Information processing device and information processing method

Abstract

To accurately grasp a state of a road surface.SOLUTION: An information processing device determines abnormality of a road surface based on a sensor value acquired by a sensor mounted on a first vehicle. At this time, a determination reference is determined based on a point where the sensor value is acquired.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to road sensing technology. [Background technology]

[0002] There is a technology for determining road surface conditions based on sensor data acquired by a vehicle. In this regard, Patent Document 1 discloses a system for determining uneven points on the road surface based on acceleration acquired by a probe car. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2018-071318 Summary of the Invention [Problem to be solved by the invention]

[0004] The present disclosure aims to accurately grasp the condition of the road surface. [Means for solving the problem]

[0005] A first aspect of the present disclosure is an information processing device having a control unit that determines abnormalities in the road surface based on sensor values acquired by a sensor mounted on a first vehicle, and the control unit determines criteria for the determination based on the point where the sensor values were acquired.

[0006] Furthermore, a second aspect of the present disclosure is an information processing method that includes the steps of acquiring a sensor value from a sensor mounted on a first vehicle and determining an abnormality in the road surface based on the sensor value, and that varies the criteria for the determination using the sensor value based on the point at which the sensor value was acquired.

[0007] Another aspect of the present disclosure is a computer-readable storage medium that non-transitoryly stores a program for executing the above-described method. [Effects of the Invention]

[0008] According to the present disclosure, the road surface condition can be accurately grasped. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an overview of a vehicle system. [Figure 2] 1 is a diagram illustrating components of a vehicle 10. FIG. [Figure 3] FIG. 2 is a schematic diagram of driving data stored in a storage unit 202. [Figure 4] FIG. 2 is a diagram showing the components of the server device 200 in detail. [Figure 5] FIG. 4 is a diagram illustrating the transition of wheel speed. [Figure 6] 1 is a diagram illustrating an example of a structure installed on a road surface. [Figure 7] FIG. 4 is a diagram for explaining a method of determining an abnormality. [Figure 8] FIG. 2 is a schematic diagram of structure data stored in a storage unit 202. [Figure 9] 4 is a flowchart of a process executed by the in-vehicle device 100. [Figure 10] 10 is a flowchart of a process executed by the server device 200. [Figure 11] FIG. 10 is a diagram showing the magnitude relationship between thresholds in the second embodiment. [Figure 12] FIG. 10 is a diagram illustrating the transition of wheel speed in the second embodiment. [Figure 13] FIG. 11 is a diagram illustrating a transition of wheel speed in the third embodiment. [Figure 14] FIG. 10 is a diagram showing in detail components of a server device 200A according to a fourth embodiment. [Figure 15] 1 is a diagram illustrating the trajectory of a vehicle that is about to deviate from its lane. [Figure 16] FIG. 10 is a diagram illustrating a transition of wheel speed in the fourth embodiment. [Figure 17] 10 is a flowchart of a process executed by a server device 200A in the fourth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] There are systems that determine whether there is an abnormality in the road surface condition based on sensor data acquired by a vehicle. For example, if the vertical acceleration applied to a vehicle traveling on a road that should be flat exceeds a predetermined threshold, it is estimated that the road surface is uneven. In addition to acceleration, road unevenness can also be determined by wheel speed. For example, when a vehicle goes over a bump, the wheel speed fluctuates slightly due to slippage caused by elastic deformation of the wheel. Therefore, the size of the bump can be determined based on the rate of change of wheel speed per unit time.

[0011] However, there are areas on roads where specially engineered structures exist. Examples of such structures include anti-skid grooves, bumps (humps) that restrict passing speeds, and three-dimensional lane markings (which cause vibrations when tires ride on them; also known as rumble strips). While the presence of irregularities in such areas is normal, existing technology may erroneously detect them as abnormal. The information processing device according to the present disclosure solves such a problem.

[0012] An information processing device according to one aspect of the present disclosure has a control unit that determines abnormalities in the road surface based on sensor values acquired by a sensor mounted on a first vehicle, and the control unit determines criteria for the determination based on the point at which the sensor values were acquired.

[0013] The sensor value is not limited to a specific one as long as it is acquired by the first vehicle (probe car), and examples of such a value include acceleration, jerk (jerk), position information, vehicle speed, and wheel speed. When using acceleration or wheel speed as sensor values, the size of a road bump can be determined based on the rate of change per unit time. If these values change suddenly in a short period of time, it can be assumed that an impact has been applied to the vehicle. The control unit determines the standard for determining an abnormality based on the location where the sensor value was acquired. For example, if the first vehicle is traveling on a road with uneven surface treatment to prevent slipping, the control unit can set a large threshold value for the sensor value to make it less likely that an abnormality will be determined.

[0014] Furthermore, the control unit may classify the points where the sensor values are acquired into a first point and a second point, and perform a determination process using different criteria based on the classification results. The first point may be, for example, a point where no structures with unevenness exist on the road surface, and the second point may be a point where structures with unevenness exist on the road surface. At a first point, an abnormality can be determined when the sensor value satisfies a first threshold (or when the sensor value is within a first range), while at a second point, an abnormality can be determined when the sensor value satisfies a second threshold different from the first threshold (or when the sensor value is within a second range that does not include the first range). With this configuration, it is possible to suppress erroneous determinations on road surfaces that have unevenness.

[0015] Furthermore, the criteria for determining an abnormality may be reversed between the first and second locations, i.e., at the first location, an abnormality may be determined when the sensor value indicates a predetermined value, and at the second location, an abnormality may be determined when the sensor value does not indicate the predetermined value. For example, if vibrations of a predetermined value or more are detected at the first point, it is assumed that the road surface has collapsed, but if vibrations of a predetermined value or more are not detected at the second point, it is assumed that the road surface has collapsed. Another abnormality is suspected: "The structure with the cracks is worn away." In this way, by reversing the criteria for determining an abnormality between the first and second locations, it becomes possible to detect a different abnormality, namely, "a structure installed for safety purposes is not functioning adequately."

[0016] The second point may be determined based on pre-stored data indicating the location of structures, such as data indicating road sections with anti-skid coatings, road sections with rumble strips, or locations of road bumps.

[0017] Furthermore, the second point may be determined based on a driving operation performed by the driver of the first vehicle. For example, if a steering operation is performed at an unnatural angle compared to the curvature of the road, it can be assumed that "the wheels hit rumble strips, causing an abrupt steering operation." Therefore, the existence of the second point may be estimated based on data related to driving operations.

[0018] Specific embodiments of the present disclosure will be described below with reference to the accompanying drawings. Unless otherwise specified, the hardware configuration, module configuration, functional configuration, etc. described in each embodiment are not intended to limit the technical scope of the disclosure to those configurations.

[0019] (First embodiment) An overview of a vehicle system according to a first embodiment will be described with reference to FIG. The vehicle system according to this embodiment includes a vehicle 10 equipped with an on-board device 100 and a server device 200.

[0020] Vehicle 10 is a vehicle for sensing road surface conditions. Vehicle 10 may be an autonomous vehicle or a vehicle driven by a driver. Vehicle 10 may be, for example, a general vehicle that has entered into a data provision contract with a service provider. Vehicle 10 has predetermined sensors and transmits data obtained by sensing to server device 200.

[0021] The server device 200 determines where there is an abnormality in the road surface condition based on the data collected from the vehicle 10. In this embodiment, the abnormality in the road surface includes, but is not limited to, unevenness, cracks, peeling asphalt, depressions (potholes), etc. The server device 200 may compile the results of the determination and generate a map showing the condition of the road (road surface).

[0022] Each element that makes up the system will be explained. The vehicle 10 is a connected car that has a communication function with an external network. The vehicle 10 is equipped with an in-vehicle device 100. Although FIG. 1 illustrates only the in-vehicle device 100, the vehicle 10 may include multiple electronic control units (ECUs) and the like.

[0023] The in-vehicle device 100 may be a device that provides information to a passenger in the vehicle 10 (for example, a car navigation device), or may be an electronic control unit (ECU) included in the vehicle 10. The in-vehicle device 100 may also be a data communication module (DCM) having a communication function.

[0024] 2 is a diagram illustrating components of the vehicle 10 according to this embodiment. The vehicle 10 according to this embodiment includes an in-vehicle device 100 and a sensor group 110.

[0025] The in-vehicle device 100 includes a processor such as a CPU or a GPU, a main memory such as a RAM or a ROM, It can be configured as a computer having an auxiliary storage device such as an EPROM, a hard disk drive, or removable media. The auxiliary storage device stores an operating system (OS), various programs, various tables, etc., and by executing the programs stored therein, various functions that match a predetermined purpose, as described below, can be realized. However, some or all of the functions may be realized by hardware circuits such as ASICs or FPGAs. The in-vehicle device 100 includes a control unit 101 , a storage unit 102 , a communication unit 103 , an input / output unit 104 , and a location information acquisition unit 105 .

