JP7693575B2 - Information processing device, information processing method, and program - Google Patents

Description

Embodiments of the present invention relate to an information processing device, an information processing method, and a program.

Vehicles such as transport vehicles are used indoors, such as in factories or plants. Because such vehicles are used indoors, they cannot use a Global Positioning System (GPS). Therefore, the vehicles need to estimate the distance they have traveled.

One method a vehicle can use to estimate the distance it has traveled is to estimate the distance based on its own vibrations and the road surface (e.g., concrete or carpet).

However, conventional vehicles have the problem of being unable to properly estimate the distance traveled when the road surface changes while in motion.

JP 2016-166853 A

To solve the above problem, we provide an information processing device, information processing method, and program that can effectively estimate travel distance.

According to an embodiment, the information processing device includes a sensor interface, a memory, and a processor. The sensor interface is connected to an inertial sensor that measures the angular velocity or acceleration acting on the vehicle as inertial information, and a movement amount sensor that measures the movement amount of the vehicle. The memory stores road surface determination function information related to a road surface determination function that indicates the relationship between the inertial information and the movement amount for each road surface pattern, and speed calculation function information related to a speed calculation function that calculates the movement speed of the vehicle for each road surface pattern. The processor acquires the inertial information and the movement amount from the inertial sensor and the movement amount sensor via the sensor interface, determines the road surface pattern on which the vehicle runs based on the acquired inertial information and the movement amount and the road surface determination function information, calculates the movement speed of the vehicle based on the inertial information and the speed calculation function information corresponding to the determined road surface pattern, and the movement distance of the vehicle based on the movement speed of the vehicle.

FIG. 1 is a diagram illustrating an example of the configuration of a vehicle system according to a first embodiment. FIG. 2 is a diagram illustrating an example of the configuration of a vehicle according to the first embodiment. FIG. 3 is a block diagram illustrating an example of the configuration of the information processing apparatus according to the first embodiment. FIG. 4 is a block diagram illustrating an example of the configuration of the inertial sensor according to the first embodiment. FIG. 5 is a block diagram showing an example of the configuration of the image sensor according to the first embodiment. FIG. 6 is a block diagram showing an example of the configuration of the weight sensor according to the first embodiment. FIG. 7 is a block diagram showing an example of the configuration of a reference position transmission device according to the first embodiment. FIG. 8 is a graph showing an example of a road surface judgment function according to the first embodiment. FIG. 9 is a graph showing an example of a corrected road surface judgment function according to the first embodiment. FIG. 10 is a flowchart illustrating an example of the operation of the information processing device according to the first embodiment. FIG. 11 is a flowchart illustrating an example of the operation of the information processing device according to the second embodiment. FIG. 12 is a diagram illustrating an example of the configuration of a vehicle according to the third embodiment. FIG. 13 is a block diagram illustrating an example of the configuration of a distance sensor according to the third embodiment. FIG. 14 is a flowchart illustrating an example of the operation of the information processing device according to the third embodiment.

Hereinafter, embodiments will be described with reference to the drawings.
(First embodiment)
First, the first embodiment will be described.
A vehicle system according to an embodiment estimates a travel distance traveled by a vehicle. The vehicle system determines a road surface (concrete, carpet, etc.) on which the vehicle is traveling based on information from a sensor of the vehicle. The vehicle system estimates the travel distance of the vehicle based on the determination result. For example, the vehicle system estimates the travel distance of the vehicle based on the determination result and the angular velocity of the vehicle, etc.
For example, the vehicle system is used in a factory, a warehouse, a plant, or the like.

Figure 1 shows an example of the configuration of a vehicle system 1000 according to an embodiment. As shown in Figure 1, the vehicle system 1000 is composed of a reference position transmission device 6 and a vehicle 10.

The reference position transmission device 6 is installed at a predetermined reference position. The reference position transmission device 6 wirelessly transmits reference position information indicating the reference position in which it is installed to vehicles 10 present within a predetermined range. The reference position transmission device 6 will be described in detail later.

Vehicle 10 is a vehicle that travels along passageway R. Vehicle 10 travels while carrying a specified load of luggage, etc. Vehicle 10 may be self-propelled. Vehicle 10 may also be towed or pushed by an operator, a robot, etc.

Figure 2 shows a schematic example of the configuration of the vehicle 10. In Figure 2, the traveling direction of the vehicle 10 is the X-axis (horizontal axis), the axis perpendicular to the X-axis and the horizontal direction is the Y-axis (horizontal axis), and the vertical direction is the Z-axis.

As shown in FIG. 2, the vehicle 10 includes an inertial sensor 20, an image sensor 30, a weight sensor 40, a vehicle body 90, and an information processing device 100. The information processing device 100 is connected to the inertial sensor 20, the image sensor 30, and the weight sensor 40.

The vehicle body 90 is the base that constitutes the vehicle 10. The vehicle body 90 has a movable structure. When the vehicle body 90 is self-propelled, it is composed of tires and a motor that drives the tires. When the vehicle body 90 is not self-propelled, it is composed of tires and a handle.

