Estimation device, estimation method, and program

Abstract

Provided is an estimation device or the like capable of estimating the range in which a vehicle moves while the brakes are applied.　An estimation device 10 according to one aspect of the present disclosure comprises: a load data acquisition unit 110 that acquires measurement data on transition in the magnitude of the load, measured by a plurality of load sensors embedded in the installation area of the road surface; a specifying unit 120 that specifies, from the measurement data, a vehicle load transition, which is a transition in the position and magnitude of the load due to the tires of the same vehicle; a range estimating unit 140 that estimates, from the specified vehicle load transition, a braking range in which the vehicle has moved with the brake applied; and an output unit 150 that outputs the estimated braking range.

Description

[Technical Field]

[0001] The present disclosure relates to a technology for estimating vehicle information, and more particularly to a technology for estimating the range traveled by a vehicle while braking. [Background technology]

[0002] As evidence of a traffic accident, it is important to identify the range of movement of a vehicle while braking. However, brake marks on the road surface are not always available. The range of movement of a vehicle while braking cannot always be determined by visual inspection of the scene.

[0003] Patent Document 1 describes a control system that acquires pressure information, including pressure values ​​from vehicles traveling on a road, output by pressure sensors installed at stopping points on the road. This control system acquires sudden braking information indicating sudden braking by the vehicle based on the pressure information, and generates a control signal for controlling a traffic light installed on the road based on the sudden braking information.

[0004] Patent Document 2 describes a slip ratio measurement device that determines the tire load center of gravity and its trajectory using the outputs of at least three or more load sensors acting on a plate buried in the road surface and the outputs of a wheel speed measurement unit. This slip ratio measurement device determines the ground speed and slip ratio from the tire load center of gravity and its trajectory.

[0005] Patent Document 3 describes a tire-road surface condition measuring device that measures the tire's contact patch shape and contact force on the road surface using load detectors buried in the measurement road surface and records the measured values ​​in chronological order. The load detectors are buried side by side in a detection area that is wider than the tire's contact patch width when the vehicle is stationary, in a transverse direction that is approximately perpendicular to the vehicle's traveling direction. The tire-road surface condition measuring device also includes protrusion detectors on both ends of the detection area, and a speed measuring device. The protrusion detectors detect when a tire traveling on the measurement road surface protrudes from the detection area. The speed measuring device measures the vehicle's traveling speed when it passes through the area where the load detectors are installed. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Japanese Patent Application Publication No. 2018-073029 [Patent Document 2] Japanese Patent Application Publication No. 2018-031690 [Patent Document 3] Japanese Patent Application Laid-Open No. 2005-096595 Summary of the Invention [Problem to be solved by the invention]

[0007] The control system described in Patent Document 1 can determine whether a vehicle has suddenly braked as it passes a stop line. The slip ratio measurement device described in Patent Document 2 can obtain the trajectory of the tire load center of gravity. The tire-road surface shape measurement device described in Patent Document 3 can obtain a time series of load measurements taken at multiple points arranged in a straight line as the tire passes through them. However, the technologies described in Patent Documents 1 to 3 cannot estimate the range traveled by a vehicle while braking.

[0008] One object of the present disclosure is to provide an estimation device or the like that can estimate the range traveled by a vehicle while the brakes are applied. [Means for solving the problem]

[0009] An estimation device according to one aspect of the present disclosure includes a load data acquisition means for acquiring measurement data of the change in magnitude of the load measured by a plurality of load sensors embedded in a laid area of ​​the road surface, an identification means for identifying a vehicle load change, which is the change in the position and magnitude of the load applied by the tires of the same vehicle, from the measurement data, a range estimation means for estimating a braking range through which the vehicle has moved with the brakes applied, from the identified vehicle load change, and an output means for outputting the estimated braking range.

[0010] An estimation method according to one aspect of the present disclosure acquires measurement data of the change in load magnitude measured by a plurality of load sensors embedded in a laid area of ​​a road surface, identifies from the measurement data a vehicle load change, which is the change in the position and magnitude of the load applied by the tires of the same vehicle, estimates from the identified vehicle load change a braking range through which the vehicle moved while the brakes were applied, and outputs the estimated braking range.

[0011] A storage medium according to one aspect of the present disclosure stores a program that causes a computer to execute the following processes: a load data acquisition process that acquires measurement data of a change in the magnitude of a load measured by a plurality of load sensors embedded in a laid area of ​​a road surface; an identification process that identifies, from the measurement data, a vehicle load change that is a change in the position and magnitude of a load applied by tires of the same vehicle; a range estimation process that estimates, from the identified vehicle load change, a braking range through which the vehicle has moved with the brakes applied; and an output process that outputs the estimated braking range. One aspect of the present disclosure is also realized by the above-described program. [Effects of the Invention]

[0012] The present disclosure has the advantage of being able to estimate the range traveled by a vehicle while braking. [Brief explanation of the drawings]

[0013] [Figure 1]FIG. 1 is a block diagram illustrating an example of the configuration of an estimation device according to a first embodiment of the present disclosure. [Figure 2] FIG. 2 is a flowchart illustrating an example of the operation of the estimation device according to the first embodiment of the present disclosure. [Figure 3] FIG. 3 is a block diagram illustrating an example of the configuration of an estimation system according to the second embodiment of the present disclosure. [Figure 4] FIG. 4 is a flowchart illustrating an example of the operation of the estimation device according to the second embodiment of the present disclosure. [Figure 5] FIG. 5 is a block diagram illustrating an example of the configuration of an estimation system according to the third embodiment of the present disclosure. [Figure 6] FIG. 6 is a flowchart illustrating an example of the operation of the estimation device according to the third embodiment of the present disclosure. [Figure 7] FIG. 7 is a block diagram illustrating an example of the configuration of an estimation system according to the fourth embodiment of the present disclosure. [Figure 8] FIG. 8 is a flowchart illustrating an example of the overall operation of the estimation device according to the fourth embodiment of the present disclosure. [Figure 9] FIG. 9 is a flowchart illustrating an example of an operation of a driving abnormality detection process of the estimation device according to the fourth embodiment of the present disclosure. [Figure 10] FIG. 10 is a flowchart illustrating an example of the operation of the abnormal sound detection process of the estimation device according to the fourth embodiment of the present disclosure. [Figure 11] FIG. 11 is a diagram illustrating an example of a hardware configuration of a computer capable of realizing an estimation device according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0014] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings.

[0015] First Embodiment First, an estimation device according to a first embodiment of the present disclosure will be described in detail with reference to the drawings.

[0016] <Configuration> FIG. 1 is a block diagram illustrating an example of the configuration of an estimation device according to a first embodiment of the present disclosure. In the example illustrated in FIG. 1, the estimation device 10 includes a load data acquisition unit 110, an identification unit 120, a range estimation unit 140, and an output unit 150. The load data acquisition unit 110 acquires measurement data of the transition of load magnitude measured by a plurality of load sensors embedded in a laid area of ​​the road surface. The laid area is an area of ​​the road where the load sensors are laid. The identification unit 120 identifies, from the measurement data, a vehicle load transition, which is a transition of the position and magnitude of the load applied by the tires of the same vehicle. The range estimation unit 140 estimates, from the identified vehicle load transition, a braking range in which the vehicle traveled while the brakes were applied. The output unit 150 outputs the estimated braking range.

[0017] <Load sensor> The load sensor is a pressure sensor that can be embedded in the road surface. Multiple load sensors are embedded in the road surface, for example, in an area including road intersections. The multiple load sensors may be embedded in the road surface, for example, in an area including pedestrian crossings. The multiple load sensors may be embedded in the road surface, for example, in an area including an area where a vehicle may stop at a traffic light. The multiple load sensors may be embedded in the road surface, for example, in an area including a stop line. The multiple load sensors may be embedded at predetermined intervals, for example. The spacing between the multiple load sensors in the vehicle's traveling direction may be different from the spacing between the multiple load sensors in the cross-sectional direction of the road. The multiple load sensors may be embedded in a regular pattern. The pattern of the multiple load sensors may not be regular. In this case, the distance between the multiple load sensors may be determined experimentally (for example, to several centimeters) for multiple types of vehicles so that at least one sensor installation position is included in the area where the tires of the traveling vehicle come into contact with the ground. The distances between the load sensors may be determined for a plurality of types of vehicles so that different tires of a traveling vehicle do not apply loads to adjacent load sensors, where different tires include different tires of the same vehicle and tires of different vehicles.

[0018] More generally, the positions of the load sensors may be determined experimentally, for example, so that the installation position of at least one sensor is included in the range where the tires of the moving automobiles contact the ground, and the positions of the load sensors may be determined so that different tires of the moving automobiles do not apply loads to adjacent load sensors for the moving automobiles.

[0019] The position where each of the plurality of load sensors is embedded is obtained in advance by measurement, etc. Information on the position where each of the plurality of load sensors is embedded is provided to the identifying unit 120 in advance.

[0020] The load sensor measures the load exerted on the road by the vehicle's tires.

[0021] <Load data acquisition unit 110> The load data acquiring unit 110 may be configured to acquire load measurement values ​​from each of a plurality of load sensors at the same time, for example. The plurality of load sensors may be configured to measure loads at the same time and transmit the measured load measurement values ​​to the load data acquiring unit 110. The load data acquiring unit 110 may acquire load magnitude measurement values ​​(i.e., trends in load magnitude measurement values, in other words, measurement data of load magnitude trends) measured at the same time at multiple points in time from each of the plurality of load sensors. The load data acquiring unit 110 may generate data of load magnitude measurement values ​​for each load sensor (hereinafter also simply referred to as measurement data) arranged, for example, in order of measurement time.

[0022] <Specific part 120> For example, for each timing at which the load is measured, the identification unit 120 estimates the position of the tire and the magnitude of the load that the tire applies to the road surface from the load measurement values ​​at the same timing measured by multiple load sensors. For example, when a measurement value at a new timing (hereinafter referred to as the latest timing) is obtained, the identification unit 120 estimates the position of the tire and the magnitude of the load that the tire applies to the road surface from the load measurement value at the latest timing.

[0023] The identification unit 120 then tracks the position of the same tire for each timing at which the load is measured, for example. Hereinafter, the time series of the positions of a tire whose position has been detected at one or more timings and which is considered to be the tire being tracked will be referred to as the transition of tire position. The tire being tracked is a tire that is the subject of a process in which, when a measurement value at the latest timing is obtained, the position at the latest timing is selected from the estimated tire positions at the latest timing.

[0024] For example, the identification unit 120 selects, from the most recent position in the tire position transition of the tire being tracked, the tire position at the most recent time that is included in the range of tire movement between the measurement time at which the position was estimated and the most recent time. The range of tire movement between one time and another time may be determined in advance as appropriate. The identification unit 120 adds the selected tire position at the most recent time to the tire position transition of the tire being tracked. If multiple tire positions at the most recent times are selected, the identification unit 120 may add all of the selected tire positions at the most recent times to the tire position transition of the tire being tracked as the tire positions at the most recent times. The identification unit 120 may add the same tire position at the most recent time to the tire position transition of each of the multiple tires being tracked.

[0025] As described above, the identification unit 120 estimates the position of the tire and the magnitude of the load that the tire applies to the road surface for each tire at each timing at which a measurement value is obtained. Therefore, by estimating the transition of the position of the tire being tracked, the identification unit 120 identifies the transition of the position of the tire being tracked and the magnitude of the load that the tire applies to the road surface up to the latest timing for each tire. The transition of the tire position and the magnitude of the load that the tire applies to the road surface is referred to as tire load transition.

[0026] The identifying unit 120 determines the tire whose position has not been added to the tire position transition of the tire being tracked, among the tires whose positions have been estimated at the latest timing, as the new tire being tracked. In other words, the identifying unit 120 determines the tire whose position has not been added to the tire position transition of the tire being tracked, among the tire positions at the latest timing, as the first tire position in the tire position history of the new tire being tracked.

[0027] Furthermore, the identification unit 120 tracks the vehicle using the transition of the tire position of the tire being tracked. This vehicle tracking involves determining the latest tire position of the tire being tracked that has been determined to belong to the same vehicle. The vehicle being tracked is a vehicle whose tires have been identified as the tire being tracked. The identification unit 120 calculates the change in relative position between the tires between successive timings in the tire position history of the vehicle being tracked. Then, it determines whether the change in the relative position of the tire from the previous timing (hereinafter referred to as the relative position change) at the latest timing falls within a possible range of relative position changes for tires of the same vehicle. In other words, the identification unit 120 identifies a relative position change at the tire position at the latest timing that does not fall within a possible range of relative position changes for tires of the same vehicle. If such a relative position change at the tire position at the latest timing is identified, the identification unit 120 identifies the tire whose tire position at the latest timing is the cause of the identified relative position change.

[0028] It should be noted that the relative positions of two tires in the description of the identification unit 120 refer to, for example, the distance between the two tires.

[0029] For example, the identification unit 120 may identify, as the cause of the relative position change, the tire with the largest number of other tires being tracked as tires of the same vehicle, whose relative position at the most recent timing is not included in the range of possible changes in the relative position of tires of the same vehicle. Hereinafter, a change in relative position that falls within the range of possible changes in the relative position of tires of the same vehicle will be referred to as "satisfying the same vehicle criterion." Furthermore, a change in relative position that does not fall within the range of possible changes in the relative position of tires of the same vehicle will be referred to as "not satisfying the same vehicle criterion." For example, the identification unit 120 may identify, as the cause of the relative position change, the tire position at the most recent time of the tire for which the number of other tires being tracked as tires of the same vehicle is the largest, and for which the change in relative position at the most recent time does not satisfy the same vehicle criterion. For example, the identification unit 120 may identify, as the cause of the relative position change, the tire position at the most recent time of the tire for which the number of other tires being tracked as tires of the same vehicle is more than half of the number of tires on the vehicle, and for which the change in relative position at the most recent time does not satisfy the same vehicle criterion.

[0030] The identifying unit 120 excludes the tire position at the latest timing of a tire that has been identified as a cause of a relative position change from the tire position transition of that tire. The identifying unit 120 may repeat identifying the cause of a relative position change and excluding the identified cause from the tire position transition until there is no longer any change in relative position that does not satisfy the same vehicle criterion.

[0031] Furthermore, when the transition of tire position of one tire includes multiple tire positions at the most recent timing, the identifying unit 120 identifies the tire position with the smallest change in relative position at the most recent timing relative to other tires on the same vehicle. Specifically, the identifying unit 120 identifies the tire position with the smallest representative value (e.g., average value) of the magnitude of change in relative position at the most recent timing relative to other tires on the same vehicle. The identifying unit 120 then excludes tire positions other than the identified tire position from the multiple tire positions at the most recent timing included in the transition of tire position of one tire.

[0032] Furthermore, the identification unit 120 extracts tires being tracked that are not tires of the vehicle being tracked. Then, from the extracted tires being tracked, the identification unit 120 extracts combinations of tires being tracked whose relative positions at the latest timing are within the range of possible relative positions of tires of the same vehicle. The identification unit 120 identifies the tires being tracked included in the extracted combinations as tires of a new vehicle being tracked. If there is a combination of tire position transitions of multiple tires being tracked whose latest relative positions are within the range of possible relative positions of tires of the same vehicle and are not the tire position transitions of tires of the vehicle being tracked, the identification unit 120 identifies these multiple tires being tracked as tires of a new vehicle being tracked. Note that in this case, the range of possible relative positions of tires of the same vehicle may be determined as appropriate for each vehicle type. In this case, vehicle types may be defined as two-wheeled vehicles and four-wheeled vehicles. Types of four-wheeled vehicles may be further subdivided into light vehicles, compact vehicles, standard vehicles, large vehicles, etc. Vehicle types are not limited to these examples. Vehicle types may be determined as appropriate.

[0033] The identification unit 120 may delete the history of a tracked tire for which the latest tire position has not been obtained for a predetermined number of timings. Furthermore, the identification unit 120 may exclude a tracked vehicle from the list of vehicles being tracked if the tracked tire is no longer present.

[0034] <Range Estimation Unit 140> For each vehicle being tracked, the range estimation unit 140 uses information on the tire load transition of the vehicle's tires to identify the range in which the vehicle moved while braking. The range in which the vehicle moved while braking may be represented, for example, by the start and end positions of each tire in the tire load transition of the vehicle's tires during the vehicle's movement while braking. The range in which the vehicle moved while braking may be represented, for example, by the history of the position of each tire in the tire load transition of the vehicle's tires during the vehicle's movement while braking.

[0035] The range estimation unit 140 may determine whether the vehicle is in a braked state based on the ratio between the load on the front wheels of the vehicle and the load on the rear wheels of the vehicle. In this case, the range estimation unit 140 determines whether the tires are front wheels or rear wheels based on the direction of movement of the vehicle (specifically, the direction of movement of each tire). In this case, the front wheels refer to the wheels located in the front of the vehicle in the direction of movement of the vehicle. Also, the rear wheels refer to the wheels located in the rear of the vehicle in the direction of movement of the vehicle. In this case, the front wheels and rear wheels are not necessarily the same as the front wheels and rear wheels in terms of the vehicle's structure. Hereinafter, a state in which the vehicle is moving with the brakes applied will be referred to as a brake-enabled state.

[0036] The range estimation unit 140 may determine that the vehicle has entered a brake-effective state (in other words, that the vehicle has started to enter a brake-effective state) when the ratio of the rear wheel load to the front wheel load decreases. The range estimation unit 140 may also determine that the vehicle has entered a brake-effective state when the ratio of the rear wheel load to the front wheel load decreases and, further, when the reduction rate of the rear wheel load during the period in which the ratio of the rear wheel load to the front wheel load is decreasing, satisfies a predetermined criterion (hereinafter referred to as a reduction rate criterion). When the reduction rate takes a positive value when the rear wheel load decreases, the reduction rate criterion may be, for example, that the reduction rate is greater than a reduction rate threshold. When the reduction rate takes a negative value when the rear wheel load decreases, the reduction rate criterion may be, for example, that the reduction rate is smaller than a reduction rate threshold. Then, when it is determined that the vehicle has entered a brake-effective state, the range estimation unit 140 may determine that the tire position at the time when the ratio of the rear wheel load to the front wheel load starts to decrease is the start position of the brake-effective state.

[0037] The range estimation unit 140 may determine that the vehicle is no longer in a brake-effective state (in other words, that the vehicle's brake-effective state has ended) when the ratio of the rear wheel load to the front wheel load increases and then becomes constant. The range estimation unit 140 may also determine that the vehicle is no longer in a brake-effective state when the ratio of the rear wheel load to the front wheel load increases and then becomes constant, and in addition, when the increase rate of the rear wheel load, when the ratio has become constant, relative to the rear wheel load before the increase in the ratio, satisfies an increase rate criterion. When the increase rate takes a positive value when the rear wheel load increases, the increase rate criterion may be, for example, that the increase rate is greater than an increase rate threshold. When determining that the vehicle is no longer in a brake-effective state, the range estimation unit 140 may determine that the tire position at the time when the ratio of the rear wheel load to the front wheel load increases and then becomes constant is the end point of the brake-effective state.

[0038] The method for determining whether the vehicle is in a braked state is not limited to the above example.

[0039] <Output unit 150> The output unit 150 outputs the braking range (specifically, information on the braking range) to, for example, an output destination device.

[0040] The output destination device may be a storage device. In this case, the output unit 150 outputs the braking range to, for example, the storage device. In other words, the output unit 150 stores the braking range in the storage device.

[0041] The output destination device may be a media reader / writer device that stores data in a storage medium. In this case, the output unit 150 outputs the braking range to the media reader / writer device. The media reader / writer device receives the braking range and stores the received braking range in the storage medium. In other words, the output unit 150 stores the braking range in the storage medium via the media reader / writer device.

[0042] The output destination device may be, for example, another information processing device that is communicably connected to the estimation device 10 via a communication network. In this case, the output unit 150 outputs the braking range to the other information processing device.

[0043] The output destination device is not limited to the above examples.

[0044] <Operation> Next, the operation of the estimation device 10 according to the first embodiment of the present disclosure will be described in detail with reference to the drawings.

[0045] 2 is a flowchart illustrating an example of the operation of the estimation device 10 according to the first embodiment of the present disclosure. In the example illustrated in FIG. 2, first, the load data acquisition unit 110 acquires load measurement data from a load sensor (step S11). Next, the identification unit 120 identifies the vehicle load transition of the same vehicle from the measurement data (step S12). The range estimation unit 140 estimates the braking range through which the vehicle moves when the brakes are applied from the vehicle load transition (step S13). The output unit 150 outputs the estimated braking range (step S14).

[0046] The estimation device 10 may repeat the operations shown in FIG.

[0047] <Effects> This embodiment has the advantage of being able to estimate the range in which a vehicle has moved while the brakes are applied. This is because the identification unit 120 identifies the vehicle load transition of the same vehicle from load measurement data measured by multiple load sensors embedded in the road surface. As described above, the vehicle load transition of the same vehicle represents the transition of the combination of the load position and load magnitude relative to the road surface, applied by the tires of the same vehicle. Then, the range estimation unit 140 estimates the braking range in which the vehicle has moved while the brakes are applied, from the identified vehicle load transition.

[0048] <Modification of the first embodiment> The identification unit 120 identifies the tire position at the latest timing of each of the tires being tracked of the vehicle being tracked so that the change in the relative position of the tire being tracked of the vehicle being tracked at the latest timing from the relative position at the immediately preceding timing satisfies the same vehicle criterion described above. Specifically, the identification unit 120 identifies one tire position from the estimated tire positions at the latest timing as the tire position at the latest timing of each of the tires being tracked of the vehicle being tracked so that the same vehicle criterion described above is satisfied at the latest timing. The identification unit 120 adds the tire position identified as the position at the latest timing of the tire of the vehicle being tracked and the magnitude of the load at that tire position to the tire load transition of that tire as the position at the latest timing and magnitude of the load of that tire.

