A method, system and electronic device for determining the advance travel time of passengers
By obtaining and predicting congestion information on the passenger's route to the airport, the time when passengers should depart in advance and correcting it based on the passenger flow, the problem that existing navigation software is difficult to accurately calculate the arrival time in traffic congestion situations is reduced, and the error is reduced The computer risk improves the user experience.
Patent Information
- Application Number
- CN202110194392.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2021-02-20
- Publication Date
- 2024-12-31
- Estimated Expiration
- 2041-02-20
AI Technical Summary
Existing navigation software is difficult to accurately calculate the time when passengers arrive at the airport in traffic congestion, resulting in passengers being unable to make the plane mistakes.
By obtaining the path between the location entered by the passenger and the departure airport, predicting congestion information for each critical section and associated section, using the traffic congestion prediction model to calculate the time when passengers should set off in advance, and correcting it based on passenger flow to ensure that Accurate arrival at the airport.
It improves the accuracy of passengers' early departure time, reduces the probability of missed flights, and improves user experience.
Smart Images
Figure CN112966859B_ABST
Abstract
Description
Background Art
[0002] As my country's strategy of transforming from a major aviation transport country to a powerful aviation transport country gradually unfolds, more and more passengers choose to travel by plane. At present, passengers often use software such as AutoNavi and Baidu Map to check the route between their current location and the departure airport of their scheduled flight. When passengers choose different modes of travel, such as taking a taxi or a bus, AutoNavi, Baidu Map and other software will calculate the time required from the passenger's current location to the departure airport based on the distance between the current location and the departure airport of the scheduled flight and the travel mode chosen by the passenger, thereby estimating the time to depart in advance.
[0003] However, when passengers encounter traffic jams on the way to the departure airport, although software such as Amap Navigation and Baidu Maps can calculate the time required to pass through the congested section, this cannot play any substantial role in ensuring that passengers can reach the departure airport smoothly. It is very likely to result in passengers missing their flights, causing great inconvenience to the passengers. Summary of the invention
[0004] The present invention provides a method, system and electronic device for determining the advance travel time of passengers, and aims to solve the technical problem of how to accurately determine the advance travel time of passengers to avoid passengers missing their flights due to traffic congestion.
[0005] The technical solution of a method for determining the advance travel time of passengers of the present invention is as follows:
[0006] S1. Obtain at least one path between the location input by the passenger and the departure airport of the preset flight, and obtain the key sections on each path;
[0007] S2, inputting the departure time of the preset flight into the time period-congestion model corresponding to each key section obtained, and obtaining the congestion information corresponding to each key section of each path for the passenger;
[0008] S3, inputting the congestion information corresponding to each key section of each path into the traffic congestion prediction model, and obtaining the congestion information corresponding to each key section of each path;
[0009] S4. According to the congestion information corresponding to each key section on each path and the congestion information corresponding to the associated section of each key section on each path, the advance travel time corresponding to each path taken by the passenger is obtained and sent to the passenger's client.
[0010] The beneficial effects of a method for determining the advance travel time of passengers of the present invention are as follows:
[0011] First, the key sections on each path between the location input by the passenger and the departure airport of the preset flight are obtained; secondly, the congestion information corresponding to each key section on each path is predicted, and the congestion information corresponding to the associated section corresponding to each key section on each path is predicted; finally, since the congestion information of each key section of each path between the location input by the passenger and the departure airport of the preset flight and the associated section of each key section are predicted in advance, the accuracy of the advance travel time corresponding to each path taken by the passenger is improved. When the passenger departs according to the reminded advance departure time and encounters congestion on the way to the departure airport, the passenger will also have sufficient time to arrive at the departure airport, which greatly reduces the probability of passengers missing their flights and improves the user experience.
[0012] Based on the above solution, the method for determining the advance travel time of passengers of the present invention can also be improved as follows.
[0013] Further, the step S4 includes: obtaining the advance travel time corresponding to each travel path taken by the passenger through a first formula, wherein the first formula is: T i =T i,A +T i,B +T i,C +T D , where T i represents the advance travel time corresponding to the passenger taking the i-th path, T i,A represents the total time taken to pass through all key sections in the i-th path, T i,B represents the total time taken to pass through all associated sections in the i-th path, T i,C It represents the total time taken to pass through the remaining sections of the i-th path except all key sections and all associated sections, T D Represents the fixed time taken to check in.
