Title of invention: Processing apparatus, processing method and program
Technical field
[0001]
　The present invention relates to a processing device, a processing method and a program.
Background technology
[0002]
　Patent Document 1 discloses a technique for calculating traffic volume. Patent Documents 2 and 3 disclose a technique for calculating the number of passengers by analyzing an image. Non-Patent Document 1 discloses a technique for calculating carbon dioxide emissions.
Prior art literature
Patent documents
[0003]
Patent Document 1: Japanese Patent Application Laid-Open No. 2018-55455
Patent Document 2: Japanese Patent Application Laid-Open No. 2005-014690
Patent Document 3: International Publication No. 2014/061195
Non-patent literature
[0004]
Non-Patent Document 1: Tetsuhiro Ishizaka, 3 others, "Arrangement of methods for estimating CO2 emissions in automobile traffic and its application", [online], [Search on August 27, 2018], Internet
Outline of the invention
Problems to be solved by the invention
[0005]
　Measures to alleviate traffic congestion such as carpooling are being considered. In order to realize such congestion mitigation measures, it is necessary to secure a parking space for cars that have reached the carpooling start position and prepare large cars that can be shared by multiple people. In order to calculate the required number of such advance preparations, it is necessary to obtain the number of people who ride in a car and pass through the road, but conventionally there has been no means for accurately calculating this number of people. An object of the present invention is to provide such means.
Means to solve problems
[0006]
　According to the present invention,
　data processing for calculating the traffic volume, which is the number of vehicles passing through the road within a predetermined period, and the average number of passengers within the predetermined period, based on the data generated by the detection device installed on the road. Based on the means, the
　traffic volume and the average number of passengers, the actual condition calculation means for calculating the number of people moving on the road, which is the number of people who got on the vehicle within the predetermined period, and the
　calculation result by the actual condition calculation means.
A processing apparatus having an output means for outputting is provided.
[0007]
　Further, according to the present invention, the
　computer is
　based on the data generated by the detection device installed on the road, the traffic volume which is the number of vehicles passing through the road within a predetermined period, and the average number of passengers within the predetermined period. 　Is provided, a processing method is provided in which the
　number of people traveling on the road, which is the number of people who got on the car within the predetermined period, is calculated based on the traffic volume and the average number of passengers, and the
calculation result is output. To.
[0008]
　Further, according to the present invention, the
　computer is
　based on the data generated by the detection device installed on the road, the traffic volume which is the number of vehicles passing through the road within a predetermined period, and the average number of passengers within the predetermined period. Based on the data processing means for calculating the
　above traffic volume and the average number of passengers, the actual condition calculation means for calculating the number of people moving on the road within the predetermined period, the actual
　condition calculation means.
A program that functions as an output means for outputting the calculation result is provided.
[0009]
　Further, according to the present invention,
　based on the data processing means for calculating the number of passengers of each vehicle passing through the road within a predetermined period based on the data generated by the detection device installed on the road,
　and based on the number of passengers. Provided is a processing device having an actual condition calculation means for calculating the number of people moving by a vehicle, which is the number of people who got on a vehicle and passed the road within the predetermined period, and
　an output means for outputting a calculation result by the actual condition calculation means.
..
[0010]
　Further, according to the present invention, the
　number of passengers of each vehicle passing through the road is calculated based on the data generated by the detection device installed on the road, and within the predetermined period based on the number of passengers
　.
　Provided is a processing method for calculating the number of people moving by car, which is the number of people who got on the car and passed the road, and output the calculation result.
[0011]
　Further, according to the present invention,
　a computer,
　based on data that the installed detector generated in the road, the data processing means for calculating the number of passengers of the car, each passing through the road within a predetermined time period,
　the number of passengers Based on this, a program is provided that functions as an
　actual condition calculation means for calculating the number of people moving by a vehicle, which is the number of people who got on a vehicle and passed through the road within the predetermined period, and an output means for outputting the calculation result by the actual condition calculation means.
..
Effect of the invention
[0012]
　According to the present invention, it is possible to accurately calculate the number of people who get on a car and pass through a road.
A brief description of the drawing
[0013]
　The above-mentioned objectives and other objectives, features and advantages will be further clarified by the preferred embodiments described below and the accompanying drawings below.
[0014]
FIG. 1 is a diagram showing an example of a hardware configuration of the processing device of the present embodiment.
FIG. 2 is an example of a functional block diagram of the processing device of the present embodiment.
FIG. 3 is a diagram schematically showing an example of information processed by the processing apparatus of the present embodiment.
FIG. 4 is a diagram schematically showing an example of information output by the processing apparatus of the present embodiment.
FIG. 5 is a diagram schematically showing an example of information output by the processing apparatus of the present embodiment.
FIG. 6 is a flowchart showing an example of a processing flow of the processing apparatus of the present embodiment.
FIG. 7 is an example of a functional block diagram of the processing device of the present embodiment.
FIG. 8 is a diagram schematically showing an example of information processed by the processing apparatus of the present embodiment.
FIG. 9 is a diagram schematically showing an example of information output by the processing apparatus of the present embodiment.
FIG. 10 is a diagram schematically showing an example of information output by the processing apparatus of the present embodiment.
FIG. 11 is a flowchart showing an example of a processing flow of the processing apparatus of the present embodiment.
FIG. 12 is an example of a functional block diagram of the processing device of the present embodiment.
FIG. 13 is an example of a functional block diagram of the processing device of the present embodiment.
FIG. 14 is a flowchart showing an example of a processing flow of the processing apparatus of the present embodiment.
FIG. 15 is a diagram schematically showing an example of information output by the management device of the present embodiment.
FIG. 16 is an example of a functional block diagram of the processing device of the present embodiment.
FIG. 17 is an example of a functional block diagram of the processing device of the present embodiment.
FIG. 18 is a flowchart showing an example of a processing flow of the processing apparatus of the present embodiment.
FIG. 19 is a diagram for explaining a section of the present embodiment.
Mode for carrying out the invention
[0015]
<
　First Embodiment> First, an outline of the processing device 10 of the present embodiment will be described. The processing device 10 of the present embodiment calculates the number of people traveling by car, which is the number of people who got on the car and passed through the road within a predetermined period, based on the data generated by the detection device installed on the road. The details of the processing apparatus 10 will be described below.
[0016]
　First, an example of the hardware configuration of the processing device 10 will be described. Each functional unit included in the processing device 10 of the present embodiment includes a CPU (Central Processing Unit) of an arbitrary computer, a memory, a program loaded into the memory, and a storage unit such as a hard disk for storing the program (the device is shipped in advance). In addition to programs stored from the stage, programs downloaded from storage media such as CDs (Compact Discs) and servers on the Internet can also be stored), and optional hardware and software centered on network connection interfaces. It is realized by the combination of. And, it is understood by those skilled in the art that there are various modifications of the realization method and the device.
[0017]
　FIG. 1 is a block diagram illustrating a hardware configuration of the processing device 10 of the present embodiment. As shown in FIG. 1, the processing device 10 includes a processor 1A, a memory 2A, an input / output interface 3A, a peripheral circuit 4A, and a bus 5A. The peripheral circuit 4A includes various modules. The processing device 10 does not have to have the peripheral circuit 4A. The processing device 10 may be composed of a plurality of physically separated devices. In this case, each of the plurality of devices can be provided with the above hardware configuration.
