Congestion situation visualization system and congestion situation visualization method

Abstract

To provide a congestion state of each delivery destination.SOLUTION: A congestion state visualization system according to an embodiment includes: a collection / reception unit which collects or receives first data containing at least one of an arrival scheduled time point to a specified position and a departure scheduled time point from the position when performing delivery by vehicle; a data creation unit which creates second data indicating a congestion state in each specified first time width at the position by using the first data; and a visualization unit which creates a graph indicating a congestion state in each specified second time width at the position by using the second data.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a congestion situation visualization system and a congestion situation visualization method. [Background technology]

[0002] Delivery companies and the like that deliver packages by trucks and the like formulate efficient delivery plans using a list of delivery destinations for packages, vehicle information, map information, etc. Here, a delivery plan is a plan on the order in which to visit each delivery destination, and in addition to the order in which the delivery destinations are to be visited, it often includes information such as the scheduled time of arrival at each destination and the scheduled time of departure from each destination.

[0003] The above-mentioned delivery plan is formulated taking into consideration the travel time between delivery destinations, the work time (or stay time) at each delivery destination, and the like. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2014-92971 A Summary of the Invention [Problem to be solved by the invention]

[0005] Incidentally, the above-mentioned working time (or staying time) is often the average working time (or staying time) at each delivery destination. However, if a delivery destination is congested, the average working time (or staying time) may be significantly exceeded, causing problems with subsequent delivery schedules. Generally, multiple delivery companies deliver to one delivery destination, so the congestion situation at each delivery destination is also affected by the delivery plans of the other delivery companies, and it is often impossible for a company to judge or predict it on its own.

[0006] An embodiment of the present invention has been made in consideration of the above points, and aims to provide the congestion status of each delivery destination. [Means for solving the problem]

[0007] In order to achieve the above-mentioned object, a congestion situation visualization system according to one embodiment includes a collection / reception unit that collects or receives, from a plurality of delivery companies, first data including at least one of an estimated time of arrival at a specified location and an estimated time of departure from the specified location when delivering by vehicle, a data creation unit that uses the first data to create second data representing the degree of congestion at the location for each specified first time span, and a visualization unit that uses the second data to create a graph representing the degree of congestion at the location for each specified second time span. Effect of the Invention

[0008] It is possible to provide information on the congestion status of each delivery destination. [Brief description of the drawings]

[0009] [Figure 1] 1 is a diagram illustrating an example of an overall configuration of a congestion situation visualization system according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a diagram illustrating an example of a hardware configuration of the congestion situation visualization device according to the present embodiment. [Diagram 3] FIG. 2 is a diagram illustrating an example of a functional configuration of the congestion situation visualization device according to the present embodiment. [Figure 4] 10 is a flowchart showing an example of the flow of a congestion status visualization process according to the present embodiment. [Diagram 5] FIG. 13 is a diagram illustrating an example of a congestion status graph. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] An embodiment of the present invention will be described below. In this embodiment, a congestion status visualization system 1 that can provide a driver with a graph or the like that visualizes the congestion status of each delivery destination when delivering luggage (goods) by a vehicle such as a truck will be described.

[0011] In this embodiment, the term "delivery" is used assuming that parcels are delivered to destinations such as collection centers and commercial facilities, but terms such as "transportation," "shipping," "transportation," and "carriage" may be used instead of "delivery." However, collection centers and commercial facilities are only examples of destinations, and destinations may also be various stores such as department stores, supermarkets, and convenience stores. In addition, this embodiment is not limited to the case of delivering parcels to each destination, but can also be applied to, for example, the case of collecting parcels from collection destinations and the case of a mixture of delivery and collection of parcels.

[0012] <Overall composition> First, the overall configuration of a congestion situation visualization system 1 according to this embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of the overall configuration of the congestion situation visualization system 1 according to this embodiment.

