A smart travel method and system for low-carbon travel

Abstract

This invention discloses an intelligent travel method and system for low-carbon travel. The method includes: S1, periodically and automatically acquiring the latest flight carbon emission data from international and domestic aviation data platforms, and acquiring carbon emission data for ground transportation modes other than flights in virtual flights; S2, integrating flights and ground transportation modes to provide comprehensive travel solutions, and searching for travel results based on user-input travel requests; S3, splitting each travel result into segments, attaching fare information, flight and ground transportation mode information to each segment, generating and verifying travel results; S4, for each verified travel segment, calculating the per-minute carbon dioxide emissions per passenger in each segment based on the carbon emission data, and statistically calculating the total carbon emissions per passenger for the entire trip; S5, attaching and displaying the carbon emission data to each travel result. This invention displays travel carbon emission data, facilitating users to make environmentally friendly choices.

Description

Technical Field

[0001] This invention relates to a low-carbon travel technology, and more particularly to a smart travel method and system for low-carbon travel. Background Technology

[0002] In the process of globalization and modernization, the civil aviation industry, as a vital link connecting the world, has experienced continuous growth in both speed and scale. However, the resulting carbon emissions have become increasingly prominent, attracting widespread attention from the international community. According to statistics from the International Air Transport Association (IATA), the aviation industry accounts for approximately 2% of global anthropogenic carbon dioxide emissions, and this proportion is showing an upward trend year by year.

[0003] Faced with this challenge, although the aviation industry has taken a series of measures to improve fuel efficiency and reduce carbon emissions, such as improving aircraft design, optimizing routes and operating processes, there is still a lack of a comprehensive and systematic solution to manage the carbon footprint of air travel.

[0004] Existing technologies for carbon emissions management have significant shortcomings. First, most airlines and travel service platforms only offer itinerary planning based on a single mode of transportation (such as air travel), failing to fully leverage the potential of multimodal transport to reduce overall journey carbon emissions. Second, existing itinerary recommendation systems typically do not consider users' low-carbon travel preferences, lacking personalized low-carbon travel plans based on user travel preferences, historical data, and carbon emission targets. Furthermore, the integration of real-time fares with carbon emission data is insufficient, making it difficult for users to comprehensively assess the cost-effectiveness and environmental impact when searching and comparing different itinerary options. While some carbon offset programs exist, they are often disconnected from the itinerary planning process, requiring users to purchase carbon offset credits separately on different platforms or services—a process that is neither convenient nor transparent. Finally, users lack intuitive tools to compare the carbon emissions of different routes or modes of transportation when choosing travel options, limiting their ability to make environmentally friendly choices. Summary of the Invention

[0005] To address the aforementioned issues, this invention proposes an intelligent travel planning method and system for low-carbon travel. The system aims to recommend low-carbon solutions based on user travel preferences and carbon emission targets using a convenient and rapid algorithm, integrate different modes of transportation to optimize multimodal transport, and display real-time fare and carbon emission data to facilitate users' environmentally friendly choices.

[0006] To this end, the present invention provides a smart travel implementation method for low-carbon travel, comprising the following steps: S1. Regularly and automatically acquiring the latest flight carbon emission data from international and domestic aviation data platforms, and acquiring carbon emission data of ground transportation modes other than flights in virtual flights; S2. Integrating flights and ground transportation modes to provide comprehensive travel solutions, and searching for travel results based on the user's input travel request; S3. Dividing each travel result into segments, each segment representing a single mode of transportation, and attaching fare information, flight and ground transportation mode information after splitting to generate and verify travel results; S4. For each verified travel segment, calculating the carbon dioxide emissions per minute per unit passenger in each travel segment based on the carbon emission data of flights and ground transportation modes, and statistically calculating the total carbon emissions per unit passenger for the entire trip; S5. Attaching and displaying the carbon emission data information to each travel result.

[0007] According to another aspect of the present invention, a smart travel system for low-carbon travel is provided, comprising a data processing module, a multimodal transport module, a central database, a carbon offset calculation module, and a display module. The data processing module automatically retrieves the latest flight carbon emission data from international and domestic air travel information platforms monthly, calculates the per-minute carbon dioxide emissions per passenger for each flight, and stores it in the central database. The multimodal transport module retrieves carbon emission data for ground transportation modes other than flights in virtual flights, calculates the per-minute carbon dioxide emissions per passenger for the corresponding travel segment of the ground transportation mode, and stores it in the central database. The carbon offset calculation module integrates flights and ground transportation modes to provide comprehensive travel solutions and searches for travel results based on user-input travel requests. Each travel result is divided into segments, each segment representing a single mode of transportation. After division, fare information, flight and ground transportation mode information are linked to generate and verify travel results. For each verified travel segment, the total carbon emissions per passenger for the entire trip are calculated based on the per-minute carbon dioxide emissions per passenger in each segment. The carbon emission data is then linked to each travel result.

