Moving obstacle detection support program, moving obstacle detection support device, moving obstacle detection support method, and recording medium

Abstract

To provide a moving obstacle detection support program that enables easy estimation of factors that impede movement on a road surface.SOLUTION: The moving obstacle detection support program of the present disclosure includes a moving obstruction factor estimation procedure, which estimates moving obstruction factors of a road surface on which the mobile body has traveled based on moving obstruction factor information including at least one of gravity information and acceleration information when the mobile body is moving.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a moving obstacle detection support program, a moving obstacle detection support device, a moving obstacle detection support method, and a recording medium. [Background technology]

[0002] Wheeled mobile objects such as wheelchairs have difficulty traveling when there are steps or steep slopes on the road surface. Therefore, barrier-free maps have been created that display slopes and steps on a map to make it easier for wheelchair users to travel. For example, Patent Document 1 describes a display system that includes: a storage means for storing barrier points that may be an obstacle to the travel of the mobile object, information about the obstacle (the magnitude of the step or slope), and map data; a determination means for determining a recommended approach direction to the step or slope when displaying the barrier point; a map information generation means for generating map information including the approach direction; and a provision means for providing the generated map information to an electronic device, the electronic device having a display means for displaying the map information provided from a server. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-056674 Summary of the Invention [Problem to be solved by the invention]

[0004] However, updating the barrier-free map is performed manually, which takes time and effort, making it difficult to continue updating the barrier-free map. Updating the barrier-free map requires detecting factors that impede the movement of moving objects on the road surface, so a simple method for detecting factors that impede movement is needed.

[0005] Therefore, an object of the present disclosure is to provide a moving obstacle detection support program, a moving obstacle detection support device, a moving obstacle detection support method, and a recording medium that can easily estimate factors that impede travel on a road surface. [Means for solving the problem]

[0006] In order to achieve the above object, the moving obstacle detection support program of the present disclosure includes: Including a procedure for estimating factors impeding mobility, the travel-impedance factor estimation step estimates a travel-impedance factor of a road surface on which the moving body has traveled, based on travel-impedance factor information including at least one of gravity information and acceleration information during the movement of the moving body; The present invention provides a moving obstacle detection support program for causing a computer to execute the above-described procedures.

[0007] The moving obstacle detection support device of the present disclosure comprises: a movement obstruction factor estimation unit; The movement-impeding factor estimating unit estimates movement-impeding factors of a road surface on which the moving body has moved, based on movement-impeding factor information including at least one of gravity information and acceleration information when the moving body is moving.

[0008] The moving obstacle detection support method of the present disclosure includes: A step of estimating a factor that impedes movement, the travel obstruction factor estimation step estimates a travel obstruction factor of a road surface on which the moving body has traveled based on travel obstruction factor information including at least one of gravity information and acceleration information during the movement of the moving body; Each of the steps is a computer-implemented method.

[0009] The recording medium of the present disclosure includes: Including a procedure for estimating factors impeding mobility, the travel-impedance factor estimation step estimates a travel-impedance factor of a road surface on which the moving body has traveled, based on travel-impedance factor information including at least one of gravity information and acceleration information during the movement of the moving body; A computer-readable recording medium storing a moving obstacle detection support program for causing a computer to execute each of the above procedures. [Effects of the Invention]

[0010] According to the present disclosure, movement-impeding factors on the road surface can be easily estimated. [Brief explanation of the drawings]

[0011] [Figure 1] FIG. 1 is a block diagram showing a configuration of an example of a moving obstacle detection support device according to the present disclosure. [Figure 2] FIG. 2 is a block diagram showing an example of a hardware configuration of a moving obstacle detection support device according to the present disclosure. [Figure 3] FIG. 3 is a flowchart showing an example of a procedure according to the movement obstacle detection support program of the present disclosure. [Figure 4] FIG. 4 is a block diagram showing the configuration of another example of a moving obstacle detection support device according to the present disclosure. [Figure 5] FIG. 5 is a flowchart showing another example of the procedure of the movement obstacle detection support program of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. The present disclosure is not limited to the following embodiments. In the following drawings, identical parts are designated by the same reference numerals. Furthermore, the descriptions of the embodiments can be used interchangeably unless otherwise specified, and the configurations of the embodiments can be combined unless otherwise specified. In the present disclosure, each drawing may apply to one or more embodiments.

