JP7023825B2 - Electronics, methods and programs - Google Patents

Description

Embodiments of the present invention relate to electronic devices, methods and programs for inspecting road surfaces.

A road surface property measuring vehicle is used for inspecting the road surface. The road surface property measuring vehicle inspects the condition of the road surface by irradiating the road surface with a laser and measuring the reflected laser, or by taking a picture of the road surface with a camera and performing image analysis.

Japanese Patent Application Laid-Open No. 2003-57051

An object to be solved by an embodiment of the present invention is to provide electronic devices, methods and programs that can further simplify the inspection of road surfaces and reduce time and cost.

In order to solve the above problems, the electronic device of the embodiment is a first route information indicating a route including a position of the moving body, which is a route on which the moving body that automatically operates on the road surface is scheduled to travel, and the first route information. 1 Second route information that is a reference route when calculating route information and indicates a route including the position of the moving body, and a route that the moving body has traveled on the road surface and is the position of the moving body. Among the third route information indicating the route including the above, the processing unit for calculating the difference between the two routes from at least two route information and the estimation unit for estimating the state of the road surface from the difference between the routes are provided.

The road surface inspection system diagram in the 1st embodiment. The figure for demonstrating the reference route in 1st Embodiment. The figure for demonstrating the planned traveling route in 1st Embodiment. The figure for demonstrating the traveling route in 1st Embodiment. The block diagram of the moving body in 1st Embodiment. The flowchart of the moving body in 1st Embodiment. The block diagram of the electronic apparatus in 1st Embodiment. The flowchart of the electronic device in 1st Embodiment. The figure of the vertical acceleration measurement point of the moving body in 1st Embodiment. The figure in the case of presuming a crack from the deviation of the vertical acceleration in the 1st embodiment. The figure when it is estimated that the flatness is lowered from the deviation of the vertical acceleration in the 1st embodiment. The figure of the planned travel route and the travel route in the first embodiment. The figure of the reference route and the traveling route in 1st Embodiment. The figure of the planned travel route calculated at different time in 1st Embodiment. The conceptual diagram of the model of the deep learning which estimates the state of the road surface in 1st Embodiment.

Hereinafter, embodiments for carrying out the invention will be described.

(First Embodiment)
FIG. 1 is a road surface inspection system diagram according to the first embodiment. The moving body 200 may be any vehicle as long as it is a vehicle traveling on the road surface. For example, automobiles and motorcycles. The mobile body 200 of the present embodiment is an automobile that automatically drives. The mobile body 200 transmits the route information obtained when performing automatic operation to the electronic device 100. The electronic device 100 does not necessarily have to be provided in the vicinity of the moving body 200, but is provided at an arbitrary place. The electronic device 100 calculates the difference in the route information from the route information acquired from the mobile body 200. The electronic device 100 estimates the state of the road surface on which the moving body 200 is traveling using this difference, and outputs information including the state of the road surface and the position of the road surface to the electronic device. The output destination electronic device is, for example, a display, a desktop, a laptop, a tablet, a smartphone, or the like. As an example, FIG. 1 shows a road A, which is presumed to have deteriorated road surface, surrounded by a broken line and represented on a two-dimensional map B.

Next, the route information will be described. The route information is information indicating a route required when the mobile body 200 performs automatic operation. In the present embodiment, this route information is a planned travel route indicating a route on which the mobile body 200 is scheduled to travel, and a reference route (RP: Reference) indicating a reference route when the mobile body 200 calculates the planned travel route. Path), and refers to information on three routes of the travel route indicating the route traveled by the mobile body 200.

First, the reference route will be described with reference to FIG. The roadway 250, which is the subject of the road surface inspection, is represented here by two one-way lanes, and is separated by a white line 270. Of these, the lower traveling lane 260 shown by the broken line is the lane designated by the reference route so that the moving body 200 performs automatic driving. Hereinafter, the same applies to the roadways of FIGS. 3, 4, 9, and 12 to 14.

Next, the reference route will be described. The reference route is a reference route when the mobile body 200 calculates the planned travel route. The mobile body 200 receives the route information of the reference route from the holding device of the reference route (not shown). This holding device is, for example, a server, but may be an electronic device 100. In the present embodiment, this reference route is referred to as a reference route 300. The reference route 300 is composed of a sequence of points of a plurality of waypoints. That is, the information of the reference route 300 is the information of the relay point of the reference route 300. This relay point is represented by a black circle in FIG. At the relay point i of each reference route 300, the coordinates (x _Ri , y _Ri ) of the moving body 200 as a reference, the posture of the moving body 200 (θ _Ri ), and the speed of the moving body 200 (v). _Ri ) is defined. The mobile body 200 associates the current time with these relay points, and defines the relay point of the reference path 300 at the time _{ti as (x Rti ,} y _Rti , θ _Rti , v _Rti ).

The reference route 300 can be considered in various ways, but in the present embodiment, the reference route 300 is used, and in the section of the roadway 250, the route traveling in the center of the traveling lane 260 at the legal speed is used.

Further, in the present embodiment, in order to specify the relay point of the reference route 300, a time is added. For example, when specifying the relay point of the reference route 300 at the time t ₀ in FIG. 2, it is expressed as the relay point 300 t ₀ .

Next, the planned travel route will be described with reference to FIG. The planned travel route is a route on which the mobile body 200 is scheduled to travel, and in the first embodiment, the mobile body 200 calculates the route with reference to the reference route. In the present embodiment, this planned travel route is referred to as a planned travel route 400. The planned travel route 400 is also composed of a sequence of points of a plurality of relay points. That is, the information on the planned travel route 400 is the information on the relay point of the planned travel route 400. As an example of the planned travel route 400, for example, in FIG. 3, the moving body 200 is shifted to the right from the reference route 300 in the traveling direction at time _t0 . The mobile body 200 calculates each relay point of the planned travel route 400 so as to asymptotically approach the reference route 300.

In FIG. 3, the relay point of the planned travel route 400 is represented by a white circle. Similar to the relay point of the reference route 300, the relay point of the scheduled travel route 400 at time ti is defined as (x _Cti , _{y Cti} , θ _Cti , v _Cti ). In particular, (x _Cti , _{y Cti} ) represents a position where the moving body 200 is scheduled to travel at time ti, and the moving body 200 is driven toward this position. This position will also be referred to as the target position. As in the case of the reference route 300, the time is added to specify the relay point of the planned travel route 400. For example, when specifying a relay point of the planned travel route 400 at time t ₀ in FIG. 3, it is expressed as a relay point 400 t ₀ .

In addition, the steering amount ζ _C and the accelerator amount η _C for realizing the travel of the planned travel route 400 are calculated at the time when the planned travel route 400 is calculated. For example, when the moving body 200 calculates the planned travel route 400 at time t ₀ , the steering amount ζ _Ct 0 and the accelerator amount η _Ct 0 at time t ₀ are calculated together. It is assumed that these calculated steering amount ζ _C and accelerator amount η _C are included in the information of the planned travel route 400.

The steering amount represents the amount of turning the steering in order to turn the moving body 200, and is also expressed as the steering angle amount. The accelerator amount represents the amount of accelerating to accelerate the moving body 200, and is also expressed as the acceleration amount.