[0014] Furthermore, it also includes:
[0015] The departure time of the preset flight is input into the time-passenger flow function to obtain the passenger flow corresponding to the departure time of the preset flight, and the advance travel time corresponding to each travel path taken by the passengers is corrected according to the passenger flow.
[0016] The beneficial effect of adopting the above further scheme is: according to the passenger flow corresponding to the departure time of the preset flight, the corresponding advance travel time when the passengers take each travel route is corrected, so as to avoid the situation where passengers miss the flight due to excessive passenger flow.
[0017] Furthermore, it also includes: when a passenger chooses any path to depart, obtaining the key section of at least one path between the passenger's current location and the departure airport of the preset flight, repeating S2 to S4, obtaining the shortest path, and sending it to the passenger's client.
[0018] The beneficial effect of adopting the above further scheme is that when a passenger chooses any path to depart, the path between the current location and the departure airport of the preset flight can be obtained in real time according to the passenger's current location. By repeatedly executing S2 to S4, the advance travel time corresponding to each path taken by the passenger at the current location can be obtained. The advance travel time here can be understood as: the time required for the passenger to reach the departure airport of the preset flight from the current location. The shortest path is obtained by comparison, and recommendations are sent to the customer's client in real time, so that passengers who take taxis or drive themselves can flexibly adjust the path, reduce the time spent on the road, and arrive at the airport as soon as possible to complete the check-in procedures, etc.
[0019] Furthermore, it also includes: constructing the traffic congestion prediction model and constructing a time period-congestion model corresponding to each key road section according to the historical traffic information of each road section within the preset range of the departure airport of the preset flight.
[0020] The technical solution of a system for determining the advance travel time of passengers of the present invention is as follows:
[0021] It includes an acquisition module, a first congestion information acquisition module, a second congestion information acquisition module and a determination module;
[0022] The acquisition module is used to acquire at least one path between the permanent residence input by the passenger and the departure airport of the preset flight, and to acquire the key sections on each path;
[0023] The first congestion information acquisition module is used to: input the departure time of the preset flight into the time period-congestion model corresponding to each key section obtained, and obtain the congestion information corresponding to each key section of each path for the passenger;
[0024] The second congestion information acquisition module is used to: input the congestion information corresponding to each key section of each path into the traffic congestion prediction model to obtain the congestion information corresponding to each key section of each path;
[0025] The determination module is used to obtain the advance travel time corresponding to each path taken by the passenger based on the congestion information corresponding to each key section on each path and the congestion information corresponding to the associated section of each key section on each path, and send the advance travel time to the passenger's client.
[0026] The beneficial effects of a system for determining the advance travel time of passengers of the present invention are as follows:
[0027] First, the key sections on each path between the location input by the passenger and the departure airport of the preset flight are obtained; secondly, the congestion information corresponding to each key section on each path is predicted, and the congestion information corresponding to the associated section corresponding to each key section on each path is predicted; finally, since the congestion information of each key section of each path between the location input by the passenger and the departure airport of the preset flight and the associated section of each key section are predicted in advance, the accuracy of the advance travel time corresponding to each path taken by the passenger is improved. When the passenger departs according to the reminded advance departure time and encounters congestion on the way to the departure airport, the passenger will also have sufficient time to arrive at the departure airport, which greatly reduces the probability of passengers missing their flights and improves the user experience.
[0028] Based on the above solution, the system for determining the advance travel time of passengers of the present invention can also be improved as follows.
[0029] Further, the determination module is specifically used for:
[0030] The first formula is used to obtain the corresponding advance travel time when the passenger takes each route to travel. The first formula is: T i =T i,A +T i,B +T i,C +T D , where T i represents the advance travel time corresponding to the passenger taking the i-th path, T i,A represents the total time taken to pass through all key sections in the i-th path, T i,B represents the total time taken to pass through all associated sections in the i-th path, T i,C It represents the total time taken to pass through the remaining sections of the i-th path except all key sections and all associated sections, T D Represents the fixed time taken to check in.
[0031] Furthermore, a correction module is also included:
[0032] The departure time of the preset flight is input into the time-passenger flow function to obtain the passenger flow corresponding to the departure time of the preset flight, and the advance travel time corresponding to each travel path taken by the passengers is corrected according to the passenger flow.
