surface state measuring apparatus. It is a figure for demonstrating the smoothness Ds measured by the road surface state measuring apparatus. It is a figure which shows an example of the graph display which makes a horizontal axis | shaft KP (kilo post) and a vertical axis | shaft dynamic load fd. It is a figure which shows an example of the change of the value of the dynamic load fd which measured the joint part of the driving lane of an expressway. It is a figure which shows an example of distribution of the smoothness Ds in the loading platform of a truck. It is a figure which shows an example of the determination result of the smoothness in a highway. It is a figure for demonstrating the evaluation criteria which used the determination result shown in FIG. It is a figure for demonstrating an example of conversion of the smoothness Ds of a vehicle type. It is a figure for demonstrating an example of conversion of the smoothness Ds of a vehicle type. It is a flowchart which shows the process of the road surface smoothness evaluation method by one Embodiment of this invention. It is a flowchart which shows the process which visualizes the value acquired by the road surface smoothness evaluation method.

  Hereinafter, a specific example of an embodiment for carrying out the road surface smoothness evaluation method of the present invention will be described in detail with reference to the drawings.

  The daily inspection of the expressway is carried out by visual inspection on the vehicle and on-vehicle sensation in order to determine whether necessary and appropriate measures and repairs are necessary, and get off the vehicle as necessary to check the state of deformation. Since the force applied to the body is equivalent to the force pushing the body as a reaction force, it corresponds to measuring body weight. The force applied to a person is equivalent to the force applied to the same weight as the weight. If the weight is 60 kgf, it is equivalent to the force applied to the 60 kg weight.

  FIG. 1 is a schematic diagram showing a vehicle 11 for carrying out a road surface smoothness evaluation method according to an embodiment of the present invention.

  As shown in FIG. 1, in order to measure the state of the road surface 2 of the road 1, for example, the vehicle 11 having the road surface state measuring device 101 mounted on the loading platform 12 travels on the road surface 2 to be measured. When the vehicle 11 passes through a step 3 or an unevenness (not shown) generated on the road surface 2, the road surface state measuring device 101 outputs a measured value in response thereto. There is no need to prepare a special vehicle 11, and any vehicle such as a general passenger car, a light vehicle, a wagon, a light van, or a truck can be used. Further, the road surface state measuring device 101 is not limited to the loading platform 12 and can be installed on the seat 13 or on the floor 14 of the vehicle, for example. However, in general, since the flatness evaluation differs between the front, middle, and rear mounting positions of the vehicle, the mounting positions of the vehicle and the road surface state measuring device 101 must be in accordance with the measurement purpose. For example, the road surface condition measuring device 101 should not be mounted on the passenger seat of a truck in order to measure the flatness of the truck bed with respect to the cargo.

  FIG. 2 is an exploded perspective view of the sensing device 112 according to an embodiment, and FIG. 3 is a cross-sectional view of the sensing device shown in FIG.

  As shown in FIG. 2, the sensing device 112 provided in the road surface state measuring device 101 houses a sensor base 116 having a built-in strain gauge type load cell in a frame-shaped holding base 117, and places a weight 113 on the sensor base 116. Structure. The sensor base 116 is a structure incorporating a load sensor using a strain gauge type load cell. The load cell is a converter that converts a force (load) into an electric signal and outputs it, and a strain gauge type is generally used. Other than the strain gauge type using electric resistance, there are a magnetostrictive type, a capacitance type, a gyro type and the like.

  A weight 113 is placed on the sensor base 116. For example, one weight 113 is formed with a weight of 15 kgf. In the present embodiment, four weights 113 are placed on the sensor base 116. Accordingly, a total load of 60 kgf by the weight 113 is applied to the sensor base 116. Since the weight 113 is divided into four parts, it is easy to carry and handle.

  As shown in FIG. 3, in the sensing device 112, a sensor base 116 on which four weights 113 are placed is directly mounted on the cargo bed 12 or the like via a rubber pad 121. Accordingly, when the vehicle 11 on which the sensing device 112 on which the four weights 113 are mounted on the sensor base 116 is run, vibration is transmitted to the vehicle 11, so that the load due to vibration is constantly applied to the sensor base 116 by the weight 113. The change is transmitted.

  The positions of the individual weights 113 are fixed so that the four weights 113 move integrally by vibration transmitted from the vehicle 11. As an example, the fixing of the positions of the individual weights 113 forms a concave and convex fitting structure on the upper surface of the weight 113 positioned below and the lower surface of the weight 113 stacked thereon.

