Road closure estimation device, road closure estimation method, road closure estimation program

Abstract

To provide a road closure estimation device that is capable of estimating an occurrence and a cancellation of a road closure on a road.SOLUTION: A road closure estimation device comprises: an acquisition unit that acquires an average number of vehicles indicating the number of vehicles that have traveled a road of interest in each time slot; a calculation unit that calculates a probability that there will be no passing vehicle within a predetermined period on the basis of the average number of vehicles; an estimation unit that estimates that a road closure is occurring on the road of interest when the probability calculated by the calculation unit is equal to a predetermined first threshold value or less, and estimates that the road closure has been cancelled on the basis of a probability that is calculated by the calculation unit at or after the time when it is estimated that the road is occurring; and an output unit that outputs information indicating that it is estimated by the estimation unit that the road closure is occurring in association with information indicating the road of interest, or that outputs information indicating that it is estimated by the estimation unit that the road closure has been cancelled in association with information indicating the road of interest.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a road closure estimation device, a road closure estimation method, and a road closure estimation program. [Background Art]

[0002] On roads, road closures may occur due to reasons such as road construction or traffic accidents. If such road closures can be recognized in advance, the driver can be notified via a navigation device, and route guidance can be provided to avoid the closed road. Patent Document 1 discloses a technology that, based on probe information, determines whether travel between different non-closure sections is possible for each non-closure section, and determines that a road is closed when there is almost no traffic on the road despite a predetermined traffic volume under normal conditions. Further, Patent Document 2 discloses a technology that, based on probe information, calculates an average value of the number of passing vehicles for each link and each time period as a statistical value, calculates the number of passing vehicles for each link in the latest current time period, and estimates a traffic event by referring to both the average value and the latest value. [Prior Art Documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Unexamined Patent Publication No. 2020-112481 [Patent Document 2] Japanese Unexamined Patent Publication No. 2016-186762 [Summary of the Invention] [Problem to be Solved by the Invention]

[0004] By the way, in the case of the above Patent Document 1 and Patent Document 2, real-time probe information is required, so there is a problem that road closure cannot be estimated in an environment where real-time probe information cannot be obtained.

[0005] Therefore, the present invention has been made in view of the above problems, and aims to provide a road closure estimation device, a road closure estimation method, and a road closure estimation program that can estimate road closures even without real-time probe information. [Means for solving the problem]

[0006] To solve the above problems, a road closure estimation device according to one aspect of the present invention includes: an acquisition unit that acquires an average number of vehicles indicating the average number of vehicles that traveled on the target road for each time period; a calculation unit that calculates the probability that no vehicles passed through the road during a predetermined period based on the average number of vehicles; an estimation unit that estimates that a road closure has occurred on the target road if the probability calculated by the calculation unit is less than or equal to a predetermined first threshold, and estimates that the road closure has been lifted based on the probability calculated by the calculation unit after the time at which the road closure was estimated to have occurred; and an output unit that outputs information indicating that the estimation unit has estimated that a road closure has occurred, associated with information indicating the target road, or outputs information indicating that the estimation unit has estimated that the road closure has been lifted, associated with information indicating the target road.

[0007] To solve the above problems, a road closure estimation method according to one aspect of the present invention is performed by a computer which performs an acquisition step of acquiring an average number of vehicles, which indicates the average number of vehicles that traveled on the target road for each time period; a calculation step of calculating the probability that no vehicles passed through the road during a predetermined period based on the average number of vehicles; an estimation step of estimating that a road closure has occurred on the target road if the probability calculated in the calculation step is less than or equal to a predetermined first threshold, and estimating that the road closure has been lifted after the time at which the road closure was estimated to have occurred, based on the probability calculated in the calculation step; and an output step of outputting information indicating that the estimation step estimated that a road closure has occurred, associated with information indicating the target road, or outputting information indicating that the estimation step estimated that the road closure has been lifted, associated with information indicating the target road.

[0008] To solve the above problems, a road closure estimation program according to one aspect of the present invention provides a computer with an acquisition function to acquire the average number of vehicles, which indicates the average number of vehicles that traveled on the target road for each time period; a calculation function to calculate the probability that no vehicles passed through the road during a predetermined period based on the average number of vehicles; an estimation function that estimates that a road closure has occurred on the target road if the probability calculated by the calculation function is below a predetermined first threshold, and estimates that the road closure has been lifted based on the probability calculated by the calculation function after the time when the road closure was estimated to have occurred; and an output function that outputs information indicating that the estimation function has estimated that a road closure has occurred, associated with information indicating the target road, or outputs information indicating that the estimation function has estimated that the road closure has been lifted, associated with information indicating the target road.

