JP2008310577A - Guidance method for tourist, and system and program therefor - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To perform guidance incorporating the intention of a community operation main body for a tourist after taking a present congestion situation into account, and to acquire dynamic state results of the tourist. <P>SOLUTION: Member registration information and pre-registration information are previously received from a user and are held. Material information that is information about each destination point present on a previously prescribed regular route is held. The intention to the guidance of a guide is received as decision information and is held. Trend information that is information related to trend of the user is received and held. Guidance information is generated based on the member registration information, the pre-registration information, the material information, the decision information, and the trend information. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a tourist guidance method that incorporates the intention of a local management entity in consideration of the current congestion status of expected visit points.

  Expected visit points where local management entities want to visit more tourists, such as tourism promotion departments of local governments, local tourism associations and chambers of commerce, or tourism-related companies operating in the region, are so-called tourist destinations. There are many places in the area as well as places known as

  Many tourists share the perception that this is common across the majority of the country.

  Here, each regional management entity has set the ideal goal of having the maximum number of tourists visit all the year round at all expected visits. To achieve the ideal goal, many local management entities set a large number of tourism excursions that incorporate multiple points as “recommended sightseeing courses”, and travel through the pamphlet and other paper media and websites. Offer to customers.

  However, this is the provision of static and fixed information assembled at a certain point in time, and it does not exceed what is expected from desktop design on the part of the regional management. Moreover, it is only one-way information provided by the local management body uniformly for all tourists. Despite the fact that each tourist seeks guidance information tailored to the individuality of each individual and the situation at that time, the information provided by each regional management entity is limited to providing uniform guidance information.

  That is, the local management entity is completely passive with respect to tourists, and the regional management entity does not have a means for timely control of the traffic flow of tourists including their own intentions. This is one limit in improving the productivity of tourism information services.

  For example, the person in charge of the local management who happens to be consulted over the phone may give recommended information to tourists, but it cannot be more than an answer based on pre-assembled information.

  Also, it is impossible to know at least immediately whether or not tourists are traveling around the expected visit points according to the expected order. And even if it can be grasped, the tourist's sightseeing behavior has ended at that time. Moreover, it does not have a means to control it including local intentions. As described above, there are structural problems in the current information service, and it is necessary to improve them.

  To explain further, in many famous tourist destinations, the degree of congestion frequently increases during a certain time period, which lowers the satisfaction of visitors. There are times when it is unevenly distributed at a certain point where the number of tourists in the region is distributed in a certain time zone.

  For example, a corner in a museum is crowded and is not likely to be viewed slowly, but a nearby museum is quiet.

  Such an uneven distribution phenomenon can occur not only among a plurality of facilities but also within one facility.

  For example, one zoo may be crowded in front of a chimpanzee but quiet in front of a zebra. Despite the importance of leveling this up in the region and facilities to increase the satisfaction of tourists and increase the residence time at each point, the local management body effectively solves this problem. Or have no means to improve.

  Such a current situation is a big issue in terms of regional revitalization, tourism revitalization and tourist satisfaction.

  On the other hand, there is a very high demand to know local tourism statistics as accurate information. The fixed-point measurement of the number of tourists has been continued for many years at major points nationwide, mainly by the Ministry of Land, Infrastructure, Transport and Tourism. The information obtained by fixed point measurement is finally compiled into a tourism white paper and used as reference material not only for the country but also for local governments and tourism operators nationwide.

  However, improvement of the fixed-point measurement method that wants to obtain more accurate information in a timely manner, while from the perspective of tourism promotion, themes that should be tackled by actively increasing the number of inbound visitors in the region and promoting migration It is getting attention as. The idea is that it is essential for the region itself to make more use of tourist information.

  The number of local governments working on tourist movement surveys is increasing, and at the same time, the number of local governments planning to expand tourism promotion measures has also increased. In this regard, there is a tendency that measurement analysis and tourism promotion measures have been operated as separate and independent ones.

  There is a need to devise a new business model for the region itself to make use of local information by closely linking these two fields that have not been synchronized in the past.

  The fixed-point measurement of the number of tourists, which has been done as a manual extraction survey, has been developed into an automated tourist dynamics survey that incorporates detectors. There is a potential expectation for an autonomous business model that promotes the excursion of customers. There is a need for a technology that can meet this demand.

  As a technique for measuring fixed points, there are already human flow measurement technology, vehicle number measurement technology, information transfer technology to portable information terminals, information storage technology in portable information terminals, information management technology using computers, and individual identification technology using IC tags. It has been put into practical use. In the tourism field, methods for utilizing the single technology have been devised in the past or in a combination of several technologies.

  As described above, traditionally, tourist movement information collection and tourism proposal information planning by human methods are often managed as independent work by independent teams, both of which are conducted through human work. Only tied and indirectly linked.

  However, the time difference in content collaboration is extremely long, year by year, and it is a common perception among tourists that the collaboration was virtually impossible when viewed from local tourists.

  From the point of view of tourists, what should be the operation system that should be closely linked to each other has been closed in each system.

  In other words, in order to break the current situation that has become a common-sense technique in the tourism industry for many years, measurement information collection technology and mobile information distribution technology are closely integrated through information generation functions related to tourism information. It is demanded.

  Here, an example of a sightseeing guide method is shown as a related technique.

  In patent document 1, the technique regarding performing guidance guidance to a visit point is described. First, guide information managed in the service center and guide information are read in advance into a portable information terminal held by a tourist. And when a tourist arrives at the gate of a certain tour site, the gate ID is sent to the service center via the portable information terminal. By this transmission, the service center recognizes that the tourist has reached the gate point and guides to the next tour point.

  In this example, taking into account changes in the degree of congestion over time in a number of sights that have been recognized empirically, tourists will be guided to the planned route before departure by optimally combining the tour sites requested by the tourists. However, it is possible to guide the next tour site along the predetermined route while confirming the tour site arrival information.

  Next, in Patent Document 2, when a certain tourist spot is connected to a highway through a general road, the number of roads based on the number of vehicles grasped on the premise that the influence of foreign vehicles on congestion is greater than that of local vehicles. It has been shown to predict congestion.

  This example predicts road congestion before reaching a tourist spot or on the way home, and indirectly provides the driver or other passengers with information on the degree of congestion or ease of reaching the tourist spot. It is intended to guide the flow line to tourists.

  Next, in Patent Document 3, the tourist information stored in a database is read in advance by a portable information terminal of a tourist through a network, and the location is recognized by GPS when the tourist comes to a certain area, and a map of the vicinity It is shown that the display of tourist facilities.

In this example, it is possible to display tourist spot information searched for each point and commentary information on tourist facilities on a portable information terminal.
Japanese Patent Laid-Open No. 2002-24460 JP 2006-91981 A JP 2002-73872 A

  By using the technique described in Patent Document 1, it is possible to guide the next tour site along the predetermined route while confirming the tour site arrival information.

  However, the technique described in Patent Document 1 is a technique for avoiding congestion by setting information guidance based on experience values, and there is a problem that the current degree of congestion is not considered. In this regard, there is a need for a technique for recognizing congestion level information that changes from moment to moment, and generating an optimal “scheduled route in the future” at that time and proposing it to tourists.

  In addition, by using the technique described in Patent Document 2, it is possible to predict the degree of congestion on the road and guide the traffic line to tourists.

  However, depending on how many tourists are on a single vehicle, the forecast of the congestion level of the sightseeing area will change, and even if you reach the sightseeing area, you may immediately go back to the reverse without going sightseeing. .

  Therefore, it is natural to think that the degree of congestion by tourists in the tourist area is fundamentally different from the degree of congestion of vehicles.

  Therefore, it is important to grasp the congestion level information of the tourist destination, which is one of the final destinations, not the congestion level of the route, and recommend the route based on that information, and finally the tourists who are intended by the local management entity There is a demand for guidance toward

  In other words, there is a need for a technology that realizes such things as suggesting a visit point that was not originally considered by the tourist or re-proposing the excursion route.

  In addition, by using the technique described in Patent Document 3, it is possible to display a map or a tourist facility near the current position of the tourist.

  In this example, the sightseeing spot information searched for each point and the commentary information of the tourist facility are displayed on the portable information terminal, but the congestion degree information of the tourist facility is not included in the database. In other words, this example is merely a navigator for each sightseeing spot, and does not perform sightseeing guidance across a plurality of points in the area.

  Therefore, the present invention provides tourists with guidance that incorporates the intentions of the local management body, taking into account the current congestion situation, and tourists' ability to grasp the movement performance of tourists. An object is to provide a guidance method, a system thereof, and a program thereof.

  According to a first aspect of the present invention, as a device, a guide information generating device for generating guide information for a user, which receives and holds member registration information and pre-registration information from the user in advance, and holds registration information A means for holding material information, which is information about each destination point on a route specified in advance, and a material information holding means, and accepting and holding the intention to guide the guide as judgment information Information holding means, trend information holding means for receiving and holding trend information that is information relating to user trends, the member registration information, the pre-registration information, the material information, the judgment information, and the trend information There is provided a guidance information generation device comprising guidance information generation means for generating guidance information based on the guidance information.

  Furthermore, according to the second aspect of the present invention, as a method, a guide information generating method for generating guide information for a user, wherein member registration information and pre-registration information are received from a user in advance and stored. An information holding step, a material information holding step for holding material information as information on each destination point on a predetermined route, and an intention to guide the guide are received and held as judgment information. A judgment information holding step, and a trend information holding step for receiving and holding trend information that is information relating to a user trend, the member registration information, the pre-registration information, the material information, the judgment information, and the trend There is provided a guidance information generation method comprising a guidance information generation step of generating guidance information based on information.

  Furthermore, according to the third aspect of the present invention, as a program, a guide information generating program for generating guide information for a user, which receives and holds member registration information and pre-registration information from the user in advance Information holding function and material information holding function that holds information about each destination point on the route specified in advance, and material information holding function, and the intention to guide the guide is received and held as judgment information A judgment information holding function, and a trend information holding function that receives and holds trend information that is information on a user trend, the member registration information, the pre-registration information, the material information, the judgment information, and the trend A guidance information generation program is provided that causes a computer to realize a guidance information generation function for generating guidance information based on information.

  According to the present invention, it is possible to guide a tourist who incorporates the intention of a local management entity after taking into account the current congestion situation.

  Next, examples of the present invention will be described.