  FIG. 4 is a schematic configuration diagram of a road surface state measuring device according to an embodiment, and FIG. 5 is a block diagram showing configurations of a personal computer (PC) and peripheral devices shown in FIG.

  As shown in FIG. 4, the road surface state measuring apparatus 101 includes a combination of a sensing device 112 including a sensor base 116 with a built-in strain gauge type load cell, a personal computer (PC) 131, a GPS unit 151, and a web camera 141. A sensor base 116 provided in the sensing device 112 measures a vertical load. The sensing device 112 applies a gravitational load to the sensor base 116 with a weight 113 having a predetermined weight. Thereby, when the vehicle is stationary, the sensor base 116 outputs an electrical signal corresponding to the weight of the weight 113, for example, 60 kgf. The output of the sensor base 116 is sent to the personal computer 131 via the measuring circuit 114. The weighing circuit 114 amplifies an analog electric signal output from the sensor base 116, converts the signal into a digital signal, and outputs the digital signal. The personal computer 131 refers to the digital signal output from the weighing circuit 114 and recognizes the load value applied to the sensor base 116. The sensor base 116 and the weighing circuit 114 constitute a load sensor unit 115 (see FIG. 5). Load measurements can be recorded directly using a data logger. In this case, only the load measurement value and the measurement time are sequentially recorded, and after the measurement is completed, the measurement data is analyzed to generate other data. Even when the personal computer 131 is used, only the load measurement value and the measurement time are sequentially recorded and the measurement data is analyzed after the measurement is completed. However, the measurement data may be processed in real time according to the processing capability of the personal computer.

  As shown in FIG. 5, the sensing device 112 is configured by connecting a load sensor unit 115 and a GPS unit 151 to a personal computer 131. The personal computer 131 is mainly composed of a microcomputer 135 in which a ROM 133 and a RAM 134 are connected to a CPU 132 that executes various arithmetic processes. The ROM 133 is, for example, an EEPROM, and stores fixed data such as BIOS. The RAM 134 stores various variable data in a rewritable manner. The microcomputer 135 is connected to a hard disk drive (HDD) 136, a display unit 137 such as a liquid crystal display, and an input unit 138 including a keyboard and a pointing device to constitute a personal computer 131. The HDD 136 is installed with a computer program for measuring the road surface condition, and various data relating to the road surface condition measurement are stored as a database. When the program is activated, all or part of the program is copied to the work area of the RAM 134, and the CPU 132 accesses the RAM 134 and executes processing according to the program. Further, when the database is created by the activated program, the CPU 132 creates a database associated with the road surface state measurement and stores it in the HDD 136, and stores data to be accumulated in the database in the work area of the RAM 134, and then sequentially. Stored in the database of the HDD 136.

  A load sensor unit 115, a web camera 141 (not shown) included in the input unit, and a GPS unit 151 are connected to the CPU 132 of the personal computer 131 so that data communication is possible. As described above, the load sensor unit 115 has a configuration in which the weighing circuit 114 is combined with the sensor base 116 provided in the sensing device 112. The Web camera 141 is a camera that can display a captured image in real time via a browser, and captures a surrounding image while the vehicle is traveling in order to identify a segment segment on the road surface. Instead of the Web camera 141, other video cameras that can be connected to a personal computer besides the Web camera 141 can be used. Based on the surrounding image of the Web camera 141 recorded in the personal computer 131 and the time information recorded at the same time, the segment section of the road surface on which the vehicle is traveling is specified. When specifying the segment section, for example, it is necessary to have an accuracy to know whether the point where vibration or impact was detected is a bridge joint or a pavement joint in front of it, and one segment 22m (when the speed is 80 km / hour, Since it is necessary to know which position is equivalent to the travel distance for 1 second), a peripheral image using a moving image is used. KP (kilo post) is also read during this process. The position information is acquired by analyzing the recorded video of the Web camera after the load measurement is completed in this way. The GPS unit 151 obtains coordinate information of the current position by calculation based on a signal from a GPS satellite received via the antenna 152, and transmits the coordinate information (coordinate data) to the personal computer 131. The position data acquired by the GPS unit 151 is used to display the measurement position on the map by collating with the map data. When position information can be acquired with high accuracy by combining D (differential) GPS and other navigation satellite systems, it is possible to measure in real time without analyzing the recorded video of the Web camera by combining map matching etc. it can. The personal computer 131 and the load sensor unit 115 are not limited to the above-described configuration, and can be embodied by various components so as to have the same function.