[0049] If the tire position transition of the tracked vehicle includes a tire whose tire position at the timing immediately before the latest timing is not included in the tire position transition, the identification unit 120 estimates the tire position at the latest timing for that tire, for example, as follows. Specifically, the identification unit 120 first calculates the change in position from the immediately previous timing for the tire whose latest position is identified as described above. The identification unit 120 also calculates the relative position of the tire in the tire position transition of the tracked tire of the tracked vehicle. The identification unit 120 estimates the latest position of the tire whose position at the immediately previous timing is obtained when the tire whose position at the immediately previous timing moves to the position identified as described above while maintaining the calculated relative position of the tire. The identification unit 120 extracts the tire position at the latest timing that is included in a predetermined range based on the estimated position. The predetermined range based on the estimated position may be determined in advance as appropriate. If multiple tire positions are extracted, the identification unit 120 selects one tire position using a predetermined method. For example, the identification unit 120 may select, from among the extracted tire positions, the tire position closest to the estimated position as the position of the latest timing for the tire for which the position of the latest timing has not been obtained. The identification unit 120 adds the position selected as the position of the latest timing for the tire for which the position of the latest timing has not been obtained and the magnitude of the load at that position to the tire load transition of the tire as the position of the latest timing and the magnitude of the load for that tire.

[0050] <Detailed example of the identification unit 120> The following will be described in detail, focusing on the method for identifying the tire position and the load magnitude.

[0051] The identifying unit 120 receives data on the measurement values ​​of the load magnitude for each load sensor, arranged in order of measurement time, for example (i.e., the above-mentioned measurement data). The identifying unit may group, from among the measurement values ​​of loads measured at the same timing among the measurement values ​​included in the measurement data, the measurement values ​​of loads caused by the same tire, using the positions of the load sensors that measured the loads. For example, the identifying unit 120 may group the load sensors that measured a load magnitude equal to or greater than a predetermined minimum load value into one or more groups, such that two adjacent load sensors are included in the same group. Then, the identifying unit 120 calculates a representative value (e.g., one of the maximum, average, median, intermediate value, etc., that is predetermined) of the measurement values ​​of the loads included in the same group. The identifying unit 120 also calculates a representative value of the positions where the measurement values ​​of the loads included in the same group were measured. The representative value of the positions where the measurement values ​​of the loads included in the same group were measured may be, for example, the center of gravity of the positions of the load sensors that measured the measurement values ​​included in the same group. The representative value of the positions where the load measurements of loads included in the same group were measured may be, for example, another value (e.g., the leading position in the direction of travel) calculated from the positions of the load sensors that measured the load measurements of loads included in the same group. The representative value of the positions where the load measurements of loads included in the same group were measured will hereinafter be referred to as the tire load value. The representative value of the positions where the load measurements of loads included in the same group were measured will hereinafter be referred to as the tire load position. The position where a load is generated by one tire (hereinafter referred to as the tire load position) and the magnitude of the generated load (hereinafter referred to as the tire load magnitude) are represented by a combination of the tire load position and the tire load value. The position where a load is generated by one tire (hereinafter referred to as the tire load position) and the magnitude of the generated load (hereinafter referred to as the tire load magnitude) are represented by data including a combination of the tire load position and the tire load value, hereinafter referred to as the tire data value. The tire data value includes a combination of the tire load position and the tire load value for one tire at one timing.

[0052] The identification unit 120 calculates tire data values ​​(i.e., combinations of tire load values ​​and tire load positions) at multiple times from measurement values ​​measured by multiple load sensors at multiple times. Then, the identification unit 120 determines the association between the combinations of tire load values ​​and tire load positions calculated from measurement values ​​at consecutive times (i.e., associations between tire data values). That is, the identification unit 120 selects a tire data value that represents the load magnitude and load position at a next time for a tire whose load magnitude and load position are represented by a tire data value at a certain time. Then, the identification unit 120 associates the tire data value at a certain time with the tire data value at the next time that is selected for that tire data value.

[0053] In this case, the identification unit 120 may determine whether the magnitude of change in tire load position between the tire data value at a certain timing and the tire data value at the next timing is within a range in which the vehicle can move between consecutive timings. If the determination result indicates that the magnitude of change in tire load position is within a range in which the vehicle can move between consecutive timings, the identification unit 120 may associate the tire data value at the certain timing with the tire data value at the next timing. The range in which the vehicle can move between consecutive timings is not limited to the range in which the vehicle can move during normal driving. The movement of the vehicle between consecutive timings includes movement of the vehicle due to a collision accident.

[0054] A combination of tire data values ​​at a certain timing and tire data values ​​at a next timing that are associated with each other is referred to as a tire data value set. The tire data value set includes one tire data value at a certain timing and one tire data value at a next timing. In other words, the identification unit 120 generates the tire data value set.

[0055] <Second embodiment> Next, a second embodiment of the present disclosure will be described in detail with reference to the drawings.

[0056] <Configuration> FIG. 3 is a block diagram illustrating an example of the configuration of an estimation system according to a second embodiment of the present disclosure. In the example illustrated in FIG. 3, the estimation system 1 of this embodiment includes an estimation device 100, a load sensor 200, and an output destination device 300. The estimation device 100 includes a load data acquisition unit 110, an identification unit 120, a driving abnormality detection unit 130, a range estimation unit 140, and an output unit 150. The load sensor 200 of this embodiment is the same as the load sensor of the first embodiment. The output destination device 300 of this embodiment is the same as the output destination device of the first embodiment. The load data acquisition unit 110, the identification unit 120, the range estimation unit 140, and the output unit 150 of this embodiment are the same as the load data acquisition unit 110, the identification unit 120, the range estimation unit 140, and the output unit 150 of the first embodiment, respectively, except for the differences described below. The load data acquisition unit 110, the identification unit 120, the range estimation unit 140, and the output unit 150 of this embodiment operate in the same manner as the load data acquisition unit 110, the identification unit 120, the range estimation unit 140, and the output unit 150 of the first embodiment, respectively, except for the differences described below.

[0057] <Driving Abnormality Detection Unit 130> The driving abnormality detection unit 130 detects the occurrence of a driving abnormality of the vehicle from at least one of the transition of the tire position and the transition of the vehicle load of the vehicle.

[0058] An abnormality in the vehicle's driving may be, for example, when the magnitude of acceleration of any of the vehicles being tracked exceeds a predetermined acceleration threshold. The magnitude of the vehicle's acceleration may be a representative value of the magnitude of acceleration of the vehicle's tires. The representative value of the magnitude of acceleration of the vehicle's tires represents a statistical value, such as the average or maximum value, of the acceleration of multiple tires of the vehicle. An abnormality in the vehicle's driving may be, for example, when the magnitude of acceleration of any of the tires being tracked exceeds a predetermined acceleration threshold. In these cases, the driving abnormality detection unit 130 calculates the magnitude of the acceleration of that tire from the position transition included in the tire position transition.