[0013] In the present disclosure, the term "mobile object" is not particularly limited and may be, for example, an object with wheels. Specific examples of the mobile object include a wheelchair, a walking aid (also known as a silver cart), a stroller, a bicycle, and a kick scooter.

[0014] [Embodiment 1] The travel obstacle detection support program of the present disclosure is a program for causing a computer to execute a travel obstacle estimation procedure. The travel obstacle detection support program of the present disclosure can also be said to be a program for causing a computer to function as a travel obstacle estimation procedure. Furthermore, the travel obstacle detection support program of the present disclosure can also be said to be a program for causing a computer to execute, for example, each step of a travel obstacle detection support method described below.

[0015] The movement-impeding factor estimating step estimates a movement-impeding factor of a road surface on which the moving body has moved, based on movement-impeding factor information including at least one of gravity information and acceleration information when the moving body is moving.

[0016] In each of the steps, for example, "step" can be read as "processing." The mobility obstacle detection support program of the present disclosure may be recorded on, for example, a computer-readable recording medium. The recording medium is, for example, a non-transitory computer-readable storage medium. The recording medium is not particularly limited, and examples thereof include random access memory (RAM), read-only memory (ROM), hard disk (HD), flash memory (e.g., SSD (Solid State Drive), USB flash memory, SD / SDHC card, etc.), optical disk (e.g., CD-R / CD-RW, DVD-R / DVD-RW, BD-R / BD-RE, etc.), magneto-optical disk (MO), floppy disk (FD), etc. The mobility obstacle detection support program of the present disclosure (also referred to as, for example, a programming product or program product) may be distributed from an external computer. The "distribution" may be, for example, distribution via a communication network or via a device connected via a wire. The mobile obstacle detection support program of the present disclosure may be installed and executed on the device to which it is distributed, or may be executed without being installed. An information processing device capable of executing the mobile obstacle detection support program of the present disclosure can be referred to as, for example, a mobile obstacle detection support device of the present disclosure.

[0017] Next, the configuration of an example of a travel obstacle detection support device according to the present disclosure will be described with reference to FIG. 1. FIG. 1 is a block diagram showing an example of the configuration of a travel obstacle detection support device 10 according to the present disclosure (hereinafter also referred to as the present device 10). As shown in FIG. 1, the present device 10 includes a travel obstruction factor estimation unit 11. Although not shown, the present device 10 may also include, for example, an input unit, an output unit, a display unit, and / or a storage unit. The travel obstruction factor estimation unit 11 is capable of executing, for example, a travel obstruction factor estimation procedure in the travel obstacle detection support program according to the present disclosure.

[0018] The device 10 may be, for example, a single device including the above-described units, or a device in which the units can be connected via a communication network. The device 10 can also be connected to an external device (described later) via the communication network. The communication network is not particularly limited and any known network can be used, for example, a wired or wireless network. Examples of the communication network include the Internet, the World Wide Web (WWW), a telephone line, a Local Area Network (LAN), a Storage Area Network (SAN), a Delay Tolerant Networking (DTN), a Low Power Wide Area Network (LPWA), and a Local 5G (L5G). Examples of wireless communication include Wi-Fi (registered trademark), Bluetooth (registered trademark), Local 5G, and LPWA. Examples of the wireless communication include direct communication between devices (Ad Hoc communication), infrastructure communication, and indirect communication via an access point. The device 10 may be incorporated into a server as a system. Furthermore, the present device 10 may be, for example, a personal computer (PC, for example, desktop or notebook type) on which the program of the present disclosure is installed, a smartphone, a tablet terminal, etc. The present device 10 may be in the form of cloud computing or edge computing, for example, in which at least one of the above-mentioned units is located on a server and the other units are located on a terminal.

[0019] 2 shows a block diagram of the hardware configuration of the device 10. The device 10 includes, for example, a central processing unit (CPU, GPU, etc.) 101, a memory 102, a bus 103, a storage device 104, an input device 105, an output device 106, and a communication device 107. The components of the device 10 are connected to each other via the bus 103 and their respective interfaces (I / F).

[0020] The central processing unit 101 operates in cooperation with other components via a controller (such as a system controller or an I / O controller) and is responsible for overall control of the device 10. In the device 10, the central processing unit 101 executes, for example, the program of the present disclosure (the travel obstacle detection support program) and other programs, and also reads and writes various information. Specifically, for example, the central processing unit 101 functions as a travel obstruction factor estimation unit 11. The device 10 may include, as a computing device, other computing devices such as a CPU, a GPU (Graphics Processing Unit), an APU (Accelerated Processing Unit), or a combination of these.