[0026] The control unit 101 is a calculation unit that executes a predetermined program to realize various functions of the in-vehicle device 100. The control unit 101 may be realized by, for example, a CPU or the like. The control unit 101 is configured to have, as functional modules, a data acquisition unit 1011 and a data transmission unit 1012. These functional modules may be realized by executing stored programs by a CPU.

[0027] The data acquisition unit 1011 acquires data from sensors included in the sensor group 110, which will be described later, and stores the data in the storage unit 102. In this embodiment, the data acquisition unit 1011 acquires data representing the vehicle speed and the wheel speed as sensor data. The vehicle speed is the traveling speed of the vehicle 10. The vehicle speed may be acquired by a speed sensor, or may be calculated based on position information acquired via a GPS module. The vehicle speed may be expressed, for example, as a value in kilometers per hour. The wheel speed is the rotational speed of the wheels of the vehicle 10. The wheel speed can be expressed, for example, as a value in revolutions per minute. The wheel speed may be the rotational speed of a specific wheel, or may be a representative value of the rotational speeds of multiple wheels.

[0028] During operation of the in-vehicle device 100, the data acquisition unit 1011 periodically acquires data including vehicle speed and wheel speed (hereinafter referred to as sensor data), and stores the acquired sensor data in the storage unit 102. Furthermore, the data acquisition unit 1011 acquires vehicle position information via the position information acquisition unit 105 (described later), and stores the information in association with the sensor data. The sensor data can be acquired at a predetermined cycle (for example, every 100 milliseconds).

[0029] The data transmission unit 1012 transmits the data acquired by the data acquisition unit 1011 to the server device 200 at a predetermined timing. The predetermined timing may be a timing that occurs periodically. For example, the data transmission unit 1012 may transmit the accumulated data to the server device 200 when one trip of the vehicle 10 (hereinafter, a trip) is completed (for example, when the power supply to the vehicle system is shut off).

[0030] FIG. 3 is a schematic diagram of data transmitted to the server device 200. As shown in FIG. The vehicle ID is an identifier that uniquely identifies the vehicle 10. The trip ID is an identifier that uniquely identifies a trip. A new trip ID is assigned for each trip. The date and time are the date and time when the sensor data was generated. As shown in the figure, there is one-to-one correspondence between the sensor data and the position information data. Hereinafter, the data transmitted from the in-vehicle device 100 to the server device 200 will be referred to as driving data.

[0031] The storage unit 102 is a memory device including a main storage device and an auxiliary storage device. The auxiliary storage device stores an operating system (OS), various programs, various tables, etc., and by loading the programs stored therein into the main storage device and executing them, various functions that meet predetermined purposes, as will be described later, can be realized. The main memory includes RAM (Random Access Memory) and ROM (Read Only Memory). The auxiliary storage device may be an EPROM (Erasable Programmable ROM) or a hard disk. It may also include a disk drive (HDD, Hard Disk Drive). may include removable media, i.e., portable recording media.

[0032] The storage unit 102 temporarily stores data generated by the control unit 101, that is, sensor data and position information data.

[0033] The communication unit 103 is a wireless communication interface for connecting the in-vehicle device 100 to a network. The communication unit 103 is configured to be able to communicate with the server device 200 using a communication standard such as a mobile communication network, a wireless LAN, or Bluetooth (registered trademark).

[0034] The input / output unit 104 is a unit that receives input operations performed by the user and presents information to the user. The input / output unit 104 is configured to include, for example, a liquid crystal display, a touch panel display, and hardware switches.

[0035] The location information acquisition unit 105 calculates location information based on a positioning signal transmitted from a positioning satellite (also referred to as a GNSS satellite). The location information acquisition unit 105 may include an antenna that receives radio waves transmitted from the GNSS satellite.

[0036] The sensor group 110 is a collection of multiple sensors that the vehicle 10 has. The sensor group 110 includes sensors that acquire sensor data related to the state of the vehicle 10, such as a vehicle speed sensor that acquires the vehicle speed, a wheel speed sensor that acquires the speeds of multiple wheels (wheel speeds), and a steering sensor that acquires the steering angle. The sensor data acquired by each sensor is transmitted to the in-vehicle device 100 via a network bus.