  In order to use the road surface state measuring apparatus 101, the road surface state measuring apparatus 101 is mounted on the vehicle 11, and the road 1 where the road surface 2 is to be measured is traveled. And the program for a road surface state measurement is started, and it drive | works on the road surface 2 which is a measuring object. The CPU 132 of the personal computer 131 executes a dynamic load acquisition process, a position information acquisition process, and a background process in parallel by a multitask process according to the activated program, and constructs a database associated with road surface state measurement. The dynamic load acquisition process and the position information acquisition process will be described later with reference to a flowchart showing the process of the road surface smoothness evaluation method in FIG.

  FIG. 6 is a graph showing the output of the load sensor unit for explaining the relationship between the static load fs, the dynamic load fd, and the impact force Pimp.

  The graph of FIG. 6 shows the measurement time (or position) on the horizontal axis and the load value on the vertical axis. As described above, when the weight of the weight 113 is 60 kgf, when the vehicle is stationary, the personal computer 131 recognizes a load of 60 kgf based on the output of the sensor base 116 taken from the weighing circuit 114. This load value is an output of the sensor base 116 in a state where only the gravity load of the weight 113 is applied. In the present specification, this is referred to as a static load fs.

  When the vehicle 11 travels on the road 1 and passes through the level difference 3 and the unevenness generated on the road surface 2, the sensor base 116 is pressed against the weight 113 by the push-up of the vehicle 11 generated at that time, so that the output value of the sensor base 116 is large. Become. Accordingly, the personal computer 131 recognizes a load having a value exceeding 60 kgf based on the output of the sensor base 116 taken in from the weighing circuit 114. In the present specification, this is referred to as a dynamic load fd.

  As shown in FIG. 6, the value of the dynamic load fd decreases after passing the peak. That is, the phenomenon that the value of the dynamic load fd increases when the vehicle 11 traveling on the road 1 passes through the step 3 and the unevenness generated on the road surface 2 and decreases when reaching the peak is repeated. In such a change curve of the dynamic load fd, the maximum dynamic load fm at the peak is referred to as an impact force Pimp in this specification.

  Referring to FIGS. 4 and 5 again, the personal computer 131 recognizes the change in the load value as shown in FIG. 6 by taking in the output of the sensor base 116 at predetermined sampling time intervals. The sampling time interval for accurately recognizing the change in the load value is preferably about 1/100 second when the traveling speed of the vehicle 11 is 80 to 100 km / hour. When this is converted into distance, the vehicle 11 is about 222 mm when the speed is 80 km / h, 250 mm when the speed is 90 km / h, and about 278 mm when the speed is 100 km / h. This substantially coincides with IRI (International Roughness Index) that defines a measurement interval of 250 mm or less. By defining the sampling time interval in this way, it is possible to accurately collect data of the impact force Pimp. On the other hand, when the output of the sensor base 116 is captured at a sampling time interval finer than 1/100 second, more abundant data of the dynamic load fd can be obtained, but for the purpose of obtaining data of the impact force Pimp. If you look at it, the amount of data will be excessive. Therefore, when the traveling speed of the vehicle 11 is 80 to 100 km / hour, it is best to capture the output of the sensor base 116 at a sampling period of 1/100 seconds.

  The personal computer 131 acquires position information from the GPS unit 151. The GPS unit 151 is equipped with a GPS (Global Positioning System) and obtains coordinate information of the current position by calculation based on a signal from a GPS satellite received via the antenna 152. The personal computer 131 takes in coordinate information of the current position from the GPS unit 151 at predetermined sampling time intervals, for example, every second while the vehicle is traveling. The acquired coordinate information is recorded as position coordinate data together with the output of the sensor base 116 in correspondence with the output of the sensor base 116 acquired at a sampling time interval of 1/100 second. At this time, the sampling time interval (1/100 second) of the data of the dynamic load fd obtained by the output of the sensor base 116 and the sampling time interval (about 1 second) of the coordinate information obtained from the GPS unit 151 are exactly It is not necessary to synchronize, and it is only necessary to correspond roughly. The position data acquired by the GPS unit 151 is used to display the measurement position on the map by collating with the map data.

  FIG. 7 is a diagram showing an example of the contents of the analyzed database generated based on the collected data of the road surface state measuring apparatus 101. As shown in FIG.