[0021] The bus 103 can also be connected to, for example, external devices. Examples of the external devices include an external storage device (such as an external database), a printer, an external input device, an external display device, and an external imaging device. The device 10 can be connected to an external network (the communication line network) by, for example, a communication device 107 connected to the bus 103, and can also be connected to other devices via the external network.

[0022] The memory 102 may be, for example, a main memory (primary storage device). When the central processing unit 101 performs processing, the memory 102 reads various operating programs, such as the program of the present disclosure, stored in the storage device 104 (described later), and the central processing unit 101 receives data from the memory 102 and executes the programs. The main memory may be, for example, a RAM (random access memory). The memory 102 may also be, for example, a ROM (read only memory).

[0023] The storage device 104 is also referred to as an auxiliary storage device, for example, in contrast to the main memory (primary storage device). As described above, the storage device 104 stores an operating program including the program of the present disclosure. The storage device 104 may be, for example, a combination of a recording medium and a drive for reading and writing data from and to the recording medium. The recording medium is not particularly limited and may be, for example, an internal or external type, such as a hard disk (HD), CD-ROM, CD-R, CD-RW, MO, DVD, flash memory, or memory card. The storage device 104 may be, for example, a hard disk drive (HDD) or a solid state drive (SSD) in which the recording medium and drive are integrated. When the device 10 includes the storage unit, for example, the storage device 104 functions as the storage unit.

[0024] In the present device 10, the memory 102 and the storage device 104 can also store various information such as log information, information acquired from an external database (not shown) or an external device, information generated by the present device 10, and information used when the present device 10 executes processing. In this case, the memory 102 and the storage device 104 may store, for example, the above-mentioned information on the user of the present device. Note that at least a portion of the information may be stored, for example, in an external server other than the memory 102 and the storage device 104, or may be stored in a distributed manner across multiple terminals using blockchain technology or the like.

[0025] The device 10 further includes, for example, an input device 105 and an output device 106. Examples of the input device 105 include pointing devices such as a touch panel, track pad, and mouse; a keyboard; imaging means such as a camera and scanner; card readers such as an IC card reader and a magnetic card reader; and audio input means such as a microphone. Examples of the output device 106 include display devices such as an LED display and a liquid crystal display; audio output devices such as a speaker; a printer; and the like. In the first embodiment, the input device 105 and the output device 106 are configured separately, but the input device 105 and the output device 106 may be configured as an integrated device, such as a touch panel display.

[0026] An example of processing by the travel obstacle detection support program of the present disclosure will be described in more detail with reference to FIG. 3. FIG. 3 is a flowchart showing an example of each procedure of the travel obstacle detection support program of the present disclosure. In the following description, a wheelchair is used as an example of a moving object, and a case will be described in which information for travel obstacle estimation is measured by a smartphone attached to the wheelchair, but the present disclosure is not limited to the following example. Note that the measuring device for information for travel obstacle estimation is not limited to a smartphone, and any device capable of acquiring the travel obstacle estimation information described below can be used.

[0027] First, prior to the processing of the device 10, for example, a wheelchair user moves around with their smartphone fixed to the wheelchair, and uses the smartphone to collect information for estimating movement obstruction factors for estimating movement obstruction factors along their own route of travel. The information for estimating movement obstruction factors will be described later.

[0028] The travel-impeding factor estimation unit 11 of the device 10 estimates travel-impeding factors of the road surface on which the moving object traveled based on travel-impeding factor information including at least one of gravity information and acceleration information during the movement of the moving object (S1, travel-impeding factor estimation step). The travel-impeding factor estimation information includes at least one of gravity information and acceleration information during the movement of the moving object. The gravity information and acceleration information may be, for example, information measured intermittently or continuously. In the former case, the measurement interval is not particularly limited, and examples include intervals of 0.01 seconds, 0.02 seconds, 0.03 seconds, 0.05 seconds, 0.1 seconds, 0.5 seconds, and 1 second. The travel-impeding factor estimation unit 11 can obtain the travel-impeding factor estimation information from a device (e.g., a smartphone) attached to the wheelchair. Furthermore, when the device is a smartphone, the travel obstruction factor estimation unit 11 may acquire, for example, sensor data (sensing data from a gravity sensor, an acceleration sensor, and a GPS sensor) of the smartphone collected by a logger app (e.g., SensorLoger) of the smartphone as the travel obstruction factor estimation information, or may acquire the sensor data from various sensors (gravity sensor, acceleration sensor, and GPS sensor) of the smartphone. The travel obstruction factor estimation unit 11 may record the acquired travel obstruction factor estimation information in the memory 102 or the storage device 104, for example.

