JP-2026076026-A - Road surface damage prediction device, road surface repair support device, road surface damage prediction system, road surface repair support system, road surface damage prediction method, and road surface damage prediction program

Abstract

[Problem] Predict when road surface damage will occur based on the results of aggregating indicator values representing road surface damage over a certain period of time. [Solution] The server 20 comprising the road surface damage prediction device includes a calculation unit 24 that calculates an index value representing road surface damage at a target location, linked to location information, at regular intervals; an aggregation unit 25 that aggregates the calculated values at regular intervals in a time series; and a prediction unit 26 that predicts when the road surface will be damaged based on the aggregation results. [Selection Diagram] Figure 3

Inventors

• 田中 準二
• 紺野 克也
• 荒木 龍治

Assignees

• 矢崎総業株式会社

Dates

Publication Date

20260511

Application Date

20241023

Claims (12)

1. A calculation unit that calculates an index value representing road surface damage at a target location, linked to location information, at regular intervals, A summation unit that aggregates the calculated values for each of the aforementioned fixed periods in a time series, The system includes a prediction unit that predicts the timing of damage to the road surface based on the aggregated results, Road surface damage prediction device.
2. The system includes an acquisition unit that acquires data including vertical acceleration detected by an on-board device installed in a vehicle that has passed the aforementioned target point. The calculation unit calculates the variance of acceleration included in the data as the index value, The prediction unit estimates the period until the variance value exceeds a predetermined threshold and predicts the timing. The road surface damage prediction device according to claim 1.
3. The aggregation unit aggregates the calculated values for each set period and the number of vehicles that passed through the target location in a time series. The prediction unit takes the number of units into consideration and predicts the timing. The road surface damage prediction device according to claim 2.
4. The prediction unit predicts the timing according to the rate of change of the number of units. The road surface damage prediction device according to claim 3.
5. The prediction unit predicts the timing by taking into account repair information, which includes at least one of the past repair history of the road surface and the repair method. The road surface damage prediction device according to claim 1.
6. A road surface damage prediction device according to any one of claims 1 to 5, The system includes a presentation unit that presents the time predicted by the prediction unit as the time when repairs to the road surface are required. Road surface repair support device.
7. The display unit presents the repair timing for each target section, categorized into levels according to the time remaining until the repair timing. The road surface repair support device according to claim 6.
8. The aforementioned display unit displays the repair period on the map. The road surface repair support device according to claim 6.
9. A road surface damage prediction device according to any one of claims 1 to 5, An in-vehicle device that collects data used to calculate the aforementioned index value and transmits it to the road surface damage prediction device in association with the location information, A road surface damage prediction system equipped with the following features.
10. A road surface repair support device according to claim 6, An in-vehicle device that collects data used to calculate the aforementioned index value and transmits it to the road surface damage prediction device in association with the location information, A road surface repair support system equipped with [features/equipment].
11. The steps include: calculating an index value representing road surface damage at a target location, linked to location information, at regular intervals; The steps include: aggregating the calculated values for each period in a time series; The method includes the step of predicting the timing of damage to the road surface based on the aggregated results. Method for predicting road surface damage.
12. The steps include: calculating an index value representing road surface damage at a target location, linked to location information, at regular intervals; The steps include: aggregating the calculated values for each period in a time series; The steps include predicting the timing of damage to the road surface based on the aggregated results, A road surface damage prediction program that is executed by a computer.

Description

This invention relates to a road surface damage prediction device, a road surface repair support device, a road surface damage prediction system, a road surface repair support system, a road surface damage prediction method, and a road surface damage prediction program. A system is known that determines whether the road surface being driven on is good or bad, and that checks for road damage. Patent Document 1 discloses a road surface condition determination system capable of determining the condition of the road surface. An acceleration sensor built into an in-vehicle unit is mounted on the vehicle and detects the vehicle's vertical acceleration. The in-vehicle unit transmits the acceleration to a server. Based on the received acceleration, the server obtains the variance of the absolute value of the acceleration detected while the vehicle travels a predetermined distance within a predetermined speed range, and determines the road surface condition the vehicle traveled on based on the obtained variance. Japanese Patent Publication No. 2022-139988 Figure 1 is a system configuration diagram showing an example of the configuration of a road surface damage prediction system and a road surface repair support system according to one embodiment of the present invention.Figure 2 is a block diagram showing an example of the configuration of an in-vehicle device.Figure 3 is a block diagram showing an example of a server configuration.Figure 4 is a schematic diagram showing an example of acceleration dispersion data and a map indicating the locations where this data was measured.Figure 5 is a schematic diagram of the road surface to illustrate an example of the operation of the prediction unit.Figure 6 is a flowchart illustrating the general procedure of the road surface damage prediction method implemented by the server according to the embodiment.Figure 7 is a flowchart illustrating the general procedure of the road surface damage prediction method that the server performs again after executing the road surface damage prediction in Figure 6.Figure 8 shows the screen displayed on the administrator's PC after the results of the first road surface damage prediction.Figure 9 shows the screen displayed on the administrator's PC after performing a second road damage prediction following the first road damage prediction in Figure 8.Figure 10 shows the screen displayed on the administrator's PC after the road damage prediction has been performed again, taking into account the increase or decrease in the number of vehicles passing through the road surface, following the first road damage prediction in Figure 8, and adjusting the coefficients. Specific embodiments of the present invention will be described below with reference to the figures. As shown in Figure 1, the road surface damage prediction system 1 according to this embodiment is a system that predicts when the road surface will be damaged. The road surface damage prediction system 1 comprises an on-board unit 10 mounted on a vehicle V and a server 20 capable of communicating with the on-board unit 10. The on-board unit 10 is installed in a vehicle V, such as a truck, and collects operational data (so-called digital tachograph data) including the vehicle V's driving status. The collected operational data is used, for example, to create a daily report based on a day's worth of operational information. Specifically, the on-board unit 10 records operational data such as the vehicle V's speed, driving time, driving distance, and the start and end times of the operational work. The on-board unit 10 can wirelessly connect to a network N, such as the Internet, for example, via wireless communication. Server 20 constitutes the core road surface damage prediction device of the road surface damage prediction system 1. Server 20 is a computer device capable of communicating with other devices via the network N. Server 20 is operated, for example, by a business operator (e.g., a transportation company) that operates the vehicle V. Figure 1 also shows the administrator PC (personal computer) 30. The administrator PC 30 is a communication terminal used by vehicle managers, etc., of the operator of the vehicle V, and can communicate with other devices via the network N. The communication terminal is not limited to a fixed-installation type like a business PC; it may also be a portable device such as a tablet or smartphone. Next, the in-vehicle unit 10 will be described. The in-vehicle unit 10 comprises a control unit 11, a position information acquisition unit 12, an acceleration sensor 13, and a communication unit 14. The control unit 11 is the main processing unit (computer) responsible for controlling the in-vehicle unit 10. The control unit 11 reads various programs stored in memory (not shown) and causes each part of the in-vehicle unit 10 to execute predetermined processes. The location information acquisition unit 12 acquires the location information of the vehicle V using,