  First, an outline of an embodiment of the present invention will be described. In this embodiment, tourist movement information and staying information are continuously captured in time and location, so that dynamic route information reconfiguration for tourists is automatically executed, and the tourists in the optimal region Realize relocation, including the forced intentions of local management entities.

  Through this, it will contribute greatly to solving the conventional problems and improving the productivity of tourism information services.

  First, the movement information and staying information of the current person and vehicle at each point of the tourist are continuously acquired by an automatic detector, and immediately transferred to the central system via the network along with incidental information such as time information and tourist information. . Here, it is conceivable that the automatic detector is not an infrared detector but an automatic detector having an image recognition function. By using an automatic detector having an image recognition function, it is possible not only to simply measure the number of people but also to collect information such as the number of people determined for each gender and age group.

  Furthermore, the manual detector installed in the area reads the IC tag held by the tourist and transmits the visit information to the central system, whereby the number of people in the area can be measured.

  On the other hand, the central system stores judgment reference information based on judgment standard information set in advance by the regional management entity.

  The central system dynamically recognizes multiple dwelling information while referring to this information, and dynamically generates fluctuation information that guides each tourist to a series of points expected by the local management entity. .

  This guidance information is again delivered to the mobile phone or mobile terminal owned by the tourist via the network. Tourists register desired information such as the desired visit point and the allowable congestion at that point in advance in their central computer in advance from their mobile phone. Then, the regional management entity can provide optimal guidance and supplementary information by comparing the demands of tourists with the current situation.

  Furthermore, in order to motivate tourists to determine their future direction of travel and to make this guidance even more effective, information on entertainment privileges that have been predefined along the excursion journey is also provided by the local management entity. Is done.

  Specifically, the entertainment privilege is a sales promotion service in which the point score is accumulated by reaching each point, or the point score is further increased by reaching a plurality of points within a certain time.

  The point does not arbitrarily change the intent of the tourist, but contributes to the improvement of the overall customer satisfaction of the tourist. The main point of the present invention is that a tourist spot is selected by the tourist himself / herself in accordance with the intention of the tourist.

  The basic operation at the center of the present invention is to always recognize the current congestion level at each point, and to guide tourists according to the intention of the local management entity set in advance for that season and time zone. To do it automatically.

  Generally, tourists are guided from a point with high congestion to a point with low congestion, but even if high congestion is shown, it is still below the maximum capacity and there is room If this is the case, you can also use a method to attract customers by deliberately appealing to the popularity of the spot by giving additional guidance.

  For example, the museum's dinosaur exhibition is very crowded with children, but it is very popular with children without telling them that it is crowded and it is better to go to another museum now If you are traveling with children, you should definitely look at it now. "

  With the present invention that can always automatically level out and optimize the distribution of the number of tourists in a region while referring to the intention information of the region management entity, the region management entity can give tourists a high customer to the area and the location. It can provide satisfaction and promote the planning of better tourism guidance measures by constantly and easily grasping tourist information.

  In other words, the present invention contributes to improving the productivity of tourism information services in the area.

  Next, the configuration of the embodiment of the present invention will be described with reference to FIG. 1 and FIGS.

  The novel embodiment of the present invention comprises a computer system, a network system, a detector system, a terminal system, and an information system stored in the computer.

  Referring first to FIG. 1, the computer system includes a computer 100 that operates under program control. The computer 100 operates as a central processing unit, a data storage device, a data input / output device, and a data display device.

  The network system includes a network 110 including the Internet and a mobile phone line.

  The detector system is for automatic detectors 200, 201... For passengers as measurement targets, automatic vehicle detectors 210, 211... For passenger cars and buses as targets for measurement, and tourists with IC tags. , Manual detectors 220, 221..., Fixed information input devices 230, 231... Operated by a person in charge of the local management subject for tourists who do not have IC tags.

  The terminal system includes mobile phones 300, 301... And mobile terminals 310, 311,.

  The information system stored in the central computer is pre-registration information 400, member registration information 401, attracting customers information 500, maximum accommodation number 501/502, sightseeing spot information 600, course information 610, tourism material information 620, judgment information 700/701. , Guidance reference information 710, fluctuation guidance information 720, tourist distributed display information 801, and the like.

  Specific contents of each information are shown in FIGS.

  The automatic detectors 200, 201,... Are devices for counting people using image sensors or infrared sensors.

  The vehicle automatic detectors 210, 211,... Are devices that perform vehicle measurement using an image sensor or an infrared sensor.

  Manual detectors 220, 221... Are devices for reading IC tags. IC tags are issued by local management entities, and tourists possess them by purchasing or lending them.

  The fixed information input machines 230, 231... Are information input devices such as personal computers, and are operated by a person in charge on the local administration side.

  All these devices have a network connection function, an information control function, and an information temporary storage function, and are always connected to the Internet via ADSL, optical fiber, etc., and are mutually connected to the computer 100.

  The automatic detectors 200, 201,... Are installed at tourist facilities, main branching points of streets, etc., and automatically measure the number of tourists moving, and send the measurement information to the computer 100 via the network 110 together with accompanying information. Forward.

  The vehicle automatic detectors 210, 211,... Are installed in a large parking lot or a pull-in road, automatically measure the number of moving vehicles, and transfer the measurement information to the computer 100 via the network 110 together with the accompanying information.

  The manual detectors 220, 221... Are installed in major tourist facilities and retail stores, and automatically measure the number of tourists who visit and transfer the measurement information to the computer 100 via the network 110 together with the accompanying information. .

  If a large number of manual detectors are installed in the area, the flow line trajectory of a specific tourist can be recognized, so that the local management body can use it as reference information for recommendation guidance.

  The fixed information input machines 230, 231... Cannot be installed or are difficult for the automatic detectors 200, 201..., The automatic vehicle detectors 210, 211. It is installed at a major point in a facility or retail store, and the person in charge of the local management body manually inputs the number of tourists to visit along with the accompanying information, and transfers the input information to the computer 100 via the network 110. .

  In this embodiment, tourist guidance is realized by mail delivery to a mobile phone.

  Therefore, a tourist who wants to receive this service from a local management body needs to register his / her mobile phone e-mail address with the local management body in advance to obtain the qualification as a member. An example of guidance information distributed to tourists is shown in FIG.

  The tourist registers personal information such as an e-mail address of his / her mobile phone in advance from the mobile phones 300, 301... Or mobile terminals 310, 311. The member registration information 400 stored in is generated in advance (see FIGS. 6 and 10). The membership number is provided in advance by the local operating entity, but can be automatically generated from the computer 100.

  Further, tourists can request a tour course that they want to participate in according to a format determined by the local management body and requests that are premised on receiving guidance from each point from the mobile phones 300, 301... Or the mobile terminals 310, 311. Pre-registration information 401 that is registered in advance and stored in the computer 100 is generated (see FIGS. 6 and 10).

  The local management entity inputs sightseeing spot information and course information into the computer 100 in advance to generate sightseeing spot information 600 and course information 610.

  The computer 100 generates tourism material information 620 from the sightseeing spot information 600 and the course information 610 (see FIGS. 8 and 10).

  The regional management entity inputs the judgment information 700 to the computer 100 as a setting standard for expressing the guidance policy of each point intended by the user in the form of a coefficient, and generates the judgment information 701. The computer 100 further generates course information from the judgment information 701. Guide reference information 710 for each point based on the above is generated (see FIGS. 9 and 10).

  Information from automatic detectors 200, 201 ..., information from automatic vehicle detectors 210, 211 ..., information from manual detectors 220, 221 ..., fixed information input machines 230, 231 ... Is transferred to the computer 100 at a predetermined time interval (for example, 10 minutes) via the network 110, and the customer collection status information 500 is dynamically generated.

  In advance, the regional management entity inputs the maximum accommodation number 501 of people and vehicles at each point (including attached roads) to the computer 100 to generate the maximum accommodation number 502.

  The computer 100 generates fluctuation guidance information 720 from the customer attraction status information 500, the tourism material information 620, the guidance reference information 710, the member registration information 400, and the pre-registration information 401 (see FIG. 10).

  The computer 100 distributes the fluctuation guidance information 720 to the mobile phones 300, 301... Or the mobile terminals 310, 311.

  When the tourist who has acquired the variation guidance information arrives at the recommended visited place, automatic detectors 200, 201..., Automatic vehicle detectors 210, 211..., Manual detectors 220, 221. The input machines 230, 231... Detect new status information and transfer it to the computer 100 (see FIG. 7).

  By repeating this operation, the computer 100 executes recommended guidance guidance according to the current state of each point with the intention of the regional management entity.

  An example of how to assemble guidance information will be described with reference to FIG.

  The tourist has informed the local management in advance that he / she will participate in the course X by pre-registration information.

  Course X includes point A, point B, point C, point D, and point E, but the tourist has registered request profiles for three points, point B, point D, and point E.

  As specific registration contents of the request profile, the congestion at the point B may be up to 50%, but if it is more than that, the visit is not desired. At the point D, the congestion at the parking lot may be up to 70%. If it is more than that, it is registered that a visit is not desired, and at point E, the male ratio may be up to 30%, but if it is more than that, a visit is not desired.

  As a result of the computer 100 judging based on the current situation and the tendency of the day, only the point B does not meet the request, so an alternative that matches the request condition from the points included in the course Y registered as a preliminary course by this tourist A point X is selected as a point, and a course X ′ in which the point G is incorporated instead of the point B is proposed.

  In the proposal, the connectivity from the point G, which is an alternative point, to the next destination point C of the X course is also considered. If an alternative point that meets the request is not found in the preliminary course, the guidance is terminated by proposing the exclusion of point B.

  Furthermore, it is possible to extend this method so that the local management entity performs separate management of reserve points and proposes the next best alternative to the tourist even if it is not the best.

  The computer 100 generates tourist dispersion display information 801 from the customer attraction status information 500, and displays the information on attraction of each point on the display device of the computer 100 in an easy-to-view manner. An example of the display screen is shown in FIG.

  The local operating entity can use this display device as an operation panel for guiding tourists, such as being able to easily instruct the computer 100 with intentional guidance and the like while watching the situation of each point on the screen.

  The local management entity adjusts the judgment information 701, confirms the tourist dispersion display information 801, and designates the recommended spot on the tourist dispersion display screen, so that the most anticipated tourism in the current or near future or in a certain period It can create or contemplate a distributed state of customers.