The vehicle body 90 is equipped with an inertial sensor 20, an image sensor 30, a weight sensor 40, and an information processing device 100.

The inertial sensor 20 is a sensor that measures the angular velocity and acceleration acting on the vehicle 10. The inertial sensor 20 measures the angular velocity around the X-axis, Y-axis, and Z-axis as the angular velocity. The inertial sensor 20 also measures the acceleration in the X-axis, Y-axis, and Z-axis directions as the acceleration. The inertial sensor 20 will be described in detail later.

The image sensor 30 (movement amount sensor) is a sensor that captures an image of the road surface on which the vehicle 10 is traveling. The image sensor 30 captures an image downward from the vehicle body 90. The image sensor 30 functions as a sensor that measures the amount of movement of the vehicle 10. The image sensor 30 will be described in detail later.

The weight sensor 40 is a sensor that measures the weight of luggage carried by the vehicle 10. For example, the weight sensor 40 is installed under the loading platform. The weight sensor 40 will be described in detail later.

The information processing device 100 estimates the distance traveled by the vehicle 10 based on information from the inertial sensor 20, the image sensor 30, and the weight sensor 40. The information processing device 100 also estimates the orientation of the vehicle 10. The information processing device 100 estimates the position of the vehicle 10 based on the travel distance and orientation.

Figure 3 shows an example of the configuration of the information processing device 100. As shown in Figure 3, the information processing device 100 includes a processor 11, a ROM 12, a RAM 13, an NVM 14, a communication unit 15, a sensor interface 16, an operation unit 17, and a display unit 18.

The processor 11, the ROM 12, the RAM 13, the NVM 14, the communication unit 15, the sensor interface 16, the operation unit 17, and the display unit 18 are connected to one another via a data bus or an interface.
The information processing device 100 may include components as necessary in addition to the components shown in FIG. 3, or specific components may be excluded from the information processing device 100.

The processor 11 has the function of controlling the operation of the entire information processing device 100. The processor 11 may include an internal cache and various interfaces. The processor 11 realizes various processes by executing programs stored in advance in the internal memory, the ROM 12, or the NVM 14.

Note that some of the various functions realized by the processor 11 executing the program may be realized by a hardware circuit. In this case, the processor 11 controls the functions executed by the hardware circuit.

ROM 12 is a non-volatile memory in which control programs, control data, etc. are pre-stored. The control programs and control data stored in ROM 12 are pre-installed according to the specifications of the information processing device 100.

RAM 13 is a volatile memory. RAM 13 temporarily stores data being processed by processor 11. RAM 13 stores various application programs based on instructions from processor 11. RAM 13 may also store data required for the execution of application programs and the execution results of application programs.

NVM14 is a non-volatile memory to which data can be written and rewritten. NVM14 is composed of, for example, a hard disk drive (HDD), a solid state drive (SSD), or a flash memory. NVM14 stores control programs, applications, various data, etc. according to the operational use of information processing device 100.

The NVM 14 prestores road surface determination function information that indicates a road surface determination function used by the processor 11 to determine the road surface (road surface pattern). The road surface determination function will be described in detail later.

The NVM 14 also stores in advance speed calculation function information indicating a speed calculation function used by the processor 11 to calculate the moving speed of the vehicle 10. The speed calculation function will be described in detail later.

The communication unit 15 (communication interface) is an interface for communicating with the reference position transmission device 6. For example, the communication unit 15 connects wirelessly to the reference position transmission device 6. For example, the communication unit 15 is an interface that supports wireless LAN (Local Area Network) connection, Bluetooth (registered trademark) connection, UWB (Ultra Wide Band) communication, or the like.

The sensor interface 16 is an interface for communicating with the inertial sensor 20, the image sensor 30, and the weight sensor 40. For example, the sensor interface 16 is an interface that supports a wired or wireless LAN connection.

The sensor interface 16 may be composed of an interface for communicating with the inertial sensor 20, an interface for communicating with the image sensor 30, and an interface for communicating with the weight sensor 40.

The sensor interface 16 may also be formed integrally with the communication unit 15.

The operation unit 17 (operation interface) accepts various operation inputs from an operator. The operation unit 17 transmits a signal indicating the input operation to the processor 11. For example, the operation unit 17 is composed of a button or a touch panel.

The display unit 18 displays various information according to control from the processor 11. For example, the display unit 18 is composed of a lamp or a liquid crystal monitor. When the operation unit 17 is composed of a touch panel, the display unit 18 is formed integrally with the touch panel as the operation unit 17.

Next, the inertial sensor 20 will be described.
Fig. 4 shows an example of the configuration of the inertial sensor 20. As shown in Fig. 4, the inertial sensor 20 includes an inertial information acquisition unit 21 and a communication unit 22. The inertial information acquisition unit 21 and the communication unit 22 are connected to each other.

The inertial information acquisition unit 21 acquires inertial information indicating the angular velocity and acceleration acting on the vehicle 10. The inertial information indicates the angular velocity around the X-axis, Y-axis, and Z-axis, and the acceleration in the X-axis, Y-axis, and Z-axis directions. The inertial information acquisition unit 21 transmits the acquired inertial information to the communication unit 22.