[0018]
　The bus 5A is a data transmission path for the processor 1A, the memory 2A, the peripheral circuits 4A, and the input / output interface 3A to transmit and receive data to and from each other. The processor 1A is, for example, an arithmetic processing unit such as a CPU or a GPU (Graphics Processing Unit). The memory 2A is, for example, a memory such as a RAM (Random Access Memory) or a ROM (Read Only Memory). The input / output interface 3A includes an interface for acquiring information from an input device, an external device, an external server, an external sensor, a camera, etc., an interface for outputting information to an output device, an external device, an external server, etc. .. The input device is, for example, a keyboard, a mouse, a microphone, or the like. The output device is, for example, a display, a speaker, a printer, a mailer, or the like. The processor 1A can issue commands to each module and perform calculations based on the calculation results thereof.
[0019]
　FIG. 2 shows an example of a functional block diagram of the processing device 10. As shown in the figure, the processing device 10 includes a data processing unit 11, an actual condition calculation unit 12, and an output unit 13.
[0020]
　The data processing unit 11 calculates various values ​​based on the data generated by the detection device installed on the road. The detection device may be a camera that photographs the road on which the vehicle passes and generates a moving image or a still image, a sensor that detects the passage of an object, or the like. Hereinafter, the data generated by the detection device will be referred to as road measurement data.
[0021]
　One or more detectors are set at any position on the road. Then, the road measurement data generated by one or more detection devices is input to the processing device 10 at an arbitrary timing. For example, the detection device and the processing device 10 may be configured to be able to communicate with each other by wire and / or wirelessly. Then, the detection device may transmit the road measurement data to the processing device 10 by real-time processing or batch processing. In addition, the road measurement data generated by the detection device may be stored in a storage device provided in the detection device or in an external device connected to the detection device. Then, the operator may output the road measurement data stored in the storage device from the storage device by any means and input it to the processing device 10. The road measurement data output from the detection device is associated with the measurement date and time and the measurement position (example: shooting date and time, shooting position (installation position of the detection device)) of the data.
[0022]
　Based on the road measurement data, the data processing unit 11 calculates "traffic volume, which is the number of vehicles passing through the road within a predetermined period" and "average number of passengers of vehicles passing through the road within a predetermined period". The calculation of traffic volume and the calculation of the average number of passengers can be realized by using any technology. For example, an image analysis technique such as pattern matching may be used to count the number of vehicles that have passed a predetermined position on the road within a predetermined period. Further, using the image analysis technology disclosed in Patent Documents 2 and 3, after calculating the number of passengers of each vehicle that has passed a predetermined position on the road within a predetermined period, the average of the calculated number of passengers is calculated. May be good.
[0023]
　The data processing unit 11 can calculate the traffic volume and the average number of passengers for each of the plurality of periods. The data processing unit 11 may calculate, for example, the traffic volume and the average number of passengers in each period every 1 minute, 5 minutes, 10 minutes, 30 minutes, 1 hour, and 1 day.
[0024]
　FIG. 3 schematically shows an example of the information generated by the data processing unit 11. In the information, the measurement position, the date (measurement date), the time zone (measurement time zone), the traffic volume, and the average number of passengers are associated with each other. The information shown shows the traffic volume and the average number of passengers every 5 minutes.
[0025]
　The data processing unit 11 can calculate the traffic volume and the average number of passengers for each second period based on the traffic volume and the average number of passengers calculated for each first period. The second period is an integral multiple of the first period. For example, the data processing unit 11 is based on the traffic volume calculated every 5 minutes and the average number of passengers as shown in FIG. 3, every 5 × M minutes (M is an integer of 2 or more), specifically 10 minutes. The traffic volume and the average number of passengers can be calculated every, every 15 minutes, every 20 minutes, and so on.
[0026]
　In addition, the data processing unit 11 can calculate various statistical values ​​(average value, maximum value, minimum value, mode value, median value, etc.) based on the traffic volume and the average number of passengers in each of the plurality of periods. For example, the data processing unit 11 performs a predetermined period (example: from January 1, 2018) for each time zone (example: a time zone one hour later such as 9:00 to 10:00, 10:00 to 11:00). The statistics of traffic volume and average number of passengers as of December 31, 2018) may be calculated.
[0027]
　The actual condition calculation unit 12 calculates various values ​​indicating the actual condition of the traffic condition of the road based on the data processing result of the data processing unit 11.
[0028]
　Specifically, the actual condition calculation unit 12 is the number of people who got on the car within the predetermined period and passed through the road based on the traffic volume within the predetermined period and the average number of passengers within the predetermined period calculated by the data processing unit 11. Calculate the number of people moving by car. The actual condition calculation unit 12 calculates the product of the traffic volume within the predetermined period and the average number of passengers within the predetermined period as the number of vehicles moving within the predetermined period.
[0029]
　The actual condition calculation unit 12 can calculate the number of people moving in each of the plurality of periods. The actual condition calculation unit 12 may calculate the number of people moving in each period, for example, every 1 minute, every 5 minutes, every 10 minutes, every 30 minutes, every hour, every day, and so on.
[0030]
　In addition, the actual condition calculation unit 12 can calculate the number of vehicles moving for each second period based on the number of vehicles moving for each first period. The second period is an integral multiple of the first period. For example, when the data processing unit 11 calculates the traffic volume and the average number of passengers every 5 minutes as shown in FIG. 3, the actual condition calculation unit 12 concretely calculates every 5 × M minutes (M is an integer of 2 or more). The number of people moving by car can be calculated every 10 minutes, every 15 minutes, every 20 minutes, and so on.
[0031]
　In addition, the actual condition calculation unit 12 can calculate various statistical values ​​based on the number of vehicles moving in each of the plurality of periods. For example, the actual condition calculation unit 12 performs a predetermined period (example: from January 1, 2018) for each time zone (example: time zone one hour later such as 9:00 to 10:00, 10:00 to 11:00). The statistical value of the number of people moving by car as of December 31, 2018) may be calculated.
[0032]
　The output unit 13 outputs various information. The output unit 13 can output the calculation result by the actual condition calculation unit 12 and the processing result by the data processing unit 11. The output can be realized by using any output device such as a display, a printer, a speaker, a projection device, and a mailer.
[0033]
　FIG. 4 schematically shows an example of the information output by the output unit 13. The information shown is the result based on the road measurement data measured before the XX alternation on XX street. The data period is from July 1st to 31st, 2018, and the number of people moving by car per day is shown in a line graph.
[0034]
　Although not shown, the processing device 10 may accept user input for designating a "measurement position", a "data period", "which period the number of vehicles moving is displayed", and the like. Then, the output unit 13 may change the display content based on the user input.
[0035]
　FIG. 5 schematically shows another example of the information output by the output unit 13. The illustrated information includes a map and displays the number of people moving by the vehicle in association with each of the plurality of measurement positions existing on the displayed map. The data period is from July 1st to 31st, 2018, and the average number of vehicles moving per day within the data period is shown.
[0036]
　Although not shown, the processing device 10 has a "map area to be displayed", a "data period", a type of number of vehicles moving to be displayed (average value, maximum value, minimum value, mode, median value, etc. within the data period). ) ”, Etc. may be accepted. Then, the output unit 13 may change the display content based on the user input.