[0013] 1, the congestion situation visualization system 1 according to this embodiment includes a congestion situation visualization device 10 and a plurality of driver terminals 20. The congestion situation visualization device 10 and each driver terminal 20 are communicatively connected via any communication network such as the Internet.

[0014] The congestion situation visualization device 10 collects delivery plans (more precisely, data representing the delivery plans) from a plurality of delivery companies, and creates a graph (hereinafter, referred to as a "congestion situation graph") representing the congestion situation for each predetermined time period at each delivery destination using these delivery plans. Here, the congestion situation graph includes at least the congestion situation for future time periods. Typically, the congestion situation graph includes the congestion situation for each time period after the time period including the creation time of the congestion situation graph. For example, the congestion situation graph shown in FIG. 1 is created for a time period before 8:00, and represents the congestion situation for each time period for each hour after 8:00. However, the congestion situation graph may include the congestion situation for the current time period (i.e., the time period including the creation time of the congestion situation graph), or may include the congestion situation for a time period before the current time period (i.e., a past time period).

[0015] Then, the congestion situation visualization device 10 provides the congestion situation graph of each delivery destination to the driver's terminal 20. In this way, the congestion situation visualization device 10 according to the present embodiment creates a congestion situation graph of each delivery destination taking into account the delivery plans of multiple delivery companies. This allows each driver to know the congestion situation due to the influence of delivery plans of not only his / her own company but also other companies (in other words, a prediction of future congestion situation taking into account the influence of delivery plans of not only his / her own company but also other companies).

[0016] Here, each delivery company creates a delivery plan manually or by using a known delivery plan creation system using a delivery destination list, vehicle information, map information, etc. The delivery destination list is, for example, a list of delivery destination locations, designated delivery time periods, information about packages to be delivered, etc. Vehicle information is information about vehicles that are available for operation on a daily or time period basis. Map information is information necessary for the delivery plan creation system to calculate travel times between delivery destinations, and includes not only map display information but also, for example, road network information, etc.

[0017] In the example shown in Figure 1, a delivery plan creator of delivery company A manually creates a delivery plan using a delivery destination list and vehicle information, and delivery company A creates a delivery plan using a delivery plan creation system using the delivery destination list and vehicle information. The delivery plan creation system is a computer or computer system that outputs an optimal delivery plan by solving optimization problems such as a delivery optimization problem, a transportation route problem, or a vehicle routing problem (VRP).

[0018] Each delivery plan created by each delivery company includes at least the order of visiting each delivery destination, and may also include, for example, identification information of the vehicle (or driver) visiting the delivery destination, the scheduled arrival time and scheduled departure time at the delivery destination, the scheduled stay time at the delivery destination, etc. Hereinafter, unless otherwise specified, it is assumed that each delivery plan includes the order of visiting each delivery destination, identification information of the vehicle (or driver), and the scheduled arrival time and scheduled departure time at the delivery destination.

[0019] The driver's terminal 20 is a smartphone, tablet terminal, in-vehicle device, etc., used by the driver of a vehicle such as a truck. A congestion status graph of each delivery destination is displayed on the display of the driver's terminal 20 in response to the driver's operation, etc. In the example shown in FIG. 1, a congestion status graph showing the hourly congestion level of the delivery destination "X Center" is displayed on the display of the driver's terminal 20. This enables the driver to change the plan, for example, by changing the time to deliver the package, depending on the congestion status of the delivery destination during the time period when the driver is scheduled to deliver the package.

[0020] The overall configuration of the congestion situation visualization system 1 shown in Fig. 1 is an example, and other configurations may be used. For example, a terminal used by a delivery plan creator may be included in the congestion situation visualization system 1, and a congestion situation graph for each delivery destination may also be displayed on the display of this terminal. This allows the delivery plan creator to refer to the congestion situation graph for each delivery destination and re-create the delivery plan to avoid busy times.