[0029] The gravity information is, for example, information obtained by measuring the gravitational acceleration acting on the moving body. The gravity information may be, for example, information measured directly by a gravity sensor, or gravity information estimated from measurements by an acceleration sensor or a pressure sensor.

[0030] The acceleration information is, for example, information about the acceleration of the moving object when it is moving, and includes, for example, at least one selected from the group consisting of Z-axis acceleration information, X-axis acceleration information, and Y-axis acceleration information. The Z-axis acceleration information is, for example, information on the acceleration of the moving body in the vertical direction. The X-axis acceleration information is, for example, information on acceleration in the forward and backward directions of the moving body, which are perpendicular to the Z-axis acceleration information. The Y-axis acceleration information is, for example, information on acceleration in the left-right direction of the moving body, which is perpendicular to the Z-axis acceleration information. The front-rear direction is, for example, a direction parallel to the traveling direction of the moving body, and the left-right direction is, for example, a direction perpendicular to the traveling direction of the moving body.

[0031] Furthermore, the information for estimating travel obstruction factors may include, for example, a travel history. The travel history is, for example, a history of a route traveled by a mobile object. The travel history may be, for example, information in which GPS (Global Positioning System) information and date and time are linked, or may be travel history information in a known map application or the like (for example, Google Maps (registered trademark)). In this case, the acceleration information and / or the gravity information included in the travel obstruction factor estimation information may be detected position information linked to the travel history.

[0032] The travel obstruction factor estimation unit 11 estimates travel obstruction factors of the road surface on which the moving object has traveled based on the travel obstruction factor information. The travel obstruction factor estimation unit 11 can estimate at least one of a step on the road surface and an unevenness on the road surface based on the acceleration information, for example. The travel obstruction factor estimation unit 11 also estimates the gradient of the road surface as the travel obstruction factor based on the gravity information.

[0033] The process of estimating a road step by the travel obstruction factor estimation unit 11 will now be described. The travel obstruction factor estimation unit 11 can estimate the presence or absence of a road step based on, for example, the Z-axis acceleration information. Specifically, the travel obstruction factor estimation unit 11 can calculate the vertical vibration acceleration level of the moving object based on, for example, the Z-axis acceleration information, and determine that a road step exists when the vertical vibration acceleration level exceeds a threshold. The threshold is not particularly limited and can be set to any value, for example, 50 dB, 75 dB, 100 dB, 125 dB, etc. Furthermore, the travel obstruction factor estimation unit 11 may estimate the presence or absence of a road step by taking into account the inclination of the moving object in addition to the acceleration information. In this case, the travel obstruction factor estimation unit 11 can estimate the presence of a road step when, for example, the vibration acceleration level exceeds a threshold and the inclination of the moving object exceeds a predetermined value. The travel obstruction factor estimation unit 11 can estimate the inclination of the moving object based on, for example, the gravity information. Estimation of the inclination (gradient) based on gravity information will be described later.

[0034] The process of estimating road surface unevenness by the travel obstruction factor estimation unit 11 will be described. The travel obstruction factor estimation unit 11 estimates the effective vibration acceleration value of the moving body based on, for example, the acceleration information (Z-axis acceleration information, X-axis acceleration information, and Y-axis acceleration information). The travel obstruction factor estimation unit 11 may, for example, perform sensory correction on the acceleration information. The sensory correction can be performed, for example, with reference to JIS C 1510-1995. The effective vibration acceleration value is calculated by, for example, Fourier transforming the acceleration information to calculate frequency components, and then calculating frequency-weighted effective vibration acceleration values ​​(X, Y, Z) using the following equation (1). Next, the travel obstruction factor estimation unit 11 calculates a three-axis (X-axis, Y-axis, Z-axis) composite value from the frequency-weighted effective vibration acceleration value using the following equation (2). Then, the vibration acceleration level can be calculated from the three-axis composite value using the following equation (3). Note that the calculation of the vibration acceleration level based on the acceleration information is not limited to using the following formulas (1), (2), and (3). The travel obstruction factor estimation unit 11 can estimate the road surface unevenness based on, for example, the vibration acceleration level and the unevenness determination standard information in which the road surface unevenness level and the reference vibration acceleration level are linked.