  In addition, the determination information 701 can be adjusted in consideration of the popularity based on experience values and questionnaire information. It is also conceivable to induce by consciously directing a peculiar point.

  Further, the guidance reference information 710 is not unique within the computer 100. A plurality of guidance reference information 710X including various characteristics such as seasons, point groups, and features of participating retail stores are mounted, and a guidance concept called a regional subgroup is defined as an operational system. In addition, it is possible to realize the migratory recommendation guidance aiming at regional activation in a wide area by generating the variation guidance information 720X in order to perform guidance within the defined regional subgroups or guidance across groups.

  There are two possible guidance methods. One is a direct guidance method that presents and recommends a planned visit point based on current information such as congestion information.

  The other is an indirect guidance method that presents a privilege for guiding tourists and indirectly promotes guidance to other points.

  Here, the guidance privilege is uniquely defined by the regional management entity from the viewpoint of regional appeal. Specifically, a higher privilege is given to a tourist who purchases a specific product at a specific retail store by a specified time, or a privilege amount in the local currency is given to a tourist who completes the specified route to be presented within a specified time. An example is giving.

  Although the means of granting these privilege services has already been devised in many regions, the role effect intended by the local management entity will be dramatically increased by combining with the automatic guidance method in this embodiment. It is done.

  The structural feature of the present invention is that the tourist guidance information can be immediately and optimally controlled by automatically measuring the number of tourists. At the same time, the value-added information that contributes to the revitalization of local tourism, such as tourist information, is managed locally. It is a mechanism that is generated daily for the subject.

The concept of change guidance information is newly defined to realize semi-automatic tourist guidance according to the regional marketing policy of the local management entity, which has been difficult with the information transmission on paper media and homepage.
The information that is the core of the fluctuation guidance information 720 is guidance guidance information based on the degree of congestion and the tendency value calculated from the number of stays at the present time. It is possible to recommend a different point if necessary.

  On the other hand, as shown in FIGS. 2 and 3, the conventional technology is a mechanism that continuously provides fixed guidance information such as sightseeing spot information and course information generated at a certain point of time in advance. And even when the current location information of tourists is used dynamically, a “help function that is a little convenient for tourists” that assists in searching for tourist information of the point or course generated in advance without manual input of the current location Stays in the range.

[Description of operation of embodiment]
Next, the operation of the embodiment of the present invention will be described in detail.

  The related diagrams are the main functional configuration diagram of FIG. 1, the functional configuration diagram of FIGS. 6 to 10, the information configuration of FIGS. 11 to 18, the data structure of FIGS. 19 to 48, and the operation transition diagram of FIGS. FIGS. 53 to 57 are diagrams showing examples of screen display, and FIGS. 61 to 64 are diagrams showing transition of numbers in the facilities of FIGS. 61 to 64. FIGS.

  First, the configuration data of the member registration information 400 and the pre-registration information 401 will be described. The member registration information 400 in this embodiment includes a member number, a telephone / terminal address, a gender, an age group, and a nearby / remote area. The contents of the pre-registration information 401 are shown in FIG. “Near / remote” is a code for determining whether or not a tourist has visited from a remote location.

  In the present embodiment, it is assumed that the membership number is a number unique to the tourist α that is separately notified from the regional management entity. In this regard, a number automatically issued by the computer 100 at the time of registration may be used as a member number.

  The age group is a division number defined by the regional management entity, but is not normally changed in a short period of time, and is therefore managed as a constant in the computer 100.

  Here, as specific classification numbers, 1 male Y (Youth) (under 40 years old), 2 male A (Age) (over 41 years old), 3 female Y (under 40 years old), 4 female A (over 41 years old) Defined as 5 remote visits.

  Here, it is assumed that the 5 remote visits have the intention of the local management entity to operate as the highest condition for 1-4.

  Next, the pre-registration information 401 in the present embodiment will be described with reference to FIG. The pre-registration information 401 includes a desired course, an individual point for registering a request profile, and request profile information.

  A registration subject is a tourist, and a tourist α, a tourist β, a tourist γ,... Are registered respectively, but here, the description will be given focusing on the tourist α.

  The desired course is selected from a group of courses defined by the regional management entity. In this embodiment, it is assumed that course X is selected. The course X is defined as a course in which the point A, the point B, the point C, the point D, and the point E travel around in order.

  The request profile consists of congestion, congestion, group attribute (male ratio), and group attribute (Y age group ratio), ranging from 0 to 1 for each of point A, point B, point C, point D, and point E. Managed as a value.

  When the degree of congestion is 0, it indicates that there is no person at that point, and when it is 1, it indicates that the capacity may be full. When the degree of traffic congestion is 0, a request is made that there is no vehicle at that point (a parking lot or an attachment road determined by the regional management entity), and when it is 1, the vehicle is full.

  When the group attribute level (male ratio) is 0, it is desired that there is no male at that point, and when it is 1, it indicates that all the stayers may be male.

  When the group attribute level (Y age group ratio) is 0, it is desirable that there is no person in the Y age group (here, 40 years old or less) at that point. Then, it shows a desire to be in a state of 40 years old or younger.

  In addition to the desired course, the desired preliminary course is selected from the group of preliminary courses defined by the regional management entity and registered.

  In this embodiment, it is assumed that the course Y is selected. The course Y is defined as a course in which the point F, the point G, the point H, the point I, and the point J travel around in order. By registering the preliminary course Y, the tourist α can receive change guidance information for the course X in which the point F, the point G, the point H, the point I, and the point J included therein are the alternative point candidate groups.

  In order to further increase the number of candidates, it is possible to select a plurality of preliminary courses, but here it is assumed that only the course Y is selected as the preliminary course.

  Reference is now made to FIGS. The member registration information is transferred to the computer 100 from the mobile phone 30X possessed by the tourist.

  First, according to the input screen shown on the display unit 30X2, the member number, telephone address, gender, age group, neighborhood / remote location are entered. A display example shown on the display unit 30X2 is shown in FIG.

  The membership number is assumed to be provided in advance by the local management entity.

  These pieces of information are sent to the storage unit 30X1 and displayed on the display unit 30X2. At the same time, the information is transferred to the computer 100 via the transmitting means 30X3, the network 110, and the information receiving means 1002 of the computer 100, and member registration information 400 is generated in the computer 100.

  Next, the pre-registration information is transferred to the computer 100 from the mobile phone 30X possessed by the tourist. First, a desired course, a preliminary course, an individual point, and a desired profile are input according to the input screen displayed on the display unit 30X2. A display example of the input screen is shown in FIG.

  The desired course is displayed in advance as a group of courses determined by the local management entity.

  Individual points are selected from a part or all of points constituting the desired course. Further, a preliminary course is input in the same manner in order to receive the fluctuation guidance information.

  These pieces of information are sent to the storage unit 30X1 and displayed on the display unit 30X2. At the same time, the information is transferred to the computer 100 via the transmission unit 30X3, the network 110, and the information reception unit 1002 of the computer 100, and pre-registration information 401 is generated in the computer 100.

  Next, the member registration information is transferred to the computer 100 from the portable terminal 31X possessed by the tourist.

  First, a member number, a terminal address, a gender, an age group, and a neighborhood / remote place are input according to an input screen displayed on the display unit 31X2.

  The membership number is assumed to be provided in advance by the local management entity.

  These pieces of information are sent to the storage unit 31X1 and displayed on the display unit 31X2. At the same time, the information is transferred to the computer 100 via the transmission means 31X3, the network 110, and the information reception means 1002 of the computer 100, and member registration information 400 is generated in the computer 100.

  Next, the pre-registration information is transferred to the computer 100 from the portable terminal 31X possessed by the tourist.

  First, a desired course, a preliminary course, an individual point, and a desired profile are input according to the input screen displayed on the display unit 31X2. The desired course is displayed in advance as a group of courses determined by the local management entity.

  Individual points are selected from a part or all of points constituting the desired course. Further, a preliminary course is input in the same manner in order to receive the fluctuation guidance information. These pieces of information are sent to the storage unit 31X1 and displayed on the display unit 31X2. At the same time, the information is transferred to the computer 100 via the transmission unit 31X3, the network 110, and the information reception unit 1002 of the computer 100, and the pre-registration information 401 is generated in the computer 100.

  Reference is now made to FIG. Information on the measurement time intervals of the automatic detector 20X and the vehicle automatic detector 21X input by the local operating entity using the operation unit 1000 of the computer 100 is sent to the automatic detector 20X and the vehicle via the information transmission means 1001 and the network 110. It is transferred to the automatic detector 21X.

  The receiving means 20X2 of the automatic detector 20X transfers the information to the detector 20X0 and sets it as control information for the measurement time interval.

  The reception means 21X2 of the vehicle automatic detector 21X transfers the information to the detection unit 21X0 and sets it as control information for the measurement time interval.

  The automatic detector 20X measures the detection time, sex, age group, number of entrance directions, and number of exit directions at the measurement time interval set in the detection unit 20X0, and transfers the integrated value to the storage unit 20X1.

  The degree of congestion is (total number of entrance directions−number of exit directions) up to that point / (maximum accommodation number MaxP at that point).

  The maximum accommodation number MaxP is determined by the local management entity according to the situation at the site, and is input from the operation unit 1000 of the computer 100.

  The transmission means 20X3 of the automatic detector 20X transfers the measurement information stored in the storage unit 20X1 to the computer 100 via the network 110 and the information reception means 1002 of the computer 100, thereby constructing the customer acquisition status information 500 (FIGS. 9 and 10). reference).

  The automatic vehicle detector 21X measures the detection time, the vehicle type division multiplier, the forward direction number, and the reverse direction number at the time intervals set in the detection unit 21X0, and transfers the integrated value to the storage unit 21X1.

  The degree of traffic congestion is (the number of forward directions−the number of backward directions) as the total value up to that point / (the maximum number of parking spaces or attached roads MaxV).

  The maximum capacity MaxV is determined by the local operating body according to the situation at the site, and is input from the operation unit 1000 of the computer 100.

  The transmission means 21X3 of the vehicle automatic detector 21X transfers the measurement information stored in the storage unit 21X1 to the computer 100 via the network 110 and the information reception means 1002 of the computer 100, thereby constructing the customer acquisition status information 500 (FIGS. 9 and 10). reference).

  The manual detector 22X reads the information of the IC tag provided by the tourist from the local operating body by the detection unit 22X0, and transfers the detection time and the member number to the storage unit 22X1.