The communication unit 22 is an interface for communicating with the information processing device 100. For example, the communication unit 22 is an interface that supports a wired or wireless LAN connection.
The communication unit 22 transmits the inertial information from the inertial information acquisition unit 21 to the information processing device 100 .

Next, the image sensor 30 will be described.
Fig. 5 shows an example of the configuration of the image sensor 30. As shown in Fig. 5, the image sensor 30 includes an image acquisition unit 31 and a communication unit 32. The image acquisition unit 31 and the communication unit 32 are connected to each other.

The image acquisition unit 31 acquires an image of the road surface on which the vehicle 10 is traveling. The image acquisition unit 31 is composed of a camera and the like. The image acquisition unit 31 may also be equipped with a light that illuminates the road surface. The image acquisition unit 31 transmits the acquired image to the communication unit 32.

The communication unit 32 is an interface for communicating with the information processing device 100. For example, the communication unit 32 is an interface that supports a wired or wireless LAN connection.
The communication unit 22 transmits the image from the image acquisition unit 31 to the information processing device 100 .

Next, the weight sensor 40 will be described.
Fig. 6 shows an example of the configuration of the weight sensor 40. As shown in Fig. 4, the weight sensor 40 includes a weight acquisition unit 41 and a communication unit 42. The weight acquisition unit 41 and the communication unit 42 are connected to each other.

The weight acquisition unit 41 acquires the weight of the luggage carried by the vehicle 10. The weight acquisition unit 41 transmits the acquired weight to the communication unit 42.

The communication unit 42 is an interface for communicating with the information processing device 100. For example, the communication unit 42 is an interface that supports a wired or wireless LAN connection.
The communication unit 42 transmits the weight from the weight acquisition unit 41 to the information processing device 100 .

Next, the reference position transmitting device 6 will be described.
Fig. 7 shows an example of the configuration of the reference position transmission device 6. As shown in Fig. 7, the reference position transmission device 6 is composed of a storage unit 61, a communication unit 62, etc. The storage unit 61 and the communication unit 62 are connected to each other.

The storage unit 61 prestores reference position information indicating the reference position where the reference position transmission device 6 is installed. The storage unit 61 may update the reference position information in accordance with an operation by an operator.

The communication unit 62 is an interface for communicating with the information processing device 100. For example, the communication unit 62 is an interface that supports a wireless LAN connection, a Bluetooth connection, or a UWB connection.

The communication unit 62 transmits the reference position information stored in the storage unit 61 to the information processing device 100. For example, the communication unit 62 transmits the reference position information at a predetermined interval to the information processing device 100 that is present within a predetermined range (a range of a predetermined distance from the reference position transmission device 6).

Next, the road surface judgment function will be described.
Fig. 8 is a graph showing an example of the road surface judgment function. In Fig. 8, the horizontal axis indicates the movement amount (e.g., the movement amount per unit time, m) of the vehicle 10 estimated from the image acquired by the image sensor 30. The vertical axis indicates the standard deviation (g) of the angular velocity around the X-axis and Y-axis indicated by the inertial information.

Figure 8 shows graphs 71 to 73. Here, graphs 71 to 73 are assumed to be linear. Graphs 71 to 73 also show the relationship between m and g when the vehicle 10 is not loaded with luggage (when the weight sensor 40 measures 0).

Graph 71 shows the relationship between m and g on road surface 1. Graph 71 is expressed by the following formula.

Graph 72 shows the relationship between m and g on road surface 2. Graph 72 is expressed by the following formula.

Graph 73 shows the relationship between m and g on road surface 3. Graph 73 is expressed by the following formula.

The road surface judgment function information stores the coefficients of graphs 71 to 73. That is, the road surface judgment function information is

Multiple sets are stored as one road surface set, where i indicates the road surface.

The number of coefficient sets stored in the road surface judgment function information may be two or more, and is not limited to a specific number.

Next, the functions realized by the information processing device 100 will be described. The functions realized by the information processing device 100 are realized by the processor 11 executing a program stored in the internal memory, the ROM 12, the NVM 14, or the like.

First, the processor 11 has a function of inputting the number of road surfaces to be determined (number of road surfaces).
For example, if the operator knows in advance the number of road surfaces on which the vehicle 10 will be traveling, the operator inputs this number as the number of road surfaces into the operation unit 17 of the vehicle 10 or the like.

The processor 11 determines the road surface based on the number of road surfaces that has been input. That is, when the processor 11 determines the same number of road surfaces as the number of road surfaces, it thereafter determines the road surface on which the vehicle 10 is traveling from among the road surfaces that have been determined so far. For example, when the processor 11 inputs 2 as the number of road surfaces, after determining two different road surfaces, it determines one of the two determined road surfaces as the road surface on which the vehicle 10 is traveling.

The processor 11 also has the function of calculating the standard deviation of the angular velocity acting on the vehicle 10.

The processor 11 acquires inertial information from the inertial sensor 20 while traveling. When the processor 11 acquires the inertial information, the processor 11 acquires the angular velocities around the X-axis and the Y-axis from the inertial information. Here, the processor 11 acquires the angular velocities around the X-axis and the Y-axis for a predetermined period (for example, 1 second).

Once the angular velocities around the X-axis and Y-axis are obtained, the processor 11 calculates the standard deviation (g) of the combined distribution of the angular velocities around the X-axis and the Y-axis.

The processor 11 also has the function of estimating the amount of movement based on the image from the image sensor 30.

The processor 11 acquires images from the image sensor 30 over a predetermined period (e.g., one second). Upon acquiring the images, the processor 11 calculates the amount of movement of the vehicle 10 (e.g., the amount of movement per unit time) based on the images over the predetermined period.

For example, the processor 11 determines the amount of movement on the XY plane from the change in pixel shading between images acquired at different times. For example, the processor 11 determines the amount of movement using the Lucas-Kanade method, which is a representative method for estimating the amount of movement.

The processor 11 may use distance or number of pixels as a unit of movement amount.

In addition, the processor 11 may have the image sensor 30 calculate the amount of movement based on images captured during a specified period, and the processor 11 may acquire the calculated amount of movement from the image sensor 30.

The processor 11 also has the function of modifying the road surface judgment function based on the weight of the luggage loaded on the vehicle 10.

The processor 11 acquires the weight of the luggage loaded on the vehicle 10 through the weight sensor 40. Note that the processor 11 does not need to correct the coefficient if the weight is equal to or less than a predetermined threshold.

Once the weight is obtained, the processor 11 modifies the coefficients based on the weight.
The standard deviation of the angular velocity of the vehicle 10 is reduced as the weight increases, so the processor 11 corrects the coefficients so that the value of g becomes smaller as the weight increases.

Figure 9 is a graph showing an example of coefficients modified by processor 11. In the example shown in Figure 9, processor 11 modifies c i .

Figure 9 shows graphs 71, 71' and 71''.

Graph 71 is as described above.

Graph 71' is a graph in which the coefficient c1 of graph 71 has been modified. Graph 71' is a graph in the case where the vehicle 10 is loaded with a specified weight of luggage. As shown in FIG. 9, graph 71' is formed below graph 71. That is, g of graph 71' is smaller than that of graph 71 at the same m.

Graph 71'' is a graph in which c1 is further modified than in graph 71'. Graph 71'' is a graph in the case where the vehicle 10 is loaded with a heavier load. As shown in FIG. 9, graph 71'' is formed below graph 71'. That is, g in graph 71'' is smaller than that in graph 71' at the same m.

The processor 11 similarly modifies the coefficients of the road surface judgment functions corresponding to other road surfaces.

The processor 11 may modify ai and bi. The method by which the processor 11 modifies the coefficients is not limited to a specific method.

The processor 11 also has the function of determining the road surface on which the vehicle 10 is traveling based on the standard deviation (g) of the angular velocity and the amount of movement (m) from the image.

Here, the processor 11 identifies the corrected road surface judgment function that is closest to g and m.
For example, the processor 11 calculates the distance between g and m and the corrected road surface judgment function according to the following equation.

Here, di indicates the distance. Also, ai, bi, and ci indicate the modified coefficients.

The processor 11 identifies the modified road surface determination function with the smallest distance. When the modified road surface determination function with the smallest distance is identified, the processor 11 determines that the road surface corresponding to the identified road surface determination function is the road surface on which the vehicle 10 is traveling.

The processor 11 also has the function of calculating the travel distance of the vehicle 10 based on the determined road surface.

Once the road surface is determined, the processor 11 sets a speed calculation function that corresponds to the determined road surface.

The speed calculation function is expressed by the following formula:

Here, v indicates the moving speed of the vehicle 10, g indicates the standard deviation of the angular velocity, and i indicates the road surface.

The speed calculation function information stores the coefficients of the above formula. In other words, the calculation function information is

Multiple sets are stored as one road surface set.

The processor 11 substitutes g into the set speed calculation function to calculate the speed of the vehicle 10. Once the speed is calculated, the processor 11 integrates the speed over time to calculate the traveled distance.

The processor 11 may set a speed calculation function into which the amount of movement can be substituted to calculate the speed, and calculate the speed of the vehicle 10 based on the amount of movement. The processor 11 may also set a speed calculation function into which the amount of movement and the standard deviation of the angular velocity can be substituted to calculate the speed, and calculate the speed of the vehicle 10 based on the amount of movement and the standard deviation of the angular velocity.

The processor 11 also updates the location information indicating the current location of the vehicle 10 based on the traveled distance. For example, the NVM 14 stores the location information.

For example, the processor 11 determines the orientation of the vehicle 10 by correcting the angular velocity around the z-axis with an offset and integrating it over time. The processor 11 determines the position of the vehicle 10 based on the vehicle's orientation and traveled distance, and updates the position information.

The processor 11 also has the function of updating the position information based on the reference position information from the reference position transmission device 6.

