Travel route planning method and system based on public travel

Abstract

The invention relates to the technical field of travel route planning, in particular to a travel route planning method based on public travel. The method comprises the following steps: A1, obtaining a target position input by a user and a current position of the user, and generating a planning topological graph corresponding to the target position and the current position of the user based on a regional road planning graph; a2, generating a planning route group, a wharf node corresponding to each planning route in the planning route group and theoretical arrival time based on the planning topological graph by using a preset route planning sub-strategy; and A3, calculating the actual cost value of each planned route according to the wharf node corresponding to each planned route and the theoretical arrival time on the basis of the passenger route diagram by using a preset cost calculation sub-strategy, and outputting the planned route with the lowest actual cost value. According to the route planning method based on the public trip, the route planning accuracy is improved, and the planning deviation caused by no ticket is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of itinerary planning, and in particular to a itinerary planning method and system based on public travel. Background Art

[0002] With the development of big data technology, urban bus route planning can now be evaluated comprehensively and efficiently by modern scientific and technological means. This includes collecting various data related to bus planning, such as urban population data, traffic flow data, bus station location and operation data, etc. Through in-depth analysis of these data, different types of data analysis results can be obtained, which can assist in bus route planning.

[0003] In the field of transportation planning, due to the existence of various uncontrollable factors, such as weather changes, traffic congestion, ticketing status, etc., the originally planned route may have problems in actual execution. For example, passengers arrive at the designated shipping terminal according to the planned route, but find that there are no available tickets for some reason (such as ticketing system failure, temporary flight cancellation, etc.). This situation is difficult for the planning system to predict. In addition, compared with other modes of transportation, shipping often has more limited route options. In some remote areas or niche routes, shipping schedules may be very rare, and passengers may even have to wait for a whole day to wait for the next ship. This uncertainty not only brings inconvenience to passengers, but also poses higher challenges to the accuracy and reliability of the transportation planning system.

[0004] The Chinese patent "A multi-tourism itinerary planning method and intelligent system based on density ant colony algorithm", publication number: CN118134221A, publication date: June 4, 2024, specifically discloses the method including: receiving and processing input user needs; extracting scenic spot information matching the received user needs from a database established based on user needs; importing the extracted scenic spot information into the density ant colony optimization model to obtain solutions corresponding to multiple heuristic information sources; sending multiple heuristic information sources and their corresponding solutions to the large language model for enhanced generation of travel itinerary planning schemes, and transmitting the generated multiple alternative travel itinerary planning schemes to the user. This scheme only matches the scenic spot information required by the user, and also performs user itinerary planning based on global user habits. It has a low degree of adaptability to the user himself and cannot improve the user experience. Summary of the invention

[0005] The present invention aims at the planning deviation caused by not considering the actual flight ticket sales situation or queuing situation in the route planning process in the prior art, and provides an itinerary planning method and system based on public travel. The system obtains and processes the user's location information in real time, obtains all roads between the target location and the current location and the traffic corresponding to the roads based on the regional road planning map according to the user's target location and current location, and adopts a preset path planning sub-strategy to generate a variety of planned routes according to different roads and traffic conditions. Each planned route includes a corresponding terminal node and a theoretical arrival time. The actual cost value of each planned route is calculated through a preset cost calculation sub-strategy, and the planned path with the lowest actual cost value is output, thereby ensuring that the user can obtain the optimal travel plan, improving the route planning efficiency, and obtaining the route with the lowest user cost value based on the passenger route map, which can provide users with more efficient and convenient travel suggestions, incorporate the impact of ship terminal node differences on the itinerary, and improve the accuracy of itinerary planning on the island.

[0006] To achieve the above technical objectives, the present invention provides a technical solution, which is a method for itinerary planning based on public transportation, comprising the following steps: A1: obtaining the target location input by the user and the user's current location, and generating a planning topology map corresponding to the target location and the user's current location based on the regional road planning map; A2: generating a planning route group and the corresponding terminal node and theoretical arrival time of each planning route in the planning route group based on the planning topology map using a preset path planning sub-strategy; A3: calculating the actual cost value of each planning route based on the passenger route map according to the corresponding terminal node and theoretical arrival time of each planning route using a preset cost calculation sub-strategy, and outputting the planning path with the lowest actual cost value.