[0037] The network bus is a communication bus that constitutes an in-vehicle network. Although one bus is illustrated in this example, the vehicle 10 may have two or more communication buses. The multiple communication buses may be connected to each other by a gateway that manages the multiple communication buses.

[0038] Next, the server device 200 will be described. The server device 200 has a function of detecting abnormalities on the road surface based on sensor data acquired from a plurality of vehicles 10 (on-vehicle devices 100). FIG. 4 is a diagram showing in detail the components of the server device 200 included in the vehicle system according to this embodiment.

[0039] The server device 200 can be configured as a computer having a processor such as a CPU or GPU, a main memory such as a RAM or ROM, and an auxiliary memory such as an EPROM, a hard disk drive, and removable media. The auxiliary memory stores an operating system (OS), various programs, various tables, etc., and the programs stored therein are loaded into a working area of the main memory and executed. By controlling each component through the execution of the programs, various functions matching a predetermined purpose can be realized, as described below. However, some or all of the functions may be realized by hardware circuits such as ASICs and FPGAs.

[0040] The server device 200 includes a control unit 201 , a storage unit 202 , and a communication unit 203 . The control unit 201 is a computing device that controls the server device 200. This can be realized by a processing unit such as a CPU. The control unit 201 is configured to have, as functional modules, a data collection unit 2011 and a determination unit 2012. Each functional module may be realized by executing a stored program by a CPU.

[0041] The data collection unit 2011 executes a process of collecting driving data transmitted from a plurality of vehicles 10 (on-vehicle devices 100). The collected driving data is stored as driving data 202B in the storage unit 202, which will be described later.

[0042] The determination unit 2012 determines abnormalities in the road surface (typically, depressions or peeling paint) based on a plurality of pieces of travel data collected from a plurality of vehicles 10.

[0043] Here, a method for determining abnormalities in the road surface will be described. 5 is a diagram plotting sensor data (wheel speed in this embodiment) collected from a vehicle 10. In this example, the vertical axis represents wheel speed, and the horizontal axis represents traveling position. Normally, when the vehicle 10 is traveling on a flat road surface, the wheel speed is approximately equal to the vehicle speed. On the other hand, when there are irregularities on the road surface, the wheel speed fluctuates slightly. Here, the rate of change of the wheel speed per unit time is defined as ΔV. For example, if the wheel speed increases from 40 km / h to 41 km / h in a unit time (e.g., 100 milliseconds), ΔV = 2.5%. In the illustrated example, it is assumed that a fluctuation in the wheel speed is observed in the section indicated by the reference numeral 501. For example, if the maximum value of ΔV (referred to as ΔVm) in a predetermined period exceeds a predetermined threshold value (hereinafter referred to as Th, e.g., 2%), it can be estimated that there is an abnormality in the road surface in the corresponding section (typically, there is an irregularity). This method is a known technique.

[0044] On the other hand, various structures may be installed on the road surface. In this disclosure, the term "structure" refers to an object with irregularities that is installed on the road surface mainly for the purpose of ensuring safety. FIG. 6 is a diagram showing an example of a structure. For example, in gradient sections, grooves are sometimes provided in the asphalt to provide anti-slip properties. Furthermore, in residential roads, before intersections, before sharp curves, etc., raised portions of the road surface (bumps or humps; referred to as bumps in this disclosure) are sometimes provided to reduce speed or alert drivers. When a vehicle passes through such a section, vibrations and shocks occur. This causes fluctuations in wheel speed, and in conventional technology, when a vehicle 10 passes through such a section, it may be determined that there is an abnormality in the road surface.

[0045] Therefore, in this embodiment, the server device 200 stores information about sections where the road surface is uneven, and the abnormality determination criteria are different for those sections and other sections. Fig. 7 is a diagram explaining the abnormality determination criteria. Note that, here, "when a variation in wheel speed is recognized" refers to when the aforementioned ΔV exceeds a predetermined threshold (ΔV>Th). In this embodiment, in a section where there are no irregularities on the road surface (hereinafter referred to as the first section), it is determined that an abnormality has occurred if ΔV exceeds a predetermined threshold. That is, in the first section, it is determined that an abnormality has occurred if ΔV>Th. On the other hand, in a section where there are irregularities on the road surface (hereinafter referred to as the second section), the predetermined threshold is increased from Th to Th2. That is, in the second section, it is determined that an abnormality has occurred if ΔV>Th2 (Th2>Th). In the example shown in FIG. 7, for example, when a wheel speed such as that indicated by reference numeral 701 is obtained, it is determined that the wheel speed is within the normal range, and when a wheel speed such as that indicated by reference numeral 702 is obtained, it is determined that an abnormality has occurred. This makes it possible to prevent erroneous determination in the second section. Although the threshold value is a positive number here, it may be a negative number. In this case, if ΔV falls below a predetermined threshold value, it is considered to be abnormal.