[0037]
　Next, an example of the processing flow of the processing apparatus 10 of the present embodiment will be described with reference to the flowchart of FIG.
[0038]
　In S10, the data processing unit 11 calculates the traffic volume and the average number of passengers within a predetermined period based on the road measurement data. For example, as shown in FIG. 3, the data processing unit 11 can calculate the traffic volume and the average number of passengers for each of the plurality of periods. Further, as shown in FIG. 3, the data processing unit 11 can calculate the traffic volume and the average number of passengers for each measurement position.
[0039]
　In S11, the actual condition calculation unit 12 calculates the number of people moving within a predetermined period based on the traffic volume and the average number of passengers calculated in S10. For example, the actual condition calculation unit 12 can calculate the number of people moving in each of a plurality of periods. In addition, the actual condition calculation unit 12 can calculate the number of people moving by vehicle for each measurement position.
[0040]
　In S12, the output unit 13 outputs the calculation result of S11. An example of the information output by the output unit 13 is shown in FIGS. 4 and 5. The output unit 13 may output the calculation result of S10.
[0041]
　According to the processing device 10 of the present embodiment described above, the number of people traveling by car, which is the number of people who got on the car and passed through the road within a predetermined period, is calculated based on the road measurement data generated by the detection device installed on the road. can do. According to such a processing device 10, it is possible to accurately calculate the number of people who get on a car and pass through the road.
[0042]
　Here, a modified example of the present embodiment will be described. The data processing unit 11 may calculate the number of passengers of each vehicle passing through the road within a predetermined period based on the data generated by the detection device installed on the road. Then, the actual condition calculation unit 12 adds up the "number of passengers of each vehicle that has passed the road within the predetermined period" calculated by the data processing unit 11, and thereby, the number of passengers who have passed the road within the predetermined period. The number of people moving by car may be calculated. The data processing unit 11 can calculate the number of passengers of each vehicle that has passed a predetermined position on the road within a predetermined period by using, for example, the image analysis technique disclosed in Patent Documents 2 and 3. In the modified example, the same effect is realized.
[0043]

　The processing device 10 of the present embodiment calculates the priority of the traffic congestion mitigation measures on each road by using the number of vehicles moving and the like calculated in the first embodiment. The details of the processing apparatus 10 will be described below.
[0044]
　An example of the hardware configuration of the processing device 10 is the same as that of the first embodiment.
[0045]
　FIG. 7 shows an example of a functional block diagram of the processing device 10. As shown in the figure, the processing device 10 includes a data processing unit 11, an actual condition calculation unit 12, an output unit 13, and a priority determination unit 14.
[0046]
　The data processing unit 11 calculates a value indicating a road congestion status within a predetermined period based on the road measurement data. Other configurations of the data processing unit 11 are the same as those of the first embodiment.
[0047]
　In the present embodiment, the average speed of a vehicle that has passed the road within a predetermined period is calculated as a value indicating a traffic jam situation, but the present embodiment is not limited to this. For example, the detection device is a sensor that detects the speed of a vehicle, and the data processing unit 11 may calculate an average value of the speeds of each vehicle detected by the detection device. In addition, the data processing unit 11 analyzes the moving image generated by the detection device, and the time required for each vehicle to move from the first position to the second position on the image, and the first position. The distance to the second position may be obtained, and the moving speed of each vehicle may be calculated based on the time and the distance. Then, the data processing unit 11 may calculate the average value of the calculated speeds of each vehicle.
[0048]
　The fact-finding unit 12 calculates one or both of the amount of economic loss due to traffic congestion within a predetermined period and the amount of carbon dioxide emitted by the vehicle within the predetermined period. Other configurations of the actual condition calculation unit 12 are the same as those of the first embodiment.
[0049]
　The actual condition calculation unit 12 calculates the amount of economic loss due to the traffic congestion within a predetermined period based on the value indicating the congestion situation calculated by the data processing unit 11 and the number of vehicles moving by the actual condition calculation unit 12. This will be described below.
[0050]
　FIG. 19 is a schematic view showing a section on the road. In FIG. 19, P 1 , P 2 , ..., P n-1 , and P n are the positions (measurement points) where the detection device is installed, respectively.
[0051]
　Here, as shown in FIG. 19, the section sandwiched between the measurement points Pi and Pi + 1 is defined as Pi, i + 1 . Further, the interval P i, i + 1 a distance K of i and. The distance Ki is a known distance because it is a distance determined according to the installation location of the detection device.
[0052]
　Here, the variables are further defined as follows.
S i : Measurement Point P i average moving speed of the vehicle in the detected predetermined period in
Q i : Measurement Point P i traffic within a specified period of time has been detected in
JR: Measurement Point P i detected in the the predetermined period Average number of passengers
CO 2 : Carbon dioxide emissions per unit time emitted from one vehicle
JT: Predetermined time zone
JS: Congestion speed (for example, 20 km / h)
M: Preset labor unit price
[0053]
　In the present embodiment, as an example, the actual condition calculation unit 12 determines the amount of economic loss based on the loss time due to traffic congestion, the number of vehicles that generated the loss time, the number of passengers of the vehicle, and the labor unit price. Is calculated. Specifically, the actual condition calculation unit 12 calculates the economic loss amount Z1 by, for example, the following formula (1).
[0054]
[Number 1]

[0055]
　In the formula (1), T loss represents a loss time. Loss time T loss the interval P i, i + 1 of length K i and the movement time when moving at an average moving speed of the detected vehicle by detecting device, the movement time when moving the same distance in the traffic jam rate JS The difference. That is, the loss time Loss indicates the extra travel time required due to the traffic jam. When the average moving speed of the vehicle detected by the detection device is faster than the congestion speed JS, the loss time T loss is set to 0. The actual condition calculation unit 12 calculates the loss time T loss when the average moving speed of the vehicle detected by the detection device is slower than the congestion speed JS, for example, by the following equation (2) .
[0056]
[Number 2]

[0057]
　In the formula (2), the average moving speed of the vehicle in the sections Pi and i + 1 detected by the detection device is represented by S i and i + 1 . Here, S i and i + 1 are calculated based on , for example, the average moving speeds S i and S i + 1 detected at the measurement points P i and P i + 1, respectively . For example, the statistical values ​​(average value, maximum value, minimum value, etc.) of the average moving speeds S i and S i + 1 may be S i, i + 1 . The actual condition calculation unit 12 calculates Si, i + 1 by, for example, the following equation (3) .
[0058]
[Number 3]

[0059]
　In the formula (2), the congestion speed JS is used as the reference speed used in the calculation of the loss time, but instead of the JS, another predetermined speed such as the legal speed of the road may be used.
[0060]
　Further, in the equation (1), N is the number of vehicles traveling in the sections Pi and i + 1 , and corresponds to the number of vehicles causing the loss time. The product of N and JR in the formula (1) is the number of vehicles moving that have passed the sections Pi and i + 1 within a predetermined period . N is, for example, measurement points P i and P i + 1 is detected in each traffic volume Q i and Q i + 1 based on the calculated. For example, traffic volume Q i and Q i + 1 statistics (mean, maximum value, minimum value, etc.) is calculated as N. The actual condition calculation unit 12 calculates N by, for example, the following equation (4).