[0007] In this embodiment, the system acquires and processes the user's location information in real time, obtains all roads and the corresponding traffic between the target location and the current location based on the regional road planning map according to the user's target location and current location, and uses a preset path planning sub-strategy to generate multiple planned routes according to different road and traffic conditions. Each planned route includes a corresponding terminal node and a theoretical arrival time. The actual cost of each planned route is calculated through a preset cost calculation sub-strategy, and the planned path with the lowest actual cost is output, ensuring that the user can obtain the optimal travel plan, improving the efficiency of route planning, and obtaining the route with the lowest user cost based on the passenger route map, which can provide users with more efficient and convenient travel suggestions, incorporate the impact of ship terminal nodes on the itinerary, and improve the accuracy of itinerary planning on the island.

[0008] The present invention is further configured as follows: in step A3, the actual cost value of each planned route is calculated based on the passenger route map according to the corresponding terminal node of each planned route and the theoretical arrival time using a preset cost calculation sub-strategy, including: obtaining cost basic information based on the passenger route map; matching the cost basic information according to the corresponding terminal node of each planned route and the theoretical arrival time, and the preset cost calculation sub-strategy calculates the actual cost value of each planned route according to the matched cost basic information.

[0009] The present invention is further configured as follows: in step A3, the cost basic information includes: flight plan, flight time, queuing time and delay risk.

[0010] The present invention is further configured as follows: in step A3, the queuing time includes: the queuing time for ticket purchase and the intermediate time for ticket checking.

[0011] The present invention is further configured as follows: in step A3, the preset cost calculation sub-strategy calculates the actual cost value of each planned route according to the matched cost basic information, including: calculating the flight waiting cost value, the voyage cost value, the queuing cost value and the delay cost value according to the corresponding terminal node and the theoretical arrival time; calculating the actual cost value of each planned route according to the flight waiting cost value, the voyage cost value, the queuing cost value and the delay cost value according to the preset weights.

[0012] The present invention is further configured as follows: in step A3, the actual cost of each planned route is calculated according to preset weights using the flight waiting cost, the flight distance cost, the queuing cost and the delay cost, including: obtaining user historical behavior data, and calculating, according to the user historical behavior data, a first preset weight corresponding to the flight waiting cost, a second preset weight corresponding to the flight distance cost, a third preset weight corresponding to the queuing cost, and a fourth preset weight corresponding to the delay cost.

[0013] The present invention is further configured as follows: in step A3, the calculation of the flight waiting cost value based on the corresponding terminal node and the theoretical arrival time includes: obtaining the flight schedule closest to the theoretical arrival time based on the flight plan of the corresponding terminal node; and calculating the difference between the flight schedule and the theoretical arrival time as the flight waiting cost value.

[0014] The present invention is further configured as follows: in step A3, the preset cost calculation sub-strategy calculates the actual cost value of each planned route according to the matched cost basic information and also includes: obtaining the predicted sold-out time of each flight in the flight plan based on the global user historical behavior data; obtaining the theoretical ticket purchase time according to the theoretical arrival time and the queuing cost value; obtaining the predicted flight schedule based on the predicted sold-out time and the theoretical ticket purchase time; and obtaining the flight waiting cost value based on the predicted flight schedule and the theoretical arrival time.

[0015] The present invention is further configured as follows: in step A3, the calculation of the queuing cost value according to the corresponding terminal node and the theoretical arrival time includes: obtaining the predicted number of queues at the corresponding terminal node under the theoretical arrival time based on the global user current behavior data; Based on the global user historical behavior data, the queue time correlation curve is obtained; based on the predicted number of queues and the queue time correlation curve, the queue cost value is obtained.

