CN113326956A - Integrated ticketing scheme generation method and device for MaaS system - Google Patents

Integrated ticketing scheme generation method and device for MaaS system Download PDF

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CN113326956A
CN113326956A CN202110505578.2A CN202110505578A CN113326956A CN 113326956 A CN113326956 A CN 113326956A CN 202110505578 A CN202110505578 A CN 202110505578A CN 113326956 A CN113326956 A CN 113326956A
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王伯卿
杨敏
杨桂新
王立超
任怡凤
曹欢
盛强
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Abstract

The invention discloses an integrated ticketing scheme generation method and device for a MaaS system, which are used for obtaining selection preference of a passenger trip mode for the MaaS system through classification prediction of historical trip data of the passenger and formulating a trip mode combination scheme suitable for the selection preference of the passenger; meanwhile, according to the historical travel frequency of passengