Hotel room reservation planning method in combination with travel itinerary

Abstract

The invention discloses a hotel room reservation planning method in combination with a travel itinerary. The method comprises the following steps: calculating future arrival time when a user arrives at a passing point; all target hotel rooms meeting the room requirements of the user are matched around the passing points; predicting room reservation costs of all target hotel rooms corresponding to the passing points at the arrival time in the future; predicting the travel cost of all target hotel rooms corresponding to the waypoint to the waypoint; calculating the comprehensive room reservation cost of each target hotel according to the room reservation cost and the travel cost; selecting the target hotel room with the lowest comprehensive room reservation cost as a suggested hotel room; and generating hotel room reservation plans of the passing points on the travel route for the user according to the travel route of the user, the future arrival time of the passing points and the suggested hotel rooms. According to the invention, the hotel room reservation efficiency of the user can be improved, and the user can be assisted to realize optimization of hotel room reservation cost in a travel itinerary.

Description

Technical Field

[0001] The present invention relates to the field of hotel reservation and big data technology, and in particular to a hotel room reservation planning method combined with a travel itinerary. Background Art

[0002] Online hotel room booking has become an indispensable part of modern travel, providing users with a convenient and efficient accommodation booking experience. Through major online travel booking platforms or hotel official websites, users can easily browse and compare room types, prices, geographical locations and user reviews of different hotels, so as to make more informed choices. During the online booking process, users only need to enter basic information such as destination, check-in date and check-out date, and the system will immediately display a list of hotels that meet their needs. These lists usually include detailed information such as the hotel's star rating, room type (such as single room, double room, suite, etc.), price range, and whether breakfast is included.

[0003] During the travel process, planning itineraries and booking hotels are often important tasks that users need to face. However, the existing booking methods often bring many inconveniences to tourists. Usually, users will set multiple waypoints on the travel itinerary route in order to fully experience the local customs and beautiful scenery of the destination. However, every time a new waypoint is reached, the user needs to find and book a hotel again. This process is not only cumbersome, but also often takes a lot of time and energy. More importantly, due to information asymmetry and lack of comparison, users often find it difficult to find the most affordable hotel. In addition, hotel rooms generally need to be booked, and users cannot know the hotel prices at future times, which not only increases the complexity of hotel room booking, but also may cause users to suffer losses in room prices and cannot enjoy the most cost-effective accommodation experience. Therefore, how to design a hotel room booking planning method combined with travel itinerary routes is a technical problem that needs to be solved urgently. Summary of the invention

[0004] In view of the deficiencies of the above-mentioned prior art, the technical problem to be solved by the present invention is: how to provide a hotel room reservation planning method combined with a travel itinerary, firstly calculate the future arrival time of the waypoint, then predict the room reservation cost at the future arrival time, and finally combine the room reservation cost at the future arrival time and the travel cost to select the hotel with the lowest comprehensive room reservation cost, thereby improving the user's hotel room reservation efficiency and assisting the user to optimize the hotel room reservation cost in the travel itinerary.

[0005] In order to solve the above technical problems, the present invention adopts the following technical solutions: A hotel room reservation planning method combined with a travel itinerary, comprising: S1: Obtain the user's room requirements, travel itinerary, departure time and preset passing points; S2: Calculate the future arrival time of the user at the waypoint based on the user's travel itinerary and departure time; S3: Match all target hotel rooms that meet the user's room requirements around the passing point; S4: predict the room booking costs of all target hotel rooms corresponding to the waypoints at the future arrival time; S5: predict the travel cost of all target hotel rooms corresponding to the waypoint to the waypoint; S6: Calculate the comprehensive room booking cost of each target hotel room according to the room booking cost of all target hotel rooms at the future arrival time and the travel cost to the passing points; select the target hotel room with the lowest comprehensive room booking cost as the recommended hotel room; S7: Generate a hotel room reservation plan for the user's travel points on the travel itinerary based on the user's travel itinerary route and the future arrival time of the travel points and the recommended hotel rooms; the hotel room reservation plan includes the future arrival time of each travel point on the travel itinerary and the location information of the recommended hotel rooms.