[0008] The present invention also provides a computer program product, including a computer program that, when executed, implements the steps of the above-described intelligent travel implementation method for low-carbon travel.

[0009] This invention integrates real-time flight data and multimodal transport options, enabling the system to provide users with comprehensive travel solutions, including direct and connecting flights, and even virtual flight options such as buses and subways. This comprehensive approach not only increases the likelihood of users choosing low-carbon travel options but also encourages green travel habits by prioritizing the display of trips with lower carbon emissions.

[0010] Furthermore, this invention helps airlines and transportation operators better understand the environmental impact of their operations by providing carbon emission data on trip outcomes, thereby optimizing operational strategies and further reducing carbon emissions. In the long run, the implementation of this technical solution will help drive the entire aviation and transportation industry towards a more sustainable future, contributing to the achievement of global carbon reduction goals.

[0011] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 A flowchart of a method for realizing low-carbon smart travel according to the present invention is shown.

[0014] Figure 2 A block diagram of a low-carbon intelligent travel system according to the present invention is shown;

[0015] Figure 3 A flowchart illustrating the operation of the data processing module in the system according to the present invention is shown;

[0016] Figure 4 A flowchart illustrating the operation of the multimodal transport module in the system according to the present invention is shown.

[0017] Figure 5 A CSV table of flight carbon emissions used in the system according to the present invention is shown; Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are also included.

[0019] like Figure 1 As shown, the low-carbon travel intelligent trip implementation method of the present invention includes the following steps S1-S5.

[0020] S1. Automatically retrieves the latest flight carbon emission data from international and domestic travel information platforms every month, and also retrieves carbon emission data for ground transportation modes other than flights in the virtual flight.

[0021] S2 integrates flight and ground transportation to provide comprehensive travel solutions and searches for travel results based on the user's input travel request.

[0022] S3. Divide each trip result into segments, each segment representing a single mode of transportation. After splitting, link the fare information, flight and ground transportation information to generate and verify the trip result.

[0023] S4. For each verified travel segment, calculate the carbon dioxide emissions per minute per passenger in each travel segment based on the carbon emission data of flights and ground transportation, and then calculate the total carbon emissions per passenger for the entire trip.

[0024] S5. Add and display carbon emission data to the results of each trip.

[0025] like Figure 2 As shown, the intelligent travel system for low-carbon travel of the present invention includes a data processing module, a multimodal transport module, a carbon compensation calculation module, and a display module.

[0026] The intelligent travel solution for low-carbon travel of the present invention will be described in detail below in conjunction with the intelligent travel system and implementation method.

[0027] As a key component of the intelligent travel solution for low-carbon travel in this invention, the data processing module plays a crucial role. Its core task is to automatically retrieve the latest flight carbon emission data from international and domestic air travel information platforms every month. Simultaneously, the multimodal transport module also collects carbon emission data from other modes of transportation, integrates it, carefully organizes it, and stores it in a central database.

[0028] This central database not only serves as a data storage hub, but also forms the basis for the system's carbon emission calculation module.

[0029] When a user initiates a trip request, the system will respond quickly, calculate all possible direct flights or flights with stopovers for refueling on the same flight and connecting flights, and extract carbon emission data generated by the data processing module to provide the user with detailed carbon emission information for each trip.

[0030] For trips involving virtual flights, such as those involving complex multimodal transport such as buses, ships, and coaches, the system delegates these tasks to a dedicated multimodal transport module.

[0031] This multimodal transport module breaks down the transportation information used in each segment of the journey and reads the carbon emission data corresponding to the virtual flights from the database to ensure the integrity of the carbon footprint information for the entire journey.

[0032] Subsequently, this processed carbon emission data will be sent to the carbon offset calculation module for accurate carbon emission calculation.

[0033] Ultimately, the system links the calculated total carbon emissions to the trip, displaying the total carbon emissions of the trip intuitively in the user's trip results, allowing users to clearly understand the overall environmental impact of their chosen trip.

[0034] The data processing module is mainly responsible for data collection and preprocessing of flight carbon emissions.