For example, while traveling, the processor 11 determines whether reference position information has been received through the communication unit 15. If it is determined that reference position information has been received, the processor 11 updates the existing position information to position information that indicates the reference position indicated by the received reference position information as the position of the vehicle 10.

Next, an example of the operation of the information processing device 100 will be described.
FIG. 10 is a flowchart for explaining an example of the operation of the information processing device 100.

First, the processor 11 inputs the number of road surfaces via the operation unit 17 or the like (S11). Once the number of road surfaces has been input, the processor 11 calculates the standard deviation of the angular velocities around the X-axis and Y-axis acquired from the inertial sensor 20 (S12). Once the standard deviation of the angular velocities has been calculated, the processor 11 estimates the amount of movement based on the image from the image sensor 30 (S13).

After estimating the amount of movement, the processor 11 obtains the weight of the luggage loaded on the vehicle 10 using the weight sensor 40 (S14). After obtaining the weight, the processor 11 modifies the coefficients of the road surface judgment function based on the weight (S15).

After correcting the coefficients of the road surface judgment functions, the processor 11 calculates the standard deviation and the distance between each road surface judgment function and the movement amount (S16). After calculating the distance between each road surface judgment function and the standard deviation and the movement amount, the processor 11 judges the road surface based on the calculated distances (S17).

When the road surface is determined, the processor 11 sets a speed calculation function corresponding to the determined road surface (S18). When the speed calculation function is set, the processor 11 calculates the travel distance of the vehicle 10 based on the set speed calculation function (S19).

After calculating the travel distance, the processor 11 updates the location information based on the travel distance (S20). After updating the location information, the processor 11 determines whether or not reference location information has been received through the communication unit 15 (S21).

When it is determined that the reference position information has been received (S21, YES), the processor 11 updates the position information based on the received reference position information (S22).

If it is determined that the reference location information has not been received (S21, NO), or if the location information has been updated based on the received reference location information (S22), the processor 11 returns to S12.

The processor 11 does not need to input the number of road surfaces. In this case, the processor 11 determines the road surface corresponding to the road surface determination function for which g and m are closest as the road surface on which the vehicle 10 is traveling, regardless of the road surface determined so far.

In addition, the processor 11 does not need to obtain the weight of the vehicle 10. In this case, the processor 11 does not need to modify the coefficients of the road surface judgment function.

The processor 11 may also modify the standard deviation (g) of the angular velocity based on the weight carried by the vehicle 10. For example, the processor 11 may multiply the standard deviation of the angular velocity by a coefficient corresponding to the weight.

In addition, the road surface judgment function does not have to be linear. The configuration of the road surface judgment function is not limited to a specific configuration.

The processor 11 may also include a plurality of image sensors 30. For example, the processor 11 may calculate m based on a plurality of images.
Furthermore, the vehicle 10 may be equipped with a sensor that detects the rotation of a tire installed on the vehicle body 90. In this case, the processor 11 may calculate m based on the rotation of the tire. The method by which the processor 11 calculates m is not limited to a specific method.

The inertial sensor 20 may also be an angular velocity sensor that acquires only the angular velocity acting on the vehicle 10.

The processor 11 may also calculate g using acceleration instead of angular velocity.
Furthermore, the vehicle system 1000 does not necessarily have to have the information processing device 100 mounted on the vehicle 10. That is, the information processing device 100 may be disposed outside the vehicle 10 as a higher-level device.

The vehicle system configured as described above determines the road surface based on the standard deviation of the angular velocity of the vehicle and the travel distance. The vehicle system calculates the travel speed based on the determined road surface, and calculates the travel distance of the vehicle. As a result, the vehicle system can effectively estimate the travel distance of the vehicle even if the road surface changes while the vehicle is traveling.
Second Embodiment
Next, a second embodiment will be described.
The vehicle system according to the second embodiment differs from that according to the first embodiment in that the speed calculation function is updated when the same road surface is determined to be the road surface on which the vehicle 10 is traveling during a predetermined period of time. Therefore, the other points are denoted by the same reference numerals and detailed description thereof is omitted.

The configuration of the vehicle system 1000 according to the second embodiment is similar to that according to the first embodiment, so a description thereof will be omitted.

Next, a description will be given of functions realized by the information processing apparatus 100. The functions realized by the information processing apparatus 100 are realized by the processor 11 executing a program stored in the internal memory, the ROM 12, the NVM 14, or the like.
Furthermore, the information processing device 100 realizes the following functions in addition to the functions realized by the information processing device 100 according to the first embodiment.

The processor 11 has the function of updating the speed calculation function when the same road surface is determined within a specified period of time.

When the road surface is determined, processor 11 calculates the period during which the same road surface was determined. After calculating the period, processor 11 determines whether the period exceeds a predetermined threshold (e.g., several seconds to several tens of seconds). When it determines that the period exceeds the predetermined threshold, processor 11 updates the speed calculation function used to calculate the speed from the current speed calculation function to a speed calculation function that corresponds to the determined road surface.