[0061]
[Number 4]

[0062]
　The actual condition calculation unit 12 calculates the product of the loss time T loss , the number of vehicles N, the average number of passengers JR, and the labor unit price M as the amount of economic loss generated within a predetermined period in the sections Pi and i + 1 . In addition, the actual condition calculation unit 12 can calculate various values ​​based on the economic loss amount for each section and for each predetermined period calculated in this way. For example, as shown in the equation (1), the actual condition calculation unit 12 calculates the product of the loss time T loss , the number of vehicles N, the average number of passengers JR, and the labor unit price M for a predetermined statistical acquisition period (for example, one year). You may add up for each astringent time zone JT. In addition, the actual condition calculation unit 12 calculates the product of the loss time T loss , the number of vehicles N, the average number of passengers JR, and the labor unit price M as a series of congestion sections (a plurality of adjacent sections Pi, i + 1) . It may be integrated for the integrated integrated section).
[0063]
　In addition, the actual condition calculation unit 12 can calculate the carbon dioxide emission amount of the vehicle by using any technique. For example, the actual condition calculation unit 12 is excessively discharged due to traffic congestion based on the loss time due to traffic congestion, the number of vehicles that generated the loss time, and the amount of carbon dioxide emitted from the vehicle per unit time. Carbon dioxide emissions (carbon dioxide emissions) Z2 is calculated. Specifically, the actual condition calculation unit 12 calculates the carbon dioxide emission amount Z2 by, for example, the following formula (5).
[0064]
[Number 5]

[0065]
　As shown in the equation (5), the actual condition calculation unit 12 additionally discharges the product of the loss time T loss , the number of units N, and the emission amount CO 2 due to the congestion generated within the predetermined period in the sections Pi and i + 1 . It is calculated as the amount of carbon dioxide emitted. In addition, the actual condition calculation unit 12 can calculate various values ​​based on the amount of extra carbon dioxide emitted for each section and for each predetermined period calculated in this way. For example, as shown in the equation (5), the actual condition calculation unit 12 calculates the product of the loss time T loss , the number N, and the emission amount CO 2 in each astringent time zone of a predetermined statistical acquisition period (for example, one year). You may add up for JT. In addition, the actual condition calculation unit 12 combines this integration result or the product of the loss time T loss , the number of units N, and the emission amount CO 2 into a series of congestion sections ( integrated sections in which a plurality of adjacent sections Pi and i + 1 are integrated. ) May be integrated.
[0066]
　The actual condition calculation unit 12 may use a preset value as the emission amount CO 2 in the equation (5) , but in addition, the vehicle type specified by analyzing the image generated by the detection device. The value of the average emission amount calculated from the ratio of the above and the amount of carbon dioxide emissions preset for each type of vehicle may be used as the value of CO 2 in the formula (5) . In addition, the actual condition calculation unit 12 calculates a value obtained by integrating the carbon dioxide emissions of each predetermined vehicle type based on the vehicle type identified by analyzing the image generated by the detection device. It may be used as the value of N × CO 2 in (5) .
[0067]
　Here, FIG. 8 schematically shows an example of the information generated by the data processing unit 11 and the actual condition calculation unit 12. Statistics of sections Pi, i + 1 , date, time zone, traffic volume, average number of passengers, and average vehicle speed ( average moving speeds Si and Si + 1 detected at measurement points Pi and Pi + 1 respectively) Value), the amount of economic loss, and the amount of carbon dioxide emissions are associated. The information illustrated shows traffic volume, average number of passengers, average speed, economic loss and carbon dioxide emissions every 5 minutes.
[0068]
　The priority determination unit 14 determines the priority of the congestion mitigation measures in each section Pi, i + 1 based on the road congestion condition, the amount of economic loss caused by the congestion, and at least one of the carbon dioxide emissions. To do.
[0069]
　Here, an example of the priority calculation method will be described. First, the priority determination unit 14 standardizes the values ​​of each item in each of the plurality of sections Pi and i + 1 of the road, and expresses them as standardized values ​​of 0 to 1, for example. Each item is at least one of the traffic congestion condition of the road within the predetermined period (eg, the average speed of the vehicle), the amount of economic loss within the predetermined period, and the carbon dioxide emission within the predetermined period. Here, the priority determination unit 14 increases the standardized value as the degree of traffic congestion increases (the slower the average speed of the vehicle), the greater the amount of economic loss, and the greater the amount of carbon dioxide emitted. It shall be standardized based on the rules stipulated in (to approach 1). The priority determination unit 14 is set so that the greater the degree of traffic congestion (the slower the average speed of the vehicle), the greater the amount of economic loss, and the greater the amount of carbon dioxide emissions, the smaller the standardized value. It may be standardized based on a set rule (to approach 0).
[0070]
　Next, the priority determination unit 14 calculates a value obtained by multiplying the standardized value of each item in each of the plurality of sections Pi and i + 1 of the road by the weighted value of each of the plurality of predetermined items. Then, the priority determination unit 14 calculates an evaluation value obtained by adding the product of the standardized value and the weighted value calculated for each item for each of the plurality of sections Pi and i + 1 of the road .
[0071]
　Then, the priority determination unit 14 determines the priority based on the above evaluation value. For example, the priority determination unit 14 may calculate the priority of each point based on the table showing the correspondence between the evaluation value and the priority and the evaluation value of each point on the road.
[0072]
　The output unit 13 outputs the priority calculated by the priority determination unit 14. Other configurations of the output unit 13 are the same as those of the first embodiment.
[0073]
　FIG. 9 schematically shows an example of the information output by the output unit 13. The illustrated information includes a map, and the priority calculated by the priority determination unit 14 is displayed in association with each of the plurality of sections Pi and i + 1 existing on the displayed map . Priority A has the highest priority, the next highest priority is priority B, and the next highest priority is priority C (not shown).
[0074]
　FIG. 10 schematically shows another example of the information output by the output unit 13. The illustrated information includes a map and displays the amount of economic loss, the amount of carbon dioxide emissions, and the average speed of the vehicle in association with each of the plurality of sections Pi and i + 1 existing on the displayed map . The data period is from July 1st to 31st, 2018, and the total economic loss, total carbon dioxide emissions, and average rate within the data period are shown.
[0075]
　Next, an example of the processing flow of the processing apparatus 10 of the present embodiment will be described with reference to the flowchart of FIG.
[0076]
　In S20, the data processing unit 11 calculates the traffic volume, the average number of passengers, and the average speed of the vehicle within a predetermined period based on the road measurement data. For example, as shown in FIG. 8, the data processing unit 11 can calculate the traffic volume, the average number of passengers, and the average speed of the vehicle for each of the plurality of periods. Further, as shown in FIG. 8, the data processing unit 11 can calculate the traffic volume, the average number of passengers, and the average speed of the vehicle for each measurement position.
[0077]
　In S21, the actual condition calculation unit 12 calculates the number of vehicles moving within a predetermined period, the amount of economic loss due to traffic congestion, and the amount of carbon dioxide emissions of the vehicle based on the result calculated in S20. For example, the actual condition calculation unit 12 can calculate the number of people moving by vehicle, the amount of economic loss caused by traffic congestion, and the amount of carbon dioxide emitted by a vehicle during a plurality of periods. In addition, the actual condition calculation unit 12 can calculate the number of people moving, the amount of economic loss due to traffic congestion, and the amount of carbon dioxide emitted from the vehicle for each measurement position or each section Pi, i + 1 .
