WO2021106475A1 - Congestion predicting system, taxi meter, and server device - Google Patents
Congestion predicting system, taxi meter, and server device Download PDFInfo
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- WO2021106475A1 WO2021106475A1 PCT/JP2020/040398 JP2020040398W WO2021106475A1 WO 2021106475 A1 WO2021106475 A1 WO 2021106475A1 JP 2020040398 W JP2020040398 W JP 2020040398W WO 2021106475 A1 WO2021106475 A1 WO 2021106475A1
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07B—TICKET-ISSUING APPARATUS; FARE-REGISTERING APPARATUS; FRANKING APPARATUS
- G07B13/00—Taximeters
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
Definitions
- the present invention relates to a traffic jam prediction system, a taximeter and a server device for predicting traffic jams on a road.
- Patent Document 1 a traffic jam prediction device for predicting traffic jams on an expressway based on information from such a traffic counter.
- this device has a problem that it can only predict traffic congestion in a limited area such as an expressway equipped with a traffic counter.
- the present invention has been made in view of the above circumstances, and an object of the present invention is to provide a traffic jam prediction system, a taximeter, and a server device capable of predicting traffic jams in a wide range.
- the traffic jam prediction system, the taximeter and the server device according to the present invention are characterized by the following [1] to [4].
- the taximeter transmits fare information indicating that each time the hourly fare calculating means adds the fare, and position information indicating the position when the hourly fare calculating means adds the fare.
- the server device predicts road congestion based on the received fare information and the location information. Being a traffic jam prediction system.
- the server device The current traffic congestion situation of the predetermined area predicted based on the received fare information and the location information, At least one or more information of facility information in the predetermined area, parking vacancy information in the predetermined area, weather information in the predetermined area, and event information in the predetermined area. Predict future road congestion ahead of the present based on Being a traffic jam prediction system.
- a taximeter having a distance-based fare calculation means for adding a fare each time a predetermined distance is traveled and a time-based fare calculation means for adding a fare each time a predetermined time is traveled at a predetermined speed or less.
- Each time the hourly fare calculating means adds the fare the fare information indicating that fact and the position information indicating the position when the hourly fare calculating means adds the fare are transmitted.
- the fare information indicating the addition of the fare by the hourly fare calculation means and the position information when the fare is added. Predict road congestion based on. As a result, it is possible to predict the traffic congestion on the road on which the taxi has passed, and it is possible to predict the traffic congestion in a wide range.
- road congestion is predicted based on at least one or more information of fare information, facility information, parking vacancy information, weather information, and event information. As a result, it is possible to predict road congestion more accurately.
- the present invention it is possible to provide a traffic jam prediction system and a server device capable of predicting traffic jam in a wide range.
- FIG. 1 is a diagram showing an embodiment of the traffic congestion prediction system of the present invention.
- FIG. 2 is an electrical configuration diagram of the taximeter shown in FIG.
- FIG. 3 is an electrical configuration diagram of the server device shown in FIG.
- FIG. 4 is a functional block diagram of the control unit of the server device shown in FIG.
- FIG. 1 is a block diagram showing an embodiment of the traffic congestion prediction system 1 of the present invention.
- the traffic jam prediction system 1 is provided with a taximeter 2 mounted on a vehicle, a server device 3 that communicates with the taximeter 2 to predict road congestion, and a traffic jam prediction by the server device 3.
- the user terminal 4 and the user terminal 4 are provided.
- the taximeter 2 and the server device 3 can communicate with each other via the Internet communication network 6.
- the server device 3 and the user terminal 4 can communicate with each other via the Internet communication network 6.
- the taximeter 2 is mounted on the taxi vehicle 5 and calculates the fare.
- the taximeter 2 is owned by the taxi company. As shown in FIG. 2, the taximeter 2 includes an operation unit 21, an input unit 22, a communication unit 23, a GPS receiving unit 24, and a control unit 25.
- the operation unit 21 is composed of various buttons such as an empty car button, an actual car button, and a payment button.
- the operation unit 21 allows the taxi driver to input the state of the taxi vehicle 5 (whether it is an empty vehicle on which the customer is not on board, an actual vehicle on which the customer is on board, or a payment that has arrived at the destination and is being paid). It is the operation part of.
- the input unit 22 is connected to the travel sensor 7, and a travel pulse from the travel sensor 7 is input.
- the travel sensor 7 outputs one pulse of travel pulse each time the taxi vehicle 5 travels a predetermined distance.
- the communication unit 23 is composed of a circuit, an antenna, and the like for wirelessly connecting to the Internet communication network 6.
- the GPS receiving unit 24 receives radio waves transmitted from a plurality of GPS (Global Positioning System) satellites, obtains a current position, and outputs the current position to a control unit 25 described later.
- GPS Global Positioning System
- the control unit 25 is composed of a CPU (Central Processing Unit) having a memory such as a RAM (Random Access Memory) or a ROM (Read Only Memory), and controls the entire taxi meter 2.
- the control unit 25 performs a fare calculation process when the actual vehicle button is pressed. In this fare calculation process, the control unit 25 functions as a distance-based fare calculation means and an hour-based fare calculation means, adds a distance fare each time the vehicle travels a predetermined distance, and makes the taxi vehicle 5 stand by due to congestion or customer convenience.
- the hourly fare is also added every time the vehicle travels at a predetermined speed (for example, 10 km / h) or less for a predetermined time (for example, 90 seconds).
- the control unit 25 determines whether or not the vehicle has traveled a predetermined distance by counting the travel pulses, obtains the travel speed, and determines whether or not the vehicle travels at a predetermined speed or less.
- control unit 25 transmits the fare information indicating that fact every time the distance fare is added and the position information indicating the current position fetched from the GPS receiving unit 24 at that time to the server device 3.
- the server device 3 is owned by the information provider that operates the traffic jam prediction system 1. As shown in FIG. 3, the server device 3 has a communication unit 31, a database (hereinafter, DB) 32, and a control unit 33.
- the communication unit 31 is composed of a circuit or the like for connecting to the Internet communication network 6.
- the DB 32 stores the fare information and the position information transmitted from the taximeter 2 mounted on each of the plurality of taxi vehicles 5.
- the control unit 33 is composed of a CPU having a memory such as a RAM or a ROM, and controls the entire server device 3.
- the user terminal 4 is a terminal owned by the user.
- the user terminal 4 includes a CPU having memories such as RAM and ROM, a display unit, and an operation unit (not shown).
- the user terminal 4 may be composed of a tablet terminal such as a smartphone, or may be composed of an in-vehicle terminal such as a navigation device mounted on the vehicle 5.