[0009] Furthermore, in the above-mentioned road closure estimation device, if the estimation unit can estimate that a road closure has occurred on the target road for a predetermined time or longer from the time it is estimated that a road closure has occurred, and the average number of vehicles on the target road is less than or equal to a predetermined number, the estimation unit may estimate whether the road closure has been lifted using a different method than when the average number of vehicles on the target road exceeds a predetermined number.

[0010] Furthermore, in the above-mentioned road closure estimation device, the estimation unit may estimate whether the road closure has been lifted using a different method than when the average number of vehicles on the target road exceeds a predetermined number, if the average number of vehicles on the target road is below a predetermined number.

[0011] Furthermore, in the above-mentioned road closure estimation device, the estimation unit may estimate that the road closure has been lifted if the average number of vehicles on the target road exceeds a predetermined number and the probability calculated by the calculation unit exceeds a predetermined first threshold, and if the average number of vehicles on the target road is less than or equal to the predetermined number and the probability based on the cumulative sum of the average number of vehicles for each time period corresponding to the elapsed time since the time the calculation unit estimated that the road closure occurred exceeds a predetermined second threshold, the estimation unit may also estimate that the road closure has been lifted. [Effects of the Invention]

[0012] A road closure estimation device according to one aspect of the present invention can estimate whether a road closure has occurred and whether it has been lifted on a target road, using a probability based on the average number of vehicles traveling on the target road for each time period in the past. [Brief explanation of the drawing]

[0013] [Figure 1] This is a block diagram showing an example configuration of a road closure estimation device. [Figure 2] This is a conceptual data diagram showing an example of the data structure for vehicle traffic information. [Figure 3] This is a flowchart illustrating an example of the operation of a road closure estimation device, showing the process for estimating the occurrence of a road closure. [Figure 4] This is a flowchart illustrating an example of the operation of a road closure estimation device, specifically the process of estimating when a road closure will be lifted. [Figure 5] This is a block diagram showing another example configuration of the road closure estimation device. [Modes for carrying out the invention]

[0014] A road closure estimation device according to one aspect of the present invention will be described in detail below with reference to the drawings.

[0015] <Embodiment> <Configuration of the road closure estimation device> A road closure estimation device according to one aspect of the present invention (see 100 in FIG. 1) comprises: an acquisition unit (see 105 in FIG. 1) that acquires an average number of vehicles indicating the average number of vehicles that have traveled on a target road for each time slot; a calculation unit (see 105 in FIG. 1) that calculates, based on the average number of vehicles, the probability that no vehicle passes the target road within a predetermined period; an estimation unit (see 105 in FIG. 1) that estimates that road closure has occurred on the target road when the probability calculated by the calculation unit is equal to or less than a predetermined first threshold, and estimates that the road closure has been lifted based on the probability calculated by the calculation unit after the time at which the road closure was estimated to have occurred; and an output unit (see 105 in FIG. 1) that outputs information indicating that the estimation unit has estimated that road closure has occurred in association with information indicating the target road, or outputs information indicating that the estimation unit has estimated that road closure has been lifted in association with information indicating the target road.

[0016] FIG. 1 is a block diagram showing a configuration example of the road closure estimation device 100. As shown in FIG. 1, the road closure estimation device 100 includes a communication unit 101, an input unit 102, an output unit 103, a storage unit 104, and a CPU 105.

[0017] The road closure estimation device 100 is a computer system implemented by a server device, a PC, or the like, but is not limited thereto, and may be implemented by a mobile terminal such as a smartphone or a tablet terminal. As an example, the road closure estimation device 100 may be implemented as a navigation device used for route guidance (navigation) that estimates the occurrence and lifting of road closures and notifies drivers of vehicles or the like of the estimation result.

[0018] The communication unit 101 has a function of transmitting and receiving information to and from other devices via wired or wireless communication. For example, the communication unit 101 may receive information indicating the number of passing vehicles on each road or information of the average number of vehicles, which is the average value of the number of passing vehicles, from an external device, and transmit the information to the CPU 105.