[0033] The beneficial effect of adopting the above further scheme is: according to the passenger flow corresponding to the departure time of the preset flight, the advance travel time corresponding to each route used by the passenger is corrected, so as to avoid the situation where the passenger misses the flight due to excessive passenger flow. Furthermore, it also includes an acquisition recommendation module, which is used to: when the passenger chooses any route to depart, obtain the key section of at least one route between the passenger's current location and the departure airport of the preset flight, repeatedly call the first congestion information acquisition module, the second congestion information acquisition module and the determination module, obtain the shortest path, and send it to the passenger's client.
[0034] The beneficial effect of adopting the above further scheme is that when a passenger chooses any path to depart, the path between the current location and the departure airport of the preset flight can be obtained in real time according to the passenger's current location. By repeatedly calling the first congestion information acquisition module, the second congestion information acquisition module and the determination module, the advance travel time corresponding to each path taken by the passenger at the current location can be obtained. The advance travel time here can be understood as: the time required for the passenger to reach the departure airport of the preset flight from the current location. The shortest path is obtained by comparison, and recommendations are sent to the customer's client in real time, so that passengers who take taxis or drive themselves can flexibly adjust the path, reduce the time spent on the road, and arrive at the airport as soon as possible to go through the check-in procedures, etc.
[0035] Furthermore, it also includes a construction module, which is used to: construct the traffic congestion prediction model and the time period-congestion model corresponding to each key section based on the historical traffic information of each section within a preset range of the departure airport of the preset flight.
[0036] The technical solution of an electronic device of the present invention is as follows:
[0037] The method comprises a memory, a processor and a program stored in the memory and running on the processor. When the processor executes the program, the steps of a method for determining the advance travel time of a passenger as described in any one of the above items are implemented.
[0038] The beneficial effects of an electronic device of the present invention are as follows:
[0039] First, the key sections on each path between the location input by the passenger and the departure airport of the preset flight are obtained; secondly, the congestion information corresponding to each key section on each path is predicted, and the congestion information corresponding to the associated section corresponding to each key section on each path is predicted; finally, since the congestion information of each key section of each path between the location input by the passenger and the departure airport of the preset flight and the associated section of each key section are predicted in advance, the accuracy of the advance travel time corresponding to each path taken by the passenger is improved. When the passenger departs according to the reminded advance departure time and encounters congestion on the way to the departure airport, the passenger will also have sufficient time to arrive at the departure airport, which greatly reduces the probability of passengers missing their flights and improves the user experience. BRIEF DESCRIPTION OF THE DRAWINGS
[0040] Figure 1 A flow chart of a method for determining the advance travel time of a passenger according to an embodiment of the present invention;
[0041] Figure 2 A schematic diagram of the structure of a system for determining the advance travel time of a passenger according to an embodiment of the present invention;
[0042] Figure 3 A schematic diagram of the structure of an electronic device according to an embodiment of the present invention; DETAILED DESCRIPTION
[0043] like Figure 1 As shown, a method for determining the advance travel time of a passenger according to an embodiment of the present invention includes the following steps:
[0044] S1. Obtain at least one path between the location input by the passenger and the departure airport of the preset flight, and obtain the key sections on each path;
[0045] S2, inputting the departure time of the preset flight into the time period-congestion model corresponding to each key section obtained, and obtaining the congestion information corresponding to each key section of each path for the passenger;
[0046] S3, inputting the congestion information corresponding to each key section of each path into the traffic congestion prediction model, and obtaining the congestion information corresponding to each key section of each path;
[0047] S4. According to the congestion information corresponding to each key section on each path and the congestion information corresponding to the associated section of each key section on each path, the advance travel time corresponding to each path taken by the passenger is obtained and sent to the passenger's client.
[0048] First, the key sections on each path between the location input by the passenger and the departure airport of the preset flight are obtained; secondly, the congestion information corresponding to each key section on each path is predicted, and the congestion information corresponding to the associated section corresponding to each key section on each path is predicted; finally, since the congestion information of each key section of each path between the location input by the passenger and the departure airport of the preset flight and the associated section of each key section are predicted in advance, the accuracy of the advance travel time corresponding to each path taken by the passenger is improved. When the passenger departs according to the reminded advance departure time and encounters congestion on the way to the departure airport, the passenger will also have sufficient time to arrive at the departure airport, which greatly reduces the probability of passengers missing their flights and improves the user experience.
[0049] In S1, all paths between the location entered by the passenger and the departure airport of the preset flight can be obtained with the help of software such as Gaode Navigation and Baidu Map. In S1, the historical traffic information of the city where the departure airport of the preset flight is located can be counted, and the sections prone to traffic jams can be listed as key sections and stored. After each path between the location entered by the passenger and the departure airport of the preset flight is obtained, it is matched with the pre-stored key sections to obtain the key sections on each path.