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[0035] The following describes the process of estimating the gradient of a road surface by the travel obstruction factor estimation unit 11. The gradient may be, for example, a longitudinal gradient (a gradient in a direction parallel to the traveling direction of the moving object), a transverse gradient (a gradient in a direction perpendicular to the traveling direction of the moving object), or a combination of these. The travel obstruction factor estimation unit 11 can estimate the longitudinal gradient (inclination angle) of the road surface from the gravity information, for example, using the following equation (4), but the gradient estimation method is not limited to calculation using equation (4). The travel obstruction factor estimation unit 11 can also estimate the transverse gradient (inclination angle) of the road surface from the gravity information, for example, using the following equation (5), but the gradient estimation method is not limited to calculation using equation (5). In this case, the travel obstruction factor estimation unit 11 may, for example, calculate an average value of the gravity information at predetermined intervals and estimate the gradient using the average value instead of the gravity information. The predetermined interval is not particularly limited, and examples include 0.5 seconds, 1 second, 1.5 seconds, and 2 seconds. By using the average value at predetermined intervals, it is possible to reduce the influence of noise from the gravity sensor, for example.

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[0036] The travel obstacle detection support method of the present disclosure is, for example, a method implemented by replacing each "procedure" in the travel obstacle detection support program of the present disclosure with a "step." Specifically, the travel obstacle detection support method of the present disclosure includes a travel obstacle estimation step, in which the estimation information acquisition step acquires travel obstacle estimation information for estimating travel obstacles of a moving object, and the travel obstacle estimation step estimates travel obstacles of a road surface on which the moving object has traveled based on travel obstacle information including at least one of gravity information and acceleration information during the movement of the moving object. The travel obstacle detection support method of the present disclosure can be implemented, for example, using the travel obstacle detection support device 10 of the present disclosure shown in FIG. 1 or FIG. 2. Note that the travel obstacle detection support method of the present disclosure is not limited to methods using the travel obstacle detection support device 10, for example. The travel obstacle detection support method of the present disclosure can be implemented by, for example, referencing the descriptions of the travel obstacle detection support program and the travel obstacle detection support device of the present disclosure.

[0037] According to the travel obstacle detection support program of the present disclosure, the estimation information acquisition procedure acquires travel obstruction factor estimation information for estimating travel obstruction factors of a moving body, and the travel obstruction factor estimation procedure can estimate travel obstruction factors on the road surface on which the moving body has traveled based on the travel obstruction factor information including at least one of gravity information and acceleration information when the moving body is moving. Therefore, according to the present disclosure, a user of a moving body (e.g., a wheelchair) can easily estimate travel obstruction factors on the road surface simply by carrying a measurement device (e.g., a smartphone) for travel obstruction factor estimation information while traveling.

[0038] [Embodiment 2] Another example of the travel obstacle detection support program of the present disclosure will be described.

[0039] The travel obstacle detection support program of this embodiment is similar to the travel obstacle detection support program of the first embodiment, except that it includes a map generation procedure in addition to the configuration of the travel obstacle detection support program of the first embodiment, and the description thereof can be used. The travel obstacle detection support program of this embodiment includes, for example, a map generation procedure, in which information for estimating travel obstacle factors includes a travel history of the moving body, and the map generation procedure generates a travel obstacle map linking the position information of the moving body included in the travel history with the travel obstacle factors.

[0040] Next, the travel obstacle detection support device of this embodiment will be described with reference to Figure 4. The travel obstacle detection support device 10A of the present disclosure is similar to the travel obstacle detection support device 10 of the first embodiment, except that it includes a map generator 12 in addition to the configuration of the travel obstacle detection support device 10 of the first embodiment, and the description thereof can be used. The travel obstacle detection support device 10A of this embodiment includes, for example, the map generator 12, and information for travel obstruction factor estimation includes the travel history of the moving object, and the map generator 12 generates a travel obstruction map that links the position information of the moving object included in the travel history with the travel obstruction factor.