[0006] Preferably, in step S2, for the first waypoint: future arrival time = departure time + predicted travel time from the starting point of the travel itinerary to the first waypoint; For the second and subsequent waypoints: future arrival time = future arrival time of the previous waypoint + stay time at the previous waypoint + predicted travel time from the previous waypoint to the current waypoint.

[0007] Preferably, in step S3, a circular reachable area is generated with the waypoint as the center and the set distance R as the radius; and all target hotel rooms that meet the user's room requirements are screened out from the reachable area.

[0008] Preferably, in step S4, the room booking cost of the target hotel room at the future arrival time is predicted by the following steps: S401: Obtain the current price of the target hotel room and the current remaining number of rooms in the hotel; S402: Obtaining tourist population big data associated with the future arrival time of the waypoints, and predicting the room reservation growth rate of the hotel at the future arrival time based on the tourist population big data; S403: Calculating the vacancy rate of the hotel at the future arrival time according to the current remaining number of rooms of the hotel and the room reservation growth rate at the future arrival time; S404: predicting the room booking cost of the target hotel room at the future arrival time according to the current price of the target hotel room and the vacancy rate of the hotel at the future arrival time.

[0009] Preferably, in step S402, the room reservation growth rate is predicted specifically through the following steps: S4021: The acquired tourist population big data includes the tourist peak time period and the historical foreign population flow big data of all hotels during the tourist peak period; S4022: When the current date is in the tourist peak period, obtain the inbound population flow of the current date; S4023: Match the historical foreign population flow rate with the foreign population flow rate on the current date from the tourist peak time period according to the historical foreign population flow rate big data; S4024: Calculate the date interval N between the current date and the future arrival time; push back N days the tourist peak date with the closest inflow of foreign population to the current date as the target tourist peak date corresponding to the future arrival time; S4025: Obtain the historical room reservation rate of the target hotel on the target tourist peak date corresponding to the future arrival time; S4026: Obtain the historical room reservation rates of other hotels on the target tourist peak dates corresponding to the future arrival times; S4027: Calculate the room reservation growth rate of the target hotel at the future arrival time based on the historical room reservation rates of the target hotel and other hotels at the future arrival time.

[0010] Preferably, in step S5, the travel cost from the target hotel to the waypoint includes the travel economic cost; Calculate the economic cost of travel by following these steps: S501: Calculate the walking distance between the target hotel and the waypoint; if the walking distance is greater than the distance threshold, execute step S502; otherwise, the travel economic cost is 0; S502: Obtaining the travel method from the target hotel to the passing point provided by the user; S503: Calculate the travel economic cost from the target hotel to the waypoint according to the travel mode from the target hotel to the waypoint.

[0011] Preferably, in step S5, the travel cost from the target hotel to the waypoint includes the travel time cost; Calculate the travel time cost by following the steps below: S511: Calculate the walking distance between the target hotel and the waypoint; if the walking distance is greater than the distance threshold, execute step S512; otherwise, calculate the travel time = walking distance / preset pace; S512: Obtaining the travel method from the target hotel to the passing point provided by the user; S513: Calculate travel time based on the travel mode from the target hotel to the waypoint; S514: Calculate travel time cost = travel time * time cost factor.

[0012] Preferably, in step S6, the comprehensive room booking cost = a room booking cost + b travel economic cost + c travel time cost; wherein a, b, c are weights of the room booking cost, travel economic cost, and travel time cost, respectively.

[0013] Compared with the prior art, the hotel room reservation planning method combined with the travel itinerary in the present invention has the following beneficial effects: In the present invention, firstly, the future arrival time of the user at the waypoint is calculated according to the user's travel route and departure time, and the subsequent hotel room reservation planning is performed based on the future arrival time of the waypoint, so that the user can be provided with a tailored hotel reservation suggestion to meet the personalized needs of different users. The user does not need to plan the arrival time and hotel selection of each waypoint separately, thereby improving the user's hotel room reservation efficiency. Secondly, on the basis of predicting the arrival time, all target hotel rooms that meet the user's room needs are further matched around the waypoint, and the room reservation cost of all target hotel rooms corresponding to the waypoint at the future arrival time is predicted. By predicting the room reservation cost at the future time (i.e., the future arrival time), the hotel with the lowest room reservation cost at the future time can be selected for the user, which can not only improve the user's room reservation experience and user satisfaction, but also assist the user to optimize the hotel room reservation cost in the travel itinerary. Finally, on the basis of predicting the room reservation cost, the travel cost of all target hotel rooms corresponding to the waypoint to the waypoint is further predicted, and then the hotel with the lowest comprehensive room reservation cost is selected in combination with the room reservation cost and the travel cost, thereby better assisting the user to optimize the hotel room reservation cost in the travel itinerary. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to make the purpose, technical solution and advantages of the invention more clear, the present invention will be further described in detail below with reference to the accompanying drawings, in which: Figure 1 The logical block diagram of the hotel room reservation planning method combined with the travel itinerary. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but only represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0016] The following is a further detailed description through specific implementation methods: Embodiment 1: This embodiment discloses a hotel room reservation planning method combined with a travel itinerary.