If it is determined that the period does not exceed the predetermined threshold, the processor 11 maintains the current speed calculation function (the currently set speed calculation function) as the speed calculation function to be used to calculate the speed.

If the current speed calculation function is not set, the processor 11 may set a speed calculation function corresponding to the determined road surface, regardless of the length of the period.

Next, an example of the operation of the information processing device 100 will be described.
FIG. 11 is a flowchart for explaining an example of the operation of the information processing device 100.

First, the processor 11 inputs the number of road surfaces via the operation unit 17 or the like (S31). Once the number of road surfaces has been input, the processor 11 calculates the standard deviation of the angular velocities around the X-axis and Y-axis acquired from the inertial sensor 20 (S32). Once the standard deviation of the angular velocities has been calculated, the processor 11 estimates the amount of movement based on the image from the image sensor 30 (S33).

After estimating the amount of movement, the processor 11 obtains the weight of the luggage loaded on the vehicle 10 using the weight sensor 40 (S34). After obtaining the weight, the processor 11 modifies the coefficients of the road surface judgment function based on the weight (S35).

After correcting the coefficients of the road surface judgment functions, the processor 11 calculates the standard deviation and the distance between each road surface judgment function and the movement amount (S36). After calculating the distance between each road surface judgment function and the standard deviation and the movement amount, the processor 11 judges the road surface based on the calculated distances (S37).

After determining the road surface, the processor 11 determines whether the period during which the same road surface was determined exceeds a predetermined threshold (S38).

When it is determined that the period during which the same road surface has been determined exceeds the predetermined threshold value (S38, YES), the processor 11 updates the speed calculation function (S39).
When it is determined that the period during which the same road surface has been determined does not exceed the predetermined threshold value (NO in S38), the processor 11 maintains the speed calculation function (S40).

When the speed calculation function is updated (S39) or when the speed calculation function is maintained (S40), the processor 11 calculates the travel distance of the vehicle 10 based on the speed calculation function (S41).

When the movement distance is calculated, the processor 11 updates the position information based on the movement distance (S42). After updating the position information, the processor 11 determines whether reference position information has been received through the communication unit 15 (S43).

When it is determined that the reference position information has been received (S43, YES), the processor 11 updates the position information based on the received reference position information (S44).

If it is determined that the reference position information has not been received (S43, NO), or if the position information has been updated based on the received reference position information (S44), the processor 11 returns to S32.

The vehicle system configured as described above calculates the vehicle's moving speed using a speed calculation function corresponding to the determined road surface when the road surface determination continues for a predetermined period of time. As a result, the vehicle system can properly determine the road surface even if a momentary erroneous determination of the road surface occurs due to noise in the inertial sensor or image sensor.
Third Embodiment
Next, a third embodiment will be described.
The vehicle system according to the third embodiment differs from that according to the first embodiment in that the road surface is determined based on the unevenness of the road surface as well. Therefore, the other features are denoted by the same reference numerals and detailed description thereof will be omitted.

Figure 1 shows an example of the configuration of a vehicle system 1000' according to the third embodiment. As shown in Figure 1, the vehicle system 1000' is composed of a reference position transmission device 6 and a vehicle 10'.

Figure 12 shows a schematic configuration example of a vehicle 10'. In Figure 12, the traveling direction of the vehicle 10' is the X-axis, the axis perpendicular to the X-axis and the horizontal direction is the Y-axis, and the vertical direction is the Z-axis.

As shown in FIG. 12, the vehicle 10' includes an inertial sensor 20, an image sensor 30, a weight sensor 40, a distance sensor 50, a vehicle body 90, and an information processing device 100. The information processing device 100 is connected to the inertial sensor 20, the image sensor 30, the weight sensor 40, and the distance sensor 50.

The distance sensor 50 is a sensor that measures the distance (road surface distance) from a predetermined position (for example, the position where the distance sensor 50 is installed) to the road surface. The distance sensor 50 is installed facing downward on the lower part of the vehicle body 90. The distance sensor 50 will be described in detail later.

The sensor interface 16 of the information processing device 100 is an interface for communicating with the inertial sensor 20, the image sensor 30, the weight sensor 40, and the distance sensor 50.

Next, the distance sensor 50 will be described.
Fig. 13 shows an example of the configuration of the distance sensor 50. As shown in Fig. 13, the distance sensor 50 includes a distance information acquisition unit 51 and a communication unit 52. The distance information acquisition unit 51 and the communication unit 52 are connected to each other.

The distance information acquisition unit 51 acquires distance information indicating the distance from a predetermined position (for example, the position where the distance sensor 50 is installed) to the road surface. For example, the distance information acquisition unit 51 is composed of an irradiation unit that irradiates a laser and a light receiving unit that receives the laser reflected from the road surface. The distance information acquisition unit 51 may employ a ToF (Time-for-Flight) method that measures the distance to the road surface based on the time it takes for the irradiated laser to reflect off the road surface and reach the light receiving unit.

The communication unit 52 is an interface for communicating with the information processing device 100. For example, the communication unit 52 is an interface that supports a wired or wireless LAN connection.
The communication unit 52 transmits the distance information from the distance information acquisition unit 51 to the information processing device 100 .