[0059] The acceleration threshold may vary depending on the location on the road. The acceleration threshold may also vary depending on the direction of acceleration. For example, in a location where a vehicle travels only when turning left, the acceleration threshold for the magnitude of acceleration in a direction in which acceleration may occur when turning left may be smaller than the acceleration threshold for the magnitude of acceleration in a direction in which acceleration is unlikely to occur when turning left. The direction in which acceleration may occur when turning left is, for example, a direction toward the left relative to the traveling direction before the left turn. The direction in which acceleration is unlikely to occur when turning left is, for example, a direction toward the right relative to the traveling direction before the left turn.

[0060] In a location where a vehicle travels only when turning right, the acceleration threshold for the magnitude of acceleration in a direction in which acceleration may occur when turning right may be smaller than the acceleration threshold for the magnitude of acceleration in a direction in which acceleration is unlikely to occur when turning right. The direction in which acceleration may occur when turning right is, for example, a direction to the right of the traveling direction before the right turn. The direction in which acceleration is unlikely to occur when turning right is, for example, a direction to the left of the traveling direction before the right turn.

[0061] In a location where the vehicle travels straight, the acceleration threshold for the magnitude of acceleration and deceleration in the straight-ahead direction may be greater than the acceleration threshold for the magnitude of acceleration in a direction other than the straight-ahead direction, and the acceleration threshold for the magnitude of acceleration in the straight-ahead direction may be smaller than the acceleration threshold for the magnitude of deceleration in the straight-ahead direction.

[0062] In the above examples, the locations where the vehicle can only travel when turning left, the locations where the vehicle can only travel when turning right, and the locations where the vehicle can travel straight may be determined in advance according to the shape of the road and traffic rules.

[0063] In the above example, if the magnitude of tire or vehicle acceleration is greater than the acceleration threshold, the vehicle movement is deemed to satisfy the abnormal movement criterion. The abnormal movement criterion is that the magnitude of tire or vehicle acceleration is greater than the acceleration threshold. The driving abnormality detection unit 130 detects vehicle movement that satisfies the abnormal movement criterion as abnormal.

[0064] The abnormality in the vehicle's driving may be a deviation of the tire's position from the range in which the tire can travel during normal driving. The range in which the tire can travel during normal driving may be predetermined depending on the shape of the road and traffic regulations. The abnormality in the vehicle's driving may be, for example, a deviation of the tire from the road in an intersection area. The abnormality in the vehicle's driving may be, for example, a deviation of the tire from the road in an intersection area. The abnormality in the vehicle's driving may be, for example, a deviation of the tire from the road in an oncoming lane.

[0065] In these examples, when the position of a tire moves to an area outside the range where the tire can pass during normal vehicle driving, the vehicle is deemed to have moved to a position that satisfies the abnormal position criterion. The abnormal position criterion is that the vehicle position is included in an area outside the range where the tire can pass during normal vehicle driving. The driving abnormality detection unit 130 detects the vehicle moving to a position that satisfies the abnormal position criterion as an abnormality.

[0066] Abnormalities in vehicle running are not limited to the examples described above.

[0067] <Range Estimation Unit 140> In this embodiment, when the driving abnormality detection unit 130 detects an abnormality in the driving of the vehicle, the range estimation unit 140 estimates a braking range in which the vehicle has moved while the brakes are applied.

[0068] <Operation> 4 is a flowchart illustrating an example of the operation of the estimation device 100 according to the second embodiment of the present disclosure. In the example illustrated in FIG. 4, first, the load data acquisition unit 110 acquires load measurement data from a load sensor (step S101). Next, the identification unit 120 identifies the vehicle load transition of the same vehicle from the measurement data (step S102). Next, the driving abnormality detection unit 130 detects an abnormality (step S103). Specifically, the driving abnormality detection unit 130 detects the above-mentioned abnormality in the vehicle's driving.

[0069] If no abnormality is detected (NO in step S104), the estimating device 100 ends the operation shown in FIG.

[0070] If an abnormality is detected (YES in step S104), the range estimation unit 140 estimates the braking range in which the vehicle moved while the brakes were applied, based on the transition of the vehicle load (step S105). The output unit 150 outputs the estimated braking range (step S106). Then, the estimation device 100 ends the operation shown in FIG.

[0071] The estimation device 100 may repeat the operations shown in FIG.

[0072] <Effects> This embodiment has the same effects as the first embodiment, for the same reasons as those for the effects of the first embodiment.

[0073] This embodiment has the advantage of being able to suppress the output of braking ranges with low importance. The reason for this is that when an abnormality is detected by the driving abnormality detection unit 130, the range estimation unit 140 estimates the braking range and the output unit 150 outputs the braking range. When no abnormality is detected, the possibility of a traffic accident occurring is low. When the possibility of a traffic accident occurring is low, there is no need to obtain information about the braking range, so the importance of the estimated braking range is low.

[0074] <Third embodiment> Next, a third embodiment of the present disclosure will be described in detail with reference to the drawings.

[0075] <Configuration> 5 is a block diagram illustrating an example of the configuration of an estimation system according to a third embodiment of the present disclosure. In the example illustrated in FIG. 5, an estimation system 2 according to this embodiment includes an estimation device 101, a load sensor 200, an output destination device 300, and an imaging device 400. The estimation device 101 includes a load data acquisition unit 110, an identification unit 120, a driving abnormality detection unit 130, a range estimation unit 140, an output unit 150, and an image acquisition unit 160. The load data acquisition unit 110, the identification unit 120, the driving abnormality detection unit 130, the range estimation unit 140, and the output unit 150 according to this embodiment are the same as the load data acquisition unit 110, the identification unit 120, the driving abnormality detection unit 130, the range estimation unit 140, and the output unit 150 according to the first embodiment, respectively, except for the differences described below. The load data acquisition unit 110, identification unit 120, driving abnormality detection unit 130, range estimation unit 140, and output unit 150 of this embodiment operate in the same manner as the load data acquisition unit 110, identification unit 120, driving abnormality detection unit 130, range estimation unit 140, and output unit 150 of the first embodiment, respectively, except for the differences described below.

[0076] <Imaging device 400> The imaging device 400 captures an image of the installation area. The imaging device 400 may include a plurality of imaging devices that capture images of the installation area from different directions. The resolution of the image captured by the imaging device 400 may be such that, for example, the characters on the license plates of vehicles traveling on the installation area can be recognized in the image of the vehicles traveling on the installation area.

[0077] The video captured by the imaging device 400 is transmitted to the video acquisition unit 160 .

[0078] <Video Acquisition Unit 160> The video acquisition unit 160 receives captured video from the imaging device 400. The video acquisition unit 160 holds the received video for a predetermined period of time after receiving the video.

[0079] Specifically, the imaging device 400 may transmit video data to the video acquisition unit 160, for example. The video acquisition unit 160 may then have a temporary storage device with a size capable of storing video data of a predetermined period or longer, and store the received video data in the temporary storage device for a predetermined period after receiving the video data. The length of the predetermined period may be, for example, a length determined experimentally so as to include a first time range described below.

[0080] Then, when the video acquisition unit 160 receives a request from the output unit 150 for the video captured during the first time range, the video acquisition unit 160 reads the video captured during the first time range from the temporary storage device and sends the read video to the output unit 150.

[0081] <Driving Abnormality Detection Unit 130> The driving abnormality detection unit 130 of this embodiment further estimates the time when the detected abnormality occurred. The driving abnormality detection unit 130 estimates the time when the detected abnormality occurred from the typical time required from when a load is applied to the load sensor 200 until the load data acquisition unit 110 acquires the measurement data of the applied load, and the time when the load data acquisition unit 110 receives the measurement data. The typical time required from when a load is applied to the load sensor 200 until the load data acquisition unit 110 acquires the measurement data of the applied load may be experimentally set in advance and provided to the driving abnormality detection unit 130.