Next, the traveling route in the first embodiment will be described with reference to FIG. The traveling route is a route actually traveled by the moving body 200. The moving body 200 measures the coordinates, posture, speed of the moving body 200, the vertical upward acceleration of the moving body 200, the steering amount of the moving body 200, and the accelerator amount measured by a sensor or the like described later at regular intervals. Record as a travel route. In the present embodiment, this travel route is referred to as a travel route 500. The travel path 500 is composed of a sequence of measurement points. That is, the information of the traveling route 500 is the information of the measurement point of the traveling route 500. In FIG. 4, the traveling path 500 is represented by a white square.

The travel path 500 at time ti is the same as the relay point of the scheduled travel route 400 (x _Mti , _{y Mti} , θ _Mti , v _Mti , ₎ , and the vertical upward acceleration of the moving body 200 at time ti. α _Mti is defined in the travel path 500. Therefore, the measurement points of the travel path at time ti are defined as (x _Mti , _{y Mti} , θ _Mti , v _Mti , α _Mti ). In particular, (x _Mti , _{y Mti} ,) represents the actual position of the moving body 200 at time ti. This position will also be referred to as the measurement position. Similar to the case of the relay point of the reference route 300 and the planned travel route 400, the time is added to specify the measurement point of the travel route 500. For example, when specifying the measurement point of the traveling path 500 at the time _t0 in FIG. 4, it is expressed as the traveling path 500t ₀ .

Further, the moving body 200 is actually controlled by the steering amount ζ _M and the accelerator amount η _M based on the calculated steering amount ζ _C and the accelerator amount η _C. For example, when the steering amount ζ _Ct0 and the accelerator amount η _Ct0 are calculated at time _t0 , the moving body 200 actually controls the drive unit with the steering amount ζ _Mt0 and the accelerator amount η _Mt0 . It is assumed that these controlled steering amount ζ _M and accelerator amount η _M are included in the information of the traveling path 500.

Further, in addition to the traveling route 500, the image information of the road surface around the moving body 200 and the road surface around the moving body 200 obtained by the moving body 200 by analyzing this image get wet due to rainfall. There is image analysis information on whether or not there is unevenness due to snowfall. This information is also acquired at the same time as the measurement at the measurement point of the traveling route 500, and is transmitted from the mobile body 200 to the electronic device 100 together with the three route information.

Next, the configuration of the mobile body 200 in the first embodiment will be described with reference to FIG. The moving body 200 of the present embodiment automatically operates. The moving body 200 includes a receiving unit 201, a storage unit 202, a sensor unit 203, a traveling route acquisition unit 204 for acquiring a measurement point of a traveling route 500 which is a route traveled by the moving body 200, and a route on which the moving body 200 automatically operates. The route calculation unit 205, the transmission unit 206, the power calculation unit 207, the power control unit 208, the power unit 209, and the input unit 210 for calculating the relay point of the planned travel route 400 are provided. These configurations are realized by a semiconductor integrated circuit (LSI or the like) except for the power unit 209.

The receiving unit 201 receives the rough position information of the moving body 200 by the Global Navigation Satellite System (GNSS) and the route information of the reference route 300 from, for example, the electronic device 100. This rough position information is used by the sensor unit 203 to calculate the position of the moving body 200, and the reference route 300 is used by the route calculation unit 205 to calculate the relay point of the planned travel route 400. The receiving unit 201 sends this rough position information to the sensor unit 203, and sends the information of the reference route 300 to the route calculation unit 205. Further, the receiving unit 201 receives these information from the provided antenna.

The storage unit 202 holds information on the measurement points of the travel route 500 calculated by the travel route acquisition unit 204 and information on the relay points of the travel schedule route 400 calculated by the route calculation unit 205. Further, the storage unit 202 holds information used for calculating the relay point of the planned travel route 400 and the measurement point of the travel route 500. The storage unit 202 is an arbitrary device that holds information, and is, for example, a RAM, a ROM, an HDD, an SSD, or the like.

The sensor unit 203 has a sensor and measures data indicating the status of the moving body 200 at regular time intervals. For example, the position, speed, acceleration, etc. of the moving body 200. Further, the sensor unit 203 calculates the position of the moving body 200 from the rough position information of the moving body 200 received by the receiving unit 201 and the measured data. The position information of the moving body 200 includes coordinate information. Further, the sensor unit 203 can measure the state of obstacles existing around the moving body 200 from this sensor. For example, the outline of an obstacle or an image including this obstacle. These measurement information is used for calculating the measurement points of the travel route 500 calculated by the travel route acquisition unit 204 and for calculating the relay points of the travel schedule route 400 by the route calculation unit 205. The sensor unit 203 sends the measured information of these measurements to the travel route acquisition unit 204 and the route calculation unit 205. Further, the sensor unit 203 takes an image of the road surface of the traveling lane 260 in which the moving body 200 is traveling, and analyzes whether the road surface is wet and whether there is unevenness due to snowfall. This analysis information is used for estimating the road surface condition by the electronic device 100. The sensor unit 203 stores this analysis information in the storage unit 202. The sensor measured by the sensor unit 203 is, for example, a laser sensor, a millimeter wave sensor, a camera, an acceleration sensor, or the like.

The travel route acquisition unit 204 acquires the measurement point of the travel route 500 at the current time from the information sent from the sensor unit 203 and the information read from the storage unit 202. The travel route acquisition unit 204 causes the storage unit 202 to hold the measurement points of the acquired travel route 500.

The route calculation unit 205 asymptotically approaches the reference route 300 from the measurement point of the travel route 500 at the current time calculated from the information sent from the reception unit 201 and the sensor unit 203 and the information read from the storage unit 202. The relay point of the planned travel route 400 is calculated. The route calculation unit 205 causes the storage unit 202 to hold the relay point of the reference route 300 and the relay point of the planned travel route 400. Further, the route calculation unit 205 sends the planned travel route 400 at the calculated current time to the power calculation unit 207. The planned travel route 400 is used for calculating the steering amount and the accelerator amount by the power control unit 207. Further, the route calculation unit 205 causes the storage unit 202 to hold the image information and the image analysis information sent from the sensor unit 203.

The transmission unit 206 transmits three route information including a relay point of the reference route 300, a relay point of the planned travel route 400, and a measurement point of the travel route 500, image information, and image analysis information held in the storage unit 202 for a certain period of time. Each is transmitted to the electronic device 100. The transmission unit 206 transmits through the provided antenna.

The power calculation unit 207 calculates the steering amount ζ _C and the accelerator amount η _C of the moving body 200 from the planned travel path 400. ζ _C and η _C are sent to the power control unit 208, and are used to calculate the steering amount ζ _M and the accelerator amount η _M in which the power control unit 208 actually controls the power unit 209. Further, the power calculation unit 207 causes the storage unit 202 to hold the steering control amount and the accelerator control amount as information included in the traveling path 500.

The power control unit 208 corrects the steering amount ζ _C and the accelerator amount η _C calculated by the power calculation unit 207 in consideration of the response performance to the control input of the moving body 200, and corrects the steering amount ζ _M and the accelerator amount η _M. And. The response performance to this control input differs depending on the condition of the road surface. For example, on an uneven road surface, the wheels of the moving body 200 are taken by the uneven road surface, and it is difficult to turn the vehicle body, so that the steering is increased. The steering amount ζ _M and the accelerator amount η _M are sent to the power unit 209 to drive the moving body 200. Further, the power control unit 208 causes the storage unit 202 to hold the steering amount ζ _M and the accelerator amount η _M as information included in the traveling path 500.