  As shown in FIG. 7, the database is based on data of “1/100 second value” and “dynamic load fd (kgf)” measured in real time every 1/100 seconds during vehicle travel, and analysis after measurement. Data of “1 second value”, “position coordinates”, “KP (kilo post)”, “change rate”, “smoothness Ds”, and “evaluation value” are recorded and accumulated as the obtained data of 1 second unit. . At this time, the personal computer 131 increments the value of 1/100 second, which is the sampling time interval for taking in the output of the sensor base 116, and sequentially records the value to “1/100 second value”, based on the output of the sensor base 116 at that time. Record the dynamic load fd in “dynamic load fd (kgf)”. “Position coordinates” are obtained by collating with map data based on changes in the captured image of the Web camera 141, time information, and dynamic load fd after the measurement is completed. When a road surface can be specified using a high-accuracy GPS unit 151 such as DGPS, the positioning data may be used as it is.

  “Change rate” is a ratio of a static load value and a dynamic load value at a predetermined sampling time interval, for example, every 1/100 second interval, that is, a change rate of a dynamic load value with respect to a static load value. . The personal computer 131 executes a process for obtaining a ratio between the value of the static load and the value of the dynamic load as the process of obtaining the rate of change of the value of the dynamic load with respect to the value of the static load. The ratio in this case is calculated as (dynamic load / static load). For example, when the static load is 60 kgf, the rate of change when the value of the dynamic load is 75 kgf is 1.25, and the rate of change when the value of the dynamic load is 90 kgf is 1.5. The personal computer 131 obtains the rate of change based on the value of the dynamic load obtained from the output of the sensor base 116, and records this in the “rate of change” in the database in association with the dynamic load fd as the basis. .

  “Smoothness Ds” is the maximum rate of change of the value of the dynamic load with respect to the value of the static load at a predetermined segment time interval, for example, every one second. That is, the personal computer 131 obtains the rate of change of the value of the dynamic load with respect to the value of the static load from the dynamic load / static load, and calculates the value of the maximum rate of change every 1 second interval. For example, if the static load is 60 kgf, the smoothness Ds when the maximum dynamic load value at the segment time interval is 75 kgf is 1.25, and the smoothness Ds when the maximum dynamic load value is 90 kgf is 1 .5. The personal computer 131 calculates the smoothness Ds based on the value of the maximum dynamic load for each segment time interval obtained from the output of the sensor base 116, and records this in the “smoothness Ds” in the database. In the present specification, the maximum value of the ratio of dynamic load / static load for each segment time interval is defined as smoothness (Ds: Degree of Smoothness) in the segment section.

  FIG. 8 is a diagram for explaining the dynamic load fd measured by the road surface state measuring device, and FIG. 9 is a diagram for explaining the smoothness Ds measured by the road surface state measuring device.

  Referring to FIG. 8, the road surface state measuring device 101 is installed on the passenger seat or the loading platform of the vehicle 11, the vehicle 11 is driven on the target road 1, the road surface state measuring program is started, and the static load fs 60 kgf is set. The output of the sensor base 116 using the weight 113 is used as a dynamic load fd (kgf), and the state of the road surface 2 is measured at predetermined sampling time intervals, that is, every 1/100 second interval.

  As shown in FIG. 9, the ratio between the dynamic load fd and the static load fs, that is, the rate of change of the dynamic load fd with respect to the static load fs is calculated by the dynamic load fd / static load fs. Maximum rate of change of dynamic load fd / stationary load fs per segment time interval, that is, the maximum value of (fd / fs) for one second is the segment section (corresponding to a traveling distance of 22 m for one second at a speed of 80 km / hour) Smoothness Ds (Degree of Smartness). The smoothness Ds is suitable for expressing a momentary large force, that is, an impact force, and is an index relating to riding comfort, cargo damage, and the like. For example, by continuously evaluating the smoothness Ds value for 5 seconds, it becomes an evaluation index of the incomfort of the riding comfort in the approximately 100 m section similar to IRI.

  FIG. 10 is a diagram showing an example of a graph display in which the horizontal axis is KP (kilo post) and the vertical axis is the dynamic load fd.

  As shown in FIG. 10, the CPU 132 reads the image taken by the Web camera 141 to obtain the KP (kilo post) of the highway, and takes the KP (kilo post) on the horizontal axis and the dynamic load value on the vertical axis. A graph can be displayed. The kilopost graph display makes it clear at a glance where and how the dynamic load fd or smoothness Ds shown on the vertical axis changes. For this reason, when inspecting the situation of the road surface 2 of the road 1 on site, the location of the site can be appropriately notified.

