Digital tourist travel planning system

Abstract

The invention discloses a digital tourist tourism planning system, and relates to the technical field of tourism planning. The system comprises an information acquisition unit, a preference recommendation unit, a path planning unit and a visual display unit. Wherein the information acquisition unit is used for acquiring tourist basic information, target scenic spot related information and traffic information; the preference recommendation unit is used for constructing a preference recommendation algorithm, performing content recommendation based on the tourist basic information and the target scenic spot related information, and determining a scenic spot recommendation item set; the path planning unit is used for selecting tourism living points and scenic spot recommendation items, performing path recommendation according to current traffic information and a path planning algorithm, and performing sorting and real-time updating on planned paths; and the visual display unit is used for performing visual display by taking the scenic spot recommendation item as a first-level option interface and taking the current planned route as a second-level option interface. According to the invention, dynamic planning can be realized, and tourism planning rationality of tourists is improved.

Description

Technical Field

[0001] The invention relates to the technical field of tourism planning, and in particular to a digital tourist tourism planning system. Background Art

[0002] In the prior art, tourists' travel planning often relies on traditional travel guides, travel agency recommendations, or manual searches on online travel platforms. These methods have many inconveniences and limitations. First, the information update speed of traditional travel guides is slow, and they often cannot reflect the latest attraction information, traffic conditions, or ticket price changes, causing tourists to miss the best travel experience or face unnecessary troubles. Second, although travel agency recommendations can provide certain personalized services, they are often limited to fixed travel routes and packages, making it difficult to meet the diverse needs and preferences of tourists.

[0003] Although online travel platforms provide rich travel information and convenient search functions, tourists still need to manually filter and combine various information, such as attractions, accommodation, transportation, etc., which is time-consuming and laborious. In addition, existing platforms usually lack intelligent recommendation systems and cannot provide accurate attraction recommendations based on tourists' historical itineraries and preferences, making the planning process lack of personalization and pertinence.

[0004] Therefore, the existing technology has problems in tourist travel planning, such as untimely information update, insufficient personalized recommendation, inflexible route planning, and unintuitive visualization, which makes the system recommendation unreasonable. At present, there is an urgent need for a more intelligent, personalized and convenient digital tourist travel planning system to solve these problems. Summary of the invention

[0005] The purpose of the present invention is to provide a digital tourist travel planning system that can realize dynamic planning and improve the rationality of tourist travel planning.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] A digital tourist travel planning system, comprising:

[0008] An information collection unit is used to collect basic information of tourists, relevant information of target attractions and transportation information; the basic information of tourists includes personal information logged in by users, travel preferences and historical itineraries; the relevant information of target attractions includes the location of the attractions, opening hours, ticket prices and transportation methods;

[0009] A preference recommendation unit, used to construct a preference recommendation algorithm, and to make content recommendations based on the basic information of the tourists and the relevant information of the target attractions, and to determine a set of recommended attractions items;

[0010] A path planning unit is used to select recommended tourist residences and scenic spots, recommend paths based on current traffic information and path planning algorithms, and sort and update planned routes in real time; the path planning algorithm is constructed with the set path length as the objective function and the commuting time as the constraint condition;

[0011] The visual display unit is used to visually display the recommended scenic spot items as the first-level option interface and the current planned route as the second-level option interface; the first-level option interface and the second-level option interface are in a staggered stacking form to facilitate users to switch during use.

[0012] Optionally, the preference recommendation unit specifically includes:

[0013] A target structure preference determination module is used to determine the user's target structure preference according to the user's travel preference, historical itinerary and structural characteristics of the content to be recommended; the target structure preference includes a weighted representation of the user's preference for each structure;

[0014] The scenic spot set construction module is used to determine the recommendation results for each user and obtain a set of scenic spot recommendation items based on the target structure preference through recall, sorting and fusion; wherein the recommendation results include at least two structures and the recommended content corresponding to each structure.