- the user terminal 4 can access the DB 32 of the server device 3 via the Internet communication network 6.
- the control unit 25 of the taximeter 2 calculates the fare as described above when the actual vehicle button of the operation unit 21 is operated. Further, the control unit 25 transmits the fare information and the position information when the hourly fare is added to the server device 3 every time the hourly fare is added.
- the server device 3 receives the fare information and the location information, it predicts that the traffic jam is currently present at the position indicated by the received location information, and stores the result in the DB 32 as the traffic jam prediction information.
- the server device 3 collects the fare information and the position information at that time from the plurality of taximeters 2 and stores them in the DB 32. Then, even if the server device 3 receives fare information continuously for a predetermined number of times or more within a certain period from a predetermined number or more of taxi vehicles 5 traveling in the same area, it predicts that the vehicle is congested. Good.
- the server device 3 predicts the current traffic congestion situation of the road from the fare information of the taximeter 2, and based on the predicted current traffic jam situation, for example, 30 minutes later and 1 hour later than the present. You may predict future congestion in the area. Now, the case where you want to predict the traffic congestion in a predetermined area will be described. As described above, the server device 3 predicts that the vehicle is congested if it receives the fare information from the taxi vehicle 5 traveling in the predetermined area, and if it does not receive the fare information, it is said that the server device 3 is not congested. Predict.
- the server device 3 has large facility information (number, size, etc.) in the predetermined area, parking vacancy information in the predetermined area, weather information in the predetermined area, and event information in the predetermined area. Get (event scale, number of visitors, etc.). Then, the server device 3 predicts the future traffic jam based on the current traffic jam situation in the predicted predetermined area, the acquired large-scale facility information, the parking vacancy information, the weather information, and the event information.
- the presence or absence of the current traffic jam predicted from the fare information, large facility information, parking vacancy information, weather information, and event information are input, and 30 minutes and 1 hour later.
- a classifier 33A such as a neural network that outputs the magnitude of the traffic jam.
- the classifier 33A is machine-learned using known inputs and known outputs as teacher data. These teacher data are information acquired in the past all over the country.
- the user terminal 4 can access the DB 32 in which the above-mentioned traffic jam prediction information is stored, and can acquire the current traffic jam situation in various parts of the country, and future traffic jam information such as 30 minutes and 1 hour later.
- the server device 3 predicts the traffic congestion on the road based on the fare information indicating the addition of the hourly fare and the position information at that time. As a result, it is possible to predict the traffic congestion on the road on which the taxi has passed, and it is possible to predict the traffic congestion in a wide range.
- the server device 3 predicts road congestion based on the current congestion information, facility information, parking availability information, weather information, and event information. As a result, it is possible to predict road congestion more accurately.
- the present invention is not limited to the above-described embodiment, and can be appropriately modified, improved, and the like.
- the material, shape, dimensions, number, arrangement location, etc. of each component in the above-described embodiment are arbitrary and are not limited as long as the present invention can be achieved.
- the server device 3 predicted not only the current traffic jam situation predicted from the fare information but also the future traffic jam, but the present invention is not limited to this. Only the current traffic jam may be predicted from the fare information.
- the server device 3 predicts future traffic congestion by using the classifier 33A composed of a neural network or the like, but the present invention is not limited to this. It is not essential to use the classifier 33A.
- a taximeter (2) having a distance-based fare calculation means (25) that adds a fare each time the vehicle travels a predetermined distance, and a time-based fare calculation means (25) that adds a fare each time the vehicle travels at a predetermined speed or less for a predetermined time.
- a server device (3) that predicts traffic congestion on the road by communicating with the taximeter (2), and a traffic congestion prediction system (1).
- the taximeter (2) has fare information indicating that each time the hourly fare calculating means (25) adds the fare, and when the hourly fare calculating means (25) adds the fare.
- the position information indicating the position and the position information are transmitted,
- the server device (3) predicts road congestion based on the received fare information and the location information.
- Congestion prediction system (1) [2] In the traffic jam prediction system (1) described in [1], The server device (3) The current traffic congestion situation of the predetermined area predicted based on the received fare information and the location information, At least one or more information of facility information in the predetermined area, parking vacancy information in the predetermined area, weather information in the predetermined area, and event information in the predetermined area. Predict future road congestion ahead of the present based on Congestion prediction system (1).
- a taximeter (2) having a distance-based fare calculation means (25) that adds a fare each time the vehicle travels a predetermined distance, and a time-based fare calculation means (25) that adds a fare each time the vehicle travels at a predetermined speed or less for a predetermined time.
- the fare information indicating that each time the time-based fare calculating means (25) adds the fare, and the position information indicating the position when the time-based fare calculating means (25) adds the fare.
- Send Taximeter (2).
- the present invention it is possible to provide a traffic jam prediction system and a server that can predict traffic jams in a wide range.
- the present invention that exhibits this effect is useful for a traffic jam prediction system and a server device.
- Congestion prediction system 1 Congestion prediction system 2 Taximeter 3 Server device 25 Control unit (distance-based fare calculation means, time-based fare calculation means)
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Abstract
A taxi meter (2) adds a distance fare each time a prescribed distance is traveled, and adds a time fare for each prescribed time traveled at or below a prescribed speed. Each time the time fare is added, the taxi meter (2) transmits fare information indicating the same, and position information indicating the position at that time. A server device (3) predicts road congestion on the basis of the received fare information and position information.
Description
本発明は、道路の渋滞を予測する渋滞予測システム、タクシーメータおよびサーバ装置、に関する。
The present invention relates to a traffic jam prediction system, a taximeter and a server device for predicting traffic jams on a road.
従来、地磁気の変化を利用することにより車両の通過を監視するトラフィックカウンタが高速道路の路面に設けられている。また、このようなトラフィックカウンタからの情報に基づいて、高速道路における渋滞を予測する渋滞予測装置についても提案されている（特許文献１）。
Conventionally, a traffic counter that monitors the passage of vehicles by using changes in the geomagnetism is provided on the road surface of the expressway. Further, a traffic jam prediction device for predicting traffic jams on an expressway based on information from such a traffic counter has also been proposed (Patent Document 1).
しかしながら、この装置では、トラフィックカウンタが設けられている高速道路、という限られたエリアの渋滞しか予測できない、という問題があった。
However, this device has a problem that it can only predict traffic congestion in a limited area such as an expressway equipped with a traffic counter.