[0082] <Output unit 150> When an abnormality in the vehicle's driving is detected, the output unit 150 outputs to the output destination device 300 the video captured by the video acquisition unit 160 within a predetermined range (also referred to as a first time range in this description) that includes the braking range and the time when the detected abnormality occurred. The first time range may be a period determined based on the time when the abnormality occurred. The time when the abnormality occurred used by the output unit 150 is the time when the detected abnormality occurred, estimated by the driving abnormality detection unit 130.

[0083] The output unit 150 requests the video captured during the first time range from the video acquisition unit 160. The output unit 150 receives the video captured during the first time range from the video acquisition unit 160 in response to the request. The output unit 150 may output the video captured during the first time range received from the video acquisition unit 160.

[0084] The output unit 150 may further output the time when the detected abnormality occurred, which is estimated by the driving abnormality detection unit 130.

[0085] <Operation> Fig. 6 is a flowchart illustrating an example of the operation of the estimation device 101 according to the third embodiment of the present disclosure. Among the operations illustrated in Fig. 6, the operations from step S101 to step S105 are the same as the operations from step S101 to step S105 of the estimation device 100 according to the second embodiment illustrated in Fig. 4. In steps S101 to S105, the estimation device 101 performs the same operations as the operations from step S101 to step S105 of the estimation device 100 according to the second embodiment.

[0086] In step S206, the output unit 150 outputs the video of the period including the time when the abnormality occurred and the estimated braking range. The time when the abnormality occurred is the estimated time when the detected abnormality occurred. The video of the period including the time when the abnormality occurred is the video captured during the first time range described above. In step S206, the output unit 150 may further output the time when the detected abnormality occurred, which is estimated by the driving abnormality detection unit 130.

[0087] The estimation device 101 of this embodiment may repeat the operation shown in FIG.

[0088] <Effects> This embodiment has the same effects as the second embodiment, for the same reasons as those for the second embodiment.

[0089] This embodiment further has the effect of increasing the possibility of obtaining video of a traffic accident occurring. This is because, when an abnormality is detected, the output unit 150 outputs video of a period including the time when the abnormality occurred. When an abnormality is detected, there is a possibility that a traffic accident has occurred. There is a possibility that the video of the period including the time when the abnormality occurred will include video of the traffic accident occurring.

[0090] <Fourth embodiment> Next, a fourth embodiment of the present disclosure will be described in detail with reference to the drawings.

[0091] <Configuration> Fig. 7 is a block diagram illustrating an example of the configuration of an estimation system according to a fourth embodiment of the present disclosure. In the example illustrated in Fig. 7, an estimation system 3 according to this embodiment includes an estimation device 102, a load sensor 200, an output destination device 300, an imaging device 400, and a microphone 500. The load sensor 200, the output destination device 300, and the imaging device 400 according to this embodiment are the same as the load sensor 200, the output destination device 300, and the imaging device 400 according to the third embodiment, respectively.

[0092] The estimation device 102 of this embodiment includes a load data acquisition unit 110, an identification unit 120, a driving abnormality detection unit 130, a range estimation unit 140, an output unit 150, a video acquisition unit 160, a sound data acquisition unit 170, and an abnormal sound detection unit 180. The load data acquisition unit 110, the identification unit 120, the driving abnormality detection unit 130, the range estimation unit 140, the output unit 150, and the video acquisition unit 160 of this embodiment are the same as the load data acquisition unit 110, the identification unit 120, the driving abnormality detection unit 130, the range estimation unit 140, the output unit 150, and the video acquisition unit 160 of the first embodiment, respectively, except for differences described below. The load data acquisition unit 110, identification unit 120, driving abnormality detection unit 130, range estimation unit 140, output unit 150, and video acquisition unit 160 of this embodiment operate in the same manner as the load data acquisition unit 110, identification unit 120, driving abnormality detection unit 130, range estimation unit 140, output unit 150, and video acquisition unit 160 of the first embodiment, respectively, except for the differences described below.

[0093] <Microphone 500> The microphone 500 measures the sound generated in the installation area. The microphone 500 transmits data of the measured sound (hereinafter referred to as sound data) to the sound data acquisition unit 170. The microphone 500 may include a plurality of different microphones.

[0094] <Sound data acquisition unit 170> The sound data acquisition unit 170 acquires, from the microphone 500, sound data of the sound measured by the microphone 500.

[0095] <Abnormal sound detection unit 180> The abnormal sound detection unit 180 detects an abnormal sound from the sound data acquired by the sound data acquisition unit 170. An abnormal sound is a sound that satisfies an abnormal sound criterion. The abnormal sound criterion is a criterion that is appropriately determined in advance so that, for example, a sound at the time of a vehicle collision satisfies the criterion.

[0096] When an abnormal sound is detected, the abnormal sound detection unit 180 estimates the time when the detected abnormal sound occurred. The abnormal sound detection unit 180 estimates the time when the detected abnormal sound occurred (hereinafter referred to as the abnormal sound occurrence time) from, for example, a typical period from when the sound is generated until when the sound data acquisition unit 170 receives sound data of the generated sound from the microphone 500, and the time when the sound data acquisition unit 170 receives the data at the time when the abnormal sound occurred.

[0097] When the abnormal sound detection unit 180 detects an abnormal sound, it transmits a notification to the range estimation unit 140. This notification may be a notification indicating that an abnormal sound has been detected.

[0098] When abnormal sound detection section 180 detects an abnormal sound, it sends to output section 150 information on the time when the abnormal sound occurred and sound data measured in a second time range that includes the time when the abnormal sound occurred.

[0099] <Range Estimation Unit 140> When the range estimation unit 140 receives the above-mentioned notification from the abnormal sound detection unit 180, it estimates the braking range.

[0100] <Output unit 150> In this embodiment, when an abnormal sound is detected, the output unit 150 further receives, from the abnormal sound detection unit 180, information on the time the abnormal sound occurred and sound data for a second time range that includes the time the abnormal sound occurred. The output unit 150 requests video captured during the second time range from the video acquisition unit 160, and receives the requested video captured during the second time range from the video acquisition unit 160. The output unit 150 outputs the video captured during the second time range to the output destination device 300. The output unit 150 may further output sound data measured during the second time range to the output destination device 300. The output unit 150 may further output the time the abnormal sound occurred to the output destination device 300. Furthermore, when an abnormal sound is detected, the output unit 150 further outputs an estimated braking range.

[0101] <Video Acquisition Unit 160> As described above, the video acquisition unit 160 includes a temporary storage device large enough to store video of a length equal to or greater than the predetermined period, and stores the received video data in the temporary storage device for a predetermined period after receiving the video data. In this embodiment, the length of this predetermined period is determined experimentally, for example, so as to include the first time range and the second time range described above.

[0102] <Operation> 8 is a flowchart illustrating an example of the overall operation of the estimation device 102 according to the fourth embodiment of the present disclosure. In the example shown in FIG. 8, the estimation device 102 performs a driving abnormality detection process (step S301). Then, the estimation device 102 performs an abnormal sound detection process (step S302). The driving abnormality detection process and the abnormal sound detection process will be described in detail later.