  The transmission means 22X2 of the manual detector 22X transfers the read information of the storage unit 22X1 to the computer 100 via the network 110 and the information reception means 1002 of the computer 100, and constructs the customer acquisition status information 500 (see FIGS. 7 and 10). ).

  In the fixed information input machine 23X, the person in charge of the regional management entity inputs the input time, member number, visual congestion level, and questionnaire response at the information input unit 23X0 and transfers them to the storage unit 23X1.

  The transmission means 23X2 of the fixed information input machine 23X transfers the input information of the storage unit 23X1 to the computer 100 via the network 110 and the information reception means 1002 of the computer 100, thereby constructing the customer attracting situation information 500 (FIGS. 7 and 10). reference).

  Here, the visual congestion level information and the questionnaire response are information input in accordance with a standard determined by the regional management entity. The visual congestion degree information is input by the person in charge of the local management who operates the fixed information input machine at the point between 0 and 1.

  In the case of 0, it is very quiet in terms of sensation and the visiting environment at that point is good, and in the case of 1, it is very crowded sensibly and the visiting environment at that point is poor. Expressed as a feature of

  This information is conveyed to the tourist α as a supplement to the information from the automatic detector 20X and the automatic vehicle detector 21X.

  The questionnaire response is input as a numerical expression of customer satisfaction interviewed by previous tourists. Here, customer satisfaction is quantified as 1 very satisfied, 2 generally satisfied, 3 normal, 4 slightly dissatisfied, and 5 dissatisfied. 1 is reported to tourists α as evaluation information of accumulated customers that the popularity of the point is high and 5 is low.

  A point A, a point B, a point C, a point D, a point E of the course X input by the local management entity using the operation unit 1000 of the computer 100, a point F, a point G, a point H of the course Y input as a preliminary course, The maximum accommodation number 501 of the person (Person) and the vehicle (Vehicle) at the point I and the point J is stored in the computer 100 as the maximum accommodation number 502.

  For example, the maximum accommodation number of the person at the point A is expressed as A-Max P, and the maximum accommodation number of vehicles on the parking lot or the attachment road is expressed as A-Max V.

  The data structure of the customer attraction situation information 500 described above is shown in FIGS.

  Sightseeing area information 600 (map, history explanation, explanation of points of interest, explanation of famous products, photos / videos) and course information 610 (visit point, route to visit, priority points of interest, etc.) input by the local management entity using the operation unit 1000 of the computer 100 Tourism material information 620 is generated based on (standard travel time). The data structure is shown in FIG.

  Sightseeing area information 600 is sightseeing information for each point, and digital material data posted on the tourism website can be edited and used, but new content suitable for this case of guiding moving tourists is planned. It is desirable to develop and register.

  The course information 610 manages what points are assembled in what order in each course.

  The course X is composed of five sightseeing spots, point A, point B, point C, point D, and point E.

  Further, information on whether each point is a priority spot and the standard travel time when moving to the next point are also stored for each point.

  In the example of course X with reference to FIG. 22, point A is not an important point of interest, but point B is designated as an important point of interest. For example, information that the standard travel time from point A to point B is 30 minutes. Is registered at point B. These information are defined by the local management body taking into account the local intention and the situation at the site.

  Next, generation of the determination information 701 will be described.

  This information is information set by the regional operating entity as reference information for automatically generating fluctuation guidance information provided to tourists at all times.

  Although the setting can be changed arbitrarily, the generation of variation guide information after the change is executed based on the new information.

  Applicable tourists input by the local operating entity using the operation unit 1000 of the computer 100, congestion degree coefficient, congestion degree coefficient, group attribute degree coefficient (male ratio), group attribute degree coefficient (Y age group ratio), intentional The number of inductions is transferred to determination information 701 as determination information 700. An example of the input screen is shown in FIG. 24, 25 and 26 show the data structure of the judgment information 701.

  The application target tourist is associated with the age group and neighborhood / remote district information input using the member registration information 400.

  1 Male Y (Youth) (under 40 years old) 2 Male A (Age) (over 41 years old) 3 Female Y (under 40 years old) 4 Female A (over 41 years old) Designate whether to perform determination of congestion level, congestion level, group attribute level (male ratio), group attribute level (Y age group ratio), and intentional guidance for the customer.

  The congestion degree coefficient is a coefficient that the local management body defines how much the congestion degree at the point is affected.

  The congestion degree coefficient is a coefficient that the local management body defines how much the congestion degree at the point is affected.

  The group attribute degree coefficient (male ratio) is a coefficient that the regional management entity defines how much the group attribute degree (male ratio) at the point is affected.

  The group attribute degree coefficient (Y age group ratio) is a coefficient that the regional management entity defines how much the group attribute degree (Y age group ratio) of the point is affected.

  The number of intentional guidance is a numerical value that the local governing body specifies how strong the intentional guidance of the point is.

  An example of how to use these coefficients will be described.

  In the case of 0, it is registered as a coefficient which means that no influence is given. In the case of 1, the detection value is registered as a coefficient which means that the value is affected as much as possible.

  For example, in terms of the congestion factor, the point is popular with young people. For young tourists, even if it is crowded, if you want to ignore it or underestimate it, you should use a value close to 0. Specify intentionally.

  On the other hand, the congestion at that point is particularly disliked by the elderly due to the nature of the facility, so a value close to 1 is specified when it is desired to guide the present state as it is to the elderly tourists.

  Similarly, the congestion degree coefficient, the group attribute degree coefficient (male ratio), and the group attribute degree coefficient (Y age group ratio) are input according to the management policy of the local management entity.

  The judgment information 701 input for each point is combined with the course information by the guidance reference information generation unit 702. For example, the guidance reference is used as judgment information for the course X including the point A, the point B, the point C, the point D, and the point E. Information 710 is generated and the same applies to other courses.

  Next, the operation of the fluctuation guide information generating unit 711 for generating the fluctuation guide information 720 will be described. The data flow is shown in FIG.

  The fluctuation guidance information generation means 711 generates the fluctuation guidance information 720 from the guidance reference information 710, the member registration information 400, the pre-registration information 401, the customer attraction status information 500, and the tourism material information 620. This operation is shown in the flowcharts of FIGS. Will be described by way of example.

  First, the fluctuation guide information generating means 711 reads the member registration information 400 (member number, address, sex, age group, neighborhood / remote area) of the tourist α (step S101), and the gender, age group, With reference to the information on the nearby / remote location, it is determined which of the guidance is required for the tourist (step S102).

  The target categories defined by the regional management entities are 1: male Y, 2: male A, 3: female Y, 4: female A, 5: remote visit, and the fluctuation guidance information generation means 711 is positioned at the top. / The age group is sequentially judged from the remote location, and the tourist category is recognized (steps S103 to S107).

  Here, it is recognized that it is 4: Female A (step S108).

  The reason why the neighborhood / remote area is the highest is that the tourists who have visited all the way from the remote area have the intention of the local management body to want to be able to guide routinely regardless of gender or age group. It is.

  Next, the fluctuation guidance information generation means 711 reads the desired course from the tourist registration information 401 (step S109). Here, since the tourist α desires the course X, the fluctuation guidance information generation means 711 recognizes the points A, B, C, D, and E, and fluctuation guidance information about these points. Is generated until it returns to the point E (step S110). First, the process is sequentially performed from the point A.

  Thereafter, the process proceeds for point A.

  The variation guidance information generation means 711 reads the coefficient of the point A applied to the tourist α of the target tourist type 4 from the course X of the guidance reference information 710 (step S111).

  Here, as example values, the target tourist 4 by point, the congestion factor coefficient 0.4, the congestion factor 0.8 by point, the group attribute factor by point (male ratio) 0.5, the group attribute by point It is assumed that the coefficient (Y age group ratio) is 0.6 and the number of intentional inductions by point is 0.9.

  Next, the request profile information of the point A is read from the pre-registration information 401 of the tourist α (step S112).

  Here, it is assumed that the degree of congestion 0.3, the degree of congestion 0.1, the group attribute level (male ratio) 0.2, and the group attribute level (Y age group ratio) 0.3 are registered as exemplary values.

  Next, the fluctuation guidance information generating means 711 reads the current information of the point A of the course X from the customer attracting situation information 500 (step S113).

  Here, as an example value, the current congestion degree is 0.6. It is assumed that the current congestion level is 0.1, the current group attribute level (male ratio) is 0.3, the current group attribute level (Y age group ratio) is 0.7, the visual congestion state is 0.5, and the customer satisfaction level is 5.

  The fluctuation guide information generation means 711 first determines the desired congestion level. Hereinafter, a description will be given with reference to FIG.

  The determination congestion degree is compared with the desired congestion degree. Here, the determination congestion degree = current congestion degree 0.6 × location-specific congestion degree coefficient 0.4 = 0.24 (step S501), and the determination congestion degree is the desired congestion degree. Since it is within the desired range at 0.3 or less, the process proceeds to determination of the next desired traffic jam degree (step S502). The relationship between the determination congestion level and the desired congestion level is shown in FIG.

  On the other hand, if the desired congestion level is 0.3 or more, a comparison with the expected congestion level after 1 hour is performed (step S503), and if it still does not fall within the desired range, the process proceeds to selection of an alternative point (step S503). S504).

  Here, it is assumed that the expected congestion level after one hour is defined by the local management entity as current congestion level × (1 + average time change rate of detection results on the day).

  That is, if the average value of the rate of change per hour since the start of sightseeing on the day is + 10%, the expected congestion level after one hour is the current congestion level × 1.1.

  If this expected congestion level is less than or equal to the requested congestion level, the average value of the rate of change per hour since the start of the day's tourism is used as the trend of congestion level of the variation guidance information 720 to the tourist α, and the next request Move on to judgment of traffic congestion.

  Next, the fluctuation guidance information generation means 711 determines the desired traffic jam degree.

  The judgment congestion degree and the demand congestion degree are compared. Here, the judgment congestion degree = current congestion degree 0.1 × location-specific congestion degree coefficient 0.8 = 0.08 (step S505), and the judgment congestion degree is the demand congestion degree. Since it is within the desired range at 0.1 or less, the process proceeds to determination of the next desired group attribute level (male ratio) (step S506).

  On the other hand, if the requested traffic congestion level is 0.1 or more, a comparison with the expected traffic congestion level after 1 hour is performed (step S507). If the traffic congestion still does not fall within the desired range, the process proceeds to selection of an alternative point (step S507). S508). FIG. 62 shows the relationship between the determined congestion level and the requested congestion level.