本発明は、上述した事情に鑑みてなされたものであり、その目的は、広範囲に渋滞予測することができる渋滞予測システム、タクシーメータおよびサーバ装置を提供することにある。
The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a traffic jam prediction system, a taximeter, and a server device capable of predicting traffic jams in a wide range.
前述した目的を達成するために、本発明に係る渋滞予測システム、タクシーメータおよびサーバ装置は、下記［１］～［４］を特徴としている。
［１］
所定距離走行する毎に運賃を加算する距離制運賃算出手段と、所定速度以下で所定時間走行する毎に運賃を加算する時間制運賃算出手段と、を有するタクシーメータと、前記タクシーメータとの通信によって道路の渋滞を予測するサーバ装置と、を備えた渋滞予測システムであって、
前記タクシーメータは、前記時間制運賃算出手段が前記運賃を加算する毎にその旨を示す運賃情報と、前記時間制運賃算出手段が前記運賃を加算したときの位置を示す位置情報と、を送信し、
前記サーバ装置は、受信した前記運賃情報と前記位置情報とに基づいて道路の渋滞を予測する、
渋滞予測システムであること。
［２］
［１］に記載の渋滞予測システムにおいて、
前記サーバ装置が、
受信した前記運賃情報および前記位置情報に基づいて予測した所定エリアの現在の渋滞状況と、
前記所定エリア内の施設情報、前記所定エリア内のパーキングの空き情報、前記所定エリア内の気象情報、前記所定エリア内のイベント情報、の少なくとも１以上の情報と、
に基づいて現在よりも先の未来の道路の渋滞を予測する、
渋滞予測システムであること。
［３］
所定距離走行する毎に運賃を加算する距離制運賃算出手段と、所定速度以下で所定時間走行する毎に運賃を加算する時間制運賃算出手段と、を有するタクシーメータであって、
前記時間制運賃算出手段が前記運賃を加算する毎にその旨を示す運賃情報と、前記時間制運賃算出手段が前記運賃を加算したときの位置を示す位置情報と、を送信する、
タクシーメータであること。
［４］
タクシーメータから所定速度以下で所定時間走行して運賃を加算した旨を示す運賃情報と、前記運賃を加算したときの位置を示す位置情報と、を受信するサーバ装置であって、
受信した前記運賃情報および前記位置情報に基づいて道路の渋滞を予測する、
サーバ装置であること。 In order to achieve the above-mentioned object, the traffic jam prediction system, the taximeter and the server device according to the present invention are characterized by the following [1] to [4].
[1]
Communication between a taximeter and a taximeter having a distance-based fare calculation means that adds a fare each time a predetermined distance is traveled and a time-based fare calculation means that adds a fare each time a predetermined time is traveled at a predetermined speed or less. It is a traffic jam prediction system equipped with a server device that predicts traffic jams on the road.
The taximeter transmits fare information indicating that each time the hourly fare calculating means adds the fare, and position information indicating the position when the hourly fare calculating means adds the fare. And
The server device predicts road congestion based on the received fare information and the location information.
Being a traffic jam prediction system.
[2]
In the traffic congestion prediction system described in [1],
The server device
The current traffic congestion situation of the predetermined area predicted based on the received fare information and the location information,
At least one or more information of facility information in the predetermined area, parking vacancy information in the predetermined area, weather information in the predetermined area, and event information in the predetermined area.
Predict future road congestion ahead of the present based on
Being a traffic jam prediction system.
[3]
A taximeter having a distance-based fare calculation means for adding a fare each time a predetermined distance is traveled and a time-based fare calculation means for adding a fare each time a predetermined time is traveled at a predetermined speed or less.
Each time the hourly fare calculating means adds the fare, the fare information indicating that fact and the position information indicating the position when the hourly fare calculating means adds the fare are transmitted.
Being a taximeter.
[4]
It is a server device that receives fare information indicating that the fare has been added after traveling at a predetermined speed or less for a predetermined time from the taximeter and position information indicating the position when the fare is added.
Predict road congestion based on the received fare information and location information,
Must be a server device.
［１］
所定距離走行する毎に運賃を加算する距離制運賃算出手段と、所定速度以下で所定時間走行する毎に運賃を加算する時間制運賃算出手段と、を有するタクシーメータと、前記タクシーメータとの通信によって道路の渋滞を予測するサーバ装置と、を備えた渋滞予測システムであって、
前記タクシーメータは、前記時間制運賃算出手段が前記運賃を加算する毎にその旨を示す運賃情報と、前記時間制運賃算出手段が前記運賃を加算したときの位置を示す位置情報と、を送信し、
前記サーバ装置は、受信した前記運賃情報と前記位置情報とに基づいて道路の渋滞を予測する、
渋滞予測システムであること。
［２］
［１］に記載の渋滞予測システムにおいて、
前記サーバ装置が、
受信した前記運賃情報および前記位置情報に基づいて予測した所定エリアの現在の渋滞状況と、
前記所定エリア内の施設情報、前記所定エリア内のパーキングの空き情報、前記所定エリア内の気象情報、前記所定エリア内のイベント情報、の少なくとも１以上の情報と、
に基づいて現在よりも先の未来の道路の渋滞を予測する、
渋滞予測システムであること。
［３］
所定距離走行する毎に運賃を加算する距離制運賃算出手段と、所定速度以下で所定時間走行する毎に運賃を加算する時間制運賃算出手段と、を有するタクシーメータであって、
前記時間制運賃算出手段が前記運賃を加算する毎にその旨を示す運賃情報と、前記時間制運賃算出手段が前記運賃を加算したときの位置を示す位置情報と、を送信する、
タクシーメータであること。
［４］
タクシーメータから所定速度以下で所定時間走行して運賃を加算した旨を示す運賃情報と、前記運賃を加算したときの位置を示す位置情報と、を受信するサーバ装置であって、
受信した前記運賃情報および前記位置情報に基づいて道路の渋滞を予測する、
サーバ装置であること。 In order to achieve the above-mentioned object, the traffic jam prediction system, the taximeter and the server device according to the present invention are characterized by the following [1] to [4].
[1]
Communication between a taximeter and a taximeter having a distance-based fare calculation means that adds a fare each time a predetermined distance is traveled and a time-based fare calculation means that adds a fare each time a predetermined time is traveled at a predetermined speed or less. It is a traffic jam prediction system equipped with a server device that predicts traffic jams on the road.
The taximeter transmits fare information indicating that each time the hourly fare calculating means adds the fare, and position information indicating the position when the hourly fare calculating means adds the fare. And
The server device predicts road congestion based on the received fare information and the location information.
Being a traffic jam prediction system.