[0046] The storage unit 202 includes a main storage device and an auxiliary storage device. The auxiliary storage device is a device that stores the programs executed by the control unit 201 and the data used by the control programs.

[0047] The storage unit 202 also stores structure data 202A and travel data 202B. The structure data 202A is a collection of data related to structures present on the road (road surface). As described above, the server device 200 stores information about structures that may cause vibrations when a vehicle passes over them. FIG. 8 is an example of the structure data 202A. As shown in the figure, the structure data is associated with the type of structure and its location information. Note that the location information may identify a road section (e.g., a road segment ID) or may pinpoint the location of the structure (e.g., latitude, longitude, etc.). The structure data may also be associated with a coefficient indicating the magnitude of unevenness. Furthermore, the threshold value Th2 may be set based on the coefficient.

[0048] The travel data 202B is a collection of travel data received from multiple vehicles 10 (on-board devices 100). As shown in Fig. 3, the travel data is associated with an identifier of the vehicle 10 and an identifier of the trip, which makes it possible to identify sensor data corresponding to one trip. Note that the travel data may be deleted when a predetermined time has elapsed since it was received or stored.

[0049] The communication unit 203 is a communication interface for connecting the server device 200 to a network. The communication unit 203 includes, for example, a network interface board and a wireless communication interface for wireless communication.

[0050] 2 and 4 are merely examples, and all or part of the illustrated functions may be performed using dedicated circuits. Furthermore, programs may be stored or executed using a combination of a main memory device and an auxiliary memory device other than those illustrated.

[0051] Next, the processes executed by each device included in the vehicle system will be described in detail. 9 is a flowchart of the process executed by the in-vehicle device 100. The process shown in the figure is repeatedly executed by the control unit 101 while the in-vehicle device 100 is supplied with power.

[0052] In step S11, the data acquisition unit 1011 acquires sensor data from the target sensor and also acquires position information from the position information acquisition unit 105. In this embodiment, the sensor data includes at least the wheel speed. The acquired data are associated with each other and temporarily stored.

[0053] In step S12, the data acquisition unit 1011 determines whether the vehicle 10 has finished traveling. Whether the vehicle is traveling can be determined based on the state of the vehicle system. For example, when an operation to shut down the power supply of the vehicle system is performed, it can be determined that the vehicle has finished traveling. If the determination in step S12 is negative, the process returns to step S11. If the determination in step S12 is affirmative, the process proceeds to step S13.

[0054] In step S13, the data transmission unit 1012 generates travel data based on the sensor data and position information acquired in one trip, and transmits this to the server device 200. When the server device 200 (data collection unit 2011) receives the travel data, it stores the data. The data is stored in unit 202.

[0055] Next, the process executed by the server device 200 will be described in detail. 10 is a flowchart of a process for determining road abnormalities based on collected driving data. This process is executed by the determination unit 2012 at a predetermined timing after the driving data has been accumulated.

[0056] First, in step S21, unprocessed data is extracted on a trip-by-trip basis from the travel data 202B. In this step, travel data received between the previous execution timing and the current time may be extracted.

[0057] The processes of steps S22 to S26 are executed for each of the extracted trips. First, in step S22, the travel route of the vehicle 10 is divided into a first section and a second section. The first section is a section where there are no structures with unevenness on the road, and the second section is a section where there are structures with unevenness installed on the road. The first section and the second section can be determined based on the structure data 202A. Note that the division of the sections can be performed to any length.

[0058] In step S23, the road surface is determined to be abnormal based on the sensor data corresponding to the first section. In this step, for example, if the rate of change ΔV of the wheel speed per unit time exceeds a first threshold value Th (ΔV>Th), it is determined to be abnormal.

[0059] In step S24, the road surface is determined to be abnormal based on the sensor data corresponding to the second section. In this step, for example, if the rate of change ΔV of the wheel speed per unit time exceeds a second threshold value Th2 (ΔV>Th2), it is determined to be abnormal.