[0050] Among them, road sections where traffic congestion occurs within a day and the traffic congestion time exceeds a preset time such as 1 hour or 1.5 hours can be listed as sections prone to traffic congestion, i.e. key sections. Among them, software such as Gaode Navigation and Baidu Map can be used to determine whether traffic congestion occurs, or multiple vehicles passing through any section can be monitored to determine whether congestion occurs based on the speed of each vehicle and the density between multiple vehicles.
[0051] Assume that in S1, there are two paths between the location input by the passenger and the departure airport of the preset flight, namely the first path and the second path, and the first path includes the first key segment and the second key segment in sequence, and the second path includes the third key segment and the fourth key segment in sequence, then S2 can be understood as:
[0052] The time period-congestion model corresponding to each key section on the first path is: the time period-congestion model corresponding to the first key section and the time period-congestion model corresponding to the second key section. Then, S2 can be specifically understood as:
[0053] According to the distance between the departure airport of the preset flight and the second key section, the second travel time required by taking a taxi under normal traffic conditions is obtained. According to the departure time of the preset flight, the fixed time for check-in, such as 40 minutes or 45 minutes, is pushed forward. For example, the departure time is 12:00, and 40 minutes is pushed forward, that is, 11:20, that is, the passenger needs to arrive at the departure airport at 11:20 to check in. Assuming that the second travel time is 30 minutes, the time when the passenger leaves the second key section is 10:50. Assuming that the time period-congestion model corresponding to the second key section is established with a time interval of 20 minutes, since the time when the passenger leaves the second key section is 10:50, the corresponding time period-congestion model from 10:40 to 11:00 is obtained, thereby obtaining the congestion information corresponding to the second key section of the first path. The congestion information at this time can be understood as: congestion information between 10:40 and 11:00;
[0054] Assume that, according to the congestion information corresponding to the second critical section when the passenger is on the first path, that is, according to the congestion information between 10:40-11:00, it is found that the user is still on the second critical section at 10:40, then, continue to call the time period-congestion model corresponding to the second critical section to obtain the congestion information between 10:20-10:40; at this time, the congestion information corresponding to the second critical section when the passenger is on the first path is the congestion information between 10:40-11:00 and the congestion information between 10:20-10:40, and so on for more situations.
[0055] Similarly, the congestion information corresponding to the first key section of the first path is obtained, and similarly, the congestion information corresponding to each key section of the second path, ie, the third key section and the fourth key section, is obtained.
[0056] It can be understood that the "congestion information corresponding to the passenger on the second critical section of the first path" described in this article does not mean that the passenger actually arrives at the second critical section on the first path, but assumes that the passenger is on the second critical section of the first path, the same below.
[0057] Among them, congestion information can be understood as vehicle density, vehicle speed, etc., and can also be simply understood as a congestion index. Specifically, the congestion index is: 0-2 means smooth, that is, the traffic conditions are good, there is basically no congestion, etc. The congestion index is well known to those skilled in the art and will not be elaborated here.
[0058] Among them, the time consumed by taking a taxi through key sections under different congestion information can be calculated with the help of software such as Gaode Navigation and Baidu Map, which will not be elaborated here.
[0059] Among them, according to the historical traffic information of each road section within the preset range of the departure airport of the preset flight, the time period-congestion model corresponding to each key road section is obtained by training using the regularized multivariate linear regression method or the neural network. The specific training process is well known to those skilled in the art and will not be repeated here.
[0060] S3 can be specifically understood as:
[0061] According to the congestion information of the first key section of the first path and the congestion information of the second key section and the traffic congestion prediction model, assuming that the first key section corresponds to the first associated section and the second key section corresponds to the second associated section, at this time, the congestion information of the passenger on the associated section corresponding to each key section on each path is obtained, that is, the congestion information of the first associated section and the congestion information of the second key section are obtained. Similarly, the congestion information of each associated section of each key section of the second path is obtained.