[0035] like Figure 3 As shown, the pretreatment of carbon emissions from flights mainly involves the following three key steps:

[0036] 1. Calculate the total carbon dioxide emissions of the flight.

[0037] a. Query the flight schedule database based on the selected route: If a match is found, up to 10 aircraft types are available for the user to choose from. By default, the most frequently used aircraft type is pre-selected. If no match is found, the (great circle) distance between the departure and destination airports is calculated based on the route. Up to 10 aircraft types with similar flight distances are available for the user to choose from. By default, the most frequently used aircraft type is pre-selected.

[0038] b. Total flight time (ground congestion time, from gate to gate) depends on the route and the aircraft selected. Even when operating the same aircraft type, the scheduled flight time for a particular route may differ. In these cases, a weighted average flight time is used.

[0039] c. The IATACO2Connect calculator uses a time-based algorithm. Therefore, the flight time is multiplied by the fuel consumption coefficient (in kilograms per minute) for the selected aircraft type. The total fuel consumption for a single flight is then calculated.

[0040] d. Multiply the fuel consumption by the ICAO CORSIA jet kerosene carbon emission factor of 3.16 to obtain the total carbon dioxide emissions of the flight.

[0041] 2. Allocate carbon dioxide emissions between passengers and (belly) cargo.

[0042] a. The estimated number of passengers for a flight is calculated based on the cabin configuration and load factor of the selected aircraft type.

[0043] b. The total weight of all passengers (and their luggage) is calculated by multiplying the number of passengers by the standard weight of 100 kg.

[0044] c. The estimated weight of cargo (under the fuselage) is determined based on the aircraft type.

[0045] d. Calculate the ratio of total passenger weight to total weight (passengers + belly cargo).

[0046] e. Multiplying the flight's total CO2 emissions by this ratio gives the share of total emissions from all passengers. The difference between the flight's total CO2 emissions and the total CO2 emissions from all passengers is the CO2 emissions allocated to belly cargo.

[0047] 3. Allocate carbon emissions to each passenger based on cabin class / travel category.

[0048] a. For each cabin class (economy, premium economy, business or first class), the expected number of seats in the cabin depends on the type of aircraft selected.

[0049] b. Based on cabin class, CO2 emissions are allocated to passengers according to the total CO2 emissions of all passengers and the ratio of "cabin class factor of the selected cabin class" to "total of all cabin classes (number of seats in the cabin class * cabin class factor)".

[0050] c. The cabin class selected by the passenger is used to calculate and display carbon dioxide emissions.

[0051] II. The multimodal transport optimization module is mainly responsible for collecting carbon emission data from other modes of transportation and performing preprocessing.

[0052] like Figure 4 As shown, other modes of transportation import data through an external multimodal transport module.

[0053] For example, for buses, it is necessary to collect data on bus fuel consumption in liters, train travel distance, and bus carbon dioxide emissions (kg) = fuel consumption in liters × 0.785.

[0054] The carbon emissions of a train can be calculated by the distance it travels. The specific formula is: Carbon dioxide emissions of train travel (kg) = Distance traveled (km) × 0.04.

[0055] The carbon emissions of ships are calculated by the ship's partners based on actual measurement data, and then the carbon emission data is imported into the database for calculation.

[0056] The multimodal transport module's input fields include the origin and destination codes for each mode of transport, bus fuel consumption in liters, actual train distance traveled, actual ship carbon emissions, predicted travel time, predicted actual passenger capacity, and total passenger capacity. The output is a CSV table of multimodal transport vehicles. The table structure includes: transport type (e.g., BUS, TRAIN, BOAT); transport model (e.g., tram, diesel, bullet train, high-speed rail, ship); month; passenger load factor; and CO2 emissions per person per minute.

[0057] This multimodal transport module calculates the load factor, or the ratio of predicted passenger volume to total passenger volume, by forecasting actual passenger load on journeys. Using load factor and emissions data, the average CO2 emissions per passenger during the journey, as well as their emissions per minute, can be further calculated. This entire calculation process helps analyze the environmental impact of different transport modes and provides decision support for improving transport efficiency and reducing carbon footprint.

[0058] III. The carbon emission calculation module is mainly responsible for integrating different modes of transportation and providing comprehensive travel solutions.

[0059] The carbon emission calculation module first receives the user's trip request, including information such as departure point, destination, departure date, and number of passengers, and then searches for trip results.

[0060] This system breaks down complex trips into simple segments, each representing a single mode of transportation, such as direct flights, connecting flights, or virtual flights (buses, subways, ships, buses, etc.).

[0061] After splitting the trip, the system will link fare information to calculate the cost for each segment and link detailed flight and virtual flight information to ensure that all trip details are accurately recorded. When generating trip results, the system will verify each trip according to the rules set by each airline to ensure that all trips meet the requirements of safety, convenience, and cost control.

[0062] The verified trip results will be further processed to calculate the carbon emissions for each trip. At this point, the system will assign a corresponding carbon emission amount to each trip segment based on the CSV file generated by the data processing module. The system will then sum the carbon emissions of all trip segments to obtain the total carbon emissions for the entire trip.

[0063] When displaying all trip results, the system includes carbon emission data for each trip, allowing users to clearly see the carbon emissions for each trip. Users can also choose to prioritize trips with lower carbon emissions. This not only helps users choose more environmentally friendly travel options but also encourages low-carbon travel habits, contributing to achieving carbon peaking goals.

[0064] To ensure system security and performance, all user data transmissions are encrypted using HTTPS.

[0065] The system implements multi-layered security measures, including data encryption, access control, and security auditing. In terms of performance, the system uses Redis to cache frequently queried carbon emission data, reducing database access frequency, and employs load balancing technology to distribute requests across multiple servers under high traffic conditions. For system monitoring and maintenance, Prometheus and Grafana are used to monitor system performance, and ELK stack logging and analysis logs are performed. Through these measures, the system ensures data security and privacy while providing efficient service.

[0066] The following is an example of how carbon emissions during aircraft flight are calculated.

[0067] Calculate total fuel consumption: First, based on the flight time (145 minutes) and the fuel consumption rate per minute (80 kg / min), calculate the total fuel consumption (11,600 kg).

[0068] Calculate the total CO2 emissions: Next, multiply the total fuel consumption (11,600 kg) by the emission factor (3.16 kg of CO2 per kilogram of fuel) to obtain the total CO2 emissions (36,656 kg of CO2).

[0069] Calculate the total passenger weight: Then, based on the total number of passengers (240 people) and the average weight per person (100 kg), the total passenger weight (24,000 kg) is calculated.

[0070] Calculate the total weight of passengers and cargo: Using the total weight of passengers (24,000 kg) and the percentage of passenger weight (90%), calculate the total weight of passengers and cargo (24,000 kg + 2,666 kg).

[0071] Calculate passenger CO2 emissions: Multiply the total CO2 emissions (36,656 kg CO2) by the passenger weight percentage (90%) to get the passenger CO2 emissions (32,990 kg CO2).

[0072] Calculating CO2 emissions for passengers in different cabin classes: Finally, based on the number of passengers in Economy, Premium Economy, Business, and First Class and their respective cabin class coefficients, the CO2 emissions for each cabin class are calculated. Specifically, the number of passengers in each cabin class is multiplied by the corresponding cabin class coefficient, and then summed. This calculation process takes into account flight time, fuel consumption rate, passenger and cargo weight, and passenger distribution across different cabin classes to estimate the overall carbon emissions of the flight.

[0073] In the intelligent travel planning system for low-carbon travel, the carbon emission calculation module covers the entire process from data collection to final display. Below are three specific implementation examples, corresponding to direct flights, connecting flights with stopovers, and air-rail intermodal transport, respectively.

[0074] Example 1: Carbon emission calculation for direct flights

[0075] Suppose a user plans to fly directly from Beijing (PEK) to Shanghai (SHA). The system will perform the following operations: The user first selects "Beijing" as the departure city, "Shanghai" as the destination, economy class, and sets the departure date to "2024-10-01" on the system interface. The system then splits the itinerary, assuming it generates a direct flight route from Beijing (PEK) to Shanghai (SHA). Next, the system will integrate flight information, locate all available direct flights from PEK to SHA, including flights using aircraft type MU 319, and obtain detailed information including flight number, estimated departure and arrival times. Based on the trip results that have passed rule validation, the system begins to calculate carbon emissions. It matches the airline, aircraft type, and cabin class in the trip results with the data in the CSV file. For example, based on airline MU, aircraft type 319, and economy class, it extracts the CO2 emissions per person per minute. Assuming a flight time of 155 minutes, the system calculates the carbon emissions for an economy class passenger on this trip as 155 x 1.1180827 = 173.3028185 kg / person. Finally, the system displays the trip results, including flight details, fare details, and the corresponding carbon emissions for each passenger on this trip.