[0060] In step S25, it is determined whether or not there is a section where an abnormality is found as a result of the determination. If there is a section where an abnormality is found, the process proceeds to step S26, where determination data is generated. The determination data may be data including, for example, the point or section where the abnormality was found, the sensor data used for the determination, the threshold value used for the determination, etc. The determination data may also be data in map format. If an abnormality has already been determined in another point or section and determination data exists, new data may be added to the determination data. If there is no point or section where an abnormality is found in step S25, the process returns to step S22 and continues. The determination data may be stored in the storage unit 202, or may be written to a storage medium or the like at the request of the administrator. Also, the determination data may be transmitted to an external device associated with the administrator of the road.

[0061] As described above, the server device 200 according to the first embodiment uses different criteria to determine whether a road surface is abnormal in a section where a structure is installed on the road surface and in other sections, thereby preventing erroneous determination in a section where a structure is installed on the road surface.

[0062] (Modification of the first embodiment) In the first embodiment, two thresholds (Th and Th2) are used for the judgment, but three or more thresholds may be used for the judgment. For example, the magnitude of vibration applied to the vehicle differs between when the structure is an anti-skid device and when it is a bump. Therefore, a different threshold may be set for each structure. In this case, multiple sections are extracted for each structure, and an abnormality judgment is performed for each section using the corresponding threshold. For example, multiple sections may be set, such as a first section where no structure exists, a second section where an anti-skid device is installed, and a third section where a bump is installed. In this case, the first threshold Th is set for the first section. In the second interval, a second threshold value Th2 may be used, and in the third interval, a third threshold value Th3 may be used (Th <Th2<Th3)。 For this reason, data for determining thresholds based on the type of structure may be stored in the storage unit 202, and the thresholds for each section may be set using the data. For example, the thresholds for each type of structure may be determined based on the coefficients exemplified in FIG.

[0063] (Second embodiment) In the first embodiment, a threshold value Th2 in the second section is set to be larger than that in the first section, thereby preventing erroneous determination in the second section. However, this method cannot detect wear of the structure itself. In order to address this, the second embodiment sets two threshold values in the second section and performs determination using both of them.

[0064] FIG. 11 is a diagram showing the magnitude relationship of the threshold values in the second embodiment. In the first section, as in the first embodiment, the abnormality determination is performed using a single threshold value Th. That is, when ΔV is below Th, it is determined to be normal, and when ΔV is above Th, it is determined to be abnormal.

[0065] In addition, in the second embodiment, Th2 and Th3 are set as thresholds corresponding to the second section. Th2 is the same threshold as that described in the first embodiment. When ΔV exceeds Th2, it is determined that the vibration is excessive and is regarded as abnormal. Such a case occurs, for example, when a depression occurs on a road surface that has been treated with an anti-skid coating.

[0066] On the other hand, in the second embodiment, if the variation in wheel speed in an uneven section is too small, specifically, if ΔV is below threshold value Th3 in the processing of step S24, it is determined that the vibration is too small. Such a case is, for example, a case where the anti-skid surface is worn and is becoming flat, as shown in FIG. 12. In the second embodiment, such a case is also determined to be an abnormality in the road surface. The threshold value Th3 may be set appropriately to a value at which wear of the structure is estimated.

[0067] (Third embodiment) In the first and second embodiments, the structure data 202A is used to divide the travel route of the vehicle 10 into road sections where no structures exist (first sections) and road sections where structures exist (second sections). However, depending on the situation, it may be better to narrow down the second sections by using additional data.

[0068] For example, if a structure such as a road bump is installed alone, an impact occurs only once (or several times) when a vehicle passes over it. However, it is difficult to accurately determine the timing of the impact using only the structure data. If the second section is not narrowed down sufficiently, the second threshold value Th2 may be set for the sections before and after the road bump, which may cause an erroneous determination.

[0069] Furthermore, on roads where structures are located only in part of the lane (for example, roads where rumble strips are installed on the center line), it may be difficult to accurately determine whether the tire has run over a structure. In this case, if the second section is set even though the tire has not run over a structure, this may similarly cause an erroneous determination. To deal with such cases, the second section may be narrowed down based on the sensor data. This process may be executed immediately after step S22 described in the first embodiment, for example.