[0078]
　In S22, the priority determination unit 14 prioritizes the congestion mitigation measures based on the traffic congestion condition (average speed of the vehicle), the amount of economic loss caused by the congestion, and at least one of the carbon dioxide emissions. To determine.
[0079]
　In S23, the output unit 13 outputs the priority determined in S22. The output unit 13 may further output the calculation result of S21 and the calculation result of S20. An example of the information output by the output unit 13 is shown in FIGS. 9 and 10.
[0080]
　According to the processing apparatus 10 of the present embodiment described above, the same effects as those of the first embodiment can be realized. Further, according to the processing device 10 of the present embodiment, based on the road measurement data generated by the detection device installed on the road, the road congestion status, the amount of economic loss caused by the congestion, and the carbon dioxide emission amount are included. At least one of can be calculated with high accuracy. Then, the processing device 10 can determine the priority of the congestion mitigation measure for each section Pi, i + 1 based on the calculation result . As a result, congestion mitigation measures at multiple points can be taken in an appropriate order.
[0081]

　The processing device 10 of the present embodiment is required when promoting carpooling, which is one of the measures for alleviating traffic congestion, by using the number of moving vehicles calculated in the first embodiment. Calculate the size of the parking lot.
[0082]
　Here, carpooling, which is one of the measures to alleviate traffic congestion, will be described. For carpooling, prepare a parking lot for carpooling. Multiple members who synergize move to the parking lot by their own car and meet at the parking lot. A plurality of members ride in one of the multiple members when moving from the parking lot. Then, the cars of other members are parked in the parking lot.
[0083]
　The details of the processing apparatus 10 will be described below. An example of the hardware configuration of the processing device 10 is the same as that of the first and second embodiments.
[0084]
　FIG. 12 shows an example of a functional block diagram of the processing device 10. As shown in the figure, the processing device 10 includes a data processing unit 11, an actual condition calculation unit 12, an output unit 13, a reception unit 15, and a parking lot scale calculation unit 17. As shown in FIG. 13, the processing device 10 may further include an effect calculation unit 16. Further, the processing device 10 may further have a priority determination unit 14 (not shown).
[0085]
　The configurations of the data processing unit 11, the actual condition calculation unit 12, and the priority determination unit 14 are the same as those in the first and second embodiments.
[0086]
　The reception unit 15 accepts an input for designating an average number of passengers target value, which is a target value of the average number of passengers. The reception unit 15 receives input from the user for designating an average number of passengers target value via an arbitrary input device such as a touch panel display, a keyboard, a mouse, and a microphone. The reception unit 15 may accept the input of the average number of passengers target value applied to all the roads, or may accept the input of the average number of passengers target value for each point (each measurement position) on the road.
[0087]
　The parking lot size calculation unit 17 calculates the required scale of the parking lot when the average number of passengers is achieved by sharing the vehicle, based on the traffic volume, the number of people moving, and the average number of passengers. The parking lot scale calculation unit 17 calculates the required scale of the parking lot based on the following formula (6).
[0088]
[Number 6]

[0089]
　As shown by the formula (6), the parking lot scale calculation unit 17 calculates the required scale by subtracting the value obtained by dividing the number of people moving by the vehicle by the target value of the average number of passengers from the traffic volume. According to the formula (6), the parking lot scale calculation unit 17 can calculate how many parking spaces a parking lot has is required.
[0090]
　The "traffic volume" in the formula is a statistical value of the traffic volume at a certain measurement position within a predetermined period, and the "number of vehicles moving" in the formula is a statistical value of the number of vehicles moving at the same measurement position within the same predetermined period. ..
[0091]
　For example, the average value of the daily traffic volume in the last year may be adopted as the "traffic volume", and the number of vehicles moving in the latest one year may be adopted as the "number of people moving by car".
[0092]
　In addition, the average value of the traffic volume during the weekday commuting hours (eg, 7:00 to 10:00) in the last year is adopted as the "traffic volume", and the above-mentioned commuting on weekdays in the last year is used as the "number of people traveling by car". The number of people moving by car during the time period may be adopted.
[0093]
　The parking lot scale calculation unit 17 may calculate the parking lot scale for each section Pi, i + 1 described in the second embodiment . In this case, the traffic volume in the equation (6) is a statistical value of the traffic volume detected at the measurement points Pi and Pi + 1 . Further, the number of vehicles moving in the formula (6) is a statistical value of the number of vehicles moving detected at the measurement points Pi and Pi + 1 . Further, the parking lot scale calculation unit 17 may calculate the parking lot scale for each integrated section in which a plurality of adjacent sections Pi and i + 1 are integrated. In this case, the parking lot scale calculation unit 17 calculates the statistical value of the parking lot scale calculated corresponding to each of the plurality of sections Pi and i + 1 included in the integrated section as the parking lot scale in the integrated section. May be good.
[0094]
　The effect calculation unit 16 calculates at least one of the traffic volume when the average number of passengers target value is achieved, the traffic congestion condition of the road, the amount of economic loss caused by the congestion, and the carbon dioxide emission amount.
[0095]
　For example, the effect calculation unit 16 uses the "average number of passengers" and "traffic volume and congestion status (average speed)" calculated from the past road measurement data as learning data, and "average number of passengers" and "traffic volume and congestion". By inputting the average number of passengers target value into the estimation model obtained by machine learning the relationship with "situation (average speed)", the traffic volume and road congestion when the average number of passengers target value is achieved. The situation may be calculated.
[0096]
　Then, the effect calculation unit 16 determines the amount of economic loss and carbon dioxide emissions caused by the traffic congestion based on the number of vehicles moving calculated by the actual condition calculation unit 12 and the traffic volume and road congestion status calculated as described above. May be calculated.
[0097]
　The output unit 13 outputs the calculation result by the parking lot scale calculation unit 17. The output unit 13 may further output the calculation result by the effect calculation unit 16. Other configurations of the output unit 13 are the same as those of the first and second embodiments.
[0098]
　Next, an example of the processing flow of the processing apparatus 10 of the present embodiment will be described with reference to the flowchart of FIG.
[0099]
　In S30, the data processing unit 11 calculates the traffic volume and the average number of passengers within a predetermined period based on the road measurement data. For example, as shown in FIG. 3 or FIG. 8, the data processing unit 11 can calculate the traffic volume and the average number of passengers for each of the plurality of periods. Further, as shown in FIGS. 3 and 8, the data processing unit 11 can calculate the traffic volume and the average number of passengers for each measurement position.
[0100]
　In S31, the actual condition calculation unit 12 calculates the number of vehicles moving within a predetermined period based on the result calculated in S30. For example, the actual condition calculation unit 12 can calculate the number of people moving in each of a plurality of periods. In addition, the actual condition calculation unit 12 can calculate the number of people moving by vehicle for each measurement position.
[0101]
　In S32, the reception unit 15 accepts the user input for designating the average number of passengers target value. The reception unit 15 may accept the input of the average number of passengers target value applied to all the roads, or may accept the input of the average number of passengers target value for each point (each measurement position) on the road. The execution timing of S32 is not limited to that shown, and may be executed before S30, after S30, and before S31.
[0102]
　In S33, the parking lot scale calculation unit 17 performs a carpooling average number of passengers target value based on the traffic volume calculated in S30, the number of vehicles moving calculated in S31, and the average number of passengers target value specified in S32. Calculate the required size of the parking lot when the above is achieved. The parking lot size calculation unit 17 determines the required size of the parking lot for each point on the road (for each measurement position) when the average number of passengers of vehicles passing through each point reaches the average number of passengers target value by carpooling. calculate.
[0103]
　In S34, the output unit 13 outputs the required scale of the parking lot determined in S33. The output unit 13 may further output the calculation result of S31 and the calculation result of S30.
[0104]
　According to the processing apparatus 10 of the present embodiment described above, the same effects as those of the first and second embodiments can be realized. Further, according to the processing device 10 of the present embodiment, the scale of the parking lot required for promoting carpooling, which is one of the measures for alleviating traffic congestion, is calculated based on the road measurement data generated by the detection device installed on the road. Based on this, it can be calculated with high accuracy. As a result, it is possible to reduce the inconvenience of unnecessarily preparing a lot of parking lots or running out of parking lots.
[0105]
　Here, a modified example of the present embodiment will be described. In the above example, the parking lot scale calculation unit 17 has calculated how many parking spaces are required for the parking lot. As a modification, the parking lot scale calculation unit 17 may calculate the area of ​​the parking lot and the capacity of the parking lot as the required parking lot scale based on the number of units calculated in the above example. For example, the parking lot scale calculation unit 17 can perform the above calculation based on a calculation formula for calculating the area and capacity from the number of units, a corresponding table, and the like. In the modified example, the same effect is realized.
[0106]
　Here, another modification of the present embodiment will be described. In the present embodiment, a management device that calculates and outputs the achievement rate for each parking lot prepared for promoting carpooling, which is one of the measures for alleviating traffic congestion, may be provided.
[0107]
　The management device calculates the achievement rate by dividing the "number of cars parked in the parking lot" by the "number of cars that can be parked in the parking lot (number of cars that can be parked)". The method of detecting "the number of cars parked in the parking lot" is not particularly limited and can be realized by using any technology. For example, the management device may receive notification that a car has entered and exited from a gate device that detects the entry and exit of a car at the entrance and exit of a parking lot. Then, the management device may calculate a value obtained by subtracting the number of cars leaving from the number of cars entering as "the number of cars parked in the parking lot".
[0108]
　The output can be realized by using any output device such as a display, a printer, a speaker, a projection device, and a mailer. For example, a display installed in a parking lot may show the achievement rate of each parking lot at that time (see FIG. 15).
[0109]
　In the modified example, the same effect is realized. Further, according to the management device of the modified example, the achievement rate of the traffic congestion mitigation measure can be calculated and output. By visually recognizing this achievement rate, it is possible to easily grasp whether or not the traffic congestion mitigation measures are in progress.
[0110]

　The processing device 10 of the present embodiment is necessary when promoting the transfer of a large vehicle, which is one of the measures for alleviating traffic congestion, by using the number of vehicles moving, etc. calculated in the first embodiment. Calculate the required number of large vehicles.
[0111]
　Here, the transfer of large vehicles, which is one of the measures for alleviating traffic congestion, will be described. For large vehicle transfer, prepare a large vehicle that transfers multiple members from the departure point to the arrival point. Examples of large vehicles include, but are not limited to, buses, trains, and the like. Multiple members transported by large vehicles move to the starting point by any means. Then, the plurality of members board a large vehicle and move from the departure point to the arrival point.
[0112]
　The details of the processing apparatus 10 will be described below. An example of the hardware configuration of the processing device 10 is the same as that of the first to third embodiments.
[0113]
　FIG. 16 shows an example of a functional block diagram of the processing device 10. As shown in the figure, the processing device 10 includes a data processing unit 11, an actual condition calculation unit 12, an output unit 13, a reception unit 15, and a required number calculation unit 18. As shown in FIG. 17, the processing device 10 may further include an effect calculation unit 16. Further, the processing device 10 may further have a priority determination unit 14 (not shown). Further, the processing device 10 may further include a parking lot scale calculation unit 17 (not shown).
[0114]
　The configuration of the data processing unit 11, the actual condition calculation unit 12, the priority determination unit 14, and the parking lot scale calculation unit 17 is the same as in the first to third embodiments.
[0115]
　The reception unit 15 accepts an input for designating the upper limit of the number of vehicles moving within a predetermined period. For example, the reception unit 15 may accept an input for designating the upper limit of the number of people who can move in a day, or the upper limit of the number of people who can move in a predetermined time zone (eg, commuting time from 7:00 to 10:00 on weekdays). You may accept input that specifies a value. The reception unit 15 receives an input from the user for designating the upper limit value of the number of people moving by the vehicle via an arbitrary input device such as a touch panel display, a keyboard, a mouse, and a microphone. The reception unit 15 may accept the input of the upper limit value of the number of people moving by vehicle, which is applied to all the roads, or may accept the input of the upper limit value of the number of people moving by vehicle at each point (each measurement position) on the road.
[0116]
　The required number calculation unit 18 calculates the required number of large vehicles required when a large vehicle moves a portion of the number of vehicles moving at each measurement position calculated by the actual condition calculation unit 12 that exceeds the upper limit of the number of moving vehicles. The required number calculation unit 18 calculates the required number of the large-sized vehicle based on the following formula (7).
[0117]
[Number 7]

[0118]
　As shown by the formula (7), the required number calculation unit 18 requires a value obtained by dividing the amount exceeding the upper limit of the number of moving persons among the number of moving persons at each measurement position by the number of people that can accommodate a large vehicle. Calculated as the number of units.
[0119]
　The "number of people moving by car" in the formula is a statistical value of the number of people moving by car at a certain measurement position within a predetermined period. For example, the number of people moving by car in the last year may be adopted as the "number of people moving by car". In addition, as the "number of people moving by car", the number of people moving by car during the commuting time on weekdays (eg, 7:00 to 10:00) in the last year may be adopted.
[0120]
　The required number calculation unit 18 may calculate the required number for each section Pi, i + 1 described in the second embodiment . In this case, the number of moving vehicles in the formula (7) is a statistical value of the number of moving vehicles detected at the measurement points Pi and Pi + 1 . Further, the required number calculation unit 18 may calculate the required number for each integrated section in which a plurality of adjacent sections Pi and i + 1 are integrated. In this case, the required number calculation unit 18 may calculate the statistical value of the required number calculated corresponding to each of the plurality of sections Pi and i + 1 included in the integrated section as the required number in the integrated section.
[0121]
　The value of the number of people that can accommodate a large vehicle is given to the required number calculation unit 18 by any means. For example, the value may be registered in advance, or the operator may specify the value when calculating the required number of units. Further, a plurality of values ​​may be given to the required number calculation unit 18 as the value of the number of people that can accommodate a large vehicle. Then, the required number calculation unit 18 may calculate the required number by using each of the plurality of values. In this way, the required number of vehicles can be calculated for each of a plurality of large vehicles having different sizes.