The power unit 209 drives the moving body 200 according to the steering amount ζ _M and the accelerator amount η _M sent from the power control unit 208. For example, the power unit 209 is an automobile engine, a motor, wheels, and the like.

The input unit 210 receives an instruction input by the user. For example, the input unit 210 receives instructions for starting and ending the automatic operation of the mobile body 200 by the passengers of the mobile body 200.

Next, the operation flow of the mobile body 200 that transmits the route information to the electronic device 100 will be described with reference to FIG. First, the moving body 200 collects information for the route calculation unit 205 to calculate the measurement point of the traveling path 500 at the current time of the moving body 200 (step S101). That is, the receiving unit 201 receives the rough position information of the moving body 200 by the global navigation satellite system (GNSS: Global Navigation Satellite System) through the antenna and sends it to the sensor unit 203. The sensor unit 203 acquires information around the traveling lane 260 in which the moving body 200 is traveling. The surrounding information is, for example, an image taken by the sensor unit 203, information on the distance from the moving body 200 to an object (for example, an obstacle), and the like.

Further, the sensor unit 203 measures the speed, acceleration, and the like of the moving body 200, and calculates the position of the moving body 200 together with the rough position information. The sensor unit 203 sends this information to the travel route acquisition unit 204 and the route calculation unit 205. Further, the sensor unit 203 analyzes the image and acquires analysis information on whether the road surface of the traveling lane 260 in which the moving body 200 is traveling is wet due to rainfall and whether the road surface is uneven due to snowfall. The sensor unit 203 stores this analysis information in the storage unit 202.

Next, the travel route acquisition unit 204 acquires the measurement points of the travel route 500 at the current time (step S102). The travel route acquisition unit 204 acquires the measurement points of the travel route 500 from the information such as the position information of the moving body 200, the speed of the moving body 200, and the acceleration of the moving body 200 in the vertical upward direction acquired by the sensor unit. For example, when the current time is t ₀ , 500 t ₀ (x _Mt0 , y _t0 , θ _Mt0 , v _Mt0 , α _Mt0 ) is obtained. The travel route acquisition unit 204 causes the storage unit 202 to hold the information of the travel route 500.

The route calculation unit 205 determines whether the current time corresponds to the time for calculating the scheduled travel route 400 (step S103). This specific time is predetermined, but may be any time interval. If the current time is not the time for calculating the planned travel route 400 (step S103: No), the flow returns to step S101.

When the current time is the time for calculating the planned travel route 400 (step S103: Yes), the route calculation unit 205 collects information for calculating the planned travel route 400 (step S104). That is, the receiving unit 201 acquires the reference route 300 in the traveling lane 260 in which the moving body 200 is traveling, for example, from a reference route holding device (not shown). From the relay point of the reference route 300, the relay point _i (x _Rti , y _Rti , θ _Rti , v _Rti ) of the reference route 300 at the time ti can be obtained from the reference route 300. The relay point of the reference route 300 is defined regardless of the current state of the mobile body 200. The relay points of the reference route 300 include those from the current time to the future. For example, when the current time is t ₀ , information on relay points 300 _{t 0} to t can be obtained as shown in FIG. The receiving unit 201 sends the information of the reference route 300 to the route calculation unit 205. The reference route 300 may be obtained from a high-definition map or a dynamic map.

Next, the route calculation unit 205 calculates the relay point of the planned travel route 400 so as to asymptotically approach the reference route 300 from the coordinates of the moving body 200 at the current time of the travel route 500 (step S105). At this time, the route calculation unit 205 calculates the relay point of the planned travel route 400 from the information around the moving body 200 sent from the sensor unit 203 so as to avoid the obstacle when there is an obstacle. .. That is, the relay points (x _Cti , _{y Cti} , θ _Cti , v _Cti ,) of the planned travel route 400 at the time ti are calculated. The relay point of the planned travel route 400 also includes a future relay point as in the case of the reference route 300. For example, when the current time is t ₀ , the information of the relay points 400 t ₀ to t _e in the planned travel route 400 calculated at the time t ₀ can be obtained as shown in FIG. The route calculation unit 205 calculates the planned travel route 400 by calculating the relay points of these planned travel routes 400. Further, the route calculation unit 205 stores the information of the reference route 300 and the information of the planned travel route 400 in the storage unit 202, and sends the planned travel route 400 to the power calculation unit 207.

Next, the power unit 209 drives the moving body 200 (step S106). That is, first, the power calculation unit 207 calculates the steering amount ζ _C and the accelerator amount η _C at the current time from the planned travel route 400, and sends them to the power control unit 208. Further, the power control unit 207 causes the storage unit 202 to hold the calculated steering amount ζ _C and accelerator amount η _C as information on the planned travel route 400 at the current time.

Next, the power control unit 208 corrects the steering amount ζ _C and the accelerator amount η _C sent from the power calculation unit 207 in consideration of the response performance to the control input of the moving body 200, and sets it as the control amount at the current time. The steering amount is ζ _M and the accelerator amount is η _M. The power control unit 208 holds the corrected steering amount ζ _M and accelerator amount η _M in the storage unit 202 as information on the travel path 500 at the current time, and sends the corrected steering amount ζ M to the power unit 209. The power unit 209 drives the moving body 200 according to the steering amount ζ _M and the accelerator amount η _M.

Next, the transmission unit 206 confirms whether the storage unit 202 has three route information of the reference route 300, the planned travel route 400, and the travel route 500 for a certain period of time, as well as image information and image analysis information (step 107). ). This fixed time can be changed arbitrarily. If the storage unit 202 does not have the route information for a certain period of time (step S107: No), the process proceeds to step S109.

On the other hand, when the storage unit 202 has these three route information, image information, and image analysis information for a certain period of time (step S107: Yes), the transmission unit 206 transmits these route information to the electronic device 100 (step). S108).

Next, the input unit 210 confirms whether the end command has been input (step S109). This end command instructs the mobile body 200 to end the operation in the flow currently being processed, and is delivered by an input from the user to the input unit 210 or the like.

If this end command is not input (step S109: No), the process returns to step S101. On the other hand, when this end command is input (step S109: Yes), the flow ends. By this end command, the moving body 200 may end the operation immediately.

Next, the configuration of the electronic device 100 in the first embodiment will be described with reference to FIG. 7. The electronic device 100 has a receiving unit 101 that receives route information from the moving body 200, a processing unit 102 that calculates the difference between the two routes from the route information, and an estimation that estimates the state of the road surface on which the moving body 200 travels from this difference. The unit 103 includes a display information generation unit 104 that generates information indicating the state of the road surface and an area of the road surface, an output unit 105 that outputs this information, a storage unit 106, and an input unit 107 that receives an instruction input by the user. .. These configurations are realized by a semiconductor integrated circuit (LSI or the like).

The receiving unit 101 receives the route information transmitted from the mobile body 200 via the Internet or the like. The receiving unit 101 sends this route information to the processing unit 102.

The processing unit 102 calculates the difference between the two routes from the three route information sent from the receiving unit 101. The processing unit 102 causes the storage unit 106 to hold this difference.

The estimation unit 103 estimates the state of the road surface on which the moving body 200 is traveling from the difference between the two routes held in the storage unit 106. In addition to the difference between the two routes, the estimation unit 103 may estimate the state of the road surface by using the information of the image corresponding to the road surface and the information of the image analysis. For example, the deterioration state of the road surface may be estimated. The estimation unit 103 holds the estimated road surface state in the storage unit 106.