  “KP (kilo post)” is a marker position at regular intervals from a reference point. In this embodiment, the term KP (kilo post) is broad and may be a literally labeled position every 1 km, or may be a labeled position every 100 m, for example.

  As an additional function, using the Web camera 141 connected to the personal computer 131, the CPU 132 captures and records a peripheral image that identifies a segment section of the road surface on the map in association with the position information while the vehicle is traveling, and displays the graph. They can be displayed at the same time, and detailed local location information such as bridge joints can be obtained. It is also possible to support a function of changing the scale of the horizontal axis (time, KP).

  FIG. 11 is a diagram illustrating an example of a change in the value of a dynamic load fd obtained by actually measuring a joint portion of a driving lane on an expressway, and FIG. 12 is a diagram illustrating an example of a distribution of smoothness Ds in a truck bed. is there.

  As shown in the graph of FIG. 11, as an example of measurement of a joint part with a lot of impact, a joint of Shintomei Expressway Gotenba JCT to Shin-Fuji IC up lane using a 3-ton truck that is considered to have little road surface wear. The actual measured value (kgf) in the part was obtained. The tendency of impact force differs between the front wheel (passenger seat) and the rear wheel (loading platform) of the truck. There is no clear peak at the front wheel, but there is a clear peak at the rear wheel. Therefore, it can be seen that there is no impact even if it is experienced at the front wheel position, but there is a large impact if it is experienced at the rear wheel position.

  12 (a) and 12 (b) show a 3t truck bed 12 in which the smoothness Ds calculated for each segment section of the entire Tomei Expressway between Tokyo IC and Kasugai IC is statistically arranged in order from largest to smallest. FIG. 12A shows a segment distribution having a road surface smoothness Ds of 1.8 or more as an evaluation standard (first evaluation standard) value of “abnormal”. FIG. 12B shows a segment distribution having a road surface smoothness Ds of 2.4 or more as an evaluation criterion (second evaluation criterion) value of “special abnormality”.

  The evaluation of the smoothness Ds of “abnormal” and “special abnormality” is based on the ranking of the smoothness Ds actually measured by installing the road surface state measuring device 101 on the floor surface of the microbus and the ride on the microbus at that time. It was determined based on the evaluation values determined as “abnormal” and “bad”. Based on the experience, each person “raises arms up: bad, measures needed”, “arms up sideways: abnormal, investigation needed”, “ Signaled with “arm down: acceptable”, the road surface state measurement device 101 installed on the floor measures the road surface state and records the position information, and at the same time, the state of the judge is captured and recorded by the video camera. It was performed by analyzing. Since there was a clear correlation between the determination based on the bodily sensation and the statistically arranged smoothness Ds, an evaluation criterion was set based on the determination based on the bodily sensation. In the case of three judges, one person's judgment excluding both extremes was adopted. In this specification, the evaluation based on “feel” means evaluation based on the on-vehicle sensation of a person who actually gets on the traveling vehicle. On-vehicle sensations include not only vibration and impact sensations, but also visual and auditory sensations, so in addition to load sensors, for example, by analyzing camera shake and vibration / impact sounds, the `` feel '' can be further enhanced. It is also possible to obtain evaluation results along the way.

  FIG. 13 is a diagram illustrating an example of a smoothness determination result on an expressway, and FIG. 14 is a diagram for explaining an evaluation criterion using the determination result illustrated in FIG.

  As shown in FIG. 14, the flatness between Oi Matsuda IC and Numazu IC on the Tomei Expressway was measured on the floor surface on the rear wheel axle of the microbus, and “bad” judgment exceeded 60% when Ds> 1.8. The total of “bad” determination and “abnormal” determination accounted for about 50% when Ds> 1.5. More than 50% of the “bad” judgments are at the boundary of the “bad” sensory evaluation values, and Ds> 1.8, and the ratio of “abnormal” + “bad” judgments exceeds 50%. Is the boundary of the sensory evaluation value of “abnormal”, and it is understood that Ds> 1.5. Here, the evaluation value is “special abnormality”> “abnormal”> “acceptable” in the descending order of Ds, and the corresponding determination value is “bad”> “abnormal”> “acceptable”.