[0017] like Figure 1 As shown, the hotel room reservation planning method combined with the travel itinerary includes: S1: Obtain the user's room requirements, travel itinerary, departure time and preset passing points; In this embodiment, the user's room requirements include hotel location area, hotel star, room size, room type (such as double room, standard room). The preset waypoint needs to be a specific location, such as xxx amusement park, xx park, etc.

[0018] S2: Calculate the future arrival time of the user at the waypoint based on the user's travel itinerary and departure time; S3: Match all target hotel rooms that meet the user's room requirements around the passing point; S4: predict the room booking costs of all target hotel rooms corresponding to the waypoints at the future arrival time; In this embodiment, the room booking cost at the future arrival time can be predicted by the room prices of the target hotel in the same period of previous years.

[0019] S5: predict the travel cost of all target hotel rooms corresponding to the waypoint to the waypoint; S6: Calculate the comprehensive room booking cost of each target hotel room according to the room booking cost of all target hotel rooms at the future arrival time and the travel cost to the passing points; select the target hotel room with the lowest comprehensive room booking cost as the recommended hotel room; S7: Generate a hotel room reservation plan for the user's travel points on the travel itinerary based on the user's travel itinerary route and the future arrival time of the travel points and the recommended hotel rooms; the hotel room reservation plan includes the future arrival time of each travel point on the travel itinerary and the location information of the recommended hotel rooms.

[0020] In the present invention, firstly, the future arrival time of the user at the waypoint is calculated according to the user's travel route and departure time, and the subsequent hotel room reservation planning is performed based on the future arrival time of the waypoint, so that the user can be provided with a tailored hotel reservation suggestion to meet the personalized needs of different users. The user does not need to plan the arrival time and hotel selection of each waypoint separately, thereby improving the user's hotel room reservation efficiency. Secondly, on the basis of predicting the arrival time, all target hotel rooms that meet the user's room needs are further matched around the waypoint, and the room reservation cost of all target hotel rooms corresponding to the waypoint at the future arrival time is predicted. By predicting the room reservation cost at the future time (i.e., the future arrival time), the hotel with the lowest room reservation cost at the future time can be selected for the user, which can not only improve the user's room reservation experience and user satisfaction, but also assist the user to optimize the hotel room reservation cost in the travel itinerary. Finally, on the basis of predicting the room reservation cost, the travel cost of all target hotel rooms corresponding to the waypoint to the waypoint is further predicted, and then the hotel with the lowest comprehensive room reservation cost is selected in combination with the room reservation cost and the travel cost, thereby better assisting the user to optimize the hotel room reservation cost in the travel itinerary.

[0021] During the specific implementation process, for the first stopover point: future arrival time = departure time + predicted travel time from the starting point of the travel itinerary to the first stopover point; the predicted travel time from the starting point of the travel itinerary to the first stopover point can be estimated through existing software such as Baidu Maps and Amap.

[0022] For the second and subsequent waypoints: the future arrival time = the future arrival time of the previous waypoint + the stay time of the previous waypoint + the predicted travel time from the previous waypoint to the current waypoint. The predicted travel time from the previous waypoint to the current waypoint can be estimated through existing software such as Baidu Maps and Amap.

[0023] In this embodiment, the dwell time at the waypoint is set by the user.