[2]
In the traffic congestion prediction system described in [1],
The server device
The current traffic congestion situation of the predetermined area predicted based on the received fare information and the location information,
At least one or more information of facility information in the predetermined area, parking vacancy information in the predetermined area, weather information in the predetermined area, and event information in the predetermined area.
Predict future road congestion ahead of the present based on
Being a traffic jam prediction system.
[3]
A taximeter having a distance-based fare calculation means for adding a fare each time a predetermined distance is traveled and a time-based fare calculation means for adding a fare each time a predetermined time is traveled at a predetermined speed or less.
Each time the hourly fare calculating means adds the fare, the fare information indicating that fact and the position information indicating the position when the hourly fare calculating means adds the fare are transmitted.
Being a taximeter.
[4]
It is a server device that receives fare information indicating that the fare has been added after traveling at a predetermined speed or less for a predetermined time from the taximeter and position information indicating the position when the fare is added.
Predict road congestion based on the received fare information and location information,
Must be a server device.
上記［１］、［３］および「４」の構成の渋滞予測システム、タクシーメータおよびサーバ装置によれば、時間制運賃算出手段による運賃の加算を示す運賃情報及び運賃を加算したときの位置情報に基づいて道路の渋滞を予測する。これにより、タクシーが通行した道路の渋滞を予測することができ、広範囲に渋滞予測をすることができる。
上記［２］の構成の渋滞予測システムによれば、運賃情報と、施設情報、パーキングの空き情報、気象情報、イベント情報、の少なくとも１以上の情報と、に基づいて道路の渋滞を予測する。これにより、より精度よく、道路の渋滞を予測することができる。 According to the traffic jam prediction system, the taximeter, and the server device having the above [1], [3], and "4" configurations, the fare information indicating the addition of the fare by the hourly fare calculation means and the position information when the fare is added. Predict road congestion based on. As a result, it is possible to predict the traffic congestion on the road on which the taxi has passed, and it is possible to predict the traffic congestion in a wide range.
According to the traffic congestion prediction system configured in [2] above, road congestion is predicted based on at least one or more information of fare information, facility information, parking vacancy information, weather information, and event information. As a result, it is possible to predict road congestion more accurately.
上記［２］の構成の渋滞予測システムによれば、運賃情報と、施設情報、パーキングの空き情報、気象情報、イベント情報、の少なくとも１以上の情報と、に基づいて道路の渋滞を予測する。これにより、より精度よく、道路の渋滞を予測することができる。 According to the traffic jam prediction system, the taximeter, and the server device having the above [1], [3], and "4" configurations, the fare information indicating the addition of the fare by the hourly fare calculation means and the position information when the fare is added. Predict road congestion based on. As a result, it is possible to predict the traffic congestion on the road on which the taxi has passed, and it is possible to predict the traffic congestion in a wide range.
According to the traffic congestion prediction system configured in [2] above, road congestion is predicted based on at least one or more information of fare information, facility information, parking vacancy information, weather information, and event information. As a result, it is possible to predict road congestion more accurately.
本発明によれば、広範囲に渋滞を予測することができる渋滞予測システムおよびサーバ装置を提供することができる。
According to the present invention, it is possible to provide a traffic jam prediction system and a server device capable of predicting traffic jam in a wide range.
以上、本発明について簡潔に説明した。更に、以下に説明される発明を実施するための形態（以下、「実施形態」という。）を添付の図面を参照して通読することにより、本発明の詳細は更に明確化されるであろう。
The present invention has been briefly described above. Further, the details of the present invention will be further clarified by reading through the embodiments described below (hereinafter referred to as "embodiments") with reference to the accompanying drawings. ..
本発明に関する具体的な実施形態について、各図を参照しながら以下に説明する。
Specific embodiments of the present invention will be described below with reference to each figure.
図１は、本発明の渋滞予測システム１の一実施形態を示すブロック図である。同図に示すように、渋滞予測システム１は、車両に搭載されたタクシーメータ２と、タクシーメータ２と通信を行い道路の渋滞を予測するサーバ装置３と、サーバ装置３による渋滞予測が提供されるユーザ端末４と、を備えている。タクシーメータ２とサーバ装置３とは、インターネット通信網６を介して通信可能である。サーバ装置３とユーザ端末４とは、インターネット通信網６を介して通信可能である。
FIG. 1 is a block diagram showing an embodiment of the traffic congestion prediction system 1 of the present invention. As shown in the figure, the traffic jam prediction system 1 is provided with a taximeter 2 mounted on a vehicle, a server device 3 that communicates with the taximeter 2 to predict road congestion, and a traffic jam prediction by the server device 3. The user terminal 4 and the user terminal 4 are provided. The taximeter 2 and the server device 3 can communicate with each other via the Internet communication network 6. The server device 3 and the user terminal 4 can communicate with each other via the Internet communication network 6.
タクシーメータ２は、タクシー車両５に搭載され、運賃の算出を行う。タクシーメータ２は、タクシー会社が所有するものである。タクシーメータ２は、図２に示すように、操作部２１と、入力部２２と、通信部２３と、ＧＰＳ受信部２４と、制御部２５と、を有している。
The taximeter 2 is mounted on the taxi vehicle 5 and calculates the fare. The taximeter 2 is owned by the taxi company. As shown in FIG. 2, the taximeter 2 includes an operation unit 21, an input unit 22, a communication unit 23, a GPS receiving unit 24, and a control unit 25.
操作部２１は、空車ボタン、実車ボタン、支払いボタン、などの各種ボタンから構成されている。操作部２１は、タクシー運転手がタクシー車両５の状態（お客様が乗っていない空車か、お客様を乗せている実車か、目的地まで到着して支払いをしている支払いかなど）を入力するための操作部である。
The operation unit 21 is composed of various buttons such as an empty car button, an actual car button, and a payment button. The operation unit 21 allows the taxi driver to input the state of the taxi vehicle 5 (whether it is an empty vehicle on which the customer is not on board, an actual vehicle on which the customer is on board, or a payment that has arrived at the destination and is being paid). It is the operation part of.
入力部２２は、走行センサ７に接続され、走行センサ７からの走行パルスが入力される。走行センサ７は、タクシー車両５が所定距離走行する毎に１パルスの走行パルスを出力する。通信部２３は、インターネット通信網６に無線接続するための回路やアンテナ等から構成されている。ＧＰＳ受信部２４は、周知のように複数のＧＰＳ(Global Positioning System)衛星から発信される電波を受信して、現在位置を求めて後述する制御部２５に出力する。
The input unit 22 is connected to the travel sensor 7, and a travel pulse from the travel sensor 7 is input. The travel sensor 7 outputs one pulse of travel pulse each time the taxi vehicle 5 travels a predetermined distance. The communication unit 23 is composed of a circuit, an antenna, and the like for wirelessly connecting to the Internet communication network 6. As is well known, the GPS receiving unit 24 receives radio waves transmitted from a plurality of GPS (Global Positioning System) satellites, obtains a current position, and outputs the current position to a control unit 25 described later.