[0041] As shown in Fig. 4, the travel obstacle detection support device 10A includes a map generation unit 12 in addition to the configuration of the travel obstacle detection support device 10 of embodiment 1. The hardware configuration of the travel obstacle detection support device 10A is the same as that of the travel obstacle detection support device 10 of Fig. 2, except that the central processing unit 101 includes the configuration of the travel obstacle detection support device 10A of Fig. 4 instead of the configuration of the travel obstacle detection support device 10 of Fig. 1.

[0042] An example of processing by the travel obstacle detection support program of the present disclosure will be described more specifically with reference to Fig. 5. Fig. 5 is a flowchart showing an example of each procedure of the travel obstacle detection support program of the present disclosure.

[0043] First, S1 is performed in the same manner as S1 in the embodiment 1. In the present embodiment, for example, the information for estimating movement obstruction factors includes a movement history of the moving object.

[0044] The map generation unit 12 generates a travel obstruction map linking the location information of the moving body included in the travel history with the travel obstruction factors (S1, map generation step). The travel obstruction map is, for example, information linking the locations on the travel route where the travel obstruction factor estimation information, from which the travel obstruction factors were estimated, was acquired. The map generation unit 12 can generate the travel obstruction map by linking at least one selected from the group consisting of road surface unevenness, road surface gradient, and road step estimated in S1 with location information (e.g., latitude and longitude) where the travel obstruction factor estimation information, from which each piece of information was estimated, was measured. The map generation unit 12 may, for example, output the travel obstruction map externally. In this case, for example, the travel obstruction map may be linked with an existing map service (e.g., Google Maps (registered trademark)).

[0045] The travel obstacle detection support method of the present disclosure is, for example, a method implemented by replacing each "procedure" in the travel obstacle detection support program of the present disclosure with a "step." The travel obstacle detection support method of the present disclosure can, for example, incorporate the descriptions of the travel obstacle detection support program and travel obstacle detection support device of the present disclosure.

[0046] According to the travel obstacle detection support program of the present disclosure, for example, a map generation procedure can generate a travel obstacle map that links the location information of the moving body included in the travel history of the moving body with the travel obstacle factor. Therefore, according to the travel obstacle detection support program of the present disclosure, by linking the estimated travel obstacle factor with map information, for example, navigation that takes the travel obstacle factor into consideration becomes possible.