  Here, it is assumed that the predicted congestion degree after one hour is defined by the local management entity as current congestion degree × (1 + average time change rate of detection result on the day).

  In other words, if the average value of the rate of change per hour since the start of sightseeing on the day is + 10%, the estimated congestion level after one hour is the current congestion level × 1.1.

  If this expected congestion level is less than or equal to the requested congestion level, the average value of the rate of change per hour since the start of the day's tourism is used as the trend trend of the congestion level of the fluctuation guidance information 720 to the tourist α, and the next request The process moves to the determination of the group attribute level (male ratio).

  Next, the fluctuation induction information generation means 711 determines the desired group attribute level (male ratio). This will be described below with reference to FIG.

  The determination group attribute level (male ratio) and the desired group attribute level (male ratio) are compared. Here, the determination group attribute level (male ratio) = current group attribute level (male ratio) 0.3 × point-specific group attribute level The coefficient (male ratio) is 0.5 = 0.15 (step S509), and the determination group attribute level (male ratio) is within the desired range with the desired group attribute level (male ratio) of 0.2 or less. The process proceeds to determination of the desired group attribute level (Y age group ratio) (step S510). FIG. 63 shows the relationship between the determination group attribute level (male ratio) and the desired group attribute level (male ratio).

  If the desired group attribute level (male ratio) is 0.2 or more, a comparison with the expected group attribute level (male ratio) after 1 hour is performed (step S511). The process proceeds to point selection (step S512).

  Here, it is assumed that the predicted group attribute level (male ratio) after one hour is defined by the local management entity as current group attribute level (male ratio) × (1 + average time change rate of detection results on the day).

  That is, if the average value of the rate of change per hour since the start of sightseeing on the day is + 10%, the estimated value of the group attribute (male ratio) after 1 hour is the current group attribute (male ratio) x 1.1 .

  If the predicted group attribute level (male ratio) is less than or equal to the desired group attribute level (male ratio), the average value of the rate of change per hour since the start of the day's sightseeing is calculated as the variation guidance information 720 for the tourist α. The group attribute level (male ratio) shifts to the next desired group attribute level (Y age group ratio).

  Next, the fluctuation induction information generation means 711 determines the group attribute level (Y age group ratio).

  The determination group attribute level (Y age group ratio) and the desired group attribute level (Y age group ratio) are compared. Here, the determination group attribute level (Y age group ratio) = current group attribute level (Y age group ratio) 0 7 × point-specific group attribute level (Y age group ratio) 0.6 = 0.42 (step S513), and the determination group attribute level (Y age group ratio) is the desired group attribute level (Y age group ratio). Since it is not within the desired range at 3 or more (step S514), it is compared with the expected group attribute level (Y age group ratio) after 1 hour (step S515) (step S516). If not, move to alternative point selection. FIG. 64 shows the relationship between the determination group attribute level (Y age group ratio) and the desired group attribute level (Y age group ratio).

  If the desired group attribute level (male ratio) is 0.3 or less, the process proceeds to the next congestion reference value determination.

  Estimated group attribute level (Y age group ratio) after 1 hour is defined as the current group attribute level (Y age group ratio) x (1 + average time rate of change of detection results on the day) and the local management entity To do.

  In other words, if the average value of the rate of change per hour since the start of sightseeing on the day is + 10%, the estimated value of the group attribute (Y age group ratio) after 1 hour is the current group attribute (Y age group ratio) x 1 .1.

  If this expected group attribute level (Y age group ratio) is less than the desired group attribute level (Y age group ratio), the average value of the rate of change per hour since the start of sightseeing on the day is given to the tourist α. The process shifts to the next congestion reference value determination as the trend of the group attribute level (Y age group ratio) of the fluctuation guide information 720.

  Next, the fluctuation guidance information generation means 711 compares the congestion reference value with the visual congestion status. Hereinafter, a description will be given with reference to FIG.

  Here, it is assumed that the congestion reference value is defined as 0.6 (step S601). On the other hand, since the visual congestion status is 0.5, the visual congestion status is equal to or less than the congestion reference value (step S602), and the process proceeds to the next customer satisfaction determination as the accumulated customer characteristics (environment good) of the variation guidance information 720 ( Step S603).

  When the visual congestion state is equal to or greater than the congestion reference value, the process proceeds to the next customer satisfaction determination as a feature (environmental failure) of the accumulated customers in the variation guidance information 720 (step S604).

  Next, the fluctuation guidance information generation means 711 determines customer satisfaction. Here, since the customer satisfaction is 5 (step S613), the distribution guidance information 720 moves to the distribution of the next point commentary information (point A) as the accumulated customer feature (popularity 5) (step S614).

  If the customer satisfaction is 1, the characteristics (popularity 1) of the accumulated customer of the fluctuation guidance information 720 (steps S605 and S606). If the customer satisfaction is 2, the characteristics of the accumulated customer (popularity) of the fluctuation guidance information 720. 2) (Steps S607 and S608), if customer satisfaction level is 3, characteristics of customer (popularity level 3) of fluctuation guidance information 720 (steps S609 and S610); if customer satisfaction level is 4, fluctuation guidance As the feature (popularity 4) of the accumulated customer of the information 720 (step S611, step S612), the process proceeds to the distribution of the next point commentary information (point A).

  Next, the fluctuation guidance information generation means 711 refers to the information on the point A of the tourism material information 620 in order to generate the point comment information (point A) of the fluctuation guidance information 720. Hereinafter, a description will be given with reference to FIG.

  First, let the map be point comment information (A map) (step S701). Next, the degree of congestion of shortened delivery is determined. This is a determination for distributing only the summary part of the explanatory text when the point A is more crowded than a certain reference value, so that the information can be easily read even if it is crowded.

Here, the specified congestion level of shortened delivery is set to 0.4 (step S702), but since the current congestion level is 0.6, the current congestion level is equal to or higher than the specified congestion level of shortened delivery (step S703).
Accordingly, historical commentary is point commentary information (A historical commentary, summary part only) (step S708), highlight explanation is point commentary information (A highlight explanation, summary part only) (step S709), and special product explanation is point commentary information ( A description of the famous product A, only the summary section) (step S710), the point / curve commentary information (A photograph / moving image) (step S707) is taken as the photograph / moving image, and the generation of the variation induction information at the point A ends.
If the current congestion level is equal to or less than the prescribed congestion level of shortened delivery, history explanation is point explanation information (A history explanation (step S704)), highlight explanation is point explanation information (A highlight explanation) (step S705), and special product explanation The point guidance information (A product description (step S706)) and the photograph / moving picture as the point explanation information (A photograph / moving picture) (step S707), the generation of the fluctuation guidance information at the point A ends.

  Next, selection of alternative points in the fluctuation guide information generation means 711 will be described with reference to FIGS.

  If point A does not meet the needs of tourist α in the request congestion degree determination, the request congestion degree determination, the request group attribute degree (male ratio) determination, and the request group attribute degree (Y age group ratio) determination, Before selection, it is determined whether the point A is designated as a priority spot (step S201).

  Here, since the point A is not an important highlight, the process proceeds to the next intentional guidance determination. If the point A is a priority point of interest, the process proceeds to the distribution of the point commentary information of the point A as it is even if it does not meet the demand of the tourist α.

  Next, in the determination of intentional guidance, a comparison is made between the number of intentional guidances by point and the intentional guidance reference value defined by the regional management entity.

  Here, the intentional guide reference value is set to 0.7 (step S202). In this regard, since the number of point-by-point intentional guidance is 0.9, it is determined that the number of point-by-point intentional guidance is greater than the intentional guidance reference value (step S203).

  In this case, the point A is not a point of interest that meets the demands of the tourist α, but the point that the local management entity wants to guide intentionally shifts to the distribution of point commentary information on the point A.

  If the number of point-by-point intentional guidance is less than or equal to the number of point-by-point intentional guidance, the process proceeds to selection of an alternative point.

  First, the fluctuation guidance information generation means 711 reads a preliminary course from the prior registration information 401 of the tourist α (step S204).

  Since the tourist α wants the course Y, the fluctuation guidance information generation means 711 recognizes the points F, G, H, I, and J, and the course of the fluctuation guidance information from these points. Generate recombination information.

  Assume that the standard travel time to the point B is determined as the highest level information for the alternative point search.

  The standard travel time from point A to point B of course X is 30 minutes, but here the points that fall within the range of the standard travel time ± 10 minutes are point F, point G, point H, point I of course Y, A determination is made at the point J to search for an alternative suggested point (step S205).

  Here, the process shifts to reading of guidance reference information with the point G as an alternative suggested point (step S206).

  If an alternative proposed point cannot be searched, the course recombination information of the variation guidance information 720 excludes the point A of the course X, and the generation of the variation guidance information for the point A is terminated with no substitution point.

  Thereafter, the process proceeds for the point G.

  The fluctuation guidance information generation means 711 reads the coefficient of the point G applied to the tourist α of the target tourist type 4 from the course Y of the guidance reference information 710 (step S207).

  Here, the target tourists 4 by point, the congestion factor coefficient 0.4, the congestion factor 0.8 by point, the group attribute factor by point (male ratio) 0.5, the group attribute factor by point (Y Age group ratio) is 0.6, and the number of intentional leads by location is 0.9.

  Next, the request profile information of the point G is read from the pre-registration information 401 of the tourist α (step S208).

  Here, as an example value, a congestion degree of 0.3, a congestion degree of 0.1, a group attribute level (male ratio) 0.2, and a group attribute level (Y age group ratio) 0.3 are registered.

  Next, the fluctuation guidance information generation means 711 reads the current information of the point G of the course Y from the customer attracting situation information 500 (step S209).

  Here, as an example value, the current congestion degree is 0.6. Current congestion level is 0.1, current group attribute level (male ratio) is 0.3, current group attribute level (Y age group ratio) is 0.4, visual congestion is 0.5, and customer satisfaction level is 5.

  The fluctuation guide information generation means 711 first determines the desired congestion level.

  The determination congestion degree is compared with the desired congestion degree. Here, the determination congestion degree = current congestion degree 0.6 × location-specific congestion degree coefficient 0.4 = 0.24 (step S210), and the determination congestion degree is the desired congestion degree. Since it is within the desired range at 0.3 or less, the process proceeds to determination of the next desired traffic jam degree (step S211).