[0024] The present invention calculates the future arrival time of the user at the waypoint according to the user's travel itinerary and departure time, and performs subsequent hotel room reservation planning based on the future arrival time of the waypoint, so as to provide the user with tailored hotel reservation suggestions to meet the personalized needs of different users. The user does not need to plan the arrival time and hotel selection of each waypoint separately, thereby improving the user's hotel room reservation efficiency.

[0025] During the specific implementation process, a circular reachable area is generated with the waypoint as the center and the set distance R as the radius; all target hotel rooms that meet the user's room needs are screened out from the reachable area.

[0026] In this embodiment, the distance R is set to five kilometers.

[0027] The present invention can pre-exclude hotels with excessively high travel costs through accessible areas, which can not only better assist users in optimizing hotel room booking costs during travel itineraries, but also reduce the workload of subsequent calculations, thereby improving the efficiency of hotel room booking.

[0028] In the specific implementation process, the travel cost from the target hotel to the transit point includes the economic cost of travel; Calculate the economic cost of travel by following these steps: S501: Calculate the walking distance between the target hotel and the waypoint; if the walking distance is greater than the distance threshold, execute step S502; otherwise, the travel economic cost is 0; In this embodiment, the distance threshold can be set according to user needs, such as being set to one kilometer.

[0029] S502: Obtaining the travel method from the target hotel to the passing point provided by the user; In this embodiment, the user selects his or her own travel mode, including bus, subway, taxi, self-driving, long-distance bus, high-speed rail, airplane and other travel modes.

[0030] S503: Calculate the travel economic cost from the target hotel to the waypoint according to the travel mode from the target hotel to the waypoint.

[0031] In this embodiment, if the user chooses to travel by bus, subway, long-distance bus, high-speed rail, airplane, etc., the corresponding travel economic cost shall be based on the actual ticket purchase amount. If the user chooses to travel by taxi, the corresponding travel economic cost shall be based on the taxi fare on Baidu Maps or Amap or other taxi apps. If the user chooses to travel by self-driving, the corresponding travel economic cost = the actual distance planned by Baidu Maps or Amaps * fuel consumption (or power consumption) coefficient.

[0032] In the specific implementation process, the travel cost from the target hotel to the transit point includes the travel time cost; Calculate the travel time cost by following the steps below: S511: Calculate the walking distance between the target hotel and the waypoint; if the walking distance is greater than the distance threshold, execute step S512; otherwise, calculate the travel time = walking distance / preset pace; In this implementation, the travel time can be calculated through the walking navigation planning function of Baidu Maps or Amap.

[0033] S512: Obtaining the travel method from the target hotel to the passing point provided by the user; S513: Calculate travel time based on the travel mode from the target hotel to the waypoint; In this embodiment, the travel time can be calculated through the navigation planning function of Baidu Maps or Amap.

[0034] S514: Calculate travel time cost = travel time * time cost factor.

[0035] In this embodiment, the time cost factor is designed by the user according to his or her own needs, such as being set to 100 yuan / hour.

[0036] The present invention comprehensively evaluates the travel cost by using the two aspects of travel economic cost and travel time cost, and then selects the hotel with the lowest comprehensive room booking cost in combination with the room booking cost, thereby better assisting users to optimize the hotel room booking cost in their travel itinerary.

[0037] During the specific implementation process, the comprehensive room booking cost = a room booking cost + b travel economic cost + c travel time cost; among them, a, b, and c are the weights of room booking cost, travel economic cost, and travel time cost respectively.

[0038] In this embodiment, the user can set the weights of various costs according to their own needs. For example, a and b can be set to 0.5 and 0.3, and c can be set to 0.2.

[0039] Embodiment 2: This embodiment discloses a new room booking cost prediction method.

[0040] In this embodiment, the room booking cost of the target hotel room at the future arrival time is predicted through the following steps: S401: Obtain the current price of the target hotel room and the current remaining number of rooms in the hotel; S402: Obtaining tourist population big data associated with the future arrival time of the waypoints, and predicting the room reservation growth rate of the hotel at the future arrival time based on the tourist population big data; S403: Calculating the vacancy rate of the hotel at the future arrival time according to the current remaining number of rooms of the hotel and the room reservation growth rate at the future arrival time; S404: predicting the room booking cost of the target hotel room at the future arrival time according to the current price of the target hotel room and the vacancy rate of the hotel at the future arrival time.