[0062] Due to the traffic congestion on the key road section, the traffic congestion on other road sections, namely the associated road sections, will continue to exist and spread outward, extending to other associated road sections, and then continue to shrink after a period of time until it disappears. Therefore, it is necessary to build a traffic congestion prediction model to obtain the corresponding congestion information of each associated road section according to the congestion information of any key road section. The process of building a traffic congestion prediction model includes:
[0063] According to the historical traffic information of each road section within the preset range of the departure airport of the preset flight, a traffic congestion prediction model is obtained by training using a regularized multivariate linear regression method or a neural network, specifically:
[0064] A road section where traffic congestion occurs more than a predetermined number of times per month is determined as a critical road section, or a road section where traffic congestion occurs within a day and the duration of the traffic congestion exceeds a preset time can be listed as a road section prone to traffic congestion, i.e., a critical road section. A congestion sub-graph is generated based on the congestion information of the critical road section, and a dynamic congestion sub-graph for one hour or longer is generated. Based on the changes in the congestion sub-graph, at least two critical road sections with strong correlation are obtained, and the at least two critical road sections are associated with each other; that is, the first associated road section corresponding to the above-mentioned first critical road section is also a critical road section. When the acquired critical road section is the first associated road section, the associated road section of the first associated road section is the first critical road section.
[0065] Among them, different colors can be used to represent different congestion information on the congestion sub-map, and the strength of the correlation can be determined by calculating the RGB difference between the colors; the cosine similarity algorithm can also be used to convert different congestion information into vectors, and then the cosine similarity algorithm is used to calculate the change amplitude of the cosine similarity between different congestion information within one hour or longer, and the strength of the correlation is determined according to the change amplitude.
[0066] In S4, according to the congestion information corresponding to each key section on each path and the congestion information corresponding to the associated section on each key section on each path, the advance travel time corresponding to each path taken by the passenger is obtained and sent to the passenger's client. Specifically:
[0067] The first formula is used to obtain the corresponding advance travel time when the passenger takes each route to travel. The first formula is: T i =T i,A +T i,B +T i,C +T D , where T i represents the advance travel time corresponding to the passenger taking the i-th path, T i,A represents the total time taken to pass through all key sections in the i-th path, T i,B represents the total time taken to pass through all associated sections in the i-th path, T i,C It represents the total time taken to pass through the remaining sections in the i-th path except all key sections and all associated sections. Specifically:
[0068] With the help of software such as Amap Navigation and Baidu Map, the total time taken to pass through all key sections in the first path, namely the first key section and the second key section, by taking a taxi is calculated, and the total time taken to pass through all associated sections in the first path, namely the first associated section and the second associated section, is calculated, and the total time taken to pass through the remaining sections of the first path except all key sections and all associated sections by taking a taxi is calculated. Thus, the corresponding advance travel time when the passenger takes each path and travels by taxi is obtained and sent to the passenger's client for the user to view.
[0069] In the above embodiment, the method of taking a taxi is used for explanation, and the present application is also applicable to the analysis of the method of taking a bus, and is also applicable to the analysis of the method of taking different means of transportation. At this time, for the same route, when passengers use different means of transportation to travel, different advance travel times correspond to the same route, so that customers can make choices.
[0070] Preferably, in the above technical solution, it also includes:
[0071] S5. Input the departure time of the preset flight into the time-passenger flow function to obtain the passenger flow corresponding to the departure time of the preset flight, and correct the advance travel time corresponding to each travel route taken by the passengers according to the passenger flow.
[0072] According to the passenger flow corresponding to the departure time of the preset flight, the advance travel time corresponding to each travel route of the passengers is corrected to avoid the situation where passengers miss the flight due to excessive passenger flow.
[0073] The daily passenger flow for one or two consecutive years can be obtained through cameras installed at the airport entrance, and the daily passenger flow for one or two consecutive years can be fitted using the least squares method or other data fitting algorithms to obtain a time-passenger flow function.
[0074] The advance travel time corresponding to each route taken by the passengers can be corrected according to the passenger flow in the following manner, specifically:
[0075] The functional relationship between passenger flow and the waiting time for boarding is statistically fitted. The waiting time for boarding corresponding to the departure time of the scheduled flight is obtained according to the functional relationship. The waiting time is compared with the waiting time for boarding under normal circumstances. Then:
[0076] 1) When the calculated waiting time is less than the normal waiting time for boarding, it means that the number of passengers waiting for boarding at the airport is small, and the advance travel time corresponding to each route taken by the passengers will not be corrected;
[0077] 2) When the calculated waiting time is longer than the normal waiting time for boarding, it means that there are a large number of passengers waiting for boarding at the airport, and the corresponding advance travel time for each route taken by the passengers is corrected. For example, through S1-S4, it is calculated that when the first passenger takes the first route, the corresponding advance travel time is 40 minutes, the calculated waiting time is 60 minutes, and the calculated waiting time is 30 minutes, then the corresponding advance travel time for the first passenger taking the first route is 40+(60-30)=70 minutes, so as to avoid the situation where passengers miss the flight due to excessive passenger flow. Preferably, in the above technical solution, it also includes:
[0078] S6. When the passenger chooses any path to depart, obtain the key section of at least one path between the passenger's current location and the departure airport of the preset flight, repeat S2 to S4, obtain the shortest path, and send it to the passenger's client.