[0015] Optionally, the target structure preference determination module specifically includes:

[0016] A structural preference level determination submodule is used to respond to a recommendation request, perform preference sorting according to the user's travel preferences, historical itineraries, and structural features of the content to be recommended, determine the user's current optimal structural preference, and use the current optimal structural preference as the target structural preference;

[0017] Among them, the structure is determined by dividing the content to be recommended based on a classification method of an arbitrary content tag system; the structural preference is used to describe the user's interest in recommended content of different structures; the structural characteristics are represented by a structure name and a structure attribute; and the structure attribute is used to represent the historical point expansion information of different structures.

[0018] Optionally, the scenic spot set construction module specifically includes:

[0019] A weight allocation submodule, for recalling the content under the corresponding structure in a targeted manner according to each structure and its weight in the target structure preference based on a recall algorithm;

[0020] The recommendation sorting submodule is used to sort the contents under each structure recalled based on a sorting algorithm; determine the position of each structure in the recommendation results according to the weight of each structure, and fill the corresponding contents under each structure into the corresponding structure according to the sorting results of the recalled contents under each structure, obtain the recommendation results after filling, and construct a set of recommended scenic spot items.

[0021] Optionally, the path planning unit specifically includes:

[0022] The starting and ending point determination module is used to take the selected tourist residence as the starting point and the selected scenic spot recommendation item as the passing point or the ending point; when the number of selected scenic spot recommendation items is one, the passing point and the ending point are the same target;

[0023] The path recommendation module is used to make path recommendations based on the starting point, the passing points and / or the end point according to the current traffic information and the path planning algorithm, obtain all the optimal driving routes within the set path length, and sort and update them in real time based on the commuting time and path length.

[0024] Optionally, the path recommendation module specifically includes:

[0025] a path optimization submodule, configured to optimize the path from the starting point to the waypoint and / or the end point according to the static weight of the road link, so as to determine a static driving route set from the starting point to the waypoint and / or the end point, wherein the static driving route set includes at least one driving route;

[0026] A traffic event impact link assignment submodule is used to assign dynamic weights to traffic event impact link in the driving route when the static driving route set includes a driving route passing through a traffic event impact link; wherein the dynamic weight is a road travel time calculated according to the congestion level of the link; the traffic event impact link is an upstream link of the link where the traffic event occurs, and the congestion level of the traffic event impact link is not less than the congestion level of the link where the traffic event occurs;

[0027] The dynamic path planning submodule is used to perform dynamic path planning on the static driving route set according to the road condition information and the dynamic weight, so as to determine all optimal driving routes within a set path length range.

[0028] Optionally, the traffic event impact road link assignment submodule specifically includes:

[0029] The dynamic weight assignment submodule is used to obtain the driving time to reach the road link affected by the traffic event according to the driving route; when the driving time is less than the duration of the traffic event, dynamically assign weights to the road link affected by the traffic event.

[0030] Optionally, it also includes: a marking unit, used to obtain the dynamic weather forecast within the set travel time, and mark the probability and degree of severe weather in the dynamic weather forecast in the first-level option interface and the second-level option interface; the severe weather includes rain, snow, typhoon and cold wave.

[0031] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0032] The present invention discloses a digital tourist travel planning system, which includes an information collection unit, a preference recommendation unit, a path planning unit and a visualization display unit. The information collection unit is used to collect basic information of tourists, information related to target attractions and traffic information; the preference recommendation unit is used to construct a preference recommendation algorithm, and make content recommendations based on the basic information of tourists and the information related to the target attractions, and determine a set of recommended scenic spot items; the path planning unit is used to select tourist residences and recommended scenic spot items, make path recommendations based on current traffic information and path planning algorithms, and sort and update the planned routes in real time; the visualization display unit is used to use the recommended scenic spot items as a first-level option interface, and use the current planned route as a second-level option interface for visualization. The present invention can realize dynamic planning and improve the rationality of tourist travel planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0034] Figure 1 It is a structural schematic diagram of the digital tourist travel planning system of the present invention;

[0035] Figure 2 This is a schematic diagram of the digital tourist travel planning process in this embodiment. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] The purpose of the present invention is to provide a digital tourist travel planning system that can realize dynamic planning and improve the rationality of tourist travel planning.