[0103] The estimating device 102 may repeat the operation shown in Fig. 8. The estimating device 102 may perform the operation of step S301 after step S302. The estimating device 102 may perform the operation of step S301 and the operation of step S302 in parallel.

[0104] 9 is a flowchart illustrating an example of the operation of the driving abnormality detection process of the estimation device 102 according to the fourth embodiment of the present disclosure. The operation illustrated in FIG. 9 is the same as the operation of the estimation device 101 according to the third embodiment illustrated in FIG. 7. The estimation device 102 performs the same operation as the operation of the estimation device 101 according to the third embodiment illustrated in FIG. 7.

[0105] FIG. 10 is a flowchart illustrating an example of the operation of the abnormal sound detection process of the estimation device 102 according to the fourth embodiment of the present disclosure. In the example illustrated in FIG. 10, the sound data acquisition unit 170 acquires sound measurement data from the microphone 500 (step S311). Next, the abnormal sound detection unit 180 detects an abnormal sound from the sound measurement data (step S312). If an abnormal sound is not detected (NO in step S313), the estimation device 102 ends the operation illustrated in FIG. 10. If an abnormal sound is detected (YES in step S313), the output unit 150 outputs a video of a period including the time when the abnormal sound was detected and an estimated braking range (step S314). In step S314, the output unit 150 may further output sound data measured in a second time range. In step S314, the output unit 150 may further output the time when the abnormal sound occurred. Then, the estimation device 102 ends the operation illustrated in FIG. 10.

[0106] <Effects> This embodiment has the same effects as the third embodiment, for the same reasons as those for the effects of the third embodiment.

[0107] This embodiment also has the advantage of increasing the possibility of obtaining the braking range and video when a traffic accident occurs. This is because, when an abnormal sound is detected, the output unit 150 outputs the video and braking range for the period including the time when the abnormal sound occurred. When an abnormal sound is detected, there is a possibility that a traffic accident has occurred. There is a possibility that the video for the period including the time when the abnormal sound occurred will include video of the time when the traffic accident occurred.

[0108] <Other embodiments> The estimation device 10, the estimation device 100, the estimation device 101, and the estimation device 102 according to the above-described embodiments can be realized by a computer including a memory into which a program read from a storage medium is loaded and a processor that executes the program. The estimation device 10, the estimation device 100, the estimation device 101, and the estimation device 102 can also be realized by dedicated hardware. The estimation device 10, the estimation device 100, the estimation device 101, and the estimation device 102 can also be realized by a combination of the above-described computer and dedicated hardware.

[0109] FIG. 11 is a diagram illustrating an example of a hardware configuration of a computer 1000 capable of realizing an estimation device according to an embodiment of the present disclosure. In the example illustrated in FIG. 11, the computer 1000 includes a processor 1001, a memory 1002, a storage device 1003, and an I / O (Input / Output) interface 1004. The computer 1000 can access a storage medium 1005. The memory 1002 and the storage device 1003 are, for example, storage devices such as RAM (Random Access Memory) and a hard disk. The storage medium 1005 is, for example, a storage device such as RAM or a hard disk, a ROM (Read Only Memory), or a portable storage medium. The storage device 1003 may be the storage medium 1005. The processor 1001 can read and write data and programs from and to the memory 1002 and the storage device 1003. The processor 1001 can access other devices via the I / O interface 1004. The processor 1001 can access the storage medium 1005. The storage medium 1005 stores a program that causes the computer 1000 to operate as an estimation device according to an embodiment of the present disclosure.

[0110] The processor 1001 loads a program stored in the storage medium 1005, which causes the computer 1000 to operate as an estimation device according to an embodiment of the present disclosure, into the memory 1002. The processor 1001 then executes the program loaded into the memory 1002, causing the computer 1000 to operate as the estimation device according to an embodiment of the present disclosure.

[0111] The load data acquisition unit 110, the identification unit 120, the driving abnormality detection unit 130, the range estimation unit 140, the output unit 150, the video acquisition unit 160, the sound data acquisition unit 170, and the abnormal sound detection unit 180 can be realized, for example, by a processor 1001 that executes a program loaded into a memory 1002. Some or all of the load data acquisition unit 110, the identification unit 120, the driving abnormality detection unit 130, the range estimation unit 140, the output unit 150, the video acquisition unit 160, the sound data acquisition unit 170, and the abnormal sound detection unit 180 can also be realized by a dedicated circuit that realizes the function of each unit.

[0112] Furthermore, some or all of the above-described embodiments can be described as, but are not limited to, the following supplementary notes.

[0113] (Appendix 1) a load data acquisition means for acquiring measurement data of the change in the magnitude of the load measured by a plurality of load sensors embedded in the laid area of ​​the road surface; an identification means for identifying a vehicle load transition, which is a transition of the position and magnitude of the load applied by the tire of the same vehicle, from the measurement data; a range estimation means for estimating a braking range in which the vehicle has moved while the brakes are applied, based on the identified transition of the vehicle load; an output means for outputting the estimated braking range; An estimation device comprising:

[0114] (Appendix 2) The identifying means identifies a tire load transition, which is a transition of a combination of the magnitude and position of the load for each tire, from the measurement data, and identifies a combination of the tire load transitions by tires of the same vehicle from the tire load transitions as the vehicle load transition. 10. The estimation apparatus of claim 1.

[0115] (Appendix 3) a driving abnormality detection means for detecting an abnormality from transition data that is at least one of the tire load transition and the vehicle load transition; Equipped with the range estimation means estimates the braking range when the abnormality is detected, The output means further outputs the time when the detected abnormality occurred. 10. The estimation device of claim 2.

[0116] (Appendix 4) The abnormal driving detection means detects, from the vehicle load transition, a movement of the vehicle that satisfies a predetermined abnormal movement criterion as the abnormality. 10. The estimation device according to claim 3.

[0117] (Appendix 5) The abnormal driving detection means detects, as the abnormality, the vehicle moving to a position that satisfies a predetermined abnormal position criterion based on the vehicle load transition. 5. The estimation device according to claim 3 or 4.

[0118] (Appendix 6) An image acquisition means for acquiring an image from an imaging device that captures an image of the installation area. Equipped with When the abnormality is detected, the output means further outputs the occurrence time of the detected abnormality and the video captured during a first time range including the occurrence time. 6. The estimation device according to any one of appendixes 3 to 5.

[0119] (Appendix 7) a sound data acquisition means for acquiring sound data from a microphone that measures sound in the installation area; an abnormal sound detection means for detecting an abnormal sound that satisfies an abnormal sound criterion from the sound data; Equipped with The output means further outputs the abnormal sound occurrence time when the detected abnormal sound occurred, the sound data measured during a second time range including the abnormal sound occurrence time, and the video captured during the second time range. 10. The estimation device according to claim 6.

[0120] (Appendix 8) Obtaining measurement data of the change in the magnitude of the load measured by a plurality of load sensors embedded in the laid area of ​​the road surface; From the measurement data, a vehicle load transition is identified, which is a transition of the position and magnitude of the load applied by the tire of the same vehicle; estimating a braking range in which the vehicle has moved while the brakes are applied from the identified transition of the vehicle load; outputting the estimated braking range; Estimation method.

[0121] (Appendix 9) A tire load transition, which is a transition of a combination of the magnitude and position of the load for each tire, is identified from the measurement data, and a combination of the tire load transitions for tires of the same vehicle is identified as the vehicle load transition. Estimation method described in Appendix 8.