[0016] Another technical solution provided by the present invention is a trip planning system based on public transportation, which is used to implement the above method, including: a user end and a terminal; the user end is configured with a path planning strategy, which is used to output a planned route group corresponding to the target location and the user's current location, and the terminal node corresponding to each planned route in the planned route group and the theoretical arrival time; the terminal terminal is configured with a cost calculation strategy, which is used to calculate the actual cost value of each planned route, and output the planned path with the lowest actual cost value; wherein the user end generates a cost request instruction according to the terminal node and the theoretical arrival time, and sends the cost request instruction to the corresponding terminal terminal, and the terminal terminal outputs the planned path with the lowest actual cost value according to the cost request instruction and feeds it back to the user end.

[0017] The beneficial effects of the present invention are as follows: (1) The system acquires and processes the user's location information in real time, obtains all roads between the target location and the current location and the corresponding traffic on the roads based on the regional road planning map according to the user's target location and current location, and adopts a preset path planning sub-strategy to generate multiple planned routes according to different road and traffic conditions. Each planned route includes a corresponding terminal node and a theoretical arrival time. The actual cost value of each planned route is calculated through a preset cost calculation sub-strategy, and the planned path with the lowest actual cost value is output, thereby ensuring that the user can obtain the optimal travel plan, improving the route planning efficiency, and obtaining the route with the lowest user cost value based on the passenger route map, which can provide users with more efficient and convenient travel suggestions, incorporate the impact of ship terminal node differences on the itinerary, and improve the accuracy of itinerary planning on the island.

[0018] (2) By combining global user historical behavior data to predict the time when the flight tickets are sold out, and further calculating the flight waiting cost, the preset cost calculation sub-strategy incorporates global user dynamic factors into the calculation of the actual cost value to avoid the situation where the user arrives before the flight time but has no ticket, optimizes the user's ticket purchase strategy, reduces the risk of missing the trip due to the flight being sold out, and more accurately recommends the route planning corresponding to the appropriate flight. At the same time, considering the dynamic changes of the predicted time when the ticket is sold out and the theoretical time for ticket purchase, the flight waiting cost can be adjusted in real time, providing timely feedback and suggestions for the user's travel decision. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flowchart of the method for itinerary planning based on public transportation of the present invention. DETAILED DESCRIPTION

[0020] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific implementation method described herein is only an optimal embodiment of the present invention, which is only used to explain the present invention and does not limit the scope of protection of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0021] like Figure 1 As shown, as a first embodiment of the present invention, a method for itinerary planning based on public transportation includes the following steps: A1: obtaining a target location and a current location of the user inputted by a user, and generating a planning topology map corresponding to the target location and the current location of the user based on a regional road planning map; A2: Generate a planning route group based on the planning topology graph using the preset path planning sub-strategy and the corresponding terminal node and theoretical arrival time of each planning route in the planning route group; A3: The preset cost calculation sub-strategy is used to calculate the actual cost of each planned route based on the passenger route map according to the corresponding terminal nodes and theoretical arrival time of each planned route, and the planned path with the lowest actual cost is output.

[0022] In this embodiment, the system acquires and processes the user's location information in real time, obtains all roads and the corresponding traffic between the target location and the current location based on the regional road planning map according to the user's target location and current location, and uses a preset path planning sub-strategy to generate multiple planned routes according to different road and traffic conditions. Each planned route includes a corresponding terminal node and a theoretical arrival time. The actual cost of each planned route is calculated through a preset cost calculation sub-strategy, and the planned path with the lowest actual cost is output, ensuring that the user can obtain the optimal travel plan, improving the efficiency of route planning, and obtaining the route with the lowest user cost based on the passenger route map, which can provide users with more efficient and convenient travel suggestions, incorporate the impact of ship terminal nodes on the itinerary, and improve the accuracy of itinerary planning on the island.