[0076] Example 2: Carbon emission calculation for intermediate stopovers on connecting flights

[0077] Suppose a user plans to travel from Beijing (PEK) to New York (JFK) and selects a flight with a layover in Seoul (ICN). During the user input processing phase, the user enters "Beijing" as the departure city, "New York" as the destination, and sets the departure date to "2024-10-01". Next, the system automatically provides a connecting flight option when searching for routes, splitting the entire trip into two segments: from PEK to ICN, and then from ICN to JFK. The system then links the flight information, searching and listing all available flights from PEK to ICN and from ICN to JFK. When calculating carbon emissions, the system calculates the carbon emissions for each segment separately. For example, the flight time from PEK to ICN is 180 minutes, and the flight time from ICN to JFK is 15 hours (900 minutes), and it is assumed that the user travels on an MU319 aircraft for the PEK to ICN segment and an 31B aircraft for the ICN to JFK segment. Given that the passenger selected economy class, the system will calculate the passenger's total carbon emissions for the entire trip as 180 minutes multiplied by 1.1180827 kg per minute, plus 15 hours multiplied by 1.1180827 kg per hour. Finally, the system will display the trip results, including details of connecting flights and the total carbon emissions.

[0078] Example 3: Carbon Emission Calculation of Air-Rail Intermodal Transport

[0079] Suppose a user plans to travel from Beijing (PEK) to New York (JFK) and selects air-rail intermodal transport: During the user input processing phase, the user enters "Beijing" as the departure point, "New York" as the destination, "2024-10-01" as the departure date, and selects "air-rail intermodal transport" as the mode of transport. The system then breaks down the trip into two main segments: first, a virtual high-speed rail flight from PEK to Shanghai Hongqiao Airport (SHA), and then an air intermodal transport from Shanghai to JFK. The system then links specific information for each transport segment, including flight and train timetables, aircraft types, and estimated travel times. When calculating carbon emissions, the system will calculate the carbon emissions for each transport segment separately. Taking a train journey from PEK to SHA as 120 minutes and a flight journey from SHA to JFK as 1200 minutes, assuming the PEK to SHA segment is by train and the SHA to JFK segment is by MU913 aircraft, and the user selects economy class, the system will calculate the passenger's total carbon emissions for the entire trip as follows: 120 minutes multiplied by the carbon emissions per minute for this type of vehicle per passenger in the multimodal transport table (in kilograms), plus 1200 minutes multiplied by the carbon emissions per minute for this type of vehicle per passenger in the flight table. Furthermore, the system also needs to consider the carbon emissions from the bus or subway connection from SHA to Shanghai Railway Station. Assuming this segment takes 30 minutes, the carbon emissions per minute for this type of vehicle per passenger in the multimodal transport table should be multiplied again. The final carbon emissions figure is then calculated by adding these three sets of data together. The system will display the trip results, including detailed information for each transport segment and the total carbon emissions for the entire air-rail intermodal journey.

[0080] These examples demonstrate how the system calculates corresponding carbon emissions based on different travel needs and provides this information to users as a reference for their travel decisions.

[0081] The following describes a CSV table of flight carbon emissions (e.g., Figure 5 (As shown), the table includes airlines, aircraft types, and months. It lists Economy, Premium Economy, Business, and First Class. The data in the table uses CO2 emissions per minute per person. The system should look up CO2 estimates based on the following combinations of airlines, aircraft types, and months:

[0082] a. If a match is found between the airline, aircraft, and travel month, the value for each travel class (marker = 1) reflecting the airline-specific data will be displayed.

[0083] b. If no match is found, the value for each travel cabin class that reflects general industry data for that aircraft type will be displayed (marker = 2).

[0084] The system should multiply column (4)Econ (5)Prem (6)Bi z (7)First (depending on the case) by the travel time in minutes to obtain the final CO2 estimate.

[0085] This system can also integrate carbon offsetting functionality into trip planning, allowing users to directly purchase carbon offset credits to achieve carbon neutrality. Furthermore, the system provides a carbon emissions map visualization tool, showing the carbon emission distribution of different routes or modes of transportation, helping users understand the environmental impact of different choices.