The display information generation unit 104 generates display information indicating the deterioration state of the road surface held in the storage unit 106 and the area of the road surface. There are various modes of this information, and in FIG. 1, information is generated in which a region of a road surface presumed to be deteriorated is superimposed on a map by a broken line. In addition to the image information represented by FIG. 1, the display information may be information representing the state of the road surface in characters or information representing representative points of the road surface region in latitude and longitude. The display information generation unit 104 causes the storage unit 106 to hold the generated display information.

The output unit 105 outputs the display information held in the storage unit 106. The output destination is, for example, a display such as a desktop PC or a smartphone, a file server, or the like.

The storage unit 106 is a device that holds information, and is, for example, a RAM, a ROM, an HDD, an SSD, or the like. Further, it may not exist in the electronic device 100 but may exist outside. For example, an external HDD or a cloud may be used.

The input unit 107 receives an instruction input by the user. For example, the input unit 107 receives an instruction of a parameter to be calculated, an instruction of ending the operation of the electronic device 100, and the like.

Next, the operation flow of the electronic device 100 that estimates the state of the road surface of the roadway from the three route information of the reference route 300, the planned travel route 400, and the travel route 500 will be described with reference to FIG. First, the receiving unit 101 receives these three route information, image information, and image analysis information from the moving body 200 (step S201). The receiving unit 101 sends these information to the processing unit 102.

The processing unit 102 causes the storage unit 106 to hold the three transmitted route information, the image information, and the image analysis information. Next, the processing unit 102 determines an estimation section that is a range for estimating the state on the road surface of the roadway, and extracts the route information in this section from the three received route information (step S202). For example, if the relay point _300te is defined as an estimated section from the relay point _300t0 in FIG. 3, the relay point and the travel path 500 of the planned travel route 400 in this section are extracted. The processing unit 102 can arbitrarily determine this estimated interval. For example, it is possible to obtain the difference between the travel route 500 and the planned travel route 400 within a predetermined section of the travel lane 260. Further, the steering amount ζ _C and the accelerator amount η _C included in the planned travel route 400 in the estimated section, and the steering amount ζ _M and the accelerator amount η _M included in the travel route 500 in the estimated travel section are also extracted.

However, if the extracted travel route 500 contains information calculated at the time of rainfall or snowfall (step S203: Yes), there is a possibility that the vehicle cannot travel along the planned travel route 400 due to the slip of the road surface due to rainfall or snowfall. There is. Therefore, the route information acquired and calculated at the time of rainfall or snowfall is not used for the calculation of the route difference, and the process returns to step S201. The processing unit 102 may delete this route information acquired and calculated at the time of rainfall or snowfall from the storage unit 106.

Specifically, in step S203, it is confirmed by using image information and image analysis information whether or not the travel path 500 extracted by the processing unit 102 includes the information calculated at the time of rainfall or snowfall. For example, the processing unit 102 analyzes and confirms the color of the road surface from the image information, and confirms by the image analysis information by the moving body 200 that the road surface is wet and the image analysis information that snow is present on the road surface. This is because the coefficient of friction of the road surface of the road may differ depending on the rainfall, or the unevenness of the road surface of the road may change temporarily due to the snowfall, which may affect the estimation of the deterioration of the road surface of the road. In the present embodiment, since the route information includes image analysis information on the road surface of the roadway, it is determined whether or not the image analysis information includes analysis information that the road surface is wet or information such as the presence of snow.

On the other hand, when the extracted travel route 500 does not include the information calculated at the time of rainfall or snowfall (step S203: No), the processing unit 102 includes the travel schedule route 400 and the travel route 500 included in the extracted route information. It is confirmed whether the reference path 300 is followed (step S204).

The processing unit 102 compares the coordinates and speed of the relay point of the reference route 300 at the same time, the coordinates of the relay point of the planned travel route 400, the speed, and the coordinates and speed of the relay point of the reference route 300 and the travel route 500 at the same time. However, if it is within a certain threshold value, it is determined that the relay point of the planned travel route 400 and the travel route 500 are along the relay point of the reference route 300. The reason for performing this operation is that when the moving body 200 calculates the planned travel route 400 or the travel route 500 that greatly deviates from the reference route 300, the condition of the road surface may affect the estimation. For example, this is a case where the moving body 200 travels to avoid an obstacle on the reference route 300.

When the planned travel route 400 and the travel route 500 included in the route information do not follow the reference route 300 (step S204: No), the planned travel route 400 and the travel route 500 that do not follow the reference route 300 calculate the difference between the routes. Return to step S201 without using the above. The processing unit 102 may erase the planned travel route 400 and the travel route 500 that are not along the reference route 300 from the storage unit 106. Here, when the planned travel route 400 and the travel route 500 at some times do not follow the reference route 300, only the planned travel route 400 and the travel route 500 at some times are used for calculating the difference between the routes. I can't.

When the planned travel route 400 and the travel route 500 included in the route information are along the reference route 300 (step S204: Yes), the processing unit 102 is the relay point of the reference route 300 and the relay point of the planned travel route 400 at the same time. And the difference between the two routes is calculated from the measurement points of the travel route 500 (step S205). This difference is the difference between the coordinates, the steering amount, and the accelerator amount in the two paths. The two routes may be two of the reference route 300, the scheduled travel route 400, and the travel route 500, or may be two planned travel routes 400 calculated at different times. Examples of this difference include the difference in the coordinates of the reference route 300 and the travel route 500, the difference in the coordinates of the planned travel route 400 and the travel route 500, the steering amount, and the accelerator amount, and the planned travel route calculated at time _t0 . _These are the coordinates of the planned travel route 400 calculated at 400 and time t1, the steering amount, the difference in the accelerator amount, and the like. The processing unit 102 causes the storage unit 106 to hold the calculated difference between the two routes.

Next, the estimation unit 103 estimates the state of the road surface of the roadway on which the moving body 200 is traveling from the difference of this route held in the storage unit 106 (step S206). If the difference of this route exceeds the set threshold value, the estimation unit 103 estimates that the road surface is abnormal. The estimation unit 103 estimates that there is no abnormality on this road surface unless this threshold value is exceeded. This threshold can be set arbitrarily.

When the difference between the coordinates, the steering amount, and the accelerator amount in the two paths is larger than the threshold value, it can be estimated that the moving body 200 has automatically operated due to some abnormality existing on the road surface. For example, when the difference in coordinates between the reference route 300 and the planned travel route 400 exceeds the threshold value, the moving body 200 exists at a position away from the reference route 300, and the planned travel route 400 is set so as to asymptotic to the reference route 300. It is estimated that it is calculated. In addition, from the difference between the accelerator amount of the planned travel route 400 and the accelerator amount of the travel route 500, if there is a crack on the road surface of the travel lane 260, the accelerator amount included in the planned travel route 400 is the coordinates of the planned travel route 400. Since it is not possible to reach, it is presumed that the vehicle traveled with an accelerator amount larger than the accelerator amount of the planned travel route 400. The same applies to the amount of steering.

The estimation unit 103 calculates the state of the road surface and the range of the state of the road surface from the route information held in the storage unit 106. The estimation unit 103 causes the storage unit 106 to hold information on the state of the road surface, the range of the state of the road surface, and the coordinates. The estimation unit 103 may evaluate the quality of the road surface stepwise by setting the threshold value, or may evaluate the abnormality of the road surface stepwise.