  If the desired congestion level is 0.3 or more, the expected congestion level after 1 hour is calculated (step S212). Here, it is assumed that the expected congestion level after one hour is defined by the local management entity as current congestion level × (1 + average time change rate of detection results on the day). That is, if the average value of the rate of change per hour since the start of sightseeing on the day is + 10%, the expected congestion level after one hour is the current congestion level × 1.1.

  Then, the requested congestion level is compared with the calculated expected congestion level after 1 hour (step S213). If the requested congestion level still does not fall within the desired range, the course recombination information of the variation induction information 720 is changed to the point A of the course X. And the generation of change guidance information at point A is terminated.

  When the expected congestion level is equal to or less than the desired congestion level, the process proceeds to the next determination of the requested congestion level.

  Next, the fluctuation guidance information generation means 711 determines the desired traffic jam degree.

  The judgment congestion degree and the demand congestion degree are compared. Here, the judgment congestion degree = current congestion degree 0.1 × location-specific congestion degree coefficient 0.8 = 0.08 (step S214). Since the determined congestion level is within the desired range with a requested congestion level of 0.1 or less, the process proceeds to determination of the next desired group attribute level (male ratio) (step S215).

  If the requested traffic congestion level is 0.1 or more, a comparison with the expected traffic congestion level after 1 hour is performed. If the traffic congestion still does not fall within the desired range, the course recombination information of the variation guidance information 720 is changed to the point A of the course X. The generation of change guidance information at point A ends with no exclusion or substitution.

  Here, it is assumed that the predicted congestion degree after one hour is defined by the local management entity as current congestion degree × (1 + average time change rate of detection result on the day).

  That is, assuming that the average value of the rate of change per hour since the start of sightseeing on the day is + 10%, the estimated congestion level after 1 hour is the current congestion level × 1.1 (step S216).

  When the predicted congestion level is equal to or less than the requested congestion level, the process proceeds to determination of the next requested group attribute level (male ratio) (step S217).

  Next, the fluctuation induction information generation means 711 determines the desired group attribute level (male ratio).

  The determination group attribute level (male ratio) and the desired group attribute level (male ratio) are compared. Here, the determination group attribute level (male ratio) = current group attribute level (male ratio) 0.3 × point-specific group attribute level The coefficient (male ratio) is 0.5 = 0.15 (step S218). Since the determination group attribute level (male ratio) is within the desired range with the desired group attribute level (male ratio) of 0.2 or less, the process proceeds to the next determination of the desired group attribute level (Y age group ratio) (step) S219).

  If the desired group attribute level (male ratio) is 0.2 or more, a comparison with the expected group attribute level (male ratio) after 1 hour is performed. If the desired group attribute level (male ratio) still does not fall within the desired range, the change guidance information 720 The point A of the course X is excluded from the course recombination information, and the change guidance information generation at the point A is terminated with no alternative point.

  Here, it is assumed that the predicted group attribute level (male ratio) after one hour is defined by the local management entity as current group attribute level (male ratio) × (1 + average time change rate of detection results on the day).

  That is, if the average value of the rate of change per hour since the start of sightseeing on the day is + 10%, the estimated value of the group attribute (male ratio) after 1 hour is the current group attribute (male ratio) x 1.1 (Step S220).

  If the predicted group attribute level (male ratio) is less than or equal to the desired group attribute level (male ratio), the process proceeds to determination of the next desired group attribute level (Y age group ratio) (step S221).

  Next, the fluctuation induction information generation means 711 determines the group attribute level (Y age group ratio).

  The determination group attribute level (Y age group ratio) and the desired group attribute level (Y age group ratio) are compared. Here, the determination group attribute level (Y age group ratio) = current group attribute level (Y age group ratio) 0 .Times.4 × point-specific group attribute level (Y age group ratio) 0.6 = 0.24 (step S222). Since the determination group attribute level (Y age group ratio) is less than or equal to the desired group attribute level (Y age group ratio) 0.3 (step S223), the point G is incorporated in place of the point A in the course recombination information of the variation guidance information 720. The process proceeds to the next recommendation reason as a proposal (steps S224 and S225).

  When the determination group attribute level (Y age group ratio) is equal to or greater than the desired group attribute level (Y age group ratio), a comparison determination with the expected group attribute level (Y age group ratio) after 1 hour is performed.

  Estimated group attribute level (Y age group ratio) after 1 hour is defined as the current group attribute level (Y age group ratio) x (1 + average time rate of change of detection results on the day) and the local management entity (Step S226).

  In other words, if the average value of the rate of change per hour since the start of sightseeing on the day is + 10%, the estimated value of the group attribute (Y age group ratio) after 1 hour is the current group attribute (Y age group ratio) x 1 .1.

  Next, the expected group attribute level is compared with the desired group attribute level (step S227). If the expected group attribute level (Y age group ratio) is less than or equal to the desired group attribute level (Y age group ratio), the next recommendation is to propose the course recombination information in the variation guidance information 720 as a proposal by incorporating the point G instead of the point A Transition to the reason.

  If it still does not fall within the desired range, the point A of the course X is excluded from the course recombination information of the change guide information 720, and the change guide information generation of the point A is terminated with no alternative point (step S228).

  After making proposal by incorporating the point G instead of the point A in the course recombination information of the variation guidance information 720, the reason for recommendation is the congestion level, congestion level, group attribute level (male ratio), group attribute level (currently and one hour later) It shifts to distribution of the next point commentary information (point G) as (Y age group ratio).

  Next, the fluctuation guidance information generation means 711 refers to the information on the point G of the tourism material information 620 in order to generate the point comment information (point G) of the fluctuation guidance information 720. This point will be described with reference to FIG.

  First, let the map be point comment information (G map) (step S301). Next, the degree of congestion of shortened delivery is determined.

  This is a determination for distributing only the summary part of the explanatory text when the point G is more crowded than a certain reference value so that the information can be easily read even if it is crowded.

  Here, the specified congestion degree of shortened delivery is set to 0.5 (step S302). Since the current congestion level is 0.6, the current congestion level is equal to or higher than the specified congestion level for shortened delivery (step S303).

  Therefore, historical commentary is point commentary information (G history commentary, summary part only) (step S304), highlight explanation is point commentary information (G highlight explanation, summary part only) (step S305), and special product description is point commentary information ( The explanation of the G product and the summarizing part only) (step S306), the point / guidance information (G photograph / moving image) (step S307) is taken as the photograph / moving image, and the generation of the variation induction information at the point A ends.

  If the current congestion level is equal to or less than the prescribed congestion level of shortened delivery, history explanation is point explanation information (G history explanation) (step S308), highlight explanation is point explanation information (G highlight explanation) (step S309), and special product explanation The point guidance information (G special product explanation) (step S310) and the photograph / moving picture as the point explanation information (G photograph / moving picture) (step S307), the generation of the fluctuation guidance information at the point A ends.

  After the generation of variation guidance information for the point A of the course X is completed, the generation of the variation guidance information for all points for the point B, the point C, the point D, and the point E is continued, and then the process proceeds to generation of privilege information. To do. This will be described with reference to FIGS. 36 and 37.

  Here, the privilege information generation condition is that the tourist α visits all the points designated as priority points of interest.

  When the point A is an important point of interest (step S401), the member number of the tourist α is detected by the manual detector at the point A or inputted by the fixed information input machine (step S402), and further, the point B is If it is an important point of interest (step S403), the membership number of the tourist α is detected by the manual detector at the point B or inputted by the fixed information input device (step S404), and further, the point C is the important point of interest. In some cases (step S405), when the member number of the tourist α is detected by the manual detector at the point C or is input by the fixed information input device (step S406), and the point D is an important point of interest. (Step S407) The member number of the tourist α is detected by the manual detector at the point D or input by the fixed information input device (step S408), and the point E is further emphasized. If it is a place (step S409), the member number of the tourist α is detected by the manual detector at the point E or inputted by the fixed information input device (step S410), the privilege information of the fluctuation guidance information 720 Is defined (step S411), and the operation of the fluctuation guide information generating unit 711 ends.

  If any of the conditions for generating the privilege information is not satisfied, the operation of the fluctuation guide information generating unit 711 ends without defining the privilege information.

  The change guidance information generation means 711 includes course recombination information, recommendation reason, point comment information, privilege information, congestion degree trend, congestion degree trend, group attribute level (male ratio) trend, group attribute level (Y age group ratio) Fluctuation induction information 720 composed of the transition tendency and the characteristics of the accumulated customers is generated.

  The fluctuation guide information 720 is distributed to the receiving means 30X4 of the mobile phone 30X via the information transmitting means 1001 of the computer 100 and the network 110 (see FIG. 6).

  The receiving unit 30X4 displays the fluctuation guide information 720 on the display unit 30X2.

  Further, the fluctuation guide information 720 is distributed to the receiving unit 31X4 of the portable terminal 31X via the information transmitting unit 1001 of the computer 100 and the network 110 (see FIG. 6).

  The receiving unit 31X4 displays the fluctuation guide information 720 on the display unit 31X2. A display example is shown in FIG.

  The tourist distributed display information generating means 800 generates tourist distributed display information 801 together with map information and course information. This point will be described with reference to FIGS. 47 and 48. FIG.

  The tourist dispersion display information 801 includes the current congestion level, current congestion level, current group attribute level (male ratio), current group attribute level (Y age group ratio), and the current level for each point that make up the customer attraction status information 500. Membership ratio.

  The member ratio is a ratio of the total number of member numbers detected to the total number of visitors from the reference time of the day detected or input by the manual detector 220 and the fixed information input device 230 to the current time.

  The tourist distributed display information 801 is superimposed on the map information as the current tourism status of each course and each point, and is displayed on the display device of the computer 100 or another large display device in an easy-to-understand manner. . A display example is shown in FIG.

  Furthermore, by simply clicking on an arbitrary point on the screen, the target tourist at that point, the congestion factor by point, the congestion factor by point, the group attribute factor by point (male ratio), the group attribute by point The guidance reference information 710 can be arbitrarily and easily adjusted by designating the degree coefficient (Y age group ratio) and the number of intentional guidance for each point.

  The data structure of each piece of information described above is shown in FIGS.

  Next, the flow of information among the detectors, the computer 100, and the portable terminal will be described with reference to FIGS.

  First, member registration information is transmitted from the mobile phone 30X or the mobile terminal 31X to the computer 100 (A1). The computer 100 receives the member registration information and holds it as member registration information 400 (A2).