制御部２５は、例えばＲＡＭ(Random Access Memory)やＲＯＭ(Read Only Memory)などのメモリを備えたＣＰＵ(Central Processing Unit)で構成され、タクシーメータ２全体の制御を司る。制御部２５は、実車ボタンが押されると運賃の算出処理を行う。この運賃の算出処理において制御部２５は、距離制運賃算出手段および時間制運賃算出手段として働き、所定距離走行する毎に距離運賃を加算すると共に、渋滞やお客様都合によりタクシー車両５を待機させるなどによって所定速度（例えば時速１０ｋｍ）以下で所定時間（例えば９０秒）走行する毎にも時間運賃を加算する。制御部２５は、走行パルスをカウントすることによって所定距離走行したか否かを判定すると共に、走行速度を求め、所定速度以下か否かを判定する。
The control unit 25 is composed of a CPU (Central Processing Unit) having a memory such as a RAM (Random Access Memory) or a ROM (Read Only Memory), and controls the entire taxi meter 2. The control unit 25 performs a fare calculation process when the actual vehicle button is pressed. In this fare calculation process, the control unit 25 functions as a distance-based fare calculation means and an hour-based fare calculation means, adds a distance fare each time the vehicle travels a predetermined distance, and makes the taxi vehicle 5 stand by due to congestion or customer convenience. The hourly fare is also added every time the vehicle travels at a predetermined speed (for example, 10 km / h) or less for a predetermined time (for example, 90 seconds). The control unit 25 determines whether or not the vehicle has traveled a predetermined distance by counting the travel pulses, obtains the travel speed, and determines whether or not the vehicle travels at a predetermined speed or less.
また、制御部２５は、距離運賃を加算する毎にその旨を示す運賃情報と、そのときＧＰＳ受信部２４から取り込んだ現在位置を示す位置情報と、をサーバ装置３に送信する。
Further, the control unit 25 transmits the fare information indicating that fact every time the distance fare is added and the position information indicating the current position fetched from the GPS receiving unit 24 at that time to the server device 3.
サーバ装置３は、この渋滞予測システム１を運営する情報提供会社が所有する。サーバ装置３は、図３に示すように、通信部３１と、データベース（以下、ＤＢ）３２と、制御部３３と、を有している。通信部３１は、インターネット通信網６に接続するための回路などで構成されている。ＤＢ３２は、複数のタクシー車両５各々に搭載されたタクシーメータ２から送信される上記運賃情報および位置情報が記憶される。制御部３３は、例えばＲＡＭやＲＯＭなどのメモリを備えたＣＰＵで構成され、サーバ装置３全体の制御を司る。
The server device 3 is owned by the information provider that operates the traffic jam prediction system 1. As shown in FIG. 3, the server device 3 has a communication unit 31, a database (hereinafter, DB) 32, and a control unit 33. The communication unit 31 is composed of a circuit or the like for connecting to the Internet communication network 6. The DB 32 stores the fare information and the position information transmitted from the taximeter 2 mounted on each of the plurality of taxi vehicles 5. The control unit 33 is composed of a CPU having a memory such as a RAM or a ROM, and controls the entire server device 3.
ユーザ端末４は、図１に示すように、ユーザが所有する端末である。ユーザ端末４は、ＲＡＭやＲＯＭなどのメモリを備えたＣＰＵや、表示部、操作部（図示せず）を備えている。ユーザ端末４は、スマートフォンなどのタブレット端末から構成されていてもよいし、車両５に搭載されたナビゲーション装置などの車載端末から構成されていてもよい。ユーザ端末４は、インターネット通信網６を介してサーバ装置３のＤＢ３２にアクセスすることができる。
As shown in FIG. 1, the user terminal 4 is a terminal owned by the user. The user terminal 4 includes a CPU having memories such as RAM and ROM, a display unit, and an operation unit (not shown). The user terminal 4 may be composed of a tablet terminal such as a smartphone, or may be composed of an in-vehicle terminal such as a navigation device mounted on the vehicle 5. The user terminal 4 can access the DB 32 of the server device 3 via the Internet communication network 6.
次に、上述した構成の渋滞予測システム１の動作について説明する。タクシーメータ２の制御部２５（以下、単にタクシーメータ２とも言う）は、操作部２１の実車ボタンが操作されると、上述したように運賃の算出を行う。また、制御部２５は、時間制運賃が加算される毎に運賃情報および時間制運賃が加算されたときの位置情報をサーバ装置３に送信する。サーバ装置３は、運賃情報および位置情報を受信すると、受信した位置情報が示す位置で現在、渋滞していると予測して、その結果を渋滞予測情報としてＤＢ３２に保存する。
Next, the operation of the congestion prediction system 1 having the above-described configuration will be described. The control unit 25 of the taximeter 2 (hereinafter, also simply referred to as the taximeter 2) calculates the fare as described above when the actual vehicle button of the operation unit 21 is operated. Further, the control unit 25 transmits the fare information and the position information when the hourly fare is added to the server device 3 every time the hourly fare is added. When the server device 3 receives the fare information and the location information, it predicts that the traffic jam is currently present at the position indicated by the received location information, and stores the result in the DB 32 as the traffic jam prediction information.
なお、上記時間運賃は、渋滞だけでなく、お客様の都合で待機している場合や、信号待ちしている場合も加算されるものである。そこで、本実施形態では、サーバ装置３は、複数台のタクシーメータ２から運賃情報およびそのときの位置情報を収集してＤＢ３２に格納する。そして、サーバ装置３は、同じエリアを走行している所定台数以上のタクシー車両５からの一定期間内に所定回数以上連続して運賃情報を受信すると、渋滞していると予測するようにしてもよい。
The above hourly fare is added not only to traffic jams but also to customers who are waiting for their convenience or waiting for traffic lights. Therefore, in the present embodiment, the server device 3 collects the fare information and the position information at that time from the plurality of taximeters 2 and stores them in the DB 32. Then, even if the server device 3 receives fare information continuously for a predetermined number of times or more within a certain period from a predetermined number or more of taxi vehicles 5 traveling in the same area, it predicts that the vehicle is congested. Good.