Next, the display information generation unit 104 generates display information representing the state of the road surface on the road on which the moving body 200 is traveling, the range of the state of the road surface, and the coordinates (step S207). For example, when the range and coordinate information of the road surface estimated to be deteriorated are superimposed on the map information by a broken line as shown in FIG. 1, the display information generation unit 104 is held in the storage unit 106 of the road surface. The figure shown in FIG. 1 is generated from the coordinates and the range and the map information. This information is not limited to the form as shown in FIG. 1, and the coordinate information of the road surface may be simply expressed by latitude and longitude. The display information generation unit stores this display information in the storage unit 106.

Next, the output unit 105 outputs the display information held in the storage unit 106 (step S208). The output unit 105 may output the figure to the display unit of the output destination electronic device, or may transmit the data of this display information via the Internet.

Next, the input unit 107 confirms whether the end command has been input (step S209). This end command is instructed to end the operation in the flow currently being processed by the electronic device 100, and is delivered by an input from the user to the input unit 107 or the like.

If this end command is not input (step S209: No), the process returns to step S201. On the other hand, when this end command is input (step S209: Yes), the flow ends. By this termination command, the electronic device 100 may terminate the operation immediately.

Next, the difference between the two paths calculated by the electronic device 100 will be described. Table 1 is a list of parameters calculated by the processing unit 102 of the electronic device 100 as the difference between the two paths in the present embodiment. The electronic device 100 estimates the state of the road surface of the lane 260 by calculating this parameter. Hereinafter, these parameters will be described.

The difference in vertical acceleration (Table 1: second row from the top) represents the difference between the vertical acceleration of the moving body 200 on the traveling path 500 and the vertical acceleration of the moving body 200 on a roadway having a standard surface roughness. .. Only the difference in the vertical acceleration is not the difference between the reference route 300 or the planned travel route 400 and the travel route 500, but the measured value of the vertical acceleration included in the travel route 500 and the moving body 200 on the road having a standard surface roughness. It is the difference in vertical acceleration. FIG. 9 is a diagram of measurement by the moving body 200, and represents that the moving body 200 measures the acceleration α _Mti at the time _ti . The parameters of vertical acceleration are calculated using mathematical formulas (1), (2) and (3).

The left side of the equation (1) represents the difference in vertical acceleration. The overlined α on the right side of the formula (1) is expressed as an α bar. The α-bar represents the vertical acceleration of the moving body 200 on a roadway having a standard surface roughness, which is measured in advance and held in the storage unit 106.

The formula (2) is a formula for calculating the average value of _{e α} (ti) in the estimated interval. The left side of the formula (2) is expressed as α tilde. The formula (3) is a formula for calculating the average of α tildes when there are N moving bodies 200 traveling in the same estimated section. The left side of the formula (3) is expressed as an α hat. When this α hat is equal to or higher than the threshold value, the estimation unit 103 estimates that there is an abnormality on the road surface of the roadway in the estimated section.

The type of abnormality on this road surface may be estimated. As an abnormality due to the difference in vertical acceleration, for example, it may be determined and estimated whether there is a high possibility of cracking or a decrease in flatness. This will be described with reference to FIGS. 10 and 11.

10 and 11 are deviations of vertical acceleration within the estimated section. This figure will be used to explain the estimation of the type of anomaly. In FIGS. 10 and 11, if the deviation _{e α} (ti) of the vertical acceleration is equal to or greater than the threshold value α _T , it is presumed that there is an abnormality on the road surface of the roadway. 10 and 11 also provide a time threshold t _T. When the deviation e _α (ti) of the vertical acceleration is equal to or more than the threshold value α _T over this t _T , it is highly likely that the flatness of the road surface is deteriorated, and the deviation _{e α} (t) of the vertical acceleration is estimated. If _i ) is greater than or equal to the threshold α _T and less than t _T , it is presumed that the road surface is likely to be cracked. The threshold values α _T and t _T are arbitrarily determined by the estimation unit 103.

In FIG. 10, it is estimated that the road surface is likely to be cracked because the time when the deviation _{e α} (ti) of the vertical acceleration is equal to or more than the threshold value α _T is less than t _T , and FIG. 11 shows the deviation of the vertical acceleration. Since the time when _{e α} (ti) is equal to or greater than the threshold value α _T is longer than t _T , it is highly probable that the flatness of the road surface is deteriorated.

Further, the threshold value α _T may be adjusted according to the height difference of the planned travel route 400 calculated by the moving body 200. By adjusting the threshold value α _T according to the height difference of the planned travel route 400, the estimation unit 103 can estimate the deterioration of the road surface of the road in consideration of the height difference of the planned travel route 400.

Next, the difference between the planned travel route and the coordinates of the travel route (Table 1: 3rd line from the top) will be described. This difference represents the difference between the target position and the measurement position of the moving body 200 at the same time. FIG. 12 is a diagram showing a target position and a measurement position at each time in the moving body 200. The parameter of the difference between the planned travel route and the coordinates of the travel route is calculated using mathematical formulas (4) and (5). _{e β} (ti) is the distance between the target position and the measurement position at time _ti .

At each time _ti , the moving body 200 operates toward the target position on the planned travel route 400, but the target position and the measurement position may deviate from each other due to an abnormality on the road surface such as a rut or a crack. By calculating this deviation, the estimation unit 103 estimates the state of the road surface of the roadway.

The formula (4) is a formula for calculating the average value of _{e β} (ti) in the estimated interval. The left side of the formula (4) is expressed as β tilde. The formula (5) is a formula for calculating the average of β tildes when there are N mobile bodies 200 traveling in the same estimated section. The left side of the formula (5) is expressed as β hat. When this β hat is equal to or higher than the threshold value, the estimation unit 103 estimates that there is an abnormality on the road surface of the roadway in the estimated section. As an anomaly, for example, there may be ruts or cracks on this road surface. Further, this threshold value is arbitrarily determined by the estimation unit 103.

Next, the difference in the lane width direction from the reference route of the moving body 200 (Table 1: 4th row from the top) will be described. This difference represents the difference in the lane width direction between the reference path in the moving body 200 and the coordinates of the measurement points of the traveling path 500 in the moving body 200 at the same time. FIG. 13 is a diagram showing measurement points of the traveling route 500 in the reference route 300 and the moving body 200. The parameters of the difference between the coordinates of the reference route and the travel route are calculated using mathematical formulas (6) and (7). _{e γ} (ti) is the distance in the lane width direction between the reference route 300 and the traveling route 500 _ti at the time _ti . Specifically, a perpendicular line is drawn from the traveling path _500ti with respect to the line segment obtained by connecting the relay points of the reference route 300 or the straight line obtained by complementing the relay points, and the length of the perpendicular line is e. Let it be _γ ( _ti ).

The moving body 200 finally travels along the reference route 300 through the relay point of the planned travel route 400, but when the wheel is taken by the unevenness of the road surface such as a rut, or when the mobile body 200 deviates from the reference route 300 in the lane width direction. There is. By calculating this deviation, the estimation unit 103 estimates the state of the road surface of the roadway.