[0038] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0039] like Figure 1-Figure 2 As shown, the present invention provides a digital tourist travel planning system, comprising:

[0040] An information collection unit is used to collect basic information of tourists, relevant information of target attractions and transportation information; the basic information of tourists includes personal information logged in by users, travel preferences and historical itineraries; the relevant information of target attractions includes the location of the attractions, opening hours, ticket prices and transportation methods;

[0041] A preference recommendation unit, used to construct a preference recommendation algorithm, and to make content recommendations based on the basic information of the tourists and the relevant information of the target attractions, and to determine a set of recommended attractions items;

[0042] A path planning unit is used to select recommended tourist residences and scenic spots, recommend paths based on current traffic information and path planning algorithms, and sort and update planned routes in real time; the path planning algorithm is constructed with the set path length as the objective function and the commuting time as the constraint condition;

[0043] The visual display unit is used to visually display the recommended scenic spot items as the first-level option interface and the current planned route as the second-level option interface; the first-level option interface and the second-level option interface are in a staggered stacking form to facilitate users to switch during use.

[0044] As a specific implementation, the preference recommendation unit specifically includes:

[0045] A target structure preference determination module is used to determine the user's target structure preference according to the user's travel preference, historical itinerary and structural characteristics of the content to be recommended; the target structure preference includes a weighted representation of the user's preference for each structure;

[0046] The scenic spot set construction module is used to determine the recommendation results for each user and obtain a set of scenic spot recommendation items based on the target structure preference through recall, sorting and fusion; wherein the recommendation results include at least two structures and the recommended content corresponding to each structure.

[0047] As a further implementation process, the target structure preference determination module specifically includes:

[0048] The structural preference level determination submodule is used to respond to recommendation requests, perform preference sorting according to the user's travel preferences, historical itineraries and structural characteristics of the content to be recommended, determine the user's current optimal structural preference, and use the current optimal structural preference as the target structural preference; wherein, the structure is determined by dividing the content to be recommended based on a classification method of an arbitrary content tag system; the structural preference is used to describe the user's interest in recommended content of different structures; the structural characteristics are represented by a structure name and a structure attribute; the structure attribute is used to represent the historical point expansion information of different structures.

[0049] As a further implementation process, the scenic spot set construction module specifically includes:

[0050] A weight allocation submodule, for recalling the content under the corresponding structure in a targeted manner according to each structure and its weight in the target structure preference based on a recall algorithm;

[0051] The recommendation sorting submodule is used to sort the contents under each structure recalled based on a sorting algorithm; determine the position of each structure in the recommendation results according to the weight of each structure, and fill the corresponding contents under each structure into the corresponding structure according to the sorting results of the recalled contents under each structure, obtain the recommendation results after filling, and construct a set of recommended scenic spot items.

[0052] As a specific implementation, the path planning unit specifically includes:

[0053] The starting and ending point determination module is used to take the selected tourist residence as the starting point and the selected scenic spot recommendation item as the passing point or the ending point; when the number of selected scenic spot recommendation items is one, the passing point and the ending point are the same target;

[0054] The path recommendation module is used to make path recommendations based on the starting point, the passing points and / or the end point according to the current traffic information and the path planning algorithm, obtain all the optimal driving routes within the set path length, and sort and update them in real time based on the commuting time and path length.

[0055] As a further implementation process, the path recommendation module specifically includes:

[0056] a path optimization submodule, configured to optimize the path from the starting point to the waypoint and / or the end point according to the static weight of the road link, so as to determine a static driving route set from the starting point to the waypoint and / or the end point, wherein the static driving route set includes at least one driving route;

[0057] A traffic event impact link assignment submodule is used to assign dynamic weights to traffic event impact link in the driving route when the static driving route set includes a driving route passing through a traffic event impact link; wherein the dynamic weight is a road travel time calculated according to the congestion level of the link; the traffic event impact link is an upstream link of the link where the traffic event occurs, and the congestion level of the traffic event impact link is not less than the congestion level of the link where the traffic event occurs;

[0058] The dynamic path planning submodule is used to perform dynamic path planning on the static driving route set according to the road condition information and the dynamic weight, so as to determine all optimal driving routes within a set path length range.