[0023] Specifically, in step A3, the actual cost value of each planned route is calculated based on the passenger route map according to the corresponding terminal node of each planned route and the theoretical arrival time using the preset cost calculation sub-strategy, including: Obtain cost basic information based on passenger route map; According to the matching cost basic information of the corresponding terminal node and the theoretical arrival time of each planned route, the preset cost calculation sub-strategy calculates the actual cost value of each planned route according to the matched cost basic information.

[0024] The cost basis information includes: Flight schedules, flight times, queue times and risk of delays.

[0025] Based on the passenger route map, the passenger route situation corresponding to each terminal node can be obtained as the cost basic information. The theoretical arrival time can be used to obtain the flight schedule of the terminal node closest to the theoretical arrival time, and the flight departure time and voyage time can be obtained. At the same time, the queuing time and delay risk can be predicted based on the theoretical arrival time. By evaluating the actual cost of different planned routes, that is, the actual cost value, the optimal route selection can be obtained, thereby improving the accuracy of route planning.

[0026] The target location and the current location of the user are obtained, and a planning topology map corresponding to the target location and the current location of the user is generated based on the regional road planning map. The planning route group and the corresponding terminal node and theoretical arrival time of each planning route in the planning route group are generated based on the planning topology map with the preset path planning sub-strategy. According to the regional road planning map, the routes to each terminal node and the road conditions corresponding to the routes can be obtained. The planning is performed according to the routes and road conditions, and the routes that can lead to the corresponding terminal nodes are connected. The theoretical arrival time is calculated according to the road conditions, and the planning route group and the corresponding terminal node and theoretical arrival time of each planning route in the planning route group are obtained.

[0027] In this embodiment, the queuing time includes: The queue time for purchasing tickets and the intermediate time for ticket checking.

[0028] Although there are online ticket purchases, some routes also require on-site ticket purchases, which will result in extra queuing time. In addition, the distance between the ticket purchase office and the ticket check-in office is different at different terminals. It is necessary to provide users with route planning from the ticket purchase office to the ticket check-in office and reserve time for ticket check-in to avoid missing flights due to failure to arrive at the ticket check-in office on time after purchasing tickets. The queuing time at this time is: T L =t p +t m ; Among them, T L is the queuing time, t p is the queuing time for ticket purchase, t m This is the mid-term ticket checking time.

[0029] It is understandable that the ticket purchase queue time and the ticket checking mid-term time are both predicted times, which can be obtained by constructing a relevant neural network learning model or a linear regression analysis curve based on the historical ticket purchase queue time and the historical ticket checking mid-term time.

[0030] The preset cost calculation sub-strategy calculates the actual cost value of each planned route according to the matched cost basic information, including: calculating the flight waiting cost value, the voyage cost value, the queuing cost value and the delay cost value according to the corresponding terminal node and the theoretical arrival time; The actual cost of each planned route is calculated based on the flight waiting cost, flight distance cost, queue cost and delay cost according to preset weights.

[0031] Multiple preset cost calculation sub-strategies can be set, such as multiple preset cost calculation sub-strategies based on different calculation factor weight coefficients. At this time, each preset cost calculation sub-strategy corresponds to a user demand. Similarly, multiple preset path planning sub-strategies are also set, corresponding to different user demands, that is, step A2 also includes: Set planning factor weight coefficients based on user needs and build preset path planning sub-strategies based on different planning factor weight coefficients; Obtain current user needs and match the corresponding preset path planning sub-strategy according to the current user needs.

[0032] Step A3 also includes: Set the calculation factor weight coefficients based on user needs and build preset cost calculation sub-strategies based on different preset weights; The sub-strategy is calculated based on the preset cost matching the current user needs.

[0033] User needs include at least: fastest arrival, shortest waiting, and comfort. For example, when the user needs to arrive the fastest, the matched preset path planning sub-strategy and preset cost calculation sub-strategy are the sub-strategies with the largest weight of the shortest time. The preset path planning sub-strategy is used to preferentially screen out some planned paths that do not meet user needs, thereby reducing the amount of subsequent cost calculations and improving path planning efficiency. In other cases, in order to make path planning more accurate, planned paths that do not meet user needs can also be retained and sorted according to the situation of meeting user needs, providing users with more choices for customers to choose according to their actual needs, thereby avoiding deviations caused by the inability of demand options to fully adapt to users.