The formula (6) is a formula for calculating the average value of _{e γ} (ti) in the estimated interval. The left side of the formula (6) is expressed as a γ tilde. The formula (7) is a formula for calculating the average of γ tildes when there are N moving bodies 200 traveling in the same estimated section. The left side of the formula (7) is expressed as a γ hat. When this γ hat is equal to or greater than the threshold value, the estimation unit 103 estimates that there is an abnormality on the road surface of the roadway in the estimated section. As an anomaly, for example, there may be ruts or cracks on this road surface. Further, this threshold value is arbitrarily determined by the estimation unit 103.

Next, the difference in the coordinates of the planned travel route calculated at different times (Table 1: 5th line from the top) will be described. This difference represents the difference in the coordinates of the relay points at the same time for the two scheduled travel routes 400 calculated by the moving body 200 at different times. For example, FIG. 14 is a diagram showing a relay point of the scheduled travel route 400A calculated at time t ₀ and a relay point of the scheduled travel route 400B calculated at time t ₁ . FIG. 14 shows the difference in coordinates between the relay point of the scheduled travel route 400A calculated at time t ₀ and the relay point of the scheduled travel route 400B calculated by the mobile body 200 at time t ₁ at the same time. Represents. The parameters of the difference in the coordinates of the planned travel route calculated at different times are calculated using the mathematical formulas (8) and (9). _{e δ} (ti _{) is the distance between the relay point 400 At i and the relay point 400 Bt i at the} time ti.

The moving body 200 travels through the relay point of the planned travel route 400, but when the wheels are taken by the unevenness of the road surface such as a rut, the calculated travel schedule route may be deviated. By calculating this deviation, the estimation unit 103 estimates the abnormality of the road surface of the roadway.

The formula (8) is a formula for calculating the average value of _{e δ} (ti) in the estimated interval. The left side of the formula (8) is expressed as δ tilde. The formula (9) is a formula for calculating the average of δ tildes when there are N moving bodies 200 traveling in the same estimated section. The left side of the formula (9) is expressed as a δ hat. If this δ hat is equal to or greater than the threshold value, the estimation unit 103 estimates that there is an abnormality on the road surface of the roadway in the estimated section. As an anomaly, for example, there may be ruts or cracks on this road surface. Further, this threshold value is arbitrarily determined by the estimation unit 103.

As shown in FIG. 14, the formula (8) is from time _{t 0} to time _tm when there is no deviation from the reference path 300 at time tm (below the set threshold value). The average value of _{e δ} (ti) may be calculated. This is because once the moving body 200 is located on the reference route 300, it is operated so as to travel along the reference route 300 thereafter.

Next, the difference between the calculated amount of steering and the control amount (Table 1: 6th line from the top) will be described. The parameters of the power control unit 208 difference are calculated using mathematical formulas (10), (11) and (12).

The power calculation unit calculates the amount of steering so as to travel through the relay point of the planned travel route 400, and the power control unit 208 calculates the control amount of the steering based on the calculated amount of the steering. The estimation unit 103 estimates the state of the road surface of the roadway by calculating the deviation between the calculated amount of steering and the controlled amount. For example, if the difference between the calculated amount of steering and the amount of control continues, it is presumed that the wheels are taken off by the unevenness of the road surface such as ruts.

The formula (10) is a formula for calculating _{e ζ} (ti), which is the difference between the control amount ζ _Mti of the steering amount at the time _ti and the calculation amount ζ _Cti of the steering amount at the time _ti . The formula (11) is a formula for calculating the average value of _{e ζ} (ti) in the estimated interval. The left side of the formula (11) is expressed as a ζ tilde. The formula (12) is a formula for calculating the average of ζ tildes when there are N moving bodies 200 traveling in the same estimated section. The left side of the formula (12) is expressed as a ζ hat. If this ζ hat is equal to or greater than the threshold value, the estimation unit 103 estimates that there is an abnormality on the road surface on the roadway in the estimated section. As an anomaly, for example, there may be ruts or cracks on this road surface. Further, this threshold value is arbitrarily determined by the estimation unit 103.

Further, the threshold value may be adjusted according to the curvature of the planned traveling route 400 calculated by the moving body 200. By adjusting the threshold value according to the curvature of the planned travel route 400, the estimation unit 103 can estimate the state of the road surface of the roadway in consideration of the curvature of the planned travel route 400.

Next, the difference between the calculated amount of the accelerator and the controlled amount (Table 1: 7th line from the top) will be described. This difference represents the difference between the accelerator amount calculated by the power calculation unit and the accelerator amount calculated by the power control unit. The parameters of the difference are calculated using mathematical formulas (13), (14) and (15).

The power calculation unit calculates the amount of the accelerator so as to travel through the relay point of the planned travel route 400, and the power control unit 208 calculates the control amount of the accelerator based on the calculated amount of the accelerator. The estimation unit 103 estimates the state of the road surface of the roadway by calculating the deviation between the calculated amount of the accelerator and the controlled amount. For example, if the difference between the calculated amount of the accelerator and the controlled amount continues, it is presumed that the wheels have been removed due to the unevenness of the road surface such as cracks.

The formula (13) is a formula for calculating _{e η} (ti), which is the difference between the control amount η _Mti of the accelerator amount at the time _ti and the calculation amount η _Cti of the accelerator amount at the time _ti . The formula (14) is a formula for calculating the average value of _{e η} (ti) in the estimated interval. The left side of the formula (14) is expressed as η tilde. The formula (15) is a formula for calculating the average of η tildes when there are N moving bodies 200 traveling in the same estimated section. The left side of the formula (15) is expressed as η hat. If this ζ hat is equal to or greater than the threshold value, the estimation unit 103 estimates that there is an abnormality on the road surface of the roadway in the estimated section. As an anomaly, for example, there may be ruts or cracks on this road surface. Further, this threshold value is arbitrarily determined by the estimation unit 103.

Further, the threshold value may be adjusted according to the height difference of the planned traveling route 400 calculated by the moving body 200. By adjusting the threshold value according to the height difference of the planned travel route 400, the estimation unit 103 can estimate the state of the road surface of the roadway in consideration of the height difference of the planned travel route 400.

The above shows the difference parameter and the method of estimating the road surface condition on the roadway from the difference parameter. When the estimation unit 103 estimates the abnormality of the road surface from at least one of these difference parameters, it estimates that the road surface of the roadway in the estimated section has an abnormality.

Although this embodiment has been described above, various variations can be considered. For example, in the present embodiment, the moving body 200 is said to have an automatic driving function, but it may be a moving body not having an automatic driving function. That is, even when the reference route 300 and the planned travel route 400 cannot be acquired by the user's driving, the electronic device 100 can calculate the α hat, the ζ hat, and the η hat to estimate the state of the road surface of the roadway.

Specifically, this moving body measures the amount by which the user turns the steering wheel of the moving body as the calculated steering amount ζ _C , and measures the amount of steering angle actually driven by the moving body as the steering control amount ζ _M. .. By taking the difference between these steering amounts as in the case described in the present embodiment, the electronic device 100 can estimate the state of the road surface. Further, in this moving body, the amount by which the user steps on the accelerator is measured as the calculated amount η _C of the accelerator, and the acceleration amount actually driven by the moving body is measured as the controlled amount η _M of the accelerator. The electronic device 100 can estimate the state of the road surface by taking the difference in the amount of the accelerator as in the case described in the present embodiment. Further, from the vertical acceleration _αM measured by the moving body, the electronic device 100 can calculate the parameters and estimate the state of the road surface in the same manner as in the present embodiment. The moving body without this automatic operation function measures these ζ _C , ζ _M , η _C , η _M and α _M , and these ζ _C , ζ _M , η _C , η _M and α _M. It is assumed that the data including the above can be transmitted to the electronic device 100.