  Further, the pre-registration information is transmitted from the mobile phone 30X or the mobile terminal 31X to the computer 100 (A3). The computer 100 receives the pre-registration information and holds it as the pre-registration information 401 (A4).

  Next, the computer 100 transmits information about the interval for measurement to the automatic detector 20X (A5). The automatic detector 20X sets a measurement interval based on the transmitted information, and performs measurement based on the set interval. Then, the information detected by the measurement is accumulated (A6).

  The accumulated detection information is transmitted to the computer 100 (A7), and the computer 100 receives the detection information and holds it as customer attraction status information 500 (A8).

  Next, information transmission from the vehicle automatic detector 21X will be described. First, information about the interval at which measurement is performed is transmitted from the computer 100 to the automatic vehicle detector 21X (A9). The vehicle automatic detector 21X sets a measurement interval based on the transmitted information, and performs measurement based on the set interval. Then, the information detected by measurement is accumulated (A10).

  The accumulated detection information is transmitted to the computer 100 (A11), and the computer 100 receives the detection information and holds it as customer attraction status information 500 (A12).

  Next, information transmission from the manual detector 22X will be described. The manual detector 22X reads the IC tag information and accumulates the read information (A13).

  The stored read information is transmitted as detection information to the computer 100 (A14), and the computer 100 receives the read information and holds it as customer collection status information 500 (A15).

  Next, information transmission from the fixed information input machine 23X will be described. When detection information is input to the fixed information input machine 23X, the fixed information input machine 23X accumulates the input information as detection information (A16).

  The accumulated detection information is transmitted to the computer 100 (A17), and the computer 100 receives the detection information and holds it as customer attraction status information 500 (A18).

  Next, the computer 100 has an input for the maximum number of people or vehicles by location and holds it as the maximum number 502 (A19).

Further, the information received at A8 to A18 is held as the customer collection status information 500 (A20). Furthermore, it accepts input of sightseeing spot information 600 (A21) and course information 610 (A22)
Based on the received information, tourism material information 620 is generated and held (A23).

Next, determination information 701 is input to the computer 100, and the determination information 701 is held (A24).
Then, the guidance reference information generation unit 702 generates guidance reference information 710 (A25) and holds the guidance reference information 710 (A26).
Further, the fluctuation guide information generating means 711 generates the fluctuation guide information 720 (A27) and holds the fluctuation guide information 720 (A28). And the fluctuation | variation guidance information 720 hold | maintained is transmitted to the mobile telephone 30X or the portable terminal device 31X. Then, the mobile phone 30X or the mobile terminal 31X receives the fluctuation guide information 720 (A29).
Thereafter, the customer collection status information 500 is received (A30), and the tourist distributed display information generating means 800 generates the tourist distributed display information 801 (A31).

  And the tourist dispersion | distribution display information 801 is hold | maintained (A32).

[Other embodiments of the invention]
Another embodiment will be described with reference to FIGS. 58, 59, and 60.

[Diversification of mobile terminals for tourists]
The fluctuation guidance information 720 is distributed to the mobile phone 30X or the portable terminal 31X possessed by the tourist. A method for acquiring the fluctuation guidance information 720 in a wider range of travel situations by diversifying the distribution terminals. Will be described. 58 is used for the description.

  The individual recommendation information of the variation guidance information 720 and the congestion degree transition tendency are also distributed and displayed on the status display board 910 such as roads and parking lots installed in the city via the transfer 730 to the status display board.

  On the status display board 910 in the vicinity of the point A, the fluctuation guide information 721 relating to the point A is displayed.

  On the status display board 910 in the vicinity of the point B, the fluctuation guide information 722 related to the point B is displayed.

  Further, the fluctuation guidance information 721 relating to the point A and the fluctuation guidance information 722 relating to the point B are also displayed on the car navigation device 920 via the transfer 740 to the car navigation.

  In the present embodiment, the fluctuation guidance information 720 generated from the information on the status of attracting customers collected from the points A and B is provided to the driver and passengers by means other than the mobile phone 30X or the mobile terminal 31X. It provides information to tourists traveling by vehicle while complementing terminals and display devices.

  The fluctuation guidance information 720 is simultaneously distributed to the mobile phone 30X or the portable terminal 31X, thereby realizing guidance that is seamlessly linked from moving to walking in the vehicle. As a result, the intention of the local management entity can be reflected in the guidance measure more finely.

[Application to play facilities]
The example about the play facility in the limited site is described. FIG. 59 is used for the description.

  The sightseeing spot is replaced with an amusement facility, and variation guide information 720 is generated from information on the status of attracting customers at each amusement facility.

  When there is a play facility A, a play facility B, and a play facility C, change guide information 723 related to the play facility A, change guide information 724 related to the play facility B, and change guide information 725 related to the play facility C from the change guide information 720. It is generated and distributed to the mobile phone 30X or the mobile terminal 31X of the attendee.

  Similar to the above-described sightseeing example, the optimum recommendation information is provided in accordance with the demands of the visitors and the degree of congestion of each play facility.

  Contributes to shortening the waiting time, increasing the customer satisfaction of visitors, and at the same time contributing to leveling and optimizing the operating rate of each facility expected by the organizer.

[Application to shopping streets]
An embodiment in a shopping street located in a limited area will be described. FIG. 60 is used for the description.

  The sightseeing spot is replaced with each store, and the variation guide information 720 is generated from the customer collection status information of each store.

  When there are a store A, a store B, and a store C, the change induction information 720 generates the change induction information 726 related to the store A, the change induction information 727 related to the store B, and the change induction information 728 related to the store C, Delivered to the mobile phone 30X or the mobile terminal 31X.

  Similar to the tourism example, the optimum recommendation information is provided in accordance with the consumer's demand and the degree of congestion of each store.

  The privilege grant information implemented as a shopping street and the popularity of each store are also distributed for sales promotion.

  Contribute to improving the customer satisfaction of consumers and improving the sales of each store that the shopping district expects.

[Description of effects]
In the embodiment of the present invention, the accumulated staying information in the tourist area is centrally managed, and dynamic guidance to the tourist is performed while automatically referring to the judgment information prescribed in advance by the local management body. Realize an information system that can continuously execute guidance.

  As a result, the tourist side will be provided with the latest process recommendation information for each point to improve satisfaction, and the local management side will be able to gather tourists between points by automatic excursion guidance referring to their intentions. Will contribute to the sustainable expansion of the economic contribution effect in regional tourism and the improvement of tourism service business productivity.

  The effects of the embodiments of the present invention will be enumerated from the following two viewpoints: effects on tourists and effects on local management entities.

[Effects for tourists]
1. The point where the number of visitors is larger than the standard capacity and is crowded more than one's request among the points scheduled to be visited.

  The reason is that the current congestion degree information can be acquired by a mobile phone or the like.

  2. Know where you are planning to visit and where the congestion is likely to be eased within the scope of your request.

  The reason is that the trend information of the congestion degree can be acquired with a mobile phone or the like.

  3. From the points you are planning to visit, you should be able to see where the number of vehicles is larger than the standard number of vehicles accommodated and the traffic is congested from your request.

  The reason is that the current traffic congestion degree information can be acquired with a mobile phone or the like.

  4). Know where you are planning to visit and where the degree of traffic congestion is likely to be reduced within the scope of your request.

  The reason is that the current traffic congestion degree information can be acquired with a mobile phone or the like.

  5. You can see what age group of tourists there are in the spot you are planning to visit and how many tourists meet your needs in terms of gender ratio.

  The reason is that the collective customer group attribute can be acquired by a mobile phone or the like.

  6). You will be able to understand the sensual congestion situation at the point you are planning to visit.

  The reason is that the current visual congestion situation can be acquired with a mobile phone or the like.

  7. You should be able to find the most popular points you plan to visit.

  The reason is that current popular information can be acquired by a mobile phone or the like.

  8). It is not included in the points you plan to visit in the future, but it is easy to go to the next point of the current course, and the current congestion level, congestion level, group attribute level (gender ratio), group attribute level (young / The visitor point where the ratio of seniors) matches the needs of the user, including the time-varying trend, can be understood.

  The reason is that course recombination information can be obtained together with the reason for recommendation using a mobile phone or the like.

  9. If the point you are planning to visit is busy, you can read a short summary of tourist information.

  The reason is that it is possible to acquire tourist information according to the current congestion situation with a mobile phone or the like.

  10. You can receive benefits from the local management entity based on the visits to each point along the route.

  The reason is that privilege information can be acquired with a mobile phone or the like.

[Effects on local management entities]
11. To understand the dynamics of how many tourists are gathered at each point by the local management entity.

  The reason is that the status of each point is always displayed.

  12 Know the trend of how many tourists are gathered at each point by the local management entity.

  The reason is that the situation at each point is always recorded and compared.

  13. Understanding the dynamics of how many tourists are gathering at the point where the regional management entity wants to guide.

The reason is that the situation at that point is always displayed. The local operating entity should be able to visually recognize the movement results, trend results, and intentional guidance points at each point in an easy-to-understand format.

  The reason is that the status of each point is always displayed on the display board in an easily understandable manner.

  15. The local operation entity can specify and guide the target tourists.

  This is because the reference information can be set by specifying the target tourist.

  16. The local operation entity can be guided by adjusting the degree of congestion.

  The reason is that reference information can be set by specifying a congestion degree coefficient.

  17. The local management entity can be guided by adjusting the degree of congestion.

  The reason is that the reference information can be set by designating a congestion degree coefficient.

  18. The local management entity can be guided by adjusting the degree of group attribute level (male ratio).

  The reason is that reference information can be set by specifying a group attribute degree coefficient (male ratio).

  19. The local management entity can be guided by adjusting the degree of group attribute level (age ratio).

  The reason is that the reference information can be set by specifying the group attribute level (age group ratio).

  20. Be able to deliberately guide tourists to a point where the local management entity is located.

  This is because the reference information can be set by designating the number of intentional leads.

  21. The local management entity can arbitrarily control the leveling and decentralization of visitors in terms of location (geographic), time (spring / summer / autumn / winter), and time (time).

  The reason is that an easy-to-use means of clicking on the screen can easily expand or reduce the degree of relationship by adjusting the congestion level, congestion level, group attribute level, and number of intentional leads for each target layer. This is because the priority points can be designated at any time.

  Note that the guidance information generating device can be realized by hardware, software, or a combination thereof.

  The fields in which the present invention can be used are mainly in the tourism administration field and the tourism business field. In addition, the present invention can be applied to any field where it is required to realize guidance intended by the organizer by providing optimal information to a moving person while grasping the dynamics thereof. For example, the present invention can be applied to private amusement facilities and shopping streets shown as other embodiments.

  Furthermore, it can be applied to large art museums, museums, zoos, or scattered library usage services, station-related facilities along railway lines, large shopping malls, and large department stores.

It is a figure showing the main function structure of the Example of this invention. It is a figure showing the difference of the Example of this invention and a prior art. It is a figure showing the basic composition of a prior art. It is a figure showing the information which a tourist gives and receives in the Example of this invention. It is a figure showing the example of an assembly method of guidance information. It is a figure showing the basic composition of the example of the present invention. It is a figure showing the basic composition of the example of the present invention. It is a figure showing the structure of the information in the Example of this invention. It is a figure showing the structure of the information in the Example of this invention. It is a figure showing the structure of the information in the Example of this invention. It is a figure showing the structure of the information in the Example of this invention. It is a figure showing the structure of the information in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a figure showing the data structure in the Example of this invention. It is a flowchart showing operation | movement of the Example of this invention. It is a flowchart showing operation | movement of the Example of this invention. It is a flowchart showing operation | movement of the Example of this invention. It is a flowchart showing operation | movement of the Example of this invention. It is a flowchart showing operation | movement of the Example of this invention. It is a flowchart showing operation | movement of the Example of this invention. It is a flowchart showing operation | movement of the Example of this invention. It is a flowchart showing operation | movement of the Example of this invention. It is a flowchart showing operation | movement of the Example of this invention. It is a flowchart showing operation | movement of the Example of this invention. It is a flowchart showing operation | movement of the Example of this invention. It is a flowchart showing operation | movement of the Example of this invention. It is a flowchart showing operation | movement of the Example of this invention. It is a figure explaining the production | generation of the tourist dispersion | distribution display information in the Example of this invention. It is a figure explaining the production | generation of the tourist dispersion | distribution display information in the Example of this invention. It is a figure showing the operation | movement transition in the Example of this invention. It is a figure showing the operation | movement transition in the Example of this invention. It is a figure showing the operation | movement transition in the Example of this invention. It is a figure showing the operation | movement transition in the Example of this invention. It is a figure showing the example of a display with the portable terminal in the Example of this invention. It is a figure showing the example of a display with the portable terminal in the Example of this invention. It is a figure showing the example of the input screen of the judgment information in the Example of this invention. It is a figure showing the example of a display with the portable terminal in the Example of this invention. It is a figure showing the example of a display of the tourist dispersion | distribution display information in the Example of this invention. It is a figure showing the basic composition of the example which aimed at diversification of the portable terminal for tourists of the present invention. It is a figure showing the basic composition of the example which applied the present invention to the play facility. It is a figure showing the basic composition of the example which applied the present invention to a shopping district. It is the figure shown about the congestion degree in a sightseeing spot. It is the figure shown about the congestion degree in a sightseeing spot. It is the figure shown about the demand group attribute (male ratio) degree in a sightseeing spot. It is the figure shown about the demand group attribute (Y age group ratio) degree in a sightseeing spot.

Explanation of symbols

100 Computer 110 Network 200 Automatic Detector A
201 Automatic detector B
20X automatic detector 20X1 detection unit 20X2 storage unit 20X3 reception unit 20X4 transmission unit 210 vehicle automatic detector A
211 Automatic vehicle detector B
21X Automatic vehicle detector 21X1 Detection unit 21X2 Storage unit 21X3 Reception unit 21X4 Transmission unit 220 Manual detector A
221 Manual detector B
22X Manual detector 22X0 IC tag reading unit 22X1 Storage unit 22X2 Transmitting means 230 Fixed information input machine A
231 Fixed information input machine B
23X Fixed Information Input Machine 23X0 Information Input Unit 23X1 Storage Unit 23X2 Transmitting Means 300 Mobile Phone A
301 Mobile phone B
30X mobile phone 30X0 operation unit 30X1 storage unit 30X2 display unit 30X3 transmission unit 30X4 reception unit 310 portable terminal A
311 Mobile Terminal B
31X portable terminal 31X0 operation unit 31X1 storage unit 31X2 display unit 31X3 transmission unit 31X4 reception unit 400 member registration information 401 pre-registration information 500 attracting customers status information 501, 502 maximum accommodation capacity 600 tourist spot information 610 course information 620 tourist material information 700, 701 Judgment information 702 Guidance reference information generating means 710 Guidance reference information 711 Fluctuation guidance information generating means 720 Fluctuation guidance information 721 Fluctuation guidance information relating to the point A 722 Fluctuation guidance information relating to the point B 723 Fluctuation guidance information relating to the play facility A 724 Fluctuation guidance information 725 relating to the facility B Fluctuation guidance information relating to the play facility C 726 Fluctuation guidance information relating to the store A 727 Fluctuation guidance information relating to the store B 728 Fluctuation guidance information relating to the store C 800 Fluctuation guidance information relating to the store C 800 Tourist distributed display information generating means 801 Customer distribution display Information 910 Status display board 920 Car navigation device 1000 Operation unit 1001 Information transmission means 1002 Information reception means

Claims (17)

A guidance information generation device that generates guidance information for a user,
Registration information holding means for receiving and holding member registration information and pre-registration information from users in advance;
Material information holding means for holding material information that is information about each destination point on the route specified in advance;
Judgment information holding means for accepting and holding the intention of the guide as guidance information;
Trend information holding means for receiving and holding trend information, which is information related to user trends,
Guidance information generating means for generating guidance information based on the member registration information, the pre-registration information, the material information, the determination information, and the trend information;
A guidance information generating device comprising: The guidance information generation device according to claim 1,
The pre-registration information is information capable of selecting an allowable level based on the user's intention, and items to be selected include the degree of congestion, the degree of congestion, the male ratio, and the age at the destination point. A guidance information generation device characterized by being any one of the layer ratios or a combination thereof. The guidance information generating device according to claim 1 or 2,
When the guide information is generated by the guide information generating means, the degree of congestion, the degree of congestion, the male ratio age group ratio, and the intention to guide the guide at the destination point are influenced to the whole extent. A coefficient setting means for setting a coefficient that determines
The guidance information generating device is characterized in that the guidance information generating means operates in consideration of the coefficient determined by the coefficient setting means. The guidance information generation device according to any one of claims 1 to 3,
The guidance information generated by the guidance information generating means includes information for proposing an alternative destination point when there is no destination point that completely satisfies the user's intention on the route originally selected by the user. A guidance information generation device characterized by being included. The guidance information generation device according to any one of claims 1 to 4,
A guidance information generating apparatus characterized in that, when the degree of congestion at a destination point is equal to or greater than a predetermined value, a description of the highlight of the destination point included as guidance information is only a summary. The guidance information generation device according to any one of claims 1 to 5,
A trend transition predicting means for predicting a future trend of the user based on the trend information held in the trend information holding means;
The guidance information generation device, wherein the guidance information generation unit operates in consideration of the predicted trend transition determined by the trend transition prediction unit. The guidance information generation device according to any one of claims 1 to 6,
Distributed information that displays the current congestion level, current congestion level, current male ratio, current age group ratio, current member ratio, or a combination thereof at each destination point along with the corresponding route map information A guidance information generating device, further comprising display means. The guidance information generating device according to claim 7,
An apparatus for generating guidance information, further comprising means for adjusting the guidance information by operating based on information displayed on the distributed information display means. A guide information generation method for generating guide information for a user,
A registration information holding step for receiving and holding member registration information and pre-registration information from the user in advance;
A material information holding step for holding material information, which is information about each destination point on a predetermined route,
A judgment information holding step for accepting and holding the intention of the guide as guidance information;
A trend information holding step for receiving and holding trend information, which is information relating to user trends,
A guide information generating step for generating guide information based on the member registration information, the pre-registration information, the material information, the determination information, and the trend information;
A guide information generation method comprising: The guidance information generation method according to claim 9,
The pre-registration information is information capable of selecting an allowable level based on the user's intention, and items to be selected include the degree of congestion, the degree of congestion, the male ratio, and the age at the destination point. A method for generating guidance information, which is any one of the layer ratios or a combination thereof. It is the guidance information generation method according to claim 9 or 10,
When the guidance information is generated in the guidance information generation step, how much influence is exerted on each of the degree of congestion, the degree of congestion, the male ratio age group ratio, and the intention of the guider at the destination point. A coefficient setting step for setting a coefficient that determines
The guidance information generation method characterized in that the guidance information generation in the guidance information generation step is performed in consideration of the coefficient determined in the coefficient setting step. It is the guidance information generation method according to any one of claims 9 to 11,
In the guidance information generated in the guidance information generation step, when there is no destination point that completely satisfies the user's intention on the route originally selected by the user, there is information for proposing an alternative destination point. A guide information generation method characterized by being included. It is the guidance information generation method according to any one of claims 9 to 12,
A guidance information generation method characterized in that, when the degree of congestion at a destination point is equal to or more than a predetermined value set in advance, only a summary of a description of a destination point to be included as guidance information is included. It is the guidance information generation method according to any one of claims 9 to 13,
A trend transition prediction step of predicting a transition of a user's future trend based on the trend information held in the trend information holding step;
The guidance information generation method, wherein the guidance information generation in the guidance information generation step operates in consideration of the predicted trend transition determined in the trend transition prediction step. The guidance information generation method according to any one of claims 9 to 14,
Distributed information that displays the current congestion level, current congestion level, current male ratio, current age group ratio, current member ratio, or a combination thereof at each destination point along with the corresponding route map information A guidance information generating method, further comprising a display step. The guidance information generation method according to claim 15,
The guidance information generation method further comprising the step of adjusting the guidance information by performing an operation based on the information displayed in the distributed information display step. A guide information generation program for generating guide information for a user,
A registration information holding function for receiving and holding member registration information and pre-registration information from users in advance;
A material information holding function for holding material information, which is information about each destination point on a predetermined route,
A judgment information holding function that accepts and holds the intention of the guide as guidance information;
A trend information holding function that receives and holds trend information that is information related to user trends,
A guide information generating function for generating guide information based on the member registration information, the pre-registration information, the material information, the determination information, and the trend information;
A guidance information generation program characterized by causing a computer to realize the above.

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