[0079] When the passenger chooses any route to depart, the passenger can use software such as AutoNavi and Baidu Maps to obtain the route between the current location and the departure airport of the preset flight in real time based on the passenger's current location, and by repeatedly executing S2 to S4, the advance travel time corresponding to each route taken by the passenger at the current location can be obtained. The advance travel time here can be understood as: the time required for the passenger to reach the departure airport of the preset flight from the current location. The shortest route is obtained by comparison and recommendations are sent to the customer's client in real time, so that passengers who take taxis or drive cars can flexibly adjust the route, reduce the time spent on the road, and arrive at the airport as soon as possible to complete the check-in procedures, etc.
[0080] In the above embodiments, although the steps are numbered S1, S2, etc., these are only specific embodiments given in the present application. Those skilled in the art may adjust the execution order of S1, S2, etc. according to actual conditions, which is also within the scope of protection of the present invention. It can be understood that in some embodiments, some or all of the above embodiments may be included.
[0081] like Figure 2 As shown, a system 200 for determining the advance travel time of passengers according to an embodiment of the present invention includes an acquisition module 210, a first congestion information acquisition module 220, a second congestion information acquisition module 230 and a determination module 240;
[0082] The acquisition module 210 is used to acquire at least one path between the permanent residence input by the passenger and the departure airport of the preset flight, and to acquire the key sections on each path;
[0083] The first congestion information acquisition module 220 is used to: input the departure time of the preset flight into the time period-congestion model corresponding to each key section obtained, and obtain the congestion information corresponding to each key section of each path for the passenger;
[0084] The second congestion information acquisition module 230 is used to: input the congestion information corresponding to each key section of each path into the traffic congestion prediction model to obtain the congestion information corresponding to each key section of each path;
[0085] The determination module 240 is used to obtain the advance travel time corresponding to each path taken by the passenger based on the congestion information corresponding to each key section on each path and the congestion information corresponding to the associated section of each key section on each path, and send it to the passenger's client.
[0086] First, the key sections on each path between the location input by the passenger and the departure airport of the preset flight are obtained; secondly, the congestion information corresponding to each key section on each path is predicted, and the congestion information corresponding to the associated section corresponding to each key section on each path is predicted; finally, since the congestion information of each key section of each path between the location input by the passenger and the departure airport of the preset flight and the associated section of each key section are predicted in advance, the accuracy of the advance travel time corresponding to each path taken by the passenger is improved. When the passenger departs according to the reminded advance departure time and encounters congestion on the way to the departure airport, the passenger will also have sufficient time to arrive at the departure airport, which greatly reduces the probability of passengers missing their flights and improves the user experience.
[0087] Preferably, in the above technical solution, the determination module 240 is specifically used for:
[0088] The first formula is used to obtain the corresponding advance travel time when the passenger takes each route to travel. The first formula is: T i =T i,A +T i,B +T i,C +T D , where T i represents the advance travel time corresponding to the passenger taking the i-th path, T i,A represents the total time taken to pass through all key sections in the i-th path, T i,B represents the total time taken to pass through all associated sections in the i-th path, T i,C It represents the total time taken to pass through the remaining sections of the i-th path except all key sections and all associated sections, T D Represents the fixed time taken to check in.
[0089] Preferably, the above technical solution further comprises a correction module, wherein the correction module is used to:
[0090] The departure time of the preset flight is input into the time-passenger flow function to obtain the passenger flow corresponding to the departure time of the preset flight, and the advance travel time corresponding to each travel path taken by the passengers is corrected according to the passenger flow.
[0091] According to the passenger flow corresponding to the departure time of the preset flight, the advance travel time corresponding to each travel route of the passengers is corrected to avoid the situation where passengers miss the flight due to excessive passenger flow.