[0086] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for realizing intelligent travel with low carbon emissions, characterized in that... This includes the following steps: S1. Regularly and automatically obtain the latest flight carbon emission data from international and domestic aviation data platforms, and obtain carbon emission data of ground transportation modes other than flights in virtual flights; S2 integrates air and ground transportation to provide comprehensive travel solutions and searches for travel results based on the user's input travel request; S3. Divide each trip result into segments, each trip segment representing a single mode of transportation. After splitting, link the fare information, flight and ground transportation information to generate and verify the trip results. S4. For each trip segment that passes the verification, calculate the carbon dioxide emissions per minute per passenger in each trip segment based on the carbon emission data of flights and ground transportation, and then calculate the total carbon emissions per passenger for the entire trip. Based on carbon emission data from flights and ground transportation, calculate the carbon dioxide emissions per minute per passenger for each travel segment, including the carbon dioxide emissions per minute per passenger for each flight travel segment and the carbon dioxide emissions per minute per passenger for each ground transportation travel segment. Calculating the carbon dioxide emissions per minute per passenger for a flight segment involves the following steps: S41. Calculate the total carbon dioxide emissions of a flight in minutes. S42. Allocate carbon dioxide emissions between passengers and belly cargo; S43. Allocate carbon emissions to each passenger based on cabin class / travel class; Calculating the carbon dioxide emissions per minute per passenger for a given travel segment using ground transportation methods involves the following steps: S44. Calculate the passenger load factor, i.e., the ratio of predicted passenger load to total passenger load, by predicting the actual passenger load of the trip. S45. Using passenger load factor and emissions data, calculate the average carbon dioxide emissions per passenger during the trip, as well as their emissions per minute. S5. Add and display carbon emission data to the results of each trip.

2. The intelligent trip implementation method for low-carbon travel according to claim 1, characterized in that... The trip request includes departure point, destination, departure date, flight mode preference, and cabin / travel class preference. The flight mode preference includes direct flights, connecting flights, and virtual flights. The virtual flight is a mode of transportation that combines air and ground transportation.

3. The intelligent trip implementation method for low-carbon travel according to claim 1, characterized in that... All trip results are sorted and displayed in ascending order of total carbon emissions.

4. The intelligent trip implementation method for low-carbon travel according to claim 1, characterized in that... The carbon emission data includes the total carbon emissions per passenger for the entire journey and the carbon dioxide emissions per passenger per minute for each segment of the journey.

5. The intelligent trip implementation method for low-carbon travel according to claim 1, characterized in that... The integrated travel solution includes direct flights, connecting flights, and virtual flights.

6. A smart travel system for low-carbon travel, characterized in that, It includes a data processing module, a multimodal transport module, a carbon offset calculation module, and a display module, among which: The data processing module is used to automatically obtain the latest flight carbon emission data from international and domestic travel information platforms every month, calculate the carbon dioxide emissions per minute per passenger for each flight, and store it in the central database. The multimodal transport module is used to acquire carbon emission data of ground transportation modes other than flights in the virtual flight, calculate the carbon dioxide emissions per minute per passenger in the corresponding travel segment of the ground transportation mode, and store it in the central database. The carbon offset calculation module is used to integrate flight and ground transportation modes to provide comprehensive travel solutions and search for travel results based on the user's input travel request. Each travel result is divided into segments, with each segment representing a single mode of transportation. After the segmentation, fare information, flight and ground transportation information are linked to generate travel results and verify them. For each travel segment that passes verification, the total carbon emissions per passenger for the entire trip are calculated based on the carbon dioxide emissions per minute allocated to each passenger in each travel segment. Based on carbon emission data from flights and ground transportation, calculate the carbon dioxide emissions per minute per passenger for each travel segment, including the carbon dioxide emissions per minute per passenger for each flight travel segment and the carbon dioxide emissions per minute per passenger for each ground transportation travel segment. Calculating the carbon dioxide emissions per minute per passenger for a flight segment involves the following steps: S41. Calculate the total carbon dioxide emissions of a flight in minutes. S42. Allocate carbon dioxide emissions between passengers and belly cargo; S43. Allocate carbon emissions to each passenger based on cabin class / travel class; Calculating the carbon dioxide emissions per minute per passenger for a given travel segment using ground transportation methods involves the following steps: S44. Calculate the passenger load factor, i.e., the ratio of predicted passenger load to total passenger load, by predicting the actual passenger load of the trip. S45. Using passenger load factor and emissions data, calculate the average carbon dioxide emissions per passenger during the trip, as well as their emissions per minute. Carbon emission data is appended to the results of each trip.

7. A computer program product, comprising a computer program, characterized in that, When executed, the program is used to implement the steps of the smart trip implementation method for low-carbon travel according to any one of claims 1 to 5.

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