[0034] As a second embodiment of the present invention, the actual cost of each planned route is calculated according to the flight waiting cost, the flight distance cost, the queue cost and the delay cost according to the preset weights, including: Obtain user historical behavior data, and calculate a first preset weight corresponding to the flight waiting cost value, a second preset weight corresponding to the flight cost value, a third preset weight corresponding to the queuing cost value, and a fourth preset weight corresponding to the delay cost value based on the user's historical behavior data.

[0035] By dynamically adjusting weights based on user behavior data, the actual cost of each planned route can be calculated to more accurately reflect the user's true intentions and priorities. This helps the system provide users with more reasonable and efficient travel suggestions, thereby optimizing users' travel decisions. At the same time, by accurately calculating the actual cost, the system can better balance the cost-effectiveness of different flights, routes, queues and delays, and can provide a reference for passenger route adjustments, thereby adjusting flight plans, reducing unnecessary flight waste, and improving overall operational efficiency.

[0036] In this case, the actual cost value of each planned route is calculated based on the passenger route map according to the corresponding terminal nodes and theoretical arrival time of each planned route using the preset cost calculation sub-strategy, and the planned path with the lowest actual cost value is output as: minF(i)=ω1T w(i) +ω2T c(i) +ω3T L(i) +ω4T y(i) ; Among them, F(i) is the actual cost value of the i-th planned route, ω1 is the first preset weight, T w(i) is the flight waiting cost of the ith planned route, ω2 is the second preset weight, T c(i) is the cost of the voyage of the ith planned route, ω3 is the third preset weight, T L(i) is the queuing cost of the ith planned route, ω4 is the fourth preset weight, T y(i) is the delay cost of the i-th planned route.

[0037] The first preset weight, the second preset weight, the third preset weight and the fourth preset weight are obtained based on the corresponding cost value ratio of each actual route in the user's historical behavior data.

[0038] The flight waiting cost is calculated based on the corresponding terminal node and theoretical arrival time, including: According to the flight plan of the corresponding terminal node, the flight closest to the theoretical arrival time is obtained; Calculate the difference between the flight schedule and the theoretical arrival time as the flight waiting cost.

[0039] At this time, the flight waiting cost is: T w =t h -t l ; Among them, t h is the flight time, t l is the theoretical arrival time.

[0040] Since tickets need to be purchased on site, the difference between the flight time and the theoretical arrival time also includes the queuing time. Therefore, the flight waiting cost is: T w ′=t h -t l -t p -t m .

[0041] Since the cost of queuing time and waiting time is different for different users, for example, some users can accept longer waiting time but cannot accept long queues, therefore, the user waiting time and user queuing time are calculated separately to meet the needs of different users. In some cases, users may think that queuing time and waiting time are superimposed factors, that is, the waiting time in the queue will be subjectively calculated repeatedly by the user, which reduces the user's patience. For such users, the corresponding calculation is based on the flight waiting cost without deducting the queuing time, so as to quantify the cost of queuing and waiting multiple factors. Based on the user's historical behavior data, it can be distinguished whether the user needs to calculate the multi-factor superimposed cost.

[0042] The delay cost value can be calculated based on the delay probability and delay time corresponding to the historical flight schedule.

[0043] The preset cost calculation sub-strategy calculates the actual cost value of each planned route based on the matched cost basic information and also includes: Based on the global user historical behavior data, the predicted time for ticket sales of each flight in the flight plan is obtained; The theoretical time for buying tickets is obtained based on the theoretical arrival time and the queuing cost; Get the predicted flight schedule based on the predicted time of ticket sales and the theoretical time of ticket purchase; The flight waiting cost is obtained by predicting the flight schedule and theoretical arrival time.