[0122]
　The effect calculation unit 16 is at least one of the traffic volume, road congestion, economic loss due to congestion, and carbon dioxide emissions when the amount exceeding the upper limit of the number of people traveling by vehicle is moved by a large vehicle. Calculate one.
[0123]
　For example, the effect calculation unit 16 uses the "number of people moving by car" and "traffic volume and traffic congestion (average speed)" calculated from the past road measurement data as learning data, and "number of people moving by car" and "traffic volume and traffic congestion" When the upper limit of the number of people moving by car is entered in the estimation model obtained by machine learning the relationship with "Situation (average speed)", and the amount exceeding the upper limit of the number of people moving by car is moved by a large vehicle. Traffic volume and road congestion may be calculated.
[0124]
　Then, even if the effect calculation unit 16 calculates the amount of economic loss and carbon dioxide emissions caused by the traffic congestion based on the upper limit of the number of people moving by vehicle, the traffic volume calculated as described above, and the traffic congestion condition of the road. Good.
[0125]
　The output unit 13 outputs the calculation result by the required number calculation unit 18. The output unit 13 may further output the calculation result by the effect calculation unit 16. Other configurations of the output unit 13 are the same as those of the first to third embodiments.
[0126]
　Next, an example of the processing flow of the processing apparatus 10 of the present embodiment will be described with reference to the flowchart of FIG.
[0127]
　In S40, the data processing unit 11 calculates the traffic volume and the average number of passengers within a predetermined period based on the road measurement data. For example, as shown in FIG. 3 or FIG. 8, the data processing unit 11 can calculate the traffic volume and the average number of passengers for each of the plurality of periods. Further, as shown in FIGS. 3 and 8, the data processing unit 11 can calculate the traffic volume and the average number of passengers for each measurement position.
[0128]
　In S41, the actual condition calculation unit 12 calculates the number of vehicles moving within a predetermined period based on the result calculated in S40. For example, the actual condition calculation unit 12 can calculate the number of people moving in each of a plurality of periods. In addition, the actual condition calculation unit 12 can calculate the number of people moving by vehicle for each measurement position.
[0129]
　In S42, the reception unit 15 accepts the user input for designating the upper limit value of the number of vehicles moving within the predetermined period. For example, the reception unit 15 may accept an input for designating the upper limit of the number of people who can move in a day, or the upper limit of the number of people who can move in a predetermined time zone (eg, commuting time from 7:00 to 10:00 on weekdays). You may accept input that specifies a value. The reception unit 15 may accept the input of the upper limit value of the number of people moving by vehicle, which is applied to all the roads, or may accept the input of the upper limit value of the number of people moving by vehicle at each point (each measurement position) on the road. The execution timing of S42 is not limited to that shown, and may be executed before S40, after S40, and before S41.
[0130]
　In S43, the required number of vehicles calculation unit 18 calculates the required number of large vehicles required to move a large vehicle by the amount exceeding the upper limit of the number of vehicles moving specified in S42 among the number of vehicles moving calculated in S41. To do. The required number calculation unit 18 calculates the required number of large vehicles required to set the number of vehicles moving through each point to the upper limit of the number of vehicles moving for each point on the road (for each measurement position).
[0131]
　In S44, the output unit 13 outputs the required number of units calculated in S43. The output unit 13 may further output the calculation result of S41 and the calculation result of S40.
[0132]
　According to the processing apparatus 10 of the present embodiment described above, the same effects as those of the first to third embodiments can be realized. Further, according to the processing device 10 of the present embodiment, the number of large vehicles required for promoting the transfer of large vehicles, which is one of the measures for alleviating traffic congestion, is measured by the detection device installed on the road. It can be calculated with high accuracy based on the data. As a result, it is possible to reduce the inconvenience of preparing a large number of large vehicles in vain and running out of large vehicles.
[0133]
　Here, a modified example of the present embodiment will be described. In the above example, the required number calculation unit 18 calculated the required number of large vehicles. As a modification, the required number calculation unit 18 may replace the large vehicle with another moving body such as a ship, helicopter, airplane, or train, and calculate the required number of the moving body in the same manner as in the above example. .. That is, the required number calculation unit 18 may calculate the required number of the moving body required when the portion exceeding the upper limit value of the moving number of the car is moved by the predetermined moving body. In the modified example, the same effect is realized.
[0134]
　Hereinafter, an example of the reference form will be added.
1. 1. Based on the data generated by the detection device installed on the road, the data processing means for calculating the traffic volume, which is the number of vehicles passing through the road within a predetermined period, and the average number of passengers within the predetermined period, and the
　traffic volume. An actual condition calculation means for calculating the number of people moving on the road, which is the number of people who got on the vehicle within the predetermined period, and
　an output means for outputting the calculation result by the actual condition calculation means , based on the average number of passengers .
Processing equipment with.
2. In the processing apparatus according to 1, the
　data processing means calculates the traffic volume and the average number of passengers in each of a plurality of periods, and the
　actual condition calculation means calculates the number of people moving in each of the plurality of periods. Processing equipment.
3. 3. Based on the data generated by the detection device installed on the road, the data processing means for calculating the number of passengers of each vehicle passing through the road within a predetermined period,
　and based on the number of passengers, the vehicle gets on the vehicle within the predetermined period. A processing device having an actual condition calculation means for calculating the number of people moving by a vehicle, which is the number of people passing through the road, and
　an output means for outputting a calculation result by the actual condition calculation means
.
4. In the processing device according to 3, the
　data processing means calculates the number of passengers in each of a plurality of periods, and the
　actual condition calculation means calculates the number of people moving in each of the plurality of periods.
5. In the processing apparatus according to any one of 1 to 4, the
　data processing means analyzes the data, calculates a value indicating a traffic jam condition of the road within the predetermined period, and the
　actual condition calculation means is the traffic jam. A processing device that calculates the amount of economic loss within the predetermined period based on the value indicating the situation and the number of people moving.
6. In the processing device according to any one of 1 to 5,
　the priority of the congestion mitigation measure is determined based on the congestion condition of the road, the amount of economic loss caused by the congestion, and at least one of the carbon dioxide emissions. A processing device further comprising a priority determining means.
7. In the processing device according to any one of 1 to 6, the
　average number of passengers is averaged based on the receiving means for receiving an input for designating the target value of the average number of passengers, the
　traffic volume, the number of people moving, and the target value of the average number of passengers. A processing device further having a parking lot size calculation means for calculating the required size of the parking lot required when the target value for the number of passengers is achieved.
8. In the processing device according to 7, the
　parking lot scale calculating means is a processing device that calculates a value obtained by dividing the number of people moving by the vehicle by the target value of the average number of passengers and subtracting the value from the traffic volume as the required scale.
9. In the processing apparatus according to 7 or 8,
　at least one of the traffic volume, the road congestion situation, the economic loss due to the congestion, and the carbon dioxide emission amount when the average number of passengers target value is achieved. A processing device further having an effect calculation means for calculating one.
10. In the processing device according to any one of 1 to 9, the
　receiving means for accepting the input for designating the upper limit value of the
　number of people moving by vehicle and the portion of the number of people moving by vehicle exceeding the upper limit of the number of people moving by vehicle are used by a predetermined moving body. A processing device further comprising a required number calculation means for calculating the required number of the moving bodies required for movement.