[0059] The traffic event impact road link assignment submodule specifically includes:

[0060] The dynamic weight assignment submodule is used to obtain the driving time to reach the road link affected by the traffic event according to the driving route; when the driving time is less than the duration of the traffic event, dynamically assign weights to the road link affected by the traffic event.

[0061] In addition, the system also includes: a marking unit, which is used to obtain the dynamic weather forecast within the set travel time, and mark the probability and degree of severe weather in the dynamic weather forecast in the first-level option interface and the second-level option interface; the severe weather includes rain, snow, typhoon and cold wave.

[0062] Based on the above technical solution, the following embodiments are provided.

[0063] Take user Xiao Li as an example. Tourist Xiao Li plans to visit five cities in East China (Shanghai, Nanjing, Hangzhou, Suzhou, and Wuxi) in the next week. He registers and logs in through the mobile APP of the digital tourist travel planning system. The system information collection unit automatically collects Xiao Li's personal information (such as name, age, gender, etc.), travel preferences (such as history and culture, natural scenery, etc.) and historical itineraries (such as cities and attractions visited in the past). At the same time, the system also collects information related to the target attractions such as the location, opening hours, ticket prices, and transportation methods of each attraction in the five cities in East China, as well as current transportation information (such as the real-time status of highways, railways, and flights).

[0064] Preference recommendations and attraction selection:

[0065] The preference recommendation unit determines Xiao Li's target structure preference based on his travel preferences and historical itinerary, combined with the structural characteristics of the scenic spots in the five cities in East China (such as historical and cultural categories, natural scenery categories, etc.). Through recall, sorting and fusion steps, the system generates a set of recommended items for Xiao Li, including the Confucius Temple in Nanjing and the Suzhou Gardens with a long history and culture, as well as the West Lake in Hangzhou and Yuantouzhu in Wuxi with beautiful natural scenery. These recommendation results are displayed in a structured form on Xiao Li's mobile phone APP, so that he can choose according to his interests and time.

[0066] Path planning and real-time updates:

[0067] Xiao Li chose Shanghai as his destination and selected several scenic spots of interest as his waypoints and destinations. Based on Xiao Li's choices, current traffic information and the path planning algorithm, the path planning unit generated an optimal driving route for him, starting from Shanghai, passing through Nanjing, Hangzhou, Suzhou, and finally returning to Shanghai. The system also considered constraints such as commuting time and path length, and sorted and updated the planned routes in real time.

[0068] During driving, the system monitors the road condition information in real time through the traffic event impact link assignment submodule and the dynamic path planning submodule, and dynamically adjusts the driving route according to traffic events (such as traffic accidents, road construction, etc.). For example, when the system detects that a serious traffic accident has occurred on a highway and caused congestion, it will automatically plan a detour route for Xiao Li to avoid delays.

[0069] Visual display and weather annotation:

[0070] The system displays the recommended attractions and planned routes in a staggered stacked form on Xiao Li's mobile APP. The first-level option interface displays the recommended attractions, and the second-level option interface displays the current planned route. This design allows Xiao Li to easily switch to the planned route interface when browsing the recommended attractions to view the detailed driving route and estimated arrival time.

[0071] In addition, the system also obtains the dynamic weather forecast within the set travel time through the annotation unit, and annotates the probability and degree of severe weather (such as rain, snow, typhoon, cold wave, etc.) in the first-level option interface and the second-level option interface. When planning a trip, Xiao Li can intuitively see the weather conditions in the next few days, so as to reasonably arrange travel time and bring necessary protective equipment.

[0072] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0073] This article uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only used to help understand the core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A digital tourist travel planning system, characterized in that: include: An information collection unit is used to collect basic information of tourists, relevant information of target attractions and transportation information; the basic information of tourists includes personal information logged in by users, travel preferences and historical itineraries; the relevant information of target attractions includes the location of the attractions, opening hours, ticket prices and transportation methods; A preference recommendation unit, used to construct a preference recommendation algorithm, and to make content recommendations based on the basic information of the tourists and the relevant information of the target attractions, and to determine a set of recommended attractions items; A path planning unit is used to select recommended tourist residences and scenic spots, recommend paths based on current traffic information and path planning algorithms, and sort and update planned routes in real time; the path planning algorithm is constructed with the set path length as the objective function and the commuting time as the constraint condition; The visual display unit is used to visually display the recommended scenic spot items as the first-level option interface and the current planned route as the second-level option interface; the first-level option interface and the second-level option interface are in a staggered stacking form to facilitate users to switch during use.