[0021] In addition, when the terminal used by the delivery plan creator is included in the congestion situation visualization system 1, the driver terminal 20 does not need to be included in the congestion situation visualization system 1. In other words, the congestion situation graph of each delivery destination may not be provided to the driver terminal 20 but only to the terminal used by the delivery plan creator.

[0022] <Hardware configuration of the congestion situation visualization device 10> Next, a hardware configuration of the congestion situation visualization device 10 according to the present embodiment will be described with reference to Fig. 2. Fig. 2 is a diagram illustrating an example of a hardware configuration of the congestion situation visualization device 10 according to the present embodiment.

[0023] 2, the congestion situation visualization device 10 according to this embodiment is realized by the hardware of a general computer or computer system, and has an input device 11, a display device 12, an external I / F 13, a communication I / F 14, a processor 15, and a memory device 16. Each of these hardware components is connected to each other via a bus 17 so as to be able to communicate with each other.

[0024] The input device 11 is, for example, a keyboard, a mouse, a touch panel, etc. The display device 12 is, for example, a display, etc. Note that the congestion situation visualization device 10 does not necessarily have to include at least one of the input device 11 and the display device 12.

[0025] The external I / F 13 is an interface with an external device such as a recording medium 13a. Examples of the recording medium 13a include a CD (Compact Disc), a DVD (Digital Versatile Disk), an SD memory card (Secure Digital memory card), and a USB (Universal Serial Bus) memory card.

[0026] The communication I / F 14 is an interface for connecting the congestion situation visualization device 10 to a communication network. The processor 15 is, for example, various arithmetic devices such as a CPU (Central Processing Unit). The memory device 16 is, for example, various storage devices such as a HDD (Hard Disk Drive), an SSD (Solid State Drive), a RAM (Random Access Memory), a ROM (Read Only Memory), and a flash memory.

[0027] The congestion situation visualization device 10 according to the present embodiment can realize a congestion situation visualization process described below by having the hardware configuration shown in Fig. 2. Note that the hardware configuration shown in Fig. 2 is an example, and the congestion situation visualization device 10 may have other hardware configurations. For example, the congestion situation visualization device 10 may have multiple processors 15 and multiple memory devices 16.

[0028] <Functional configuration of the congestion situation visualization device 10> Next, a functional configuration of the congestion situation visualization device 10 according to the present embodiment will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of the functional configuration of the congestion situation visualization device 10 according to the present embodiment.

[0029] 3, the congestion situation visualization device 10 according to the present embodiment has, as functional units, a delivery plan collection unit 101, a congestion statistics unit 102, and a visualization unit 103. Each of these functional units is realized, for example, by a process executed by a processor 15 of one or more programs installed in the congestion situation visualization device 10.

[0030] The delivery plan collection unit 101 collects data representing delivery plans (hereinafter referred to as "delivery plan data") from multiple delivery companies. That is, the delivery plan collection unit 101 collects, for example, delivery plan data of delivery company A, delivery plan data of delivery company B, delivery plan data of delivery company C, etc. In this way, the delivery plan collection unit 101 collects delivery plan data of multiple delivery companies.

[0031] The method for collecting the delivery plan data does not matter, and the delivery plan collection unit 101 may collect the delivery plan data by any method. For example, the delivery plan data may be uploaded from a terminal of a delivery plan creator to the congestion situation visualization device 10, or the delivery plan data may be transmitted from a delivery plan creation system to the congestion situation visualization device 10.

[0032] The congestion statistics unit 102 creates statistical data representing the degree of congestion for each predetermined time period at each delivery destination, using a plurality of delivery plan data collected by the delivery plan collection unit 101. The congestion statistics unit 102 may create any statistical data as long as it represents the degree of congestion for each predetermined time period at each delivery destination, but for example, it is considered to create the statistical data by any of the following methods (1) to (3).

[0033] (1) For each delivery destination and each time period, the number of vehicles scheduled to deliver cargo to that destination during that time period is tallied, and the result of the talliation is used as statistical data for that delivery destination.