11. In the processing apparatus according to 10, the
　required number of vehicles calculation means calculates the required number of vehicles by dividing the amount exceeding the upper limit of the number of vehicles moving by the number of people accommodated by the moving vehicle. Processing equipment.
12. In the processing apparatus according to 10 or 11, the
　traffic volume when the moving body moves a portion exceeding the upper limit value of the number of people moving by the vehicle, the traffic condition of the road, the amount of economic loss due to the traffic jam, and carbon dioxide. A processing apparatus further comprising an effect calculating means for calculating at least one of carbon emissions.
13. Computer,
　based on data that the installed detector generated in the road, and calculates the average number of passengers in traffic and in the predetermined period is a number of cars passing through the road within a predetermined period of time,
　the traffic volume and
　A processing method for calculating the number of people moving on a vehicle within the predetermined period based on the average number of passengers and passing through the road, and outputting the calculation result.
14. Computer,
　Based on the data generated by the detection device installed on the road, the data processing means for calculating the traffic volume, which is the number of vehicles passing through the road within a predetermined period, and the average number of passengers within the predetermined period, the
　traffic volume, and the traffic volume. Based on the average number of passengers
　,
it functions as an actual condition calculation means for calculating the number of people moving on the road, which is the number of people who got on the vehicle within the predetermined period, and an output means for outputting the calculation result by the actual condition calculation means . program.
15. The computer
　calculates the number of passengers of each vehicle passing through the road within a predetermined period based on the data generated by the detection device installed on the road, and based on the number of passengers
　, gets on the vehicle within the predetermined period.
　A processing method for calculating the number of people moving by vehicle, which is the number of people passing through the road, and outputting the calculation result.
16.
　A data processing means for calculating the number of passengers of each vehicle passing through the road within a predetermined period based on the data generated by the detection device installed on the road,
　and the vehicle within the predetermined period based on the number of passengers. A program that functions as an
　actual condition calculation means for calculating the number of people moving on a vehicle, which is the number of people traveling on the road, and an output means for outputting the calculation result by the actual condition calculation means
.
The scope of the claims
[Claim 1]
　Based on the data generated by the detection device installed on the road, the data processing means for calculating the traffic volume, which is the number of vehicles passing through the road within a predetermined period, and the average number of passengers within the predetermined period, and the
　traffic volume. An actual condition calculation means for calculating the number of people moving on the road, which is the number of people who got on the vehicle within the predetermined period, and
　an output means for outputting the calculation result by the actual condition calculation means , based on the average number of passengers .
Processing equipment with.
[Claim 2]
　In the processing apparatus according to claim 1, the
　data processing means calculates the traffic volume and the average number of passengers in
　each of the plurality of periods, and the actual condition calculation means calculates the number of vehicles moving in each of the plurality of periods. Processing device to calculate.
[Claim 3]
　Based on the data generated by the detection device installed on the road, the data processing means for calculating the number of passengers of each vehicle passing through the road within a predetermined period,
　and based on the number of passengers, the vehicle gets on the vehicle within the predetermined period. A processing device having an actual condition calculation means for calculating the number of people moving by a vehicle, which is the number of people passing through the road, and
　an output means for outputting a calculation result by the actual condition calculation means
.
[Claim 4]
　In the processing device according to claim 3, the
　data processing means calculates the number of passengers in each of a plurality of periods, and the
　actual condition calculation means calculates the number of people moving in each of the plurality of periods.
[Claim 5]
　In the processing apparatus according to any one of claims 1 to 4, the
　data processing means analyzes the data, calculates a value indicating a traffic congestion state of the road within the predetermined period, and calculates the
　actual condition. Is a processing device that calculates the amount of economic loss within the predetermined period based on the value indicating the traffic jam situation and the number of people moving.
[Claim 6]
　In the processing apparatus according to any one of claims 1 to 5,
　measures for alleviating traffic congestion are taken based on the traffic congestion condition of the road, the amount of economic loss caused by the traffic congestion, and at least one of carbon dioxide emissions. A processing device further comprising a priority determining means for determining a priority.
[Claim 7]
　In the processing device according to any one of claims 1 to 6, based on the
　reception means for accepting the input for designating the average number of passengers target value, the
　traffic volume, the number of vehicles moving, and the average number of passengers target value. A processing device further comprising a parking lot scale calculating means for calculating the required scale of the parking lot required when the average number of passengers target value is achieved by carpooling.
[Claim 8]
　In the processing apparatus according to claim 7, the
　parking lot scale calculation means calculates a value obtained by dividing the number of people moving by the vehicle by the target value of the average number of passengers and subtracting the value from the traffic volume as the required scale. apparatus.
[Claim 9]
　In the processing apparatus according to claim 7 or 8,
　among the traffic volume, the road congestion situation, the economic loss amount due to the congestion, and the carbon dioxide emission amount when the average number of passengers target value is achieved. A processing apparatus further comprising an effect calculating means for calculating at least one.
[Claim 10]
　In the processing device according to any one of claims 1 to 9, a
　receiving means for accepting an input for designating an upper limit value for the
　number of people moving by vehicle and a portion of the number of people moving by vehicle that exceeds the upper limit value for moving people are specified. A processing device further comprising a required number calculation means for calculating the required number of the moving bodies required when moving the moving body.
[Claim 11]
　In the processing apparatus according to claim 10, the
　required number of vehicles calculation means divides the amount exceeding the upper limit of the number of vehicles moving by the number of people accommodated by the moving body, and divides the required number of vehicles by the required number of vehicles. A processing device that calculates as.
[Claim 12]
　In the processing device according to claim 10 or 11, the
　traffic volume when the moving body moves a portion exceeding the upper limit value of the number of people moving by the vehicle, the traffic condition of the road, the amount of economic loss due to the traffic jam, and , A processing apparatus further comprising an effect calculating means for calculating at least one of carbon dioxide emissions.
[Claim 13]
　Computer,
　based on data that the installed detector generated in the road, and calculates the average number of passengers in traffic and in the predetermined period is a number of cars passing through the road within a predetermined period of time,
　the traffic volume and
　A processing method for calculating the number of people moving on a vehicle within the predetermined period based on the average number of passengers and passing through the road, and outputting the calculation result.
[Claim 14]
　The computer,
　on the basis of the data in which the installed detector were generated on the road, a number of vehicles passing through the road within a predetermined period of time traffic and data processing means for calculating the average number of passengers in the predetermined period,
　the An actual condition calculation means for calculating the number of people moving on the road, which is the number of people who got on the car within the predetermined period based on the traffic volume and the average number of passengers, and
　an output means for outputting the calculation result by the actual condition calculation means.
A program that functions as.
[Claim 15]
　The computer
　calculates the number of passengers of each vehicle passing through the road within a predetermined period based on the data generated by the detection device installed on the road, and based on the number of passengers
　, gets on the vehicle within the predetermined period.
　A processing method for calculating the number of people moving by vehicle, which is the number of people passing through the road, and outputting the calculation result.
[Claim 16]

　A data processing means for calculating the number of passengers of each vehicle passing through the road within a predetermined period based on the data generated by the detection device installed on 　the road,
　and the vehicle within the predetermined period based on the number of passengers. A program that functions as an
　actual condition calculation means for calculating the number of people moving on a vehicle, which is the number of people traveling on the road, and an output means for outputting the calculation result by the actual condition calculation means
.