  FIG.15 and FIG.16 is a figure for demonstrating an example of conversion of the smoothness Ds of a vehicle classification.

  As shown in FIGS. 15 and 16, the evaluation values based on the actual experience differ depending on the type of vehicle, the mounting position of the load sensor, the evaluation object, and the like. As shown in FIG. 15, the conversion value corresponding to the boundary value of the “abnormal” evaluation based on the respective sensations in the loading platform of the 3-ton truck, the loading platform of the microbus, and the loading platform of the patrol car (wagon type passenger car) is Ds = 1.8, Ds = 1.5 for microbuses, Ds = 1.3 for passenger cars. In addition, as shown in FIG. 16, the conversion values of the boundary values of the “bad” evaluations at the loading platform of the 3-ton truck, the loading platform of the microbus, the loading platform of the patrol car (wagon type passenger car) and the passenger seat are Ds = 2 .4, Ds = 1.8 for the microbus and Ds = 1.6 for the passenger car.

  As a result of the above examination, as a statistical evaluation of processing a large number of measured values, the evaluation standard of the loading platform (on the rear wheel shaft) of the 3 ton truck is “special abnormality” evaluation with Ds> 2.4. Is evaluated as “abnormal” when Ds> 1.8, and “abnormal” is evaluated in terms of experience. As a result of comparing the Ds values on the rear axle of a 3-ton truck, a patrol car (wagon-type passenger car), and a microbus, Ds on the truck bed in the passenger seat of the patrol car (wagon-type passenger car) It was found that cannot be estimated.

  FIG. 17 is a flowchart showing processing of the road surface smoothness evaluation method according to the embodiment of the present invention.

  As shown in FIG. 17, when the road surface state measuring device 101 is installed on the passenger seat or the loading platform of the vehicle 11, the vehicle 11 is stopped upon arrival at the target location, and the road surface state measuring program is started, first, S101. At this stage, the CPU 132 of the personal computer 131 measures the output of the sensor base 116 using the 60 kgf weight 113 taken from the load sensor unit 115 and records it in the database of the HDD 136 as the static load fs when the vehicle is stopped. The static load fs can be recorded in advance as a measured value.

  In step S102, the vehicle 11 is driven on the target road 1, and the output of the sensor base 116 using the 60 kgf weight 113 while the vehicle is running is used as the dynamic load fd (kgf) at every predetermined sampling time interval. Measure. As the dynamic load acquisition process, the CPU 132 acquires a dynamic load value from the load sensor unit 115 when a sampling period that defines a predetermined sampling time interval is reached. In this case, the sampling period is 1/100 second as exemplified above. When acquiring the dynamic load value, the CPU 132 increments the 1/100 second value, and the acquired dynamic load value together with the 1/100 second value is converted into “1/100 second value” and “dynamic load” in the database. Record. While the vehicle is running, “1/100 second value” and “dynamic load” are continuously recorded.

  In step S103, the CPU 132 obtains position information while the vehicle is traveling from the GPS unit 151 at predetermined segment time intervals. As position information acquisition processing, the CPU 132 acquires the position coordinates of the current position from the GPS unit 151 when a sampling period that defines a predetermined segment time interval is reached. The sampling period in this case is 1 second as exemplified above. The position data acquired by the GPS unit 151 is used to display the measurement position on the map by collating with the map data.

  After the measurement of the road surface condition, in step S104, the CPU 132 obtains a segment segment of the road surface corresponding to the segment time interval based on the position information acquired from the recorded video and time information of the Web camera 141. When the CPU 132 acquires the position coordinates, the CPU 132 matches the acquired position coordinates on a map stored in advance in the database of the HDD 136 to obtain a segment section of the road surface on which the vehicle is traveling, and the acquired position coordinates and the Web camera 141 The acquired KP is recorded in “position coordinates” and “KP (kilo post)” of the database.

  In step S105, the CPU 132 calculates the rate of change of the dynamic load fd with respect to the static load fs by the dynamic load fd / static load fs. The value of the calculation result is recorded in the “change rate” of the database in association with the “1/100 second value”. The CPU 132 may sequentially calculate the ratio between the dynamic load fd and the static load fs as a background process during the dynamic load acquisition process according to the processing capability while the vehicle is running.