[0019] The input unit 102 has a function of receiving an input from a user of the road closure estimation device 100 and transmitting the input to the CPU 105. The input unit 102 can be implemented by, for example, a hardware key provided in the road closure estimation device 100, or a soft key such as a touch panel or a touch key. Note that the input to the input unit 102 may be a voice input, and in this case, the input unit 102 is implemented by a microphone. For example, the input unit 102 may receive an input of information on the average number of vehicles on each road and transmit the input to the CPU 105.

[0020] The output unit 103 has a function of outputting instructed data in accordance with an instruction from the CPU 105. For example, when it is estimated that a road closure has occurred, the output unit 103 may output information indicating that a road closure has occurred and information on a road estimated to have a road closure. Further, the output unit 103 may output, for example, information indicating that a road closure has been lifted and information on a road for which the road closure has been lifted. The output of information by the output unit 103 may be performed by characters or images on a monitor (display device) attached to or connected to the road closure estimation device 100, or may be performed by outputting voice from a speaker attached to or connected to the road closure estimation device 100, or may be performed by outputting information to an external device through communication via the communication unit 110.

[0021] The storage unit 104 is a recording medium that stores various programs and various data required for the operation of the road closure estimation device 100. The storage unit 104 is implemented by, for example, an HDD (Hard Disc Drive), an SSD (Solid State Drive), a flash memory, or the like.

[0022] The memory unit 104 stores map information 141. Map information 141 is map information that includes at least road information. The memory unit 140 also stores vehicle traffic information 142. Vehicle traffic information 142 is information that shows the number of vehicles traveling (passing) on ​​each road during each time period on each day. The number of vehicles traveling in the vehicle traffic information 142 may be the sum of probe information of vehicles that traveled on each road, information counted from images captured by surveillance cameras installed on roads, etc., or information compiled by ETC, etc. Vehicle traffic information 142 may also be information that shows the average number of vehicles traveling on each road during each time period. Furthermore, the time period referred to here may be, for example, an hourly time period, a 30-minute time period, or a 2-hour time period.

[0023] The CPU 105 is a processor that uses various programs and data stored in the memory unit 104 to execute the processes that the road closure estimation device 100 should perform.

[0024] The CPU 105 executes a program stored in the memory unit 104 to estimate when road closures will occur on roads, estimate when road closures will be lifted on roads where closures have been estimated, and outputs this information.

[0025] The CPU 105 functions as an acquisition unit, calculation unit, estimation unit, and output unit.

[0026] The acquisition unit acquires the average number of vehicles that traveled on the target road for each time period. The acquisition unit may refer to the vehicle traffic information 142 stored in the storage unit 140 and calculate the average number of vehicles for each time period on the target road. For example, in the case of the vehicle traffic information 142 shown in Figure 2, the average number of vehicles in the 6 o'clock hour between October 3, 2022 and October 7, 2022 is (18+11+14+10+16) / 5 = 69 / 5 = 13.8. The number of days or dates for which the acquisition unit calculates the average number of vehicles can be arbitrary; for example, it may be the average number of vehicles for one month going back from the current date and time. Also, for example, the average number of vehicles acquired by the acquisition unit may be calculated for each day of the week, or it may be calculated separately for weekdays and holidays. If the vehicle traffic information 142 shows the average number of vehicles for each road, the acquisition unit may acquire that value. The acquisition unit transmits the acquired average number of vehicles to the calculation unit.

[0027] The calculation unit calculates the probability that no vehicles pass through during a predetermined period based on the average number of vehicles. The calculation unit calculates the probability that no vehicles pass through during a predetermined period by referring to the average number of vehicles acquired by the acquisition unit. Here, the predetermined period may be the same as the time unit that defines the number of vehicles passing through in the vehicle traffic information 142, or it may be a different time length. Here, the predetermined period is set to 1 hour for ease of calculation, but if a different time length is used, the calculated average number of vehicles is converted to the length of the predetermined period. Based on the average number of vehicles transmitted from the acquisition unit, the calculation unit calculates the probability P that no vehicles pass through during a predetermined period using the following formula (1). P=1-e -λx …(1) Here, e is the base of the natural logarithm, λ is the average number of vehicles over a predetermined period, and x is the length of the predetermined period. The calculation unit transmits the calculated probability P to the estimation unit.