[0092] Preferably, the above technical solution also includes a recommendation acquisition module, which is used to: when a passenger chooses any path to depart, obtain the key sections of at least one path between the passenger's current location and the departure airport of the preset flight, repeatedly call the first congestion information acquisition module 220, the second congestion information acquisition module 230 and the determination module 240, obtain the shortest path, and send it to the passenger's client.
[0093] When the passenger chooses any route to depart, the route between the current location and the departure airport of the preset flight can be obtained in real time according to the passenger's current location. By repeatedly calling the first congestion information acquisition module 220, the second congestion information acquisition module 230 and the determination module 240, the corresponding advance travel time when the passenger takes each route at the current location is obtained. The advance travel time here can be understood as: the time required for the passenger to reach the departure airport of the preset flight from the current location. The shortest route is obtained by comparison and a recommendation is sent to the client in real time, so that passengers who take taxis or drive themselves can flexibly adjust the route, reduce the time spent on the road, and arrive at the airport as soon as possible to complete the check-in procedures, etc.
[0094] Preferably, the above technical solution also includes a construction module, which is used to: construct the traffic congestion prediction model and construct a time period-congestion model corresponding to each key road section based on historical traffic information of each road section within a preset range of the departure airport of the preset flight.
[0095] The above-mentioned parameters in the system 200 for determining the advance travel time of passengers and the steps for each unit module to implement corresponding functions can refer to the parameters and steps in the embodiment of a method for determining the advance travel time of passengers mentioned above, and will not be repeated here.
[0096] like Figure 3 As shown, an electronic device 300 of an embodiment of the present invention includes a memory 310, a processor 320, and a program 330 stored in the memory 310 and running on the processor 320. When the processor 320 executes the program 330, the steps of a method for determining the advance travel time of a passenger implemented in any of the above-mentioned embodiments are implemented.
[0097] First, the key sections on each path between the location input by the passenger and the departure airport of the preset flight are obtained; secondly, the congestion information corresponding to each key section on each path is predicted, and the congestion information corresponding to the associated section corresponding to each key section on each path is predicted; finally, since the congestion information of each key section of each path between the location input by the passenger and the departure airport of the preset flight and the associated section of each key section are predicted in advance, the accuracy of the advance travel time corresponding to each path taken by the passenger is improved. When the passenger departs according to the reminded advance departure time and encounters congestion on the way to the departure airport, the passenger will also have sufficient time to arrive at the departure airport, which greatly reduces the probability of passengers missing their flights and improves the user experience.
[0098] Among them, the electronic device 300 can be a computer, a mobile phone, etc. Correspondingly, its program 330 is computer software or a mobile phone APP, etc., and the above-mentioned parameters and steps in an electronic device 300 of the present invention can refer to the parameters and steps in an embodiment of a method for determining the advance travel time of a passenger in the above text, and will not be repeated here.
[0099] Those skilled in the art will appreciate that the present invention may be implemented as a system, method or computer program product.
[0100] Therefore, the present disclosure may be specifically implemented in the following forms, namely: it may be completely hardware, it may be completely software (including firmware, resident software, microcode, etc.), or it may be a combination of hardware and software, generally referred to herein as a "circuit", "module" or "system". In addition, in some embodiments, the present invention may also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code.
[0101] Any combination of one or more computer-readable media can be used. Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: electrical connections with one or more wires, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this document, computer-readable storage media can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.
[0102] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.
Claims
1. A method for determining the advance travel time of a passenger, characterized in that: include: S1. Obtain at least one path between the location input by the passenger and the departure airport of the preset flight, and obtain the key sections on each path; S2, inputting the departure time of the preset flight into the time period-congestion model corresponding to each key section obtained, and obtaining the congestion information corresponding to each key section of each path for the passenger; S3, inputting the congestion information corresponding to each key section on each route into the traffic congestion prediction model, obtaining the congestion information of the associated sections corresponding to each key section on each route, determining the sections where traffic congestion occurs more than a predetermined number of times per month as key sections, or listing the sections where traffic congestion occurs within a day and the duration of the traffic congestion exceeds a preset time as sections prone to traffic congestion, i.e., key sections, generating a congestion sub-graph based on the congestion information of the key sections, generating a dynamic congestion sub-graph for a continuous period of 1 hour or longer, and obtaining at least two key sections with strong correlation based on the changes in the congestion sub-graph, wherein the at least two key sections are mutually associated sections; S4, according to the congestion information corresponding to each key section on each path of the passenger and the congestion information corresponding to the associated section of each key section on each path of the passenger, the advance travel time corresponding to each path of the passenger is obtained and sent to the passenger's client; Also includes: The departure time of the preset flight is input into the time-passenger flow function to obtain the passenger flow corresponding to the departure time of the preset flight, and the advance travel time corresponding to each travel path taken by the passengers is corrected according to the passenger flow.