また、サーバ装置３は、タクシーメータ２の運賃情報から現在の道路の渋滞状況を予測しているが、この予測した現在の渋滞状況に基づいて現在よりも例えば３０分後、１時間後の各エリアでの未来の渋滞を予測してもよい。今、所定エリアでの渋滞を予測したい場合について説明する。サーバ装置３は、上述したように所定エリア内を走行するタクシー車両５から運賃情報を受信していれば、渋滞していると予測し、運賃情報を受信していなければ、渋滞していないと予測する。
Further, the server device 3 predicts the current traffic congestion situation of the road from the fare information of the taximeter 2, and based on the predicted current traffic jam situation, for example, 30 minutes later and 1 hour later than the present. You may predict future congestion in the area. Now, the case where you want to predict the traffic congestion in a predetermined area will be described. As described above, the server device 3 predicts that the vehicle is congested if it receives the fare information from the taxi vehicle 5 traveling in the predetermined area, and if it does not receive the fare information, it is said that the server device 3 is not congested. Predict.
また、サーバ装置３は、所定エリア内における大型施設情報（大型施設の数、大きさなど）、所定エリア内にあるパーキングの空き情報、所定エリア内での気象情報、所定エリア内でのイベント情報（イベントの規模、来客者人数など）を取得する。そして、サーバ装置３は、予測された所定エリアでの現在の渋滞状況、取得された大型施設情報、パーキングの空き情報、気象情報、イベント情報に基づいて未来の渋滞を予測する。
Further, the server device 3 has large facility information (number, size, etc.) in the predetermined area, parking vacancy information in the predetermined area, weather information in the predetermined area, and event information in the predetermined area. Get (event scale, number of visitors, etc.). Then, the server device 3 predicts the future traffic jam based on the current traffic jam situation in the predicted predetermined area, the acquired large-scale facility information, the parking vacancy information, the weather information, and the event information.
この渋滞予測については、例えば図４に示すように、運賃情報から予測した現在の渋滞の有無、大型施設情報、パーキングの空き情報、気象情報、イベント情報を入力とし、３０分後、１時間後の渋滞の大きさを出力とするニューラルネットワークのような識別器３３Ａを用いることが考えられる。この識別器３３Ａは、既知の入力と、既知の出力と、を教師データとして、機械学習されている。これら教師データは、全国各地で過去に取得された情報である。
For this traffic jam prediction, for example, as shown in FIG. 4, the presence or absence of the current traffic jam predicted from the fare information, large facility information, parking vacancy information, weather information, and event information are input, and 30 minutes and 1 hour later. It is conceivable to use a classifier 33A such as a neural network that outputs the magnitude of the traffic jam. The classifier 33A is machine-learned using known inputs and known outputs as teacher data. These teacher data are information acquired in the past all over the country.
ユーザ端末４は、上記渋滞予測情報が格納されたＤＢ３２にアクセスして、全国各地の現在の渋滞状況、３０分後、１時間後などの未来の渋滞情報を取得することができる。
The user terminal 4 can access the DB 32 in which the above-mentioned traffic jam prediction information is stored, and can acquire the current traffic jam situation in various parts of the country, and future traffic jam information such as 30 minutes and 1 hour later.
上述した実施形態によれば、サーバ装置３が、時間運賃の加算を示す運賃情報およびそのときの位置情報に基づいて道路の渋滞を予測する。これにより、タクシーが通行した道路の渋滞を予測することができ、広範囲に渋滞予測をすることができる。
According to the above-described embodiment, the server device 3 predicts the traffic congestion on the road based on the fare information indicating the addition of the hourly fare and the position information at that time. As a result, it is possible to predict the traffic congestion on the road on which the taxi has passed, and it is possible to predict the traffic congestion in a wide range.
また、上述した実施形態によれば、サーバ装置３は、現在の渋滞情報、施設情報、パーキングの空き情報、気象情報、イベント情報、に基づいて道路の渋滞を予測する。これにより、より精度よく、道路の渋滞を予測することができる。
Further, according to the above-described embodiment, the server device 3 predicts road congestion based on the current congestion information, facility information, parking availability information, weather information, and event information. As a result, it is possible to predict road congestion more accurately.
なお、本発明は、上述した実施形態に限定されるものではなく、適宜、変形、改良、等が可能である。その他、上述した実施形態における各構成要素の材質、形状、寸法、数、配置箇所、等は本発明を達成できるものであれば任意であり、限定されない。
The present invention is not limited to the above-described embodiment, and can be appropriately modified, improved, and the like. In addition, the material, shape, dimensions, number, arrangement location, etc. of each component in the above-described embodiment are arbitrary and are not limited as long as the present invention can be achieved.
上述した実施形態によれば、サーバ装置３は、運賃情報から予測した現在の渋滞状況だけでなく、未来の渋滞も予測していたが、これに限ったものではない。運賃情報から現在の渋滞だけを予測するようにしてもよい。
According to the above-described embodiment, the server device 3 predicted not only the current traffic jam situation predicted from the fare information but also the future traffic jam, but the present invention is not limited to this. Only the current traffic jam may be predicted from the fare information.
また、上述した実施形態によれば、サーバ装置３は、ニューラルネットワークなどから構成された識別器３３Ａを用いて、未来の渋滞を予測していたが、これに限ったものではない。識別器３３Ａを用いるのは必須ではない。
Further, according to the above-described embodiment, the server device 3 predicts future traffic congestion by using the classifier 33A composed of a neural network or the like, but the present invention is not limited to this. It is not essential to use the classifier 33A.