[0034] Specifically, for example, a predetermined time period is an hourly time period (8:00-9:00, 9:00-10:00, 10:00-11:00, ..., 18:00-19:00, 19:00-20:00, etc.), and delivery plan data of delivery company A includes a plan for a certain vehicle to deliver a parcel to center X at 10:15, delivery plan data of delivery company B includes a plan for a certain vehicle to deliver a parcel to center X at 10:20, and delivery plan data of delivery company C includes a plan for a certain vehicle to deliver a parcel to center X at 10:05. In this case, the number of vehicles at center X in the 10:00-11:00 time period is "3".

[0035] In this way, in method (1), the number of vehicles scheduled to visit each delivery destination in each time period is tallied for each delivery destination. This allows statistical data consisting of the number of vehicles scheduled to visit each delivery destination in each time period to be created for each delivery destination. In other words, if the delivery destination index is i, the time period index is t (where t=1, . . . , T), and the number of vehicles scheduled to visit delivery destination i in time period t is a i,t Then, the statistical data for delivery destination i is a T-dimensional vector (a i,1 ,···,a i,T )

[0036] In order to create statistical data that represents a sufficiently accurate congestion degree, the method (1) requires collection of delivery plan data from a sufficient number of delivery companies. For this reason, for example, when delivery plan data can only be collected from a small number of delivery companies or when statistical data is to be created at the stage of collecting delivery plan data from a small number of delivery companies, a predetermined prediction model or the like may be used to predict delivery plan data of uncollected delivery companies, and then statistical data may be created. As an example of such a prediction model, a model that predicts future delivery plans from the past delivery performance of uncollected delivery companies may be considered. In addition to using a prediction model, for example, past delivery plan data of uncollected delivery companies (particularly, delivery plan data under the same or similar conditions (conditions such as day of the week, month, weather, etc.)) may be used to create statistical data, or statistical data created from delivery plan data of collected delivery companies may be corrected (for example, when the total number of delivery companies to be collected is 10 and the number of collected delivery companies is 5, each value included in the statistical data may be doubled). This makes it possible to improve the accuracy of the congestion degree represented by the statistical data even if delivery plan data is not collected from a sufficient number of delivery companies.

[0037] (2) If the aggregated result obtained in (1) above exceeds a certain threshold, the aggregated results for the time period following that aggregated result are corrected by a certain specified function value and used as the statistical data for the delivery destination.

[0038] That is, for example, a predetermined threshold value σ i As a i,t ≧σ i If a i,t+1 ~a i,T For the function value f(a i,t ,t+1)~f(a i,t ,T) are added together. In other words, the statistical data for destination i is added together with (a i,1 ,···,a i,t ,a i,t+1 +f(a i,t ,t+1),···,a i,T +f(a i,t ,T) where function f(a i,t ,s) is, for example, ri is a positive constant determined for each delivery destination i, and a i,t ≧s×r i When f(a i,t ,s)=a i,t -(st)×r i Then, x <s×r i When f(a i,t It is possible to use a function such that s = 0.

[0039] For example, the congestion level (number of vehicles) a during a certain time period t i,t is the threshold σ i If it is higher than t, for example, queues and work delays may occur, and congestion will not be resolved even after time slot t, meaning that the congestion level after time slot t will also increase. i represents the number of vehicles departing from destination i per time slot.

[0040] (3) Using a machine learning model that has been created in advance using machine learning techniques, delivery plan data is input into this machine learning model, and statistical data for each delivery destination is obtained as the output.

[0041] Such a machine learning model may be created, for example, by a known method such as supervised learning using the actual congestion level (number of vehicles) for each time period collected at each delivery destination and the delivery plan data at that time as learning data. Note that the learning data may include information indicating various conditions such as the day of the week and weather. For this reason, it is expected that the use of the machine learning model will make it possible to predict the congestion level with high accuracy under various conditions.