[0028] Furthermore, the calculation unit may calculate the probability P using λ as the cumulative sum of the average number of vehicles corresponding to the elapsed time since the road closure occurred, if a road closure has occurred on the target road. The calculation unit may also decide whether or not to use the cumulative sum of the average number of vehicles depending on whether or not the average number of vehicles on the target road for determining whether to lift the road closure is less than a predetermined number.

[0029] The estimation unit estimates the occurrence and lifting of road closures on the target road. The estimation unit estimates the occurrence and lifting of road closures based on the probability P transmitted from the calculation unit. Specifically, the estimation unit estimates that a road closure is occurring on the target road if the probability P is less than or equal to a predetermined first threshold. Since the probability P calculated by the above formula (1) is a value between 0 and 1, the first threshold is also a value between 0 and 1, and is a suitable value for estimating that a road closure has occurred. The first threshold may be determined by performing simulations in the case where a road closure actually occurs and in the case where it does not occur, based on the road closure estimation device 100's estimation that a road closure has occurred. The first threshold may be 0.01%, for example, but is not limited to this value.

[0030] Furthermore, if it is estimated that a road closure has occurred on the target road, the estimation unit estimates whether the road closure has been lifted based on the probability P calculated by the calculation unit after the time the road closure was estimated to have occurred.

[0031] The estimation unit may change the method for estimating the lifting of a road closure depending on whether the average number of vehicles on the target road exceeds a predetermined number. That is, when the average number of vehicles on the target road is less than or equal to a predetermined number, the estimation unit estimates whether the road closure has been lifted using a different method than when the average number of vehicles on the target road exceeds a predetermined number. Here, a different method may mean that the calculation formula for the elements used to estimate the lifting of the road closure is different, or that the threshold used as the criterion for judgment is different. Specifically, for example, the threshold used as the criterion for estimating the lifting of the road closure may be changed, or the method for calculating the probability P used to estimate the lifting of the road closure may be changed. In this case, the estimation unit may only estimate whether the road closure has been lifted using a different method than when the average number of vehicles on the target road exceeds a predetermined number, when a predetermined time has elapsed since the time when the road closure was estimated to have occurred on the target road and the average number of vehicles on the target road is less than or equal to a predetermined number. Furthermore, the predetermined number of vehicles referred to here should be any number suitable as a criterion for switching methods when estimating the lifting of the road closure. For example, an appropriate value may be determined and set based on the average number of vehicles through simulation or other means. The predetermined number of vehicles may also be determined for each target road, or according to the type of target road (public road, private road, type based on road width, etc.). Furthermore, the predetermined number of vehicles may vary depending on the time of day or season, even for the same target road. Moreover, the predetermined number of vehicles may be determined according to the elapsed time since the estimated time of the road closure. For example, the predetermined number of vehicles as a threshold may be adjusted so that it becomes relatively larger as the elapsed time since the estimated time of the road closure increases.

[0032] In this embodiment, the estimation unit estimates that the road closure has been lifted if the average number of vehicles on the target road exceeds a predetermined number, and the probability calculated by the calculation unit exceeds a first threshold. On the other hand, if the average number of vehicles on the target road is less than or equal to the predetermined number, the estimation unit estimates that the road closure has been lifted if the probability based on the cumulative sum of the average number of vehicles for each time period corresponding to the elapsed time since the time when the calculation unit estimated the road closure occurred exceeds a second threshold. Here, the second threshold may be the same value as the first threshold, or it may be a different value.

[0033] The estimation unit transmits information to the output unit when it estimates that a road closure has occurred on the target road, or when it estimates that the road closure has been lifted.

[0034] The output unit outputs information indicating that a road closure has occurred, as transmitted by the estimation unit, in association with information indicating the target road. The output unit also outputs information indicating that the road closure has been lifted, as transmitted by the estimation unit, in association with information indicating the target road. The output of information by the output unit may be output from the output unit 103 of the road closure estimation device 100, or it may be output from the communication unit 101 to an external device. That is, the output unit may output image information from the output unit 103 (for example, an image from the map information 141 that includes the vicinity of the target road, showing that a road closure has occurred or been lifted on the target road), or it may output text information from the output unit 103, including the name of the target road and a sentence indicating that a road closure has occurred or been lifted on that road, or it may output similar information by voice. The output unit may also transmit to an external device via the communication unit 101 the information that a road closure has occurred and the road on which it occurred, or the information that a road closure has been lifted and the road on which it was lifted.

[0035] The above is an example of the configuration of the road closure estimation device 100.