  In step S106, the CPU 132 obtains the maximum rate of change for each predetermined segment time interval and calculates it as the smoothness Ds in the corresponding segment section. The CPU 132 acquires the maximum rate of change at each segment time interval of 1 second from the rate of change of the dynamic load fd with respect to the static load fs acquired at every sampling time interval of 1/100 seconds. When the CPU 132 acquires the value of the maximum change rate, the CPU 132 records the acquired dynamic load value in the “smoothness Ds” of the database in association with the “position coordinates”. The processing in steps S104 to S106 is continuously performed up to the position at which the CPU 132 received the end command and ended the recording data while the vehicle was traveling on the target road section.

  In steps S107 and S108, the CPU 132 determines whether or not the maximum rate of change for each segment time interval, that is, the smoothness Ds of a predetermined segment section exceeds a preset reference value. If the CPU 132 is equal to or smaller than the first reference value in step S107, the corresponding segment section is set as an “allowed” section in step S109 and recorded in the “evaluation value” of the database.

  If the maximum rate of change for each segment time interval exceeds the first reference value in step S107 and is equal to or lower than the second reference value in step S108 (where the first reference value is less than the second reference value), the CPU 132 executes S110. At the stage, the corresponding segment section is set as the “abnormal (abnormal)” section and recorded in the “evaluation value” of the database.

  When the maximum rate of change for each segment time interval exceeds the second reference value in step S108, the CPU 132 sets the corresponding segment section as a “special abnormality (bad)” section in step S111 and sets the “evaluation value” of the database. To record. After the processing of steps S107 to S111 is completed, in step S112, the CPU 132 visualizes the vehicle running data stored in the database on the display unit 137, which is a visualization device provided in the personal computer 131, with a graph or a list. indicate. Note that the CPU 132 may perform the processing from step S102 to step S112 in real time during traveling of the vehicle as the background processing during the dynamic load acquisition processing according to the processing capability.

  The CPU 132 of the personal computer 131 executes the above-described dynamic load acquisition process, position information acquisition process, and background process according to the road surface state measurement program, thereby sequentially storing road surface data to be measured in the database while the vehicle is traveling. The data is recorded and the database is completed by analysis processing after the measurement is completed. The program for measuring the road surface condition causes the personal computer 131 to execute a function of visualizing the change rate of the value of the dynamic load fd with respect to the value of the static load fs in association with the position information based on the generated accumulated data in the database. In addition, by installing a program for measuring the road surface condition and copying the data recorded in the HDD 136 of the personal computer 131 of the road surface state measuring apparatus 101 mounted on the vehicle 11, the road surface data is analyzed and visualized by another computer. Can also be performed. Hereinafter, the visualization process will be described with reference to the flowchart of FIG.

  FIG. 18 is a flowchart illustrating a process of visualizing values acquired by the road surface smoothness evaluation method.

  As shown in FIG. 18, the CPU 132 selects and designates the recorded contents of the road desired to be visualized from the database in the display unit 137 which is a visualization device in step S201, and selects and switches the visualization display method in step S202. The CPU 132 responds to the display selection switching in step S202, and in step S203, the horizontal axis indicates the sampling time of 1/100 second value and the vertical axis indicates the rate of change of the dynamic load value relative to the static load value via the display unit 137. A two-dimensional graph is displayed.

  The CPU 132 responds to the display selection switching in step S202, and in step S204, the horizontal axis indicates the segment interval corresponding to the segment time interval of 1 second via the display unit 137, and the vertical axis indicates the maximum change rate in the segment interval, that is, the smoothness Ds. A two-dimensional graph is displayed. The horizontal axis can be switched to kiloposs display. The smoothness Ds of the target section may be displayed by color coding or pattern so that the smoothness Ds evaluated as “abnormal (abnormal)” and “special abnormality (bad)” can be identified and identified. it can. When the smoothness Ds is displayed in different colors on the kilopost graph display, it is obvious where the repair is required, and the location of the repair can be effectively notified.

  In response to the display selection switching in step S202, the CPU 132 displays the road on the map via the display unit 137 and color-codes the evaluation sections of “abnormal (abnormal)” and “special abnormal (bad)” described above. It is displayed so that it can be identified and specified by a pattern or the like. When the evaluation section is displayed in different colors, it is obvious where the repair is required, and it is possible to effectively notify the repair location.

  In step S203 to step S205, the CPU 132 also performs a pop-up display of a running peripheral image corresponding to the vehicle travel time, superimposed on the graph display or the map display. Since the pop-up display is performed in a separate window from the graph display, more abundant information can be obtained. The display screen in steps S203 to S205 can be printed out by a printer (not shown).