[0041] The present invention obtains tourist population big data associated with the user's reservation time, and then more accurately predicts the room booking growth rate of the hotel at the future arrival time by analyzing the tourist population big data and combining the historical big data, which is conducive to the subsequent better calculation of the vacancy rate and the room booking cost. The present invention calculates the vacancy rate of the target hotel at the future arrival time according to the current room remaining quantity and the room booking growth rate of the target hotel. By calculating the vacancy rate, the room supply situation of a certain period in the future can be understood, and the vacancy rate is one of the important factors affecting the room price. The present invention can more accurately and flexibly predict the room booking cost by calculating the vacancy rate to cope with changes in market demand. The present invention predicts the room prediction cost at the future arrival time according to the current price and vacancy rate of the hotel room. By predicting the room booking cost at the future arrival time, the hotel with the lowest room booking cost at the future time can be selected for the user, which can not only improve the user's room booking experience and use satisfaction, but also assist the user in optimizing the hotel room booking cost in the travel itinerary.

[0042] In actual application scenarios, there are several months of peak tourism every year. During this period, hotel room demand and prices will surge. Therefore, this application fully considers the dimension of holiday big data when calculating the room booking growth rate. And unlike holidays, the peak tourism period is only a rough interval and the time is not fixed.

[0043] In view of the above problems, in this embodiment, the room reservation growth rate is predicted through the following steps: S4021: The acquired tourist population big data includes tourist peak types and tourist peak time periods, as well as historical foreign population flow big data and historical room reservation big data of all hotels during tourist peaks; S4022: When the current date is in the tourist peak period, obtain the inbound population flow of the current date; S4023: Match the peak tourist date with the closest historical inbound population flow to the current date from the peak tourist time period according to the inbound population flow on the current date; S4024: Calculate the date interval N between the current date and the future arrival time; push back the tourist peak date closest to the current date by N days as the target tourist peak date corresponding to the future arrival time; S4025: Obtain the historical room reservation rate of the target hotel on the target tourist peak date corresponding to the future arrival time; S4026: Obtain the historical room reservation rates of other hotels on the target tourist peak dates corresponding to the future arrival times; S4027: Calculate the room reservation growth rate of the target hotel at the future arrival time based on the historical room reservation rates of the target hotel and other hotels at the future arrival time.

[0044] In actual application scenarios, the tourist peak will have a greater impact on the demand and price of hotel rooms. Therefore, the present invention fully considers the historical room reservation rate of the hotel during the tourist peak period in previous years to predict the room reservation growth rate at future moments, which is conducive to the subsequent more accurate calculation of vacancy rate and room reservation cost. At the same time, the present invention further considers the historical room reservation rate of other hotels during the tourist peak period in previous years to assist in predicting the future room reservation growth rate, because the historical room reservation rate of other hotels can also reflect the hotel room reservation trend and demand during the tourist peak, and then can make certain corrections to the target hotel room reservation growth rate, thereby improving the room reservation growth rate and the accuracy of subsequent vacancy rate and room reservation cost calculation. And the tourist peak time period is only a rough interval, and the time is not fixed. To address this problem, the present invention determines the tourist peak time period and tourist peak date corresponding to the user's scheduled time by the flow of foreign population, rather than directly corresponding the current date to the historical date, so that the tourist population big data can be better used to accurately calculate the room reservation growth rate, thereby improving the accuracy of subsequent vacancy rate and room reservation cost calculation.

[0045] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit the technical solution. Those skilled in the art should understand that those modifications or equivalent substitutions of the technical solution of the present invention that do not depart from the purpose and scope of the technical solution should be included in the scope of the claims of the present invention.

Claims

1. A hotel room reservation planning method combined with a travel itinerary, characterized in that: include: S1: Obtain the user's room requirements, travel itinerary, departure time and preset passing points; S2: Calculate the future arrival time of the user at the waypoint based on the user's travel itinerary and departure time; S3: Match all target hotel rooms that meet the user's room requirements around the passing point; S4: predict the room booking costs of all target hotel rooms corresponding to the waypoints at the future arrival time; S5: predict the travel cost of all target hotel rooms corresponding to the waypoint to the waypoint; S6: Calculate the comprehensive room booking cost of each target hotel room according to the room booking cost of all target hotel rooms at the future arrival time and the travel cost to the passing points; select the target hotel room with the lowest comprehensive room booking cost as the recommended hotel room; S7: Generate a hotel room reservation plan for the user at the travel points on the travel itinerary according to the user's travel itinerary, the future arrival time of the travel points, and the recommended hotel rooms.