[0036] <Data> Here, we will explain the vehicle traffic information 142. As mentioned above, the vehicle traffic information 142 is information that counts the number of vehicles traveling on each road during each time period on each day. The roads referred to here may be links that are defined as roads in the map information 141.

[0037] As shown in Figure 2, the vehicle traffic information 142 associates a date and time 201 with a time period 202, and indicates the number of vehicles that passed through each road during each time period 202 for each date and time 201. Figure 2 shows an example of information for one road, but the storage unit 104 may store this information for each road.

[0038] Date and time 201 indicates the date on which the number of vehicles traveling on that road was counted.

[0039] Time zone 202 refers to a time period divided into predetermined time units, and Figure 2 shows an example where it is divided into 1-hour units. The numbers 0 to 23 in time zone 202 represent 0:00, 1:00, ..., 22:00, and 23:00, respectively, and indicate the start time of each time zone. Therefore, for example, the time zone indicated by "2" in time zone 202 means the period from 2:00 AM to 3:00 AM.

[0040] According to the vehicle traffic data 142 shown in the example in Figure 2, for example, the number of vehicles passing through in the 5 o'clock hour on "October 3, 2022" was "8". Also, for example, the number of vehicles passing through in the 18 o'clock hour on "October 4, 2022" was "21". With this information, it is possible to calculate the average number of vehicles in each time period on the road to which the vehicle traffic data 142 corresponds.

[0041] <Operation of the road closure estimation device> An example of the operation of the road closure estimation device 100 will be explained using Figure 3. Figure 3 is a flowchart showing an example of the operation of the road closure estimation device 100 when estimating the occurrence of a road closure on a road to be targeted for road closure estimation, based on the probability that no vehicles will pass through the road, which is calculated from the average number of vehicles traveling on the target road.

[0042] As shown in Figure 3, the acquisition unit of the CPU 105 of the road closure estimation device 100 acquires the number of vehicles passing through the target road for each time period from the vehicle traffic information 142 stored in the storage unit 104. Then, based on the acquired number of passing vehicles, it acquires (calculates) the average number of vehicles for each time period (step S301). The acquisition unit transmits the acquired average number of vehicles for each time period to the calculation unit.

[0043] The calculation unit of CPU 105 calculates the probability that no vehicles pass through during a predetermined period, based on the average number of vehicles transmitted from the acquisition unit. Specifically, if the predetermined period is 1 hour and the start time is 0:00, the calculation unit calculates the probability P that no vehicles pass through during each time period using the above formula (1), based on the average number of vehicles during each time period transmitted from the acquisition unit (step S302). The calculation unit transmits the calculated probability P to the estimation unit.

[0044] The estimation unit of CPU 105 determines whether the probability P transmitted for each time period is less than or equal to a first threshold (step S303). If the probability P is not less than or equal to the first threshold (NO in step S303), the estimation unit estimates that no road closures have occurred on the target road during all time periods (step S305) and terminates processing. If the probability P is less than or equal to the first threshold (YES in step S303), the estimation unit estimates that a road closure has occurred on the target road (step S304). The estimation unit transmits to the output unit that it has estimated a road closure has occurred and provides information about the target road.

[0045] The output unit of the CPU 105 outputs information indicating that a road closure has occurred, corresponding to information indicating the road in question (step S306), and then terminates the process.

[0046] Next, with reference to Figure 4, we will explain the estimation process by which the road closure estimation device 100 determines whether the road closure has been lifted. Figure 4 is a flowchart showing an example of the operation of the road closure lifting process by the road closure estimation device 100.

[0047] The calculation unit continuously calculates the probability that no vehicles will pass through the road where a road closure is estimated at predetermined intervals (step S401). The calculation unit transmits the calculated probability P to the estimation unit.

[0048] The estimation unit determines whether the probability P transmitted from the calculation unit exceeds a first threshold (step S402). If the calculated probability P exceeds the first threshold (YES in step S402), it is estimated that the road closure on the target road has been lifted. The output unit then outputs information indicating that the road closure on the target road has been lifted (step S407), and the process ends.

[0049] If the calculated probability does not exceed the first threshold (NO in step S402), the calculation unit determines whether a predetermined time has elapsed since the time when the road closure was estimated on the target road (step S403). If the predetermined time has not elapsed (NO in step S403), the process returns to step S401. Note that the process in step S403 may be omitted. That is, regardless of the time elapsed since the road closure, if the average number of vehicles is less than a predetermined number, the process in steps S405 and S406 may be used to determine whether the road closure has been lifted.