[0044] By combining global user historical behavior data to predict the time when the tickets for flights are sold out, and further calculating the flight waiting cost, the preset cost calculation sub-strategy incorporates global user dynamic factors into the calculation of the actual cost value to avoid the situation where users arrive before the flight time but have no tickets, optimize the user's ticket purchase strategy, reduce the risk of missing travel due to sold-out flights, and more accurately recommend route planning corresponding to suitable flights. At the same time, considering the dynamic changes in the predicted time of ticket sales and the theoretical time of ticket purchase, the flight waiting cost can be adjusted in real time, providing timely feedback and suggestions for users' travel decisions.

[0045] At this time, the flight waiting cost is: T w =t h ( B )-t l ; Among them, t h(B) is the flight time of flight B, H is the flight number closest to the theoretical arrival time, t k Predict when the ferry tickets will be sold out.

[0046] Taking into account the possibility of differences in the predicted time, by default, when the predicted time for sold-out tickets is less than or equal to the theoretical arrival time and the ticket purchase queue time, the tickets are sold out and the next flight is used as the predicted flight.

[0047] In this embodiment, calculating the queuing cost value according to the corresponding terminal node and the theoretical arrival time includes: Based on the global user current behavior data, the predicted number of queues at the corresponding terminal node under the theoretical arrival time is obtained; Get the queue time correlation curve based on global user historical behavior data; The queue cost is obtained based on the predicted queue number and queue time related curve.

[0048] Through the global user current behavior data, the predicted queue number of the corresponding terminal node can be obtained in real time, thereby improving the prediction accuracy of the number of team leaders. Planning through the global user current behavior data can effectively divert traffic, avoid too many users concentrating at one terminal causing congestion and long waiting times, and facilitate the allocation of passenger flights to improve overall efficiency.

[0049] As a third embodiment of the present invention, a trip planning system based on public transportation includes: a user terminal and a terminal; the user terminal is configured with a path planning strategy for outputting a planned route group corresponding to a target location and a current location of the user, and a terminal node corresponding to each planned route in the planned route group and a theoretical arrival time; The terminal is configured with a cost calculation strategy for calculating the actual cost value of each planned route and outputting the planned route with the lowest actual cost value; The user end generates a cost request instruction according to the terminal node and the theoretical arrival time, and sends the cost request instruction to the corresponding terminal terminal. The terminal terminal outputs the planned path with the lowest actual cost according to the cost request instruction and feeds it back to the user end.

[0050] Through the collaborative work between the user end and the terminal, efficient and accurate path planning can be achieved. The user end and the terminal terminal can pre-store the path planning strategy and cost calculation strategy respectively to share the calculation pressure. This can avoid the need for the user end to store terminal information and the terminal terminal to process user information. While improving planning efficiency, terminal isolation can achieve security protection of user information and terminal information to avoid information leakage. At the same time, terminal node managers can reasonably allocate resources based on the predicted number of queues and queue cost values, such as increasing service personnel, optimizing operation processes, etc., to alleviate queue pressure, or reasonably allocate passenger transport based on flight waiting cost values, improve user experience, and help manage traffic flow. By adjusting the traffic flow distribution of different terminal nodes, the overall smooth operation of traffic can be achieved.

[0051] The specific description of the present invention in the above embodiments is only used to further illustrate the present invention and cannot be understood as limiting the scope of protection of the present invention. Technical engineers in this field may make some non-essential improvements and adjustments to the present invention based on the contents of the above invention, which fall within the scope of protection of the present invention.

Claims

1. A trip planning method based on public transportation, characterized by: The steps include: A1: Obtain the target location and the current location of the user input, and generate a planning topology map corresponding to the target location and the current location of the user based on the regional road planning map; A2: Generate a planning route group based on the planning topology graph using the preset path planning sub-strategy and the corresponding terminal node and theoretical arrival time of each planning route in the planning route group; A3: The preset cost calculation sub-strategy is used to calculate the actual cost of each planned route based on the passenger route map according to the corresponding terminal nodes and theoretical arrival time of each planned route, and the planned path with the lowest actual cost is output.