2. The digital tourist travel planning system according to claim 1 is characterized in that: The preference recommendation unit specifically includes: A target structure preference determination module is used to determine the user's target structure preference according to the user's travel preference, historical itinerary and structural characteristics of the content to be recommended; the target structure preference includes a weighted representation of the user's preference for each structure; The scenic spot set construction module is used to determine the recommendation results for each user and obtain a set of scenic spot recommendation items based on the target structure preference through recall, sorting and fusion; wherein the recommendation results include at least two structures and the recommended content corresponding to each structure.

3. The digital tourist travel planning system according to claim 2 is characterized in that: The target structure preference determination module specifically includes: A structural preference level determination submodule is used to respond to a recommendation request, perform preference sorting according to the user's travel preferences, historical itineraries, and structural features of the content to be recommended, determine the user's current optimal structural preference, and use the current optimal structural preference as the target structural preference; Among them, the structure is determined by dividing the content to be recommended based on a classification method of an arbitrary content tag system; the structural preference is used to describe the user's interest in recommended content of different structures; the structural characteristics are represented by a structure name and a structure attribute; and the structure attribute is used to represent the historical point expansion information of different structures.

4. The digital tourist travel planning system according to claim 2 is characterized in that: The scenic spot set construction module specifically includes: A weight allocation submodule, for recalling the content under the corresponding structure in a targeted manner according to each structure and its weight in the target structure preference based on a recall algorithm; The recommendation sorting submodule is used to sort the contents under each structure recalled based on a sorting algorithm; determine the position of each structure in the recommendation results according to the weight of each structure, and fill the corresponding contents under each structure into the corresponding structure according to the sorting results of the recalled contents under each structure, obtain the recommendation results after filling, and construct a set of recommended scenic spot items.

5. The digital tourist travel planning system according to claim 1 is characterized in that: The path planning unit specifically includes: The starting and ending point determination module is used to take the selected tourist residence as the starting point and the selected scenic spot recommendation item as the passing point or the ending point; when the number of selected scenic spot recommendation items is one, the passing point and the ending point are the same target; The path recommendation module is used to make path recommendations based on the starting point, the passing points and / or the end point according to the current traffic information and the path planning algorithm, obtain all the optimal driving routes within the set path length, and sort and update them in real time based on the commuting time and path length.

6. The digital tourist travel planning system according to claim 5 is characterized in that: The path recommendation module specifically includes: a path optimization submodule, configured to optimize the path from the starting point to the waypoint and / or the end point according to the static weight of the road link, so as to determine a static driving route set from the starting point to the waypoint and / or the end point, wherein the static driving route set includes at least one driving route; A traffic event impact link assignment submodule is used to assign dynamic weights to traffic event impact link in the driving route when the static driving route set includes a driving route passing through a traffic event impact link; wherein the dynamic weight is a road travel time calculated according to the congestion level of the link; the traffic event impact link is an upstream link of the link where the traffic event occurs, and the congestion level of the traffic event impact link is not less than the congestion level of the link where the traffic event occurs; The dynamic path planning submodule is used to perform dynamic path planning on the static driving route set according to the road condition information and the dynamic weight, so as to determine all optimal driving routes within a set path length range.

7. The digital tourist travel planning system according to claim 6, characterized in that: The traffic event impact road link assignment submodule specifically includes: The dynamic weight assignment submodule is used to obtain the driving time to reach the road link affected by the traffic event according to the driving route; when the driving time is less than the duration of the traffic event, dynamically assign weights to the road link affected by the traffic event.

8. The digital tourist travel planning system according to claim 1 is characterized in that: It also includes: a marking unit, which is used to obtain the dynamic weather forecast within the set travel time, and mark the probability and degree of severe weather in the dynamic weather forecast in the first-level option interface and the second-level option interface; the severe weather includes rain, snow, typhoon and cold wave.

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