[0122] (Appendix 10) detecting an abnormality from transition data that is data on at least one of the tire load transition and the vehicle load transition; When the abnormality is detected, the braking range is estimated; The time when the detected abnormality occurred is further output. Estimation method described in Appendix 9.

[0123] (Appendix 11) From the vehicle load transition, a movement of the vehicle that satisfies a predetermined abnormal movement criterion is detected as the abnormality. Estimation method described in Appendix 10.

[0124] (Appendix 12) The abnormality is detected when the vehicle moves to a position that satisfies a predetermined abnormal position criterion based on the vehicle load transition. The estimation method described in Appendix 10 or 11.

[0125] (Appendix 13) acquiring an image of the installation area from an imaging device that captures the image; When the abnormality is detected, the time of occurrence of the detected abnormality and the video captured during a first time range including the time of occurrence are further output. 13. The estimation method according to any one of appendices 10 to 12.

[0126] (Appendix 14) Acquire sound data from a microphone that measures sound in the installation area; Detecting an abnormal sound that satisfies an abnormal sound criterion from the sound data; The abnormal sound occurrence time when the detected abnormal sound occurred, the sound data measured during a second time range including the abnormal sound occurrence time, and the video captured during the second time range are further output. Estimation method described in Appendix 13.

[0127] (Appendix 15) a load data acquisition process for acquiring measurement data of the transition of the magnitude of the load measured by a plurality of load sensors embedded in the laid area of ​​the road surface; A process of identifying a vehicle load transition, which is a transition of the position and magnitude of the load applied by the tires of the same vehicle, from the measurement data; a range estimation process for estimating a braking range in which the vehicle has moved while the brakes are applied, based on the identified transition of vehicle load; an output process for outputting the estimated braking range; A storage medium that stores a program that causes a computer to execute the above.

[0128] (Appendix 16) The identification process identifies a tire load transition, which is a transition of a combination of the magnitude and position of the load for each tire, from the measurement data, and identifies a combination of the tire load transitions by tires of the same vehicle as the vehicle load transition. 16. The storage medium of claim 15.

[0129] (Appendix 17) A driving abnormality detection process for detecting an abnormality from transition data that is data on at least one of the tire load transition and the vehicle load transition. Then, the computer executes the range estimation process estimates the braking range when the abnormality is detected; The output process further outputs the time when the detected abnormality occurred. 17. The storage medium of claim 16.

[0130] (Appendix 18) The abnormal driving detection process detects, from the vehicle load transition, a movement of the vehicle that satisfies a predetermined abnormal movement criterion as the abnormality. 18. The storage medium of claim 17.

[0131] (Appendix 19) The abnormal driving detection process detects, as the abnormality, the vehicle moving to a position that satisfies a predetermined abnormal position criterion based on the vehicle load transition. 19. A storage medium according to claim 17 or 18.

[0132] (Appendix 20) An image acquisition process for acquiring an image from an imaging device that captures an image of the installation area. Then, the computer executes When the abnormality is detected, the output process further outputs the occurrence time of the detected abnormality and the video captured during a first time range including the occurrence time. 20. A storage medium according to any one of appendices 17 to 19.

[0133] (Appendix 21) a sound data acquisition process for acquiring sound data from a microphone that measures sound in the installation area; an abnormal sound detection process for detecting an abnormal sound that satisfies an abnormal sound criterion from the sound data; Then, the computer executes The output process further outputs the abnormal sound occurrence time when the detected abnormal sound occurred, the sound data measured during a second time range including the abnormal sound occurrence time, and the video captured during the second time range. 21. The storage medium of claim 20.

[0134] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above 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. [Explanation of symbols]

[0135] 1. Estimation System 2. Estimation System 3. Estimation System 10 Estimation device 100 Estimator 101 Estimation device 102 Estimation device 110 Load data acquisition unit 120 Specific section 130 Abnormal driving detection unit 140 Range Estimation Unit 150 Output section 160 Video acquisition unit 170 Sound data acquisition unit 180 Abnormal sound detection unit 200 Load Sensor 300 Output device 400 Imaging device 500 microphones 1000 computers 1001 processor 1002 memory 1003 Storage device 1004 I / O interface 1005 Storage medium

Claims

1. a load data acquisition means for acquiring measurement data of the change in the magnitude of the load measured by a plurality of load sensors embedded in the laid area of ​​the road surface; an identification means for identifying a vehicle load transition, which is a transition of the position and magnitude of the load applied by the tire of the same vehicle, from the measurement data; a range estimation means for estimating a braking range in which the vehicle has moved while the brakes are applied, based on the identified transition of the vehicle load; an output means for outputting the estimated braking range; An estimation device comprising:

2. The identifying means identifies a tire load transition, which is a transition of a combination of the magnitude and position of the load for each tire, from the measurement data, and identifies a combination of the tire load transitions by tires of the same vehicle from the tire load transitions as the vehicle load transition. The estimation device according to claim 1 .

3. a driving abnormality detection means for detecting an abnormality from transition data that is at least one of the tire load transition and the vehicle load transition; Equipped with the range estimation means estimates the braking range when the abnormality is detected, The output means further outputs the time when the detected abnormality occurred. The estimation device according to claim 2 .

4. The abnormal driving detection means detects, from the vehicle load transition, a movement of the vehicle that satisfies a predetermined abnormal movement criterion as the abnormality. The estimation device according to claim 3 .

5. The abnormal driving detection means detects, as the abnormality, the vehicle moving to a position that satisfies a predetermined abnormal position criterion based on the vehicle load transition. The estimation device according to claim 3 or 4.

6. An image acquisition means for acquiring an image from an imaging device that captures an image of the installation area. Equipped with When the abnormality is detected, the output means further outputs the occurrence time of the detected abnormality and the video captured during a first time range including the occurrence time. The estimation device according to any one of claims 3 to 5.

7. a sound data acquisition means for acquiring sound data from a microphone that measures sound in the installation area; an abnormal sound detection means for detecting an abnormal sound that satisfies an abnormal sound criterion from the sound data; Equipped with The output means further outputs the abnormal sound occurrence time when the detected abnormal sound occurred, the sound data measured during a second time range including the abnormal sound occurrence time, and the video captured during the second time range. The estimation device according to claim 6 .

8. Obtaining measurement data of the change in the magnitude of the load measured by a plurality of load sensors embedded in the laid area of ​​the road surface; From the measurement data, a vehicle load transition is identified, which is a transition of the position and magnitude of the load applied by the tire of the same vehicle; estimating a braking range in which the vehicle has moved while the brakes are applied from the identified transition of the vehicle load; outputting the estimated braking range; Estimation method.

9. A tire load transition, which is a transition of a combination of the magnitude and position of the load for each tire, is identified from the measurement data, and a combination of the tire load transitions for tires of the same vehicle is identified as the vehicle load transition. The estimation method according to claim 8.

10. a load data acquisition process for acquiring measurement data of the transition of the magnitude of the load measured by a plurality of load sensors embedded in the laid area of ​​the road surface; A process of identifying a vehicle load transition, which is a transition of the position and magnitude of the load applied by the tires of the same vehicle, from the measurement data; a range estimation process for estimating a braking range in which the vehicle has moved while the brakes are applied, based on the identified transition of vehicle load; an output process for outputting the estimated braking range; A program that causes a computer to execute the following.

Images