2. The hotel room reservation planning method combined with the travel itinerary as claimed in claim 1, characterized in that: In step S2, for the first waypoint: future arrival time = departure time + predicted travel time from the starting point of the travel route to the first waypoint; For the second and subsequent waypoints: future arrival time = future arrival time of the previous waypoint + stay time at the previous waypoint + predicted travel time from the previous waypoint to the current waypoint.

3. The hotel room reservation planning method combined with the travel itinerary as claimed in claim 1, characterized in that: In step S3, a circular reachable area is generated with the waypoint as the center and the set distance R as the radius; all target hotel rooms that meet the user's room requirements are screened out from the reachable area.

4. The hotel room reservation planning method combined with the travel itinerary as claimed in claim 1, characterized in that: In step S4, the room booking cost of the target hotel room at the future arrival time is predicted by the following steps: S401: Obtain the current price of the target hotel room and the current remaining number of rooms in the hotel; S402: Obtaining tourist population big data associated with the future arrival time of the waypoints, and predicting the room reservation growth rate of the hotel at the future arrival time based on the tourist population big data; S403: Calculating the vacancy rate of the hotel at the future arrival time according to the current remaining number of rooms of the hotel and the room reservation growth rate at the future arrival time; S404: predicting the room booking cost of the target hotel room at the future arrival time according to the current price of the target hotel room and the vacancy rate of the hotel at the future arrival time.

5. The hotel room reservation planning method combined with the travel itinerary as claimed in claim 4, characterized in that: In step S402, the room reservation growth rate is predicted specifically through the following steps: S4021: The acquired tourist population big data includes the tourist peak time period and the historical foreign population flow big data of all hotels during the tourist peak period; S4022: When the current date is in the tourist peak period, obtain the inbound population flow of the current date; S4023: Match the historical foreign population flow rate with the foreign population flow rate on the current date from the tourist peak time period according to the historical foreign population flow rate big data; S4024: Calculate the date interval N between the current date and the future arrival time; Push back N days the tourist peak date closest to the current date’s inbound population flow as the target tourist peak date corresponding to the future arrival time; S4025: Obtain the historical room reservation rate of the target hotel on the target tourist peak date corresponding to the future arrival time; S4026: Obtain the historical room reservation rates of other hotels on the target tourist peak dates corresponding to the future arrival times; S4027: Calculate the room reservation growth rate of the target hotel at the future arrival time based on the historical room reservation rates of the target hotel and other hotels at the future arrival time.

6. The hotel room reservation planning method combined with the travel itinerary as claimed in claim 1, characterized in that: In step S5, the travel cost from the target hotel to the waypoint includes the travel economic cost; Calculate the economic cost of travel by following these steps: S501: Calculate the walking distance between the target hotel and the waypoint; if the walking distance is greater than the distance threshold, execute step S502; otherwise, the travel economic cost is 0; S502: Obtaining the travel method from the target hotel to the passing point provided by the user; S503: Calculate the travel economic cost from the target hotel to the waypoint according to the travel mode from the target hotel to the waypoint.

7. The hotel room reservation planning method combined with the travel itinerary as claimed in claim 6, characterized in that: In step S5, the travel cost from the target hotel to the waypoint includes the travel time cost; Calculate the travel time cost by following the steps below: S511: Calculate the walking distance between the target hotel and the waypoint; if the walking distance is greater than the distance threshold, execute step S512; otherwise, calculate the travel time = walking distance / preset pace; S512: Obtaining the travel method from the target hotel to the passing point provided by the user; S513: Calculate travel time based on the travel mode from the target hotel to the waypoint; S514: Calculate travel time cost = travel time * time cost factor.

8. The hotel room reservation planning method combined with the travel itinerary as claimed in claim 7, characterized in that: In step S6, the comprehensive room booking cost = a room booking cost + b travel economic cost + c travel time cost; Where a, b, and c are the weights of room booking cost, travel economic cost, and travel time cost, respectively.

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