Next, a description will be given of functions realized by the information processing apparatus 100. The functions realized by the information processing apparatus 100 are realized by the processor 11 executing a program stored in the internal memory, the ROM 12, the NVM 14, or the like.
Furthermore, the information processing device 100 realizes the following functions in addition to the functions realized by the information processing device 100 according to the first embodiment.

First, the processor 11 has a function of calculating an evaluation value indicating the characteristics of the unevenness of the road surface based on the distance information from the distance sensor 50.
The processor 11 acquires distance information from the distance sensor 50 for a predetermined period (for example, one to several seconds). When the processor 11 acquires the distance information, the processor 11 calculates an evaluation value indicating the characteristic amount of unevenness of the road surface based on the acquired distance information.

For example, the processor 11 calculates the difference between the maximum and minimum distance values as the evaluation value. The processor 11 may also calculate the standard deviation (or variance) of the distances as the evaluation value. The method by which the processor 11 calculates the evaluation value is not limited to a specific method. The evaluation value may also be composed of multiple values.

The processor 11 also has the function of determining whether the determined road surface is consistent with the evaluation value calculated from the distance information.

For example, the NVM 14 stores in advance an evaluation value indicating the characteristics of the unevenness of each road surface.
The processor 11 acquires an evaluation value of the determined road surface from the NVM 14. When the evaluation value is acquired from the NVM 14, the processor 11 compares the evaluation value acquired from the NVM 14 with the evaluation value calculated from the distance information.

For example, if the difference (or distance) between the two is equal to or less than a predetermined threshold, the processor 11 determines that the two evaluation values match. In other words, the processor 11 determines that the determined road surface and the evaluation value calculated from the distance information match.

Furthermore, if the difference (or distance) between the two is greater than a predetermined threshold, the processor 11 determines that the two evaluation values do not match. In other words, the processor 11 determines that the determined road surface and the evaluation value calculated from the distance information do not match.

In addition, the processor 11 has the function of updating the speed calculation function when the determined road surface matches the evaluation value calculated from the distance information.

When it is determined that the determined road surface matches the evaluation value calculated from the distance information, the processor 11 updates the speed calculation function used to calculate the speed from the current speed calculation function to a speed calculation function that corresponds to the determined road surface.

Furthermore, if it is determined that the determined road surface does not match the evaluation value calculated from the distance information, the processor 11 maintains the current speed calculation function (the currently set speed calculation function) as the speed calculation function to be used to calculate the speed.

If the current speed calculation function is not set, the processor 11 may set a speed calculation function corresponding to the determined road surface, regardless of the consistency determination result.

Next, an example of the operation of the information processing device 100 will be described.
FIG. 14 is a flowchart for explaining an example of the operation of the information processing device 100.

First, the processor 11 inputs the number of road surfaces via the operation unit 17 or the like (S51). Once the number of road surfaces has been input, the processor 11 calculates the standard deviation of the angular velocities around the X-axis and Y-axis acquired from the inertial sensor 20 (S52). Once the standard deviation of the angular velocities has been calculated, the processor 11 estimates the amount of movement based on the image from the image sensor 30 (S53).

After estimating the amount of movement, the processor 11 obtains the weight of the luggage loaded on the vehicle 10 using the weight sensor 40 (S54). After obtaining the weight, the processor 11 modifies the coefficients of the road surface judgment function based on the weight (S55).

After correcting the coefficients of the road surface judgment functions, the processor 11 calculates the standard deviation and the distance between each road surface judgment function and the movement amount (S56). After calculating the distance between each road surface judgment function and the standard deviation and the movement amount, the processor 11 judges the road surface based on the calculated distances (S57).

After determining the road surface, the processor 11 calculates an evaluation value that indicates the unevenness characteristics of the road surface based on the distance information from the distance sensor 50 (S58). After calculating the evaluation value, the processor 11 determines whether the determined road surface and the evaluation value are consistent (S59).

If it is determined that the determined road surface matches the evaluation value (S59, YES), the processor 11 updates the speed calculation function (S60).
If it is determined that the determined road surface does not match the evaluation value (NO at S59), the processor 11 maintains the speed calculation function (S61).

When the speed calculation function is updated (S60) or when the speed calculation function is maintained (S61), the processor 11 calculates the travel distance of the vehicle 10 based on the speed calculation function (S62).

When the movement distance is calculated, the processor 11 updates the position information based on the movement distance (S63). When the position information is updated, the processor 11 determines whether or not reference position information has been received through the communication unit 15 (S64).

When it is determined that the reference position information has been received (S64, YES), the processor 11 updates the position information based on the received reference position information (S65).

If it is determined that the reference position information has not been received (S64, NO), or if the position information has been updated based on the received reference position information (S65), the processor 11 returns to S52.

The processor 11 may determine the road surface based on an evaluation value calculated from the distance information. In this case, the processor 11 may update the speed calculation function when the road surface determined from g and m matches the road surface determined from the evaluation value.