[0070] FIG. 13(A) shows the transition of wheel speed on a road segment with bumps. In this example, the second section is preferably the section indicated by reference numeral 1301, rather than the entire road segment. Fig. 13(B) is a diagram showing the transition of wheel speed when the vehicle 10 hits rumble strips. In this example, the second section is preferably the section indicated by reference numeral 1302 rather than the entire road segment. Fig. 13(C) is a diagram showing the transition of wheel speed when the vehicle 10 does not hit rumble strips. In such a case, it is preferable not to set the second section. Therefore, after the second section is set based on the structure data (step S22), the second section may be narrowed down (or the setting of the second section may be cancelled) based on the rate of change of the wheel speed.

[0071] For example, if a large impact occurs once in a section where a bump is present, the section corresponding to the impact (reference numeral 1301) may be set as the second section. Also, if small vibrations occur continuously in a section where rumble strips are present, the section corresponding to the vibrations (reference numeral 1302) may be set as the second section. Conversely, if no vibrations occur in a section where rumble strips or the like are present, the setting of the second section may be canceled.

[0072] In this way, by using both the structure data and the sensor data, it becomes possible to narrow down the second section with high accuracy.

[0073] (Fourth embodiment) In the third embodiment, the second section is narrowed down by using sensor data in addition. In the fourth embodiment, it is determined whether a predetermined structure has been run over based on a driving operation performed on the vehicle 10, and the second section is set only when it is determined that the structure has been run over.

[0074] 14 is a diagram showing in detail the components of the server device 200A according to the fourth embodiment. The server device 200A according to the fourth embodiment differs from the first embodiment in that it further stores road data 202C. The road data 202C is a database that stores the shape of roads on which the vehicle 10 can travel. The road data 202C stores, for example, information such as the number of lanes, road width, lane width, gradient, curvature, etc. for each of a plurality of road segments.

[0075] In the fourth embodiment, sensor data relating to driving operations is added to the travel data. Examples of such sensor data include data relating to steering operations (steering angular velocity, steering angle, wheel rudder angle, etc.).

[0076] In the fourth embodiment, the determining unit 2012A extracts road segments where driving operations that match a predetermined pattern have been performed, based on the road data 202C. FIG. 15 is a diagram illustrating driving operation patterns. Here, an example will be described in which there is a left-curve road. Reference numeral 1501 indicates the ideal trajectory of the vehicle 10 calculated from the width and curvature of the road. On the other hand, when the vehicle 10 starts to deviate from its lane, the trajectory approaches the oncoming lane, as indicated by reference numeral 1502. The trajectory of the vehicle 10 can be identified based on sensor data related to the vehicle speed, wheel speed, steering operation, etc. In particular, when the vehicle 10 is about to deviate from its lane and the tires hit rumble strips, the driver will notice the vibration and perform an operation to correct the steering, resulting in an irregular trajectory.

[0077] Therefore, it is possible to estimate whether the tires of the vehicle 10 have run over rumble strips based on the degree of deviation from the ideal trajectory and whether or not a sudden steering operation has occurred. In this embodiment, the judgment unit 2012A judges whether the two conditions, "the deviation from the ideal trajectory is equal to or greater than a predetermined value" and "a sudden steering correction operation is being performed," are met, and if they are met, it judges that a predetermined pattern is satisfied. The occurrence of a sudden steering correction operation can be determined, for example, by the steering angle per unit time. The predetermined pattern is not limited to the example, as long as it can be assumed that an operation to correct lane departure has been performed.

[0078] If a predetermined pattern is satisfied, the determination unit 2012A determines whether vibrations equal to or greater than a predetermined value are occurring continuously within the interval corresponding to the pattern. In the example of Fig. 16, vibrations are occurring continuously within the interval indicated by reference numeral 1601. In this case, the interval is set as the second interval. Conversely, if the trajectory of the vehicle 10 does not deviate from the ideal trajectory, it is estimated that the tires are not on the rumble strips even in a section where rumble strips are installed. In such a case, the second section is not set.

[0079] 17 is a flowchart of the process executed by the server device 200A in the fourth embodiment. Processes similar to those in the first embodiment are indicated by dotted lines, and detailed explanations will be omitted. In the fourth embodiment, in step S31, a section where a driving operation matches a predetermined pattern is determined. A driving operation that matches the predetermined pattern is a driving operation that can be estimated as a driving operation in which the vehicle 10 is about to deviate from its lane. The driving operation may be determined based on position information or sensor data representing a steering operation. In step S32, it is determined whether vibrations of a predetermined value or more are continuously occurring in the determined section, and if vibrations of a predetermined value or more are continuously occurring, a second section is set. In the example of FIG. 16, the section indicated by reference numeral 1601 is set as the second section. If a second section has already been set, another second section is additionally set. The subsequent processing is the same as in the first embodiment.