[0042] The visualization unit 103 uses the statistical data created by the congestion statistics unit 102 to create a congestion status graph that shows the congestion status for each specified time period at each delivery destination. That is, the visualization unit 103 uses the statistical data for each delivery destination to create, for example, a bar graph for each delivery destination with the time period on the horizontal axis and the congestion level on the vertical axis, and this bar graph is used as the congestion status graph. However, the congestion status graph is not limited to a bar graph, and may be created as any type of graph, such as a line graph.

[0043] The time span of the time period represented by the congestion degree included in the statistical data and the time span of the time period represented by the congestion degree included in the congestion status graph do not necessarily have to be the same time span. For example, while the statistical data includes the congestion degree for every 30 minutes, the congestion status graph may graph the congestion degree for every hour.

[0044] Furthermore, for example, in response to a request from the driver's terminal 20, the visualization unit 103 transmits a congestion status graph for each delivery destination to the driver's terminal 20. As a result, the congestion status graph for each delivery destination is displayed on the display of the driver's terminal 20.

[0045] <Flow of congestion visualization process> Next, a flow of the congestion situation visualization process according to this embodiment will be described with reference to Fig. 4. Fig. 4 is a flowchart showing an example of the flow of the congestion situation visualization process according to this embodiment.

[0046] First, the delivery plan collection unit 101 collects a plurality of delivery plan data from a plurality of delivery companies (step S101).

[0047] Next, the congestion statistics unit 102 uses the delivery plan data collected in the above step S101 to create statistical data indicating the degree of congestion for each predetermined time period at each delivery destination (step S102). As described above, the congestion statistics unit 102 may create statistical data for each delivery destination by any one of the above methods (1) to (3).

[0048] Here, the delivery plan data collected in the above step S101 may include delivery plan data that does not include some information. That is, for example, there may be delivery plan data that does not include all or part of the estimated arrival time, estimated departure time, and estimated stay time at each delivery destination. In this case, the congestion statistics unit 102 may calculate and estimate the travel time between each delivery destination and the time to load and unload luggage at each delivery destination based on map information, past performance, a predetermined set value, etc., and may create the above statistical data by estimating the estimated arrival time, estimated departure time, and estimated stay time from the results. Note that, for example, even if the estimated arrival time, estimated departure time, and estimated stay time at each delivery destination are included in the delivery plan data, the congestion statistics unit 102 may create the above statistical data using the estimated estimated arrival time, estimated departure time, and estimated stay time as described above.

[0049] Next, the visualization unit 103 creates a congestion status graph for each delivery destination using the statistical data for each delivery destination created in step S102 above (step S103).

[0050] Then, the visualization unit 103 transmits the congestion status graph of each delivery destination to the driver's terminal 20 in response to a request from the driver's terminal 20 (step S104). As a result, the congestion status graph of each delivery destination is displayed on the display of the driver's terminal 20. Here, an example of the congestion status graph displayed on the display of the driver's terminal 20 is shown in FIG. 5. The example shown in FIG. 5 is a congestion status graph 210 showing the congestion degree of the delivery destination "Y Center" every hour. At this time, a particularly congested time period (for example, a time period with the highest congestion degree, a time period with a congestion degree exceeding a certain threshold, etc.) may be displayed in a prominent manner. In the congestion status graph 210 shown in FIG. 5, the time period from 15:00 to 16:00 is particularly congested, and is displayed in a prominent manner compared to other time periods.

[0051] As described above, the congestion status visualization system 1 according to this embodiment can visualize the congestion status of each delivery destination using the delivery plans of multiple delivery companies and provide it to the driver. This allows each driver to know the congestion status taking into account not only his / her own company's congestion status but also the delivery plans of other companies. This allows each driver to take action such as reviewing his / her delivery plan depending on the congestion status.

[0052] <Application Examples> An application example of this embodiment will be described below.