The vehicle system configured as described above updates the speed calculation function when the determined road surface matches the unevenness of the road surface. As a result, the vehicle system can set the speed calculation function with greater accuracy.

Although several 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 embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the gist of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are included in the scope of the invention and its equivalents described in the claims.

1...road surface, 2...road surface, 3...road surface, 6...reference position transmission device, 10...vehicle, 10'...vehicle, 11...processor, 12...ROM, 13...RAM, 14...NVM, 15...communication unit, 16...sensor interface, 17...operation unit, 18...display unit, 20...inertial sensor, 21...inertial information acquisition unit, 22...communication unit, 30...image sensor, 31...image acquisition unit, 32...communication unit, 40...weight sensor, 41...weight acquisition unit, 42...communication unit, 50...distance sensor, 51...distance information acquisition unit, 52...communication unit, 61...storage unit, 62...communication unit, 71...graph, 71'...graph, 71''...graph, 72...graph, 73...graph, 90...vehicle body, 100...information processing device, 1000...vehicle system, 1000'...vehicle system.

Claims (13)

a sensor interface connected to an inertial sensor that measures an angular velocity or an acceleration acting on a vehicle as inertial information and a movement amount sensor that measures a movement amount of the vehicle;
a memory for storing road surface determination function information relating to a road surface determination function indicating the relationship between the inertia information and the movement amount for each road surface pattern, and speed calculation function information relating to a speed calculation function for calculating the movement speed of the vehicle for each road surface pattern;
acquiring the inertial information and the movement amount from the inertial sensor and the movement amount sensor via the sensor interface;
determining the road surface pattern on which the vehicle is traveling based on the acquired inertia information and the amount of movement and the road surface determination function information stored in the memory;
calculating a moving speed of the vehicle based on the speed calculation function information corresponding to the determined road surface pattern and the inertia information, and calculating a moving distance of the vehicle based on the moving speed of the vehicle;
A processor;
An information processing device comprising: The inertial sensor measures an angular velocity acting on the vehicle,
The processor,
Calculating a standard deviation of the angular velocity about a horizontal axis based on the angular velocity acquired from the inertial sensor via the sensor interface;
Calculating a distance between the point represented by the standard deviation and the amount of movement and the road surface judgment function;
determining the road surface pattern based on the distance;
The information processing device according to claim 1 . the processor calculates a moving speed of the vehicle based on the standard deviation and the speed calculation function.
The information processing device according to claim 2 . The movement amount sensor is an image sensor.
The information processing device according to claim 1 . The road surface judgment function is a linear function.
The information processing device according to claim 1 . the sensor interface is connected to a weight sensor that measures a weight of luggage loaded on the vehicle;
The processor modifies the road surface judgment function based on the weight.
The information processing device according to claim 1 . An operation interface is provided for receiving operation input;
The processor obtains, through the operation interface, an input of the number of the road surface patterns to be targeted when determining the road surface pattern.
The information processing device according to claim 1 . When the processor determines that the same road surface pattern is present during a predetermined period of time, the processor calculates a travel distance of the vehicle based on the determined road surface pattern.
The information processing device according to claim 1 . The sensor interface is connected to a distance sensor that measures a road distance, which is a distance between the vehicle and a road surface on which the vehicle is traveling;
The processor,
Calculating an evaluation value based on the road surface distance;
If the determined road surface pattern matches the evaluation value, a travel distance of the vehicle is calculated based on the determined road surface pattern.
The information processing device according to claim 1 . The memory stores location information indicating a location of the vehicle;
The processor updates position information indicating a position of the vehicle based on a distance traveled by the vehicle.
The information processing device according to claim 1 . A communication interface for connecting to other devices is provided.
When the processor receives reference position information indicating a reference position through the communication interface, the processor updates the position information based on the reference position information.
The information processing device according to claim 10. 1. An information processing method executed by a processor, comprising:
Angular velocity or acceleration acting on the vehicle is measured as inertial information,
Measure the amount of movement of the vehicle;
determining the road surface pattern on which the vehicle is traveling based on the acquired inertia information and the movement amount, and road surface determination function information relating to a road surface determination function that indicates a relationship between the inertia information and the movement amount for each road surface pattern;
Calculating a moving speed of the vehicle based on speed calculation function information for calculating a moving speed of the vehicle corresponding to the determined road surface pattern and the inertia information;
Calculating a travel distance of the vehicle based on a travel speed of the vehicle;
Information processing methods. A program executed by a processor,
The processor,
A function to measure the angular velocity or acceleration acting on the vehicle as inertial information;
A function of measuring the amount of movement of the vehicle;
a function of determining the road surface pattern on which the vehicle is traveling based on the acquired inertia information and the movement amount, and road surface determination function information relating to a road surface determination function that indicates a relationship between the inertia information and the movement amount for each road surface pattern;
A function of calculating a moving speed of the vehicle based on speed calculation function information that calculates a moving speed of the vehicle corresponding to the determined road surface pattern and the inertia information;
A function of calculating a travel distance of the vehicle based on a travel speed of the vehicle;
A program to achieve this.