[0050] If a predetermined amount of time has elapsed since the road closure (YES in step S402), the calculation unit determines whether the average number of vehicles on the target road during the time period at the time of determination is less than a predetermined number (step S404). If the average number of vehicles is not less than a predetermined number (NO in step S404), the process returns to step S401.

[0051] If the average number of vehicles is less than a predetermined number (YES in step S404), the calculation unit calculates a cumulative sum of the average number of vehicles corresponding to the elapsed time since the estimated road closure. The cumulative sum here refers to the sum of the average number of vehicles in the 1 AM hour, the average number of vehicles in the 2 AM hour, and the average number of vehicles in the 3 AM hour, for example, if the road closure was estimated to have occurred at 1 AM and three hours have passed since then. By using the cumulative sum, the number of vehicles that have passed can be increased, and by estimating that vehicles will definitely pass, the road closure can be prevented from continuing indefinitely, and the lifting of the road closure can be estimated. The calculation unit then uses the calculated cumulative sum as λ and calculates the probability P that no vehicles will pass on the target road using the above formula (1) (step S405). The calculation unit then determines whether the probability P calculated based on the cumulative sum of the average number of vehicles corresponding to the elapsed time since the road closure exceeds the second threshold (step S406). If probability P does not exceed the second threshold (NO in step S406), the process returns to step S405. If probability P exceeds the second threshold (YES in step S406), it is presumed that the road closure on the target road has been lifted. The output unit then outputs information indicating that the road closure has been lifted, associated with information indicating the target road (step S407), and the process ends.

[0052] The above is an example of the operation of the road closure estimation device 100 in the process of issuing and lifting road closures.

[0053] <Summary> As described above, the road closure estimation device 100 can calculate the probability that no vehicles will pass on the road in question based on the average number of vehicles that have passed on the road in the past, and estimate whether or not a road closure is in effect based on that probability. Furthermore, on roads with a low average number of vehicles, a road closure may not be lifted for some time. In such cases, the road closure estimation device 100 can increase the number of vehicles using the cumulative sum of the average number of vehicles on the road in question, and estimate that the road closure has been lifted by using the probability based on that cumulative sum. As shown in the above embodiment, the road closure estimation device 100 can estimate the occurrence and lifting of road closures on a road without using real-time vehicle traffic information, although it utilizes the number of vehicles that have passed on the road in the past.

[0054] <Supplement> It goes without saying that the road closure estimation device according to the above embodiment is not limited to the above embodiment and may be implemented by other methods. Various modifications will be described below.

[0055] (1) In the above embodiment, the road closure estimation device 100 may be implemented as a navigation device installed in a vehicle. That is, the road closure estimation device 100 may be built into a navigation device mounted on a vehicle, and when it estimates that a road closure has occurred on a road, it may provide route guidance to the destination without using the road in question. Furthermore, when the road closure is lifted, the system may formulate a route using the road that has been reopened as one of the candidate roads to be used for route guidance.

[0056] Alternatively, the road closure estimation device 100 may be a device that notifies a navigation system installed in a vehicle of the occurrence and lifting of a road closure via communication.

[0057] (2) In the above embodiment, the method for estimating the occurrence and lifting of a road closure in the road closure estimation device is determined by the processor of the road closure estimation device executing a predetermined program, etc. However, this may be realized in the device by logic circuits (hardware) or dedicated circuits formed on an integrated circuit (IC (Integrated Circuit) chip, LSI (Large Scale Integration)), etc. Furthermore, these circuits may be realized by one or more integrated circuits, and the functions of the multiple functional units shown in the above embodiment may be realized by a single integrated circuit. Depending on the degree of integration, LSIs may be called VLSI, super LSI, ultra LSI, etc. That is, as shown in Figure 5, the road closure estimation device 100 may consist of a communication circuit 101a, an input circuit 102a, an output circuit 103a, a memory circuit 104a, and a control circuit 105a, which correspond to the communication unit 101, input unit 102, output unit 103, memory unit 104, and CPU 105, respectively.