Further, in the present embodiment, the description has been made on the premise that the mobile body 200 performs automatic operation, but the mobile body 200 is not limited to the one that always performs automatic operation. It may be a mobile body that automatically drives on some roads (for example, a toll road) and is driven by a user on other roads. Even in the case of this moving body, in the case of automatic driving, the electronic device 100 may be made to estimate the state of the road surface as in the present embodiment.

Further, in step S203 explaining the operation of the electronic device 100, confirmation of whether the route information extracted by the processing unit 102 includes information at the time of rainfall or snowfall is not limited to confirmation by image analysis information. In addition, the receiving unit 101 may acquire the weather information of the coordinate information of the extracted route information from the Internet and the processing unit 102 may confirm it, or the processing unit 102 may obtain an image of the road surface of the extracted route information. It may be confirmed by analysis.

Further, in the present embodiment, the electronic device 100 calculates the parameters, but the parameters are calculated excluding the parameters α hat, β hat, γ hat, δ hat, ζ hat, and η hat of the plurality of moving bodies 200. May be performed by the moving body 200 and transmitted to the electronic device 100.

Further, in the present embodiment, the electronic device 100 receives three route information, image information, analysis information, and the like from the mobile body 200, and the mobile body 200 directly transmits these information to the electronic device 100. Not limited to. The mobile body 200 may be stored in an external storage unit, for example, an external hard disk or the cloud of the Internet. The electronic device 100 may also receive such information from the external storage unit and estimate the state of the road surface. This reception includes a device that directly connects an external storage unit and the electronic device 100 by wire and acquires such information.

Further, in the present embodiment, the electronic device 100 calculates the parameters shown in Table 1, but is not limited to these parameters, and calculates any parameter that can be used for estimating the road surface of the lane 260. It is a thing.

Further, in the present embodiment, the estimation unit 103 estimates the deterioration of the road surface of the road surface depending on whether the α hat, β hat, γ hat, δ hat, ζ hat and η hat exceed the respective threshold values. Deterioration may be estimated based on whether the parameter of is exceeded the threshold value. For example, the estimation unit 103 may include e _α (ti), _{e β} (ti), _{e γ} (ti), _{e δ} (ti), _{e ζ} (ti), _{e η} ( _ti ), and the like. The difference between points or the average value of the differences in one moving body 200 such as α-tilda, β-tilda, γ-tilda, δ-tilda, ζ-tilda, and η-tilda may be used.

Further, in the present embodiment, the threshold value is used for the estimation of the type of road surface abnormality by the estimation unit 103, but a plurality of these threshold values may be prepared to estimate the type of road surface abnormality. For example, in the vertical acceleration deviation diagrams shown in FIGS. 10 and 11, the thresholds were α _T and −α _T , but the thresholds were α _T 2 and − α _T 2 whose absolute values were larger than α _T. It may be provided as. When the deviation _{e α} (ti) of the vertical acceleration is larger than this α _T2 , the estimation unit 103 estimates that there is an ascending step on the road surface, and when the deviation _{e α} (ti) of the vertical acceleration is smaller than this −α _T2 . , The estimation unit 103 may presume that there is a down step on the road surface. Further, after setting t _T2 shorter than the time threshold t _{T 1} and calculating a deviation in which the deviation _{e α} (ti) of the vertical acceleration is smaller than −α _T 2, the deviation e _α of the vertical acceleration is within t _T 2. When a deviation in which ( _ti ) is larger than α _T2 is calculated, the estimation unit 103 may presume that a hole exists in the road surface.

Further, in the present embodiment, the electronic device 100 calculates a plurality of parameters and estimates the road surface condition from each parameter, but the road surface condition may be estimated by combining the plurality of parameters. For example, if it is estimated that there is an abnormality on the road surface from the β hat, which is a parameter of the difference between the planned travel route and the coordinates of the travel route, what kind of abnormality is the road surface abnormality from e _α , which is the difference in vertical acceleration? You may try to estimate whether it is.

Further, in the present embodiment, a threshold value is used for estimating the type of road surface abnormality by the estimation unit 103, but a good road surface may be estimated by setting this threshold value. For example, in the vertical acceleration deviation diagrams shown in FIGS. 10 and 11, the thresholds were α _T and −α _T , but the thresholds were α _T3 and −α _T3 whose absolute values were smaller than α _T. It may be provided as. If the deviation _{e α} (ti) of the vertical acceleration is smaller than this α _T3 and larger than this −α _T2 , the estimation unit 103 may presume that this road surface is a good road surface.

Further, in the present embodiment, the estimation unit 103 estimates the state of the road surface on the roadway depending on whether the threshold value is exceeded, but by inputting the calculated parameters into the learning model, the state of the road surface on the roadway can be obtained. You may try to estimate. For example, estimation by a deep learning model. FIG. 15 shows a conceptual diagram of estimation by this deep learning model. A weighting function _wi is set in each component of this model. When the calculated parameters are input to the model, the probability of ruts, cracks, flatness deterioration, and no abnormality is finally calculated. In addition, this model updates the weighting function _wi with the inspection result of the road surface property measuring vehicle as teacher data for the road surface.

Even in this case, the parameters to be input are not limited to those in FIG. New parameters may be created, or there may be fewer types than the parameters shown in FIG. It may be possible to output only the state with the highest probability among ruts, cracks, flatness deterioration, and no abnormality. Further, this learning model also includes a model of deep learning that will be developed in the future, and learning other than deep learning may be used as long as it is learning that outputs through the model to the input.

Further, the function of the electronic device 100 in the present embodiment can also be realized by a program. This program may be provided as a file in an installable or executable format stored on a computer-readable storage medium such as a CD-ROM, memory card, CD-R and DVD (Digital Versaille Disk). good. Further, this program may be stored on a computer connected to a network such as the Internet and provided via the network, or may be provided by being incorporated in a storage medium such as a ROM, HDD, or SSD. You may.

As described above, in the present embodiment, the electronic device 100 acquires the route information of the moving body 200, and estimates the state of the road surface on the roadway on which the moving body 200 travels based on the route information. By doing so, it is possible to further simplify the road surface inspection currently performed by the road surface property measuring vehicle. By grasping the roadway presumed to have an abnormality on the road surface by the electronic device 100 and inspecting the roadway by the road surface property measuring vehicle, the time and cost of the road surface inspection can be reduced. Further, the electronic device 100 can arbitrarily balance the reduction of the time and cost of the road surface inspection and the accuracy of the road surface inspection by setting the interval between the relay point and the measurement point of the received route information and the setting of the estimation section. can.

Although some embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other embodiments, and various omissions, replacements, and changes can be made without departing from the gist of the invention. These embodiments and variations thereof are included in the scope and gist of the invention, and are also included in the scope of the invention described in the claims and the equivalent scope thereof.