  Finally, when the CPU 132 recognizes the end command (“N” in step S202), the process ends.

DESCRIPTION OF SYMBOLS 1 Road 2 Road surface 3 Level difference 11 Vehicle 12 Loading platform 13 Seat 14 Floor surface 101 Road surface state measuring device 112 Sensing device 113 Weight 114 Weighing circuit 115 Load sensor unit 116 Sensor base (built-in strain gauge type load cell)
117 Holding base 121 Rubber pad 131 Personal computer (PC)
132 CPU
133 ROM
134 RAM
135 Microcomputer 136 Hard Disk Drive (HDD)
137 Display unit (visualization device)
138 Input unit 141 Web camera 151 GPS unit 152 Antenna

Claims (6)

A method of evaluating the smoothness of a road surface by running a vehicle equipped with a load sensor that measures a vertical load by applying a gravity load with a weight of a predetermined weight,
Recording the output of the load sensor when the vehicle is stopped by applying the gravitational load as a static load;
Recording an output of a load sensor during traveling of the vehicle to which the gravity load is applied as a dynamic load at predetermined sampling time intervals;
Recording the position information during traveling of the vehicle in correspondence with the recording time of the output of the load sensor during traveling of the vehicle;
Obtaining a road segment segment corresponding to a predetermined segment time interval based on the position information;
Obtaining a rate of change of the value of the dynamic load during travel of the vehicle relative to the value of the static load;
Obtaining a maximum rate of change for each predetermined segment time interval from the rate of change during vehicle travel;
Recording the maximum rate of change for each predetermined segment time interval as the smoothness in the segment interval;
Based on a predetermined reference value set corresponding to any one or more of the vehicle type, the load sensor mounting position, and the evaluation target, a specific smoothness of the recorded smoothness Setting a road segment segment having a degree value as a specific evaluation segment having a specific evaluation value;
Visualizing the specific evaluation value and the specific evaluation section by a graph or a list,
The predetermined reference value for setting the specific evaluation section is:
The determined value of smoothness based on the plurality of persons experience in certain conditions of the one or more conditions are set as the evaluation reference value of the specific conditions,
The distribution of smoothness under the specific condition from the distribution of smoothness in all segment sections statistically shown by arranging the smoothness values in the segment sections of the road surface for each of the one or more conditions from the largest to the smallest The value of the smoothness of the position in the distribution of smoothness for each of the one or more conditions that becomes a ratio corresponding to the evaluation reference value for the specific condition in is set as the evaluation reference value for the one or more conditions And
The specific evaluation section having the specific evaluation value is set to a first evaluation section having a first evaluation value when the smoothness is less than a predetermined first reference value, and the smoothness is set to the first reference value. A second evaluation value having a second evaluation value when the value is greater than or equal to a value and less than a second reference value greater than the first reference value, and a third evaluation value when the smoothness is greater than or equal to the second reference value A road surface smoothness evaluation method, characterized in that the road surface smoothness evaluation method is set in a third evaluation section.
  The road surface smoothness evaluation method according to claim 1, further comprising a step of recording a rate of change of the value of the dynamic load with respect to the value of the static load in association with position information during traveling of the vehicle. Visualizing the second evaluation section and the third evaluation section in association with the recorded position information;
Wherein the visualization of the second evaluation interval and the third evaluation period, the road surface smoothness according to claim 1, characterized in that it is displayed on the map showing the road segment section containing the recorded position information Evaluation method. Visualizing a value of a rate of change of a predetermined section of the value of the dynamic load with respect to the value of the static load in association with a sampling time for each sampling time interval;
The visualization of the rate of change of the value of the dynamic load is performed by a two-dimensional graph having an axis indicating the sampling time and an axis of the value of the rate of change at the sampling time. Road surface smoothness evaluation method. Visualizing a statistical distribution of smoothness values calculated for each segment interval ;
Visualization of statistical distribution of the smoothness value, characterized in that is carried out by a two-dimensional graph having the axis of the value of the axis and the smoothness that arranged in the order of smaller value from greater value the value of the smoothness The road surface smoothness evaluation method according to claim 1. And further including the step of recording a peripheral image specifying a segment section of the road surface corresponding to at least the segment time interval in association with position information during vehicle travel,
The road surface smoothness evaluation method according to any one of claims 3 to 5 , wherein the visualization is performed together with a peripheral image display that specifies a segment section of the road surface.

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