[0058] Furthermore, the above program may be recorded on a recording medium readable by the processor, and the recording medium can be a "non-temporary tangible medium," such as tape, disk, card, semiconductor memory, or programmable logic circuit. The above program may also be supplied to the processor via any transmission medium capable of transmitting the program (such as a communication network or broadcast wave). In other words, for example, the program may be downloaded and executed from a network using an information processing device such as a smartphone. The present invention can also be realized in the form of a data signal embedded in a carrier wave, in which the above program is embodied by electronic transmission.

[0059] The above program can be implemented using scripting languages ​​such as ActionScript and JavaScript®, or object-oriented programming languages ​​such as Objective-C, Java®, C++, Python, and R, but these languages ​​are just examples.

[0060] (3) The various embodiments shown in the above embodiments may be combined as appropriate. Also, the execution order of the operations shown in the flowchart may be changed or executed in parallel, as long as there is no inconsistency in the results. [Explanation of Symbols]

[0061] 100 Road Closure Estimation Device 101 Communications Department 102 Input section 103 Output section 104 Storage section 105 CPU (acquisition unit, calculation unit, estimation unit, output unit)

Claims

1. An acquisition unit that acquires the average number of vehicles that traveled on the target road for each time period, A calculation unit that calculates a probability P based on the average number of vehicles using the formula P = 1 - e - λx (where λ is the average number of vehicles over a predetermined period and x is the length of the predetermined period), An estimation unit estimates that a road closure has occurred on the target road if the probability P calculated by the calculation unit is less than or equal to a predetermined first threshold, and estimates that the road closure has been lifted based on the probability P calculated by the calculation unit after the time at which the road closure was estimated to have occurred. The system includes an output unit that outputs information indicating that the estimation unit has estimated that a road closure is in effect, in association with information indicating the target road, or an output unit that outputs information indicating that the estimation unit has estimated that the road closure has been lifted, in association with information indicating the target road. Road closure estimation device.

2. The estimation unit estimates whether the road closure has been lifted using a different method than when the average number of vehicles on the road exceeds a predetermined number, if it can estimate that the road closure has been in effect for a predetermined time or longer from the time it is estimated that a road closure has occurred on the target road, and the average number of vehicles on the target road is less than or equal to a predetermined number. The road closure estimation device according to feature 1.

3. The estimation unit estimates whether the road closure has been lifted using a different method than when the average number of vehicles on the target road exceeds a predetermined number, if the average number of vehicles on the target road is below a predetermined number. The road closure estimation device according to feature 1.

4. The estimation unit estimates that the road closure has been lifted when the average number of vehicles on the target road exceeds a predetermined number and the probability P calculated by the calculation unit exceeds a predetermined first threshold, and estimates that the road closure has been lifted when the average number of vehicles on the target road is less than or equal to the predetermined number and the probability based on the cumulative sum of the average number of vehicles for each time period corresponding to the elapsed time since the timing at which the estimation unit estimated the road closure occurred exceeds a predetermined second threshold. The road closure estimation device according to claim 2 or 3, characterized in that it is as described above.

5. Computers The acquisition step involves obtaining the average number of vehicles, which shows the average number of vehicles that traveled on the target road for each time period, and A calculation step in which the probability P is calculated based on the average number of vehicles, by P = 1 - e - λx (where λ is the average number of vehicles in a predetermined period and x is the length of the predetermined period), If the probability calculated in the calculation step is less than or equal to a predetermined first threshold, it is estimated that a road closure has occurred on the target road, and an estimation step is made to estimate that the road closure has been lifted based on the probability calculated in the calculation step after the time at which the road closure was estimated to have occurred. The process includes: outputting information indicating that the estimation step has estimated that a road closure is in effect, associated with information indicating the target road; or outputting information indicating that the estimation step has estimated that the road closure has been lifted, associated with information indicating the target road. Method for estimating road closures.

6. On the computer, A function to acquire the average number of vehicles that traveled on the target road for each time period, A calculation function that calculates the probability P based on the average number of vehicles, using the formula P = 1 - e - λx (where λ is the average number of vehicles over a predetermined period and x is the length of the predetermined period), An estimation function that estimates that a road closure has occurred on the target road if the probability calculated by the calculation function is less than or equal to a predetermined first threshold, and estimates that the road closure has been lifted based on the probability calculated by the calculation function after the time at which the road closure was estimated to have occurred, The system includes an output function that outputs information indicating that the estimation function has estimated that a road closure is in effect, associated with information indicating the target road, or an output function that indicates that the estimation function has estimated that the road closure has been lifted, associated with information indicating the target road. Road closure estimation program.

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