[0080] As described above, in the fourth embodiment, it is determined whether the vehicle 10 has run over a predetermined structure based on the driving operation performed on the vehicle 10. This makes it possible to perform a relatively accurate determination of an abnormality in the road surface even when structures are not spread across the entire lane.

[0081] (Other variations) The above-described embodiment is merely an example, and the present disclosure can be modified and implemented as appropriate within the scope that does not deviate from the gist of the disclosure. For example, the processes and means described in this disclosure can be freely combined and implemented as long as no technical contradiction occurs.

[0082] Furthermore, a process described as being performed by one device may be shared and executed by multiple devices. Alternatively, a process described as being performed by different devices may be executed by a single device. In a computer system, the hardware configuration (server configuration) by which each function is realized can be flexibly changed.

[0083] The present disclosure can also be realized by supplying a computer program that implements the functions described in the above embodiments to a computer, and having one or more processors of the computer read and execute the program. Such a computer program may be provided to the computer by a non-transitory computer-readable storage medium that can be connected to the system bus of the computer, or may be provided to the computer via a network. The non-transitory computer-readable storage medium may be, for example, a magnetic disk (floppy disk (registered trademark) This includes any type of disk, such as a hard disk (HDD), optical disk (CD-ROM, DVD, Blu-ray), read-only memory (ROM), random access memory (RAM), EPROM, EEPROM, magnetic card, flash memory, optical card, or any type of medium suitable for storing electronic instructions. [Explanation of symbols]

[0084] 10. Vehicle 100...In-vehicle equipment 101,201 Control unit 102,202...Storage section 103,203···Communications Department 104...Input / output section 105...Location information acquisition unit 200 Server device

Claims

1. a control unit that determines an abnormality in a road surface based on a sensor value acquired by a sensor mounted on the first vehicle; The control unit determines the criteria for the determination based on the point at which the sensor value is acquired. An information processing device, The control unit At a first point, if the sensor value exceeds a first threshold, it is determined that there is an abnormality in the road surface; determining that there is an abnormality in the road surface when the sensor value exceeds a second threshold value that is greater than the first threshold value or falls below a third threshold value that is less than the second threshold value at a second point different from the first point; The second point is a point where a predetermined structure is present on the road surface. Information processing device.

2. the sensor values include a rate of change of wheel speed; The information processing device according to claim 1 .

3. The structure is a bump, a rumble strip, or an anti-skid surface.

3. The information processing device according to claim 1.

4. The method further includes a storage unit that stores information about the location of the structure on the road.

3. The information processing device according to claim 1.

5. The storage unit further stores the type of the structure. The information processing device according to claim 4 .

6. The control unit varies the criteria for the determination depending on the type of the structure.

3. The information processing device according to claim 1.

7. The control unit estimates that the first vehicle is traveling at the second location based on a driving operation performed on the first vehicle.

3. The information processing device according to claim 1.

8. the control unit estimates that the first vehicle has run over rumble strips when an operation to correct a lane departure is performed on the first vehicle. The information processing device according to claim 7 .

9. acquiring a sensor value from a sensor mounted on the first vehicle; determining an abnormality in the road surface based on the sensor value; varying the criteria for the determination using the sensor values based on the point at which the sensor values are acquired; An information processing method, comprising: At a first point, if the sensor value exceeds a first threshold, it is determined that there is an abnormality in the road surface; If the sensor value at a second point different from the first point exceeds a second threshold value that is greater than the first threshold value, or if the sensor value falls below a third threshold value that is smaller than the second threshold value, it is determined that there is an abnormality on the road surface. The second point is a point where a predetermined structure is present on the road surface. Information processing methods.

10. the sensor values include a rate of change of wheel speed; The information processing method according to claim 9.

11. further comprising the step of obtaining information regarding the location of the structure on a road.

11. The information processing method according to claim 9 or 10.

12. further comprising the step of acquiring a type of the structure; The information processing method according to claim 11.

13. The criteria for the determination are varied depending on the type of the structure.

11. The information processing method according to claim 9 or 10.

14. and further comprising a step of estimating that the first vehicle is traveling at the second location based on a driving operation performed on the first vehicle.

11. The information processing method according to claim 9 or 10.

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