2. The method for planning a trip based on public transportation according to claim 1, characterized in that: In step A3, the actual cost value of each planned route is calculated based on the passenger route map according to the corresponding terminal node of each planned route and the theoretical arrival time using the preset cost calculation sub-strategy, including: Obtain cost basic information based on passenger route map; According to the matching cost basic information of the corresponding terminal node and the theoretical arrival time of each planned route, the preset cost calculation sub-strategy calculates the actual cost value of each planned route according to the matched cost basic information.

3. The method for planning a trip based on public transportation according to claim 2, characterized in that: In step A3, the cost basic information includes: Flight schedules, flight times, queue times and risk of delays.

4. The method for planning a trip based on public transportation according to claim 3, characterized in that: In step A3, the queuing time includes: The queue time for purchasing tickets and the intermediate time for ticket checking.

5. The method for planning a trip based on public transportation according to claim 3, characterized in that: In step A3, the preset cost calculation sub-strategy calculates the actual cost value of each planned route according to the matched cost basic information, including: Calculate the flight waiting cost, voyage cost, queue cost and delay cost according to the corresponding terminal node and theoretical arrival time; The actual cost of each planned route is calculated based on the flight waiting cost, flight distance cost, queue cost and delay cost according to the preset weights.

6. The method for planning a trip based on public transportation according to claim 5, characterized in that: In step A3, the actual cost of each planned route is calculated according to the flight waiting cost, the flight distance cost, the queue cost and the delay cost according to the preset weights, including: Obtain user historical behavior data, and calculate a first preset weight corresponding to the flight waiting cost value, a second preset weight corresponding to the flight cost value, a third preset weight corresponding to the queuing cost value, and a fourth preset weight corresponding to the delay cost value based on the user's historical behavior data.

7. The method for planning a trip based on public transportation according to claim 5, characterized in that: In step A3, the calculation of the flight waiting cost according to the corresponding terminal node and the theoretical arrival time includes: According to the flight plan of the corresponding terminal node, the flight closest to the theoretical arrival time is obtained; Calculate the difference between the flight schedule and the theoretical arrival time as the flight waiting cost.

8. The method for planning a trip based on public transportation according to claim 5, characterized in that: In step A3, the preset cost calculation sub-strategy calculates the actual cost value of each planned route according to the matched cost basic information, and further includes: Based on the global user historical behavior data, the predicted time for ticket sales of each flight in the flight plan is obtained; The theoretical time for buying tickets is obtained based on the theoretical arrival time and the queuing cost; Get the predicted flight schedule based on the predicted time of ticket sales and the theoretical time of ticket purchase; The flight waiting cost is obtained by predicting the flight schedule and theoretical arrival time.

9. The method for planning a trip based on public transportation according to claim 5, characterized in that: In step A3, the calculation of the queuing cost value according to the corresponding terminal node and the theoretical arrival time includes: Based on the global user current behavior data, the predicted number of queues at the corresponding terminal node under the theoretical arrival time is obtained; Get the queue time correlation curve based on global user historical behavior data; The queue cost is obtained based on the predicted queue number and queue time related curve.

10. A trip planning system based on public transportation, used to implement the trip planning method according to any one of claims 1 to 9, characterized in that: include: User and terminal terminals; The user terminal configures a path planning strategy to output a planned route group corresponding to the target location and the user's current location, and a corresponding terminal node and theoretical arrival time for each planned route in the planned route group; The terminal is configured with a cost calculation strategy for calculating the actual cost value of each planned route and outputting the planned route with the lowest actual cost value; The user end generates a cost request instruction according to the terminal node and the theoretical arrival time, and sends the cost request instruction to the corresponding terminal terminal. The terminal terminal outputs the planned path with the lowest actual cost according to the cost request instruction and feeds it back to the user end.

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