ここで、上述した本発明に係る渋滞予測システム、タクシーメータおよびサーバ装置の実施形態の特徴をそれぞれ以下［１］～［４］に簡潔に纏めて列記する。
［１］
所定距離走行する毎に運賃を加算する距離制運賃算出手段（２５）と、所定速度以下で所定時間走行する毎に運賃を加算する時間制運賃算出手段（２５）と、を有するタクシーメータ（２）と、前記タクシーメータ（２）との通信によって道路の渋滞を予測するサーバ装置（３）と、を備えた渋滞予測システム（１）であって、
前記タクシーメータ（２）は、前記時間制運賃算出手段（２５）が前記運賃を加算する毎にその旨を示す運賃情報と、前記時間制運賃算出手段（２５）が前記運賃を加算したときの位置を示す位置情報と、を送信し、
前記サーバ装置（３）は、受信した前記運賃情報と前記位置情報とに基づいて道路の渋滞を予測する、
渋滞予測システム（１）。
［２］
［１］に記載の渋滞予測システム（１）において、
前記サーバ装置（３）が、
受信した前記運賃情報および前記位置情報に基づいて予測した所定エリアの現在の渋滞状況と、
前記所定エリア内の施設情報、前記所定エリア内のパーキングの空き情報、前記所定エリア内の気象情報、前記所定エリア内のイベント情報、の少なくとも１以上の情報と、
に基づいて現在よりも先の未来の道路の渋滞を予測する、
渋滞予測システム（１）。
［３］
所定距離走行する毎に運賃を加算する距離制運賃算出手段（２５）と、所定速度以下で所定時間走行する毎に運賃を加算する時間制運賃算出手段（２５）と、を有するタクシーメータ（２）であって、
前記時間制運賃算出手段（２５）が前記運賃を加算する毎にその旨を示す運賃情報と、前記時間制運賃算出手段（２５）が前記運賃を加算したときの位置を示す位置情報と、を送信する、
タクシーメータ（２）。
［４］
タクシーメータ（２）から所定速度以下で所定時間走行して運賃を加算した旨を示す運賃情報と、前記運賃を加算したときの位置を示す位置情報と、を受信するサーバ装置（３）であって、
受信した前記運賃情報および前記位置情報に基づいて道路の渋滞を予測する、
サーバ装置（３）。 Here, the features of the embodiments of the congestion prediction system, the taximeter, and the server device according to the present invention described above are briefly summarized and listed below in [1] to [4], respectively.
[1]
A taximeter (2) having a distance-based fare calculation means (25) that adds a fare each time the vehicle travels a predetermined distance, and a time-based fare calculation means (25) that adds a fare each time the vehicle travels at a predetermined speed or less for a predetermined time. ), A server device (3) that predicts traffic congestion on the road by communicating with the taximeter (2), and a traffic congestion prediction system (1).
The taximeter (2) has fare information indicating that each time the hourly fare calculating means (25) adds the fare, and when the hourly fare calculating means (25) adds the fare. The position information indicating the position and the position information are transmitted,
The server device (3) predicts road congestion based on the received fare information and the location information.
Congestion prediction system (1).
[2]
In the traffic jam prediction system (1) described in [1],
The server device (3)
The current traffic congestion situation of the predetermined area predicted based on the received fare information and the location information,
At least one or more information of facility information in the predetermined area, parking vacancy information in the predetermined area, weather information in the predetermined area, and event information in the predetermined area.
Predict future road congestion ahead of the present based on
Congestion prediction system (1).
[3]
A taximeter (2) having a distance-based fare calculation means (25) that adds a fare each time the vehicle travels a predetermined distance, and a time-based fare calculation means (25) that adds a fare each time the vehicle travels at a predetermined speed or less for a predetermined time. ) And
The fare information indicating that each time the time-based fare calculating means (25) adds the fare, and the position information indicating the position when the time-based fare calculating means (25) adds the fare. Send,
Taximeter (2).
[4]
It is a server device (3) that receives fare information indicating that the fare has been added after traveling for a predetermined time at a predetermined speed or less from the taximeter (2) and position information indicating the position when the fare is added. hand,
Predict road congestion based on the received fare information and location information,
Server device (3).
［１］
所定距離走行する毎に運賃を加算する距離制運賃算出手段（２５）と、所定速度以下で所定時間走行する毎に運賃を加算する時間制運賃算出手段（２５）と、を有するタクシーメータ（２）と、前記タクシーメータ（２）との通信によって道路の渋滞を予測するサーバ装置（３）と、を備えた渋滞予測システム（１）であって、
前記タクシーメータ（２）は、前記時間制運賃算出手段（２５）が前記運賃を加算する毎にその旨を示す運賃情報と、前記時間制運賃算出手段（２５）が前記運賃を加算したときの位置を示す位置情報と、を送信し、
前記サーバ装置（３）は、受信した前記運賃情報と前記位置情報とに基づいて道路の渋滞を予測する、
渋滞予測システム（１）。
［２］
［１］に記載の渋滞予測システム（１）において、
前記サーバ装置（３）が、
受信した前記運賃情報および前記位置情報に基づいて予測した所定エリアの現在の渋滞状況と、
前記所定エリア内の施設情報、前記所定エリア内のパーキングの空き情報、前記所定エリア内の気象情報、前記所定エリア内のイベント情報、の少なくとも１以上の情報と、
に基づいて現在よりも先の未来の道路の渋滞を予測する、
渋滞予測システム（１）。
［３］
所定距離走行する毎に運賃を加算する距離制運賃算出手段（２５）と、所定速度以下で所定時間走行する毎に運賃を加算する時間制運賃算出手段（２５）と、を有するタクシーメータ（２）であって、
前記時間制運賃算出手段（２５）が前記運賃を加算する毎にその旨を示す運賃情報と、前記時間制運賃算出手段（２５）が前記運賃を加算したときの位置を示す位置情報と、を送信する、
タクシーメータ（２）。
［４］
タクシーメータ（２）から所定速度以下で所定時間走行して運賃を加算した旨を示す運賃情報と、前記運賃を加算したときの位置を示す位置情報と、を受信するサーバ装置（３）であって、
受信した前記運賃情報および前記位置情報に基づいて道路の渋滞を予測する、
サーバ装置（３）。 Here, the features of the embodiments of the congestion prediction system, the taximeter, and the server device according to the present invention described above are briefly summarized and listed below in [1] to [4], respectively.
[1]
A taximeter (2) having a distance-based fare calculation means (25) that adds a fare each time the vehicle travels a predetermined distance, and a time-based fare calculation means (25) that adds a fare each time the vehicle travels at a predetermined speed or less for a predetermined time. ), A server device (3) that predicts traffic congestion on the road by communicating with the taximeter (2), and a traffic congestion prediction system (1).
The taximeter (2) has fare information indicating that each time the hourly fare calculating means (25) adds the fare, and when the hourly fare calculating means (25) adds the fare. The position information indicating the position and the position information are transmitted,
The server device (3) predicts road congestion based on the received fare information and the location information.
Congestion prediction system (1).
[2]
In the traffic jam prediction system (1) described in [1],
The server device (3)
The current traffic congestion situation of the predetermined area predicted based on the received fare information and the location information,
At least one or more information of facility information in the predetermined area, parking vacancy information in the predetermined area, weather information in the predetermined area, and event information in the predetermined area.
Predict future road congestion ahead of the present based on
Congestion prediction system (1).
[3]
A taximeter (2) having a distance-based fare calculation means (25) that adds a fare each time the vehicle travels a predetermined distance, and a time-based fare calculation means (25) that adds a fare each time the vehicle travels at a predetermined speed or less for a predetermined time. ) And
The fare information indicating that each time the time-based fare calculating means (25) adds the fare, and the position information indicating the position when the time-based fare calculating means (25) adds the fare. Send,
Taximeter (2).
[4]
It is a server device (3) that receives fare information indicating that the fare has been added after traveling for a predetermined time at a predetermined speed or less from the taximeter (2) and position information indicating the position when the fare is added. hand,
Predict road congestion based on the received fare information and location information,
Server device (3).
本出願は、2019年11月29日出願の日本特許出願（特願2019-216917）に基づくものであり、その内容はここに参照として取り込まれる。
This application is based on a Japanese patent application filed on November 29, 2019 (Japanese Patent Application No. 2019-216917), the contents of which are incorporated herein by reference.
本発明によれば、広範囲に渋滞を予測することができる渋滞予測システムおよびサーバを提供することができる。この効果を奏する本発明は、渋滞予測システムおよびサーバ装置に関して有用である。
According to the present invention, it is possible to provide a traffic jam prediction system and a server that can predict traffic jams in a wide range. The present invention that exhibits this effect is useful for a traffic jam prediction system and a server device.
１ 渋滞予測システム
２ タクシーメータ
３ サーバ装置
２５ 制御部（距離制運賃算出手段、時間制運賃算出手段） 1Congestion prediction system 2 Taximeter 3 Server device 25 Control unit (distance-based fare calculation means, time-based fare calculation means)
２ タクシーメータ
３ サーバ装置
２５ 制御部（距離制運賃算出手段、時間制運賃算出手段） 1
Claims (4)
- 所定距離走行する毎に運賃を加算する距離制運賃算出手段と、所定速度以下で所定時間走行する毎に運賃を加算する時間制運賃算出手段と、を有するタクシーメータと、前記タクシーメータとの通信によって道路の渋滞を予測するサーバ装置と、を備えた渋滞予測システムであって、
前記タクシーメータは、前記時間制運賃算出手段が前記運賃を加算する毎にその旨を示す運賃情報と、前記時間制運賃算出手段が前記運賃を加算したときの位置を示す位置情報と、を送信し、
前記サーバ装置は、受信した前記運賃情報と前記位置情報とに基づいて道路の渋滞を予測する、
渋滞予測システム。 Communication between a taximeter and a taximeter having a distance-based fare calculation means that adds a fare each time a predetermined distance is traveled and a time-based fare calculation means that adds a fare each time a predetermined time is traveled at a predetermined speed or less. It is a traffic jam prediction system equipped with a server device that predicts traffic jams on the road.
The taximeter transmits fare information indicating that each time the hourly fare calculating means adds the fare, and position information indicating the position when the hourly fare calculating means adds the fare. And
The server device predicts road congestion based on the received fare information and the location information.
Congestion prediction system. - 請求項１に記載の渋滞予測システムにおいて、
前記サーバ装置が、
受信した前記運賃情報および前記位置情報に基づいて予測した所定エリアの現在の渋滞状況と、
前記所定エリア内の施設情報、前記所定エリア内のパーキングの空き情報、前記所定エリア内の気象情報、前記所定エリア内のイベント情報、の少なくとも１以上の情報と、
に基づいて現在よりも先の未来の道路の渋滞を予測する、
渋滞予測システム。 In the traffic jam prediction system according to claim 1,
The server device
The current traffic congestion situation of the predetermined area predicted based on the received fare information and the location information,
At least one or more information of facility information in the predetermined area, parking vacancy information in the predetermined area, weather information in the predetermined area, and event information in the predetermined area.
Predict future road congestion ahead of the present based on
Congestion prediction system. - 所定距離走行する毎に運賃を加算する距離制運賃算出手段と、所定速度以下で所定時間走行する毎に運賃を加算する時間制運賃算出手段と、を有するタクシーメータであって、
前記時間制運賃算出手段が前記運賃を加算する毎にその旨を示す運賃情報と、前記時間制運賃算出手段が前記運賃を加算したときの位置を示す位置情報と、を送信する、
タクシーメータ。 A taximeter having a distance-based fare calculation means for adding a fare each time a predetermined distance is traveled and a time-based fare calculation means for adding a fare each time a predetermined time is traveled at a predetermined speed or less.
Each time the hourly fare calculating means adds the fare, the fare information indicating that fact and the position information indicating the position when the hourly fare calculating means adds the fare are transmitted.
Taximeter. - タクシーメータから所定速度以下で所定時間走行して運賃を加算した旨を示す運賃情報と、前記運賃を加算したときの位置を示す位置情報と、を受信するサーバ装置であって、
受信した前記運賃情報および前記位置情報に基づいて道路の渋滞を予測する、
サーバ装置。
It is a server device that receives fare information indicating that the fare has been added after traveling at a predetermined speed or less for a predetermined time from the taximeter and position information indicating the position when the fare is added.
Predict road congestion based on the received fare information and location information,
Server device.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2019-216917 | 2019-11-29 | ||
| JP2019216917A JP7032372B2 (en) | 2019-11-29 | 2019-11-29 | Congestion prediction system and server equipment |
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| WO2021106475A1 true WO2021106475A1 (en) | 2021-06-03 |
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| PCT/JP2020/040398 WO2021106475A1 (en) | 2019-11-29 | 2020-10-28 | Congestion predicting system, taxi meter, and server device |
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| WO (1) | WO2021106475A1 (en) |
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| JP2003058984A (en) * | 2001-05-24 | 2003-02-28 | Futaba Keiki Kk | Method and system for distribution service of taxi and recording medium with estimate processing program recorded |
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| JP2003067792A (en) * | 2001-08-22 | 2003-03-07 | Yazaki Corp | Fare information setting system |
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| JPH11161899A (en) * | 1997-11-27 | 1999-06-18 | Matsushita Electric Ind Co Ltd | Method and device to determine allocation of taxi and the like |
| JP2003058984A (en) * | 2001-05-24 | 2003-02-28 | Futaba Keiki Kk | Method and system for distribution service of taxi and recording medium with estimate processing program recorded |
| JP2007178124A (en) * | 2005-12-26 | 2007-07-12 | Aisin Aw Co Ltd | Navigation system |
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| JP2018106762A (en) * | 2018-04-04 | 2018-07-05 | パイオニア株式会社 | Congestion prediction system, terminal, congestion prediction method, and congestion prediction program |
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| JP7032372B2 (en) | 2022-03-08 |
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