100 ... Electronic device 101 ... Receiving unit 102 ... Processing unit 103 ... Estimating unit 104 ... Display information generation unit 105 ... Output unit 106 ... Storage unit 107 ... Input unit 200 ... Moving unit 201 ... Receiving unit 202 ... Storage unit 203 ... Sensor unit 204 ... Travel route acquisition unit 205 ... Route calculation unit 206 ... Transmission unit 207 ... Power calculation unit 208 ... Power control unit 209 ... Power unit 210 ... Input unit 250 ... Road 260 ... Travel lane 270 ... White line 300 ... Reference route 400 ... Travel Scheduled route 400A ... Scheduled travel route 400B calculated at time t ₀ ... Scheduled travel route 500 calculated at time t ₁ ... Travel route

Claims (22)

It is a route on which a moving body that automatically operates on the road surface is scheduled to travel, and is a route that is used as a reference when calculating the first route information indicating the route including the position of the moving body and the first route information. At least two of the second route information indicating the route including the position of the moving body and the third route information indicating the route on which the moving body has traveled on the road surface and including the position of the moving body. A processing unit that calculates the difference between two routes from the route information,
An estimation unit that estimates the state of the road surface from the difference between the routes, and an estimation unit.
Electronic device equipped with. A receiving unit that receives at least two route information among the first route information, the second route information, and the third route information is further provided.
The electronic device according to claim 1. Of the routes that the mobile body that automatically drives on the road surface is scheduled to travel and includes the position of the moving body, the first route information indicating the route calculated at the first time and the first route information calculated at the second time. A processing unit that calculates the difference between the two routes of the second route information indicating the route, and
An estimation unit that estimates the state of the road surface from the difference between the routes, and an estimation unit.
Electronic device equipped with. A receiving unit for receiving the first route information and the second route information is further provided.
The electronic device according to claim 3. The processing unit calculates at least one difference among the difference in the position of the moving body, the difference in the amount of steering angle, and the difference in the amount of acceleration in the two paths as the difference in the paths .
The electronic device according to any one of claims 1 to 4. The estimation unit estimates that an abnormality exists on the road surface when the magnitude of the difference between the routes is equal to or greater than the first threshold value.
The electronic device according to any one of claims 1 to 5. The processing unit further indicates a first vertical acceleration measured when the moving body travels on the road surface, and a first vertical acceleration measured by the moving body on a reference road surface. Calculate the difference in vertical acceleration from the vertical acceleration of 2
The estimation unit estimates the state of the road surface from the difference in the path and the difference in the vertical acceleration.
The electronic device according to any one of claims 1 to 6. The estimation unit estimates that an ascending step exists on the road surface when the difference in the vertical acceleration is equal to or greater than the second threshold value.
The electronic device according to claim 7. The estimation unit estimates that a down step exists on the road surface when the difference in the vertical acceleration is equal to or less than the third threshold value.
The electronic device according to claim 7 or 8. In the estimation unit, when the difference in the vertical acceleration is equal to or greater than the fourth threshold value or equal to or less than the fifth threshold value, the difference in the vertical acceleration is equal to or greater than the fourth threshold value. Measures the time that is equal to or less than the fifth threshold value, and presumes that there is either a crack or a decrease in flatness on the road surface depending on the time.
The electronic device according to any one of claims 7 to 9. The estimation unit includes a learning model, estimates the state of the road surface from the difference in the path and the difference in the vertical acceleration, and estimates the state of the road surface.
In the learning model, the inspection result of the road surface by the vehicle for measuring the road surface properties is updated as teacher data.
The electronic device according to any one of claims 7 to 10. The processing unit calculates the difference of the route and the average value of the difference of the route in the plurality of mobile bodies, and calculates the average value.
The estimation unit estimates the state of the road surface from the average value of the differences of the routes .
The electronic device according to any one of claims 1 to 11. The processing unit calculates the difference between the vertical accelerations of the plurality of moving objects and the average value of the differences between the vertical accelerations.
The estimation unit estimates the state of the road surface on which the moving body travels from the average value of the differences in the vertical accelerations.
The electronic device according to any one of claims 7 to 11. A display information generation unit that generates display information indicating the state of the road surface and the area of the road surface, and
An output unit that outputs the display information and
To prepare
The electronic device according to any one of claims 1 to 13. Recorded information of the steering angle amount including the first steering angle amount information indicating the steering angle amount input to the moving body and the second steering angle amount information indicating the steering angle amount driven by the moving body, and input to the moving body. From the recorded information of at least one of the recorded information of the acceleration amount including the first acceleration amount information indicating the acceleration amount and the second acceleration amount information indicating the acceleration amount driven by the moving body.
A processing unit that calculates at least one difference between the first steering angle amount information and the second steering angle amount information, and the second difference between the first acceleration amount information and the second acceleration amount information. ,
An estimation unit that estimates the state of the road surface on which the moving body has traveled from at least one of the first difference and the second difference.
Electronic device equipped with. Further, a receiving unit for receiving at least one of the recorded information of the steering angle amount and the recorded information of the acceleration amount is provided.
The electronic device according to claim 15. It ’s a method that electronic devices do.
It is a route on which a moving body that automatically operates on the road surface is scheduled to travel, and is a route that is used as a reference when calculating the first route information indicating the route including the position of the moving body and the first route information. At least two of the second route information indicating the route including the position of the moving body and the third route information indicating the route on which the moving body has traveled on the road surface and including the position of the moving body. Calculate the difference between the two routes from the route information,
The state of the road surface is estimated from the difference of the road.
Method. It ’s a method that electronic devices do.
Of the routes in which a moving body that automatically operates on the road surface is scheduled to travel and includes the position of the moving body, the first route information indicating the route calculated at the first time and the first route information indicating the route calculated at the second time are calculated. The difference between the two routes of the second route information indicating the above route is calculated.
The state of the road surface is estimated from the difference of the road.
Method. It ’s a method that electronic devices do.
Recorded information of the steering angle amount including the first steering angle amount information indicating the steering angle amount input to the moving body and the second steering angle amount information indicating the steering angle amount driven by the moving body, and input to the moving body. From the recorded information of at least one of the recorded information of the acceleration amount including the first acceleration amount information indicating the acceleration amount and the second acceleration amount information indicating the acceleration amount driven by the moving body .
The difference of at least one of the first difference between the first steering angle amount information and the second steering angle amount information and the second difference between the first acceleration amount information and the second acceleration amount information is calculated.
The state of the road surface on which the moving body has traveled is estimated from the difference of at least one of the first difference and the second difference.
Method. It is a route on which a moving body that automatically operates on the road surface is scheduled to travel, and is a route that is used as a reference when calculating the first route information indicating the route including the position of the moving body and the first route information. At least two of the second route information indicating the route including the position of the moving body and the third route information indicating the route on which the moving body has traveled on the road surface and including the position of the moving body. Calculate the difference between the two routes from the route information,
The state of the road surface is estimated from the difference of the route .
program. Of the routes that the mobile body that automatically drives on the road surface is scheduled to travel and includes the position of the moving body, the first route information indicating the route calculated at the first time and the first route information calculated at the second time. The difference between the two routes of the second route information indicating the route is calculated.
The state of the road surface is estimated from the difference of the route .
program. Recorded information of the steering angle amount including the first steering angle amount information indicating the steering angle amount input to the moving body and the second steering angle amount information indicating the steering angle amount driven by the moving body, and input to the moving body. From the recorded information of at least one of the recorded information of the acceleration amount including the first acceleration amount information indicating the acceleration amount and the second acceleration amount information indicating the acceleration amount actually driven by the moving body.
The difference of at least one of the first difference between the first steering angle amount information and the second steering angle amount information and the second difference between the first acceleration amount information and the second acceleration amount information is calculated.
The state of the road surface on which the moving body has traveled is estimated from the difference of at least one of the first difference and the second difference.
program.

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