[0047] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0048] <Additional Notes> Some or all of the above embodiments can be described as, but not limited to, the following supplementary notes. (Appendix 1) Including a procedure for estimating factors impeding mobility, the travel-impedance factor estimation step estimates a travel-impedance factor of a road surface on which the moving body has traveled, based on travel-impedance factor information including at least one of gravity information and acceleration information during the movement of the moving body; A moving obstacle detection support program for causing a computer to execute each of the above procedures. (Appendix 2) 2. The travel obstacle detection support program according to claim 1, wherein the travel obstruction factor estimation step estimates at least one of a step on the road surface and an unevenness on the road surface as the travel obstruction factor based on the acceleration information. (Appendix 3) the acceleration information includes Z-axis acceleration information in a vertical direction of the moving body, 3. The travel obstacle detection support program according to claim 2, wherein the travel obstruction factor estimation step estimates at least one of a step on the road surface and an unevenness on the road surface based on the acceleration information. (Appendix 4) the acceleration information includes Z-axis acceleration information in a vertical direction of the moving body, X-axis acceleration information that is perpendicular to the Z-axis acceleration information and is in a forward / backward direction of the moving body, and Y-axis acceleration information that is perpendicular to the Z-axis acceleration information and is in a left / right direction of the moving body, 4. The travel obstacle detection support program according to claim 3, wherein the travel obstruction factor estimation step estimates unevenness of the road surface based on the Z-axis acceleration information, the X-axis acceleration information, and the Y-axis acceleration information. (Appendix 5) 5. The travel obstacle detection support program according to claim 1, wherein the travel obstruction factor estimation step estimates a gradient of the road surface as the travel obstruction factor based on the gravity information. (Appendix 6) A map generation procedure is included. The information for estimating a movement obstruction factor includes a movement history of the moving object, The travel obstacle detection support program according to any one of appendices 1 to 5, wherein the map generation procedure generates a travel obstruction map linking the location information of the moving body included in the travel history with the travel obstruction factors. (Appendix 7) a movement obstruction factor estimation unit; The travel obstruction factor estimation unit estimates travel obstruction factors on the road surface on which the moving body travels based on travel obstruction factor information including at least one of gravity information and acceleration information when the moving body is moving. (Appendix 8) 8. The travel obstacle detection support device according to claim 7, wherein the travel obstruction factor estimation unit estimates, as the travel obstruction factor, at least one of a step on the road surface and an unevenness on the road surface based on the acceleration information. (Appendix 9) the acceleration information includes Z-axis acceleration information in a vertical direction of the moving body, 9. The moving obstacle detection support device according to claim 8, wherein the movement obstruction factor estimation unit estimates at least one of a step on the road surface and an unevenness on the road surface based on the acceleration information. (Appendix 10) the acceleration information includes Z-axis acceleration information in a vertical direction of the moving body, X-axis acceleration information that is perpendicular to the Z-axis acceleration information and is in a forward / backward direction of the moving body, and Y-axis acceleration information that is perpendicular to the Z-axis acceleration information and is in a left / right direction of the moving body, 10. The moving obstacle detection support device according to claim 9, wherein the movement obstruction factor estimation unit estimates unevenness of the road surface based on the Z-axis acceleration information, the X-axis acceleration information, and the Y-axis acceleration information. (Appendix 11) 11. The travel obstacle detection support device according to any one of appendices 7 to 10, wherein the travel obstruction factor estimation unit estimates, as the travel obstruction factor, a gradient of the road surface based on the gravity information. (Appendix 12) a map generator; The information for estimating a movement obstruction factor includes a movement history of the moving object, 12. The travel obstacle detection support device according to any one of appendices 7 to 11, wherein the map generation unit generates a travel obstruction map linking the location information of the moving body included in the travel history with the travel obstruction factors. (Appendix 13) A step of estimating a factor that impedes movement, the travel obstruction factor estimation step estimates a travel obstruction factor of a road surface on which the moving body has traveled based on travel obstruction factor information including at least one of gravity information and acceleration information during the movement of the moving body; A moving obstacle detection support method in which each of the steps is executed by a computer. (Appendix 14) 14. The method for supporting detection of a moving obstacle according to claim 13, wherein the step of estimating the movement obstruction factor estimates at least one of a step on the road surface and an unevenness on the road surface as the movement obstruction factor based on the acceleration information. (Appendix 15) the acceleration information includes Z-axis acceleration information in a vertical direction of the moving body, 15. The method for supporting detection of a moving obstacle according to claim 14, wherein the step of estimating a movement obstruction factor estimates at least one of a step on the road surface and an unevenness on the road surface based on the acceleration information. (Appendix 16) the acceleration information includes Z-axis acceleration information in a vertical direction of the moving body, X-axis acceleration information that is perpendicular to the Z-axis acceleration information and is in a forward / backward direction of the moving body, and Y-axis acceleration information that is perpendicular to the Z-axis acceleration information and is in a left / right direction of the moving body, 16. The method for supporting detection of a moving obstacle according to claim 15, wherein the step of estimating a movement obstruction factor estimates unevenness of the road surface based on the Z-axis acceleration information, the X-axis acceleration information, and the Y-axis acceleration information. (Appendix 17) 17. The method for supporting detection of a moving obstacle according to any one of claims 13 to 16, wherein the step of estimating a travel obstruction factor includes estimating a gradient of the road surface as the travel obstruction factor based on the gravity information. (Appendix 18) A map generation step is included. The information for estimating a movement obstruction factor includes a movement history of the moving object, The travel obstacle detection support method according to any one of appendices 13 to 17, wherein the map generation step generates a travel obstruction map linking the location information of the moving body included in the travel history with the travel obstruction factors. (Appendix 19) Including a procedure for estimating factors impeding mobility, the travel-impedance factor estimation step estimates a travel-impedance factor of a road surface on which the moving body has traveled, based on travel-impedance factor information including at least one of gravity information and acceleration information during the movement of the moving body; A computer-readable recording medium having recorded thereon a moving obstacle detection support program for causing a computer to execute each of the above procedures. (Appendix 20) 20. The recording medium according to claim 19, wherein the step of estimating a travel obstruction factor estimates at least one of a step on the road surface and an unevenness on the road surface as the travel obstruction factor based on the acceleration information. (Appendix 21) the acceleration information includes Z-axis acceleration information in a vertical direction of the moving body, 21. The recording medium according to claim 20, wherein the step of estimating a movement-impedance factor estimates at least one of a step on the road surface and an unevenness on the road surface based on the acceleration information. (Appendix 22) the acceleration information includes Z-axis acceleration information in a vertical direction of the moving body, X-axis acceleration information that is perpendicular to the Z-axis acceleration information and is in a forward / backward direction of the moving body, and Y-axis acceleration information that is perpendicular to the Z-axis acceleration information and is in a left / right direction of the moving body, 22. The recording medium according to claim 21, wherein the step of estimating a travel obstruction factor estimates unevenness of the road surface based on the Z-axis acceleration information, the X-axis acceleration information, and the Y-axis acceleration information. (Appendix 23) 23. The recording medium according to any one of appendices 19 to 22, wherein the step of estimating a travel obstruction factor includes estimating a gradient of the road surface as the travel obstruction factor based on the gravity information. (Appendix 24) A map generation procedure is included. The information for estimating a movement obstruction factor includes a movement history of the moving object, 24. A recording medium according to any one of appendices 19 to 23, wherein the map generation step generates a movement obstruction map linking the location information of the moving body included in the movement history with the movement obstruction factors. [Industrial Applicability]