[0053] <Application example 1> The congestion status graph or statistical data created by the congestion status visualization device 10 according to the present embodiment may be fed back to the delivery plan creation system, and the delivery plan may be recreated in the delivery plan creation system. In addition, this feedback and the recreation of the delivery plan may be repeated, for example, until the delivery plan is optimized.

[0054] <Application example 2> The congestion visualization device 10 according to the present embodiment may visualize the congestion status of a specific facility, a specific point, a specific region, etc., instead of the "delivery destination." Specifically, the congestion status of a point on a road, such as a specific intersection, or a facility, such as a toll booth, may be visualized. Also, the congestion status of a point or region that a vehicle is expected to pass through when moving to the delivery destination may be visualized. Note that a region refers to a geographical range with a certain degree of spread, and a specific example is a range such as "XX 3-chome, XX ward, Tokyo."

[0055] <Application example 3> Instead of a delivery plan, the congestion situation visualization device 10 according to the present embodiment may visualize the congestion situation at each tourist spot by using, for example, a travel schedule, etc. Similarly, the congestion situation visualization device 10 according to the present embodiment may visualize the congestion situation at each business destination or at a destination for regular maintenance by using, for example, a business visit plan for sales or a regular maintenance tour plan for equipment.

[0056] The present invention is not limited to the above-described embodiments specifically disclosed, and various modifications, changes, combinations with known technologies, etc. are possible without departing from the scope of the claims. [Explanation of symbols]

[0057] 1. Congestion visualization system 10. Congestion visualization device 11 Input Devices 12 Display device 13 External I / F 13a Recording media 14 Communication I / F 15 Processors 16 Memory Devices 17 Bus 101 Delivery Plan Collection Department 102 Congestion Statistics Department 103 Visualization section

Claims

1. a collection and reception unit that collects or receives first data from a plurality of delivery companies, the first data including at least one of a scheduled arrival time at a predetermined location and a scheduled departure time from the location when delivering by a vehicle; a data creation unit that uses the first data to create second data representing a congestion degree at the location for each predetermined first time span; a visualization unit that uses the second data to create a graph showing a congestion degree at the location for each predetermined second time span; A congestion situation visualization system with

2. The visualization unit is The congestion situation visualization system according to claim 1 , wherein the graph is displayed on at least one of a terminal used by a driver of the vehicle and a terminal used by a creator who creates the first data.

3. a transmission unit that transmits the second data or the graph to a system that creates the first data; The collection and reception unit includes: The congestion situation visualization system according to claim 1 or 2, further comprising: collecting or receiving first data that is regenerated by the system based on the second data or the graph.

4. The data creation unit is tallying up the number of vehicles delivering to the location at a time included in the first time span for each of the location and the first time span; The congestion situation visualization system according to claim 1 , wherein the second data is generated by taking a result of the aggregation as a congestion degree for the first time range at the location.

5. The data creation unit is 5. The congestion situation visualization system of claim 4, wherein, when the result of the aggregation exceeds a predetermined threshold, the second data is created by correcting the congestion degree of a first time range after the first time range that was the subject of the aggregation using a predetermined function.

6. the function is a function for calculating the number of vehicles whose delivery has not been completed even after the first time span that is the subject of the counting, The data creation unit is 6. The congestion situation visualization system according to claim 5, wherein the second data is created by adding a value of the function to the congestion degree of a first time range after the first time range that was the subject of the aggregation.

7. The data creation unit 4. The congestion status visualization system according to claim 1, wherein the second data is created from the first data collected or received by the collection / reception unit using a model that learns the relationship between the first data and the congestion degree for each of the first time span using machine learning technology.

8. a collection / reception step of collecting or receiving, from a plurality of delivery companies, first data including at least one of a scheduled time of arrival at a predetermined location and a scheduled time of departure from the location when delivering by a vehicle; a data creation step of creating second data representing a congestion degree at the location for each predetermined first time span using the first data; a visualization step of creating a graph showing a congestion degree at the location for each predetermined second time span using the second data; A congestion situation visualization method implemented by a computer.

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