2. A method for determining the advance travel time of a passenger according to claim 1, characterized in that: The S4 includes: The first formula is used to obtain the corresponding advance travel time when the passenger takes each route to travel. The first formula is: T i =T i,A +T i,B +T i,C +T D , where T i represents the advance travel time corresponding to the passenger taking the i-th path, T i,A represents the total time taken to pass through all key sections in the i-th path, T i,B represents the total time taken to pass through all associated sections in the i-th path, T i,C It represents the total time taken to pass through the remaining sections of the i-th path except all key sections and all associated sections, T D Represents the fixed time taken to check in.
3. A method for determining the advance travel time of a passenger according to claim 1 or 2, characterized in that: Also includes: When the passenger chooses any path to depart, the key section of at least one path between the passenger's current location and the departure airport of the preset flight is obtained, and S2 to S4 are repeatedly executed to obtain the shortest path and send it to the passenger's client.
4. A method for determining the advance travel time of a passenger according to claim 1 or 2, characterized in that: Also includes: According to the historical traffic information of each road section within the preset range of the departure airport of the preset flight, the traffic congestion prediction model is constructed, and the time period-congestion model corresponding to each key road section is constructed.
5. A system for determining the advance travel time of passengers, characterized in that: It includes an acquisition module, a first congestion information acquisition module, a second congestion information acquisition module and a determination module; The acquisition module is used to acquire at least one path between the permanent residence input by the passenger and the departure airport of the preset flight, and to acquire the key sections on each path; The first congestion information acquisition module is used to: input the departure time of the preset flight into the time period-congestion model corresponding to each key section obtained, and obtain the congestion information corresponding to each key section of each path for the passenger; The second congestion information acquisition module is used to: input the congestion information corresponding to each key section on each path of the passenger into the traffic congestion prediction model, obtain the congestion information of the associated section corresponding to each key section on each path of the passenger, determine the section where the number of traffic congestion occurrences is greater than a predetermined number of times per month as a key section, or list the section where traffic congestion occurs within a day and the time of traffic congestion exceeds a preset time as a section prone to traffic congestion, i.e., a key section, generate a congestion sub-graph according to the congestion information of the key section, generate a dynamic congestion sub-graph for a continuous period of 1 hour or longer, and obtain at least two key sections with strong correlation according to the change of the congestion sub-graph, and the at least two key sections are mutually associated sections; The determination module is used to obtain the advance travel time corresponding to each path taken by the passenger based on the congestion information corresponding to each key section on each path and the congestion information corresponding to the associated section of each key section on each path, and send the advance travel time corresponding to each path taken by the passenger to the passenger's client; Also includes correction modules: The departure time of the preset flight is input into the time-passenger flow function to obtain the passenger flow corresponding to the departure time of the preset flight, and the advance travel time corresponding to each travel path taken by the passengers is corrected according to the passenger flow.
6. A system for determining the advance travel time of passengers according to claim 5, characterized in that: The determination module is specifically used for: The first formula is used to obtain the corresponding advance travel time when the passenger takes each route to travel. The first formula is: T i =T i,A +T i,B +T i,C +T D , where T i represents the advance travel time corresponding to the passenger taking the i-th path, T i,A represents the total time taken to pass through all key sections in the i-th path, T i,B represents the total time taken to pass through all associated sections in the i-th path, T i,C It represents the total time taken to pass through the remaining sections of the i-th path except all key sections and all associated sections, T D Represents the fixed time taken to check in.
7. A system for determining the advance travel time of passengers according to claim 5, characterized in that: It also includes an acquisition recommendation module, which is used to: when a passenger chooses any path to depart, obtain the key section of at least one path between the passenger's current location and the departure airport of the preset flight, repeatedly call the first congestion information acquisition module, the second congestion information acquisition module and the determination module, obtain the shortest path, and send it to the passenger's client.
8. An electronic device comprising a memory, a processor, and a program stored in the memory and running on the processor, characterized in that: When the processor executes the program, the steps of a method for determining the advance travel time of a passenger as described in any one of claims 1 to 4 are implemented.