[0049] According to the present disclosure, it is possible to easily estimate factors that impede movement on road surfaces. As a result, according to the present disclosure, it is possible to easily update barrier-free maps. Therefore, the present disclosure can be widely and usefully used in the fields of welfare, urban planning, etc. [Explanation of symbols]

[0050] 10. Mobile obstacle detection support device 11. Mobility Obstruction Factor Estimation Unit 12 Map generation section 101 Central Processing Unit 102 memory 103 Bus 104 Storage device 105 Input Device 106 Output Device 107 Communication Devices

Claims

1. Including a procedure for estimating factors impeding mobility, the travel-impedance factor estimation step estimates a travel-impedance factor of a road surface on which the moving body has traveled, based on travel-impedance factor information including at least one of gravity information and acceleration information when the moving body is moving; A moving obstacle detection support program for causing a computer to execute each of the above procedures.

2. 2. The mobile obstacle detection support program according to claim 1, wherein the step of estimating the movement obstruction factor estimates at least one of a step on the road surface and an unevenness on the road surface as the movement obstruction factor based on the acceleration information.

3. the acceleration information includes Z-axis acceleration information in a vertical direction of the moving body, 3. The program according to claim 2, wherein the step of estimating the movement obstruction factor estimates at least one of a step on the road surface and an unevenness on the road surface based on the acceleration information.

4. the acceleration information includes Z-axis acceleration information in a vertical direction of the moving body, X-axis acceleration information that is perpendicular to the Z-axis acceleration information and is in a forward / backward direction of the moving body, and Y-axis acceleration information that is perpendicular to the Z-axis acceleration information and is in a left / right direction of the moving body, 4. The moving obstacle detection support program according to claim 3, wherein the step of estimating the movement obstruction factor estimates the unevenness of the road surface based on the Z-axis acceleration information, the X-axis acceleration information, and the Y-axis acceleration information.

5. The mobile obstacle detection support program according to claim 1 , wherein the step of estimating the travel obstruction factor estimates a gradient of the road surface as the travel obstruction factor based on the gravity information.

6. a map generation step; The information for estimating a movement obstruction factor includes a movement history of the moving object, The travel obstacle detection support program according to claim 1 , wherein the map generation step generates a travel obstruction map linking the location information of the moving body included in the travel history with the travel obstruction factors.

7. a movement obstruction factor estimation unit; The travel obstruction factor estimation unit estimates travel obstruction factors on the road surface on which the moving body travels based on travel obstruction factor information including at least one of gravity information and acceleration information when the moving body is moving.

8. The moving obstacle detection support device according to claim 7 , wherein the travel obstruction factor estimation unit estimates, as the travel obstruction factor, at least one of a step on the road surface and an unevenness on the road surface based on the acceleration information.

9. A step of estimating a factor that impedes movement, the travel obstruction factor estimation step estimates a travel obstruction factor of a road surface on which the moving body has traveled based on travel obstruction factor information including at least one of gravity information and acceleration information during the movement of the moving body; A moving obstacle detection support method in which each of the steps is executed by a computer.

10. Including a procedure for estimating factors impeding mobility, the travel-impedance factor estimation step estimates a travel-impedance factor of a road surface on which the moving body has traveled, based on travel-impedance factor information including at least one of gravity information and acceleration information during the movement of the moving body; A computer-readable recording medium having recorded thereon a moving obstacle detection support program for causing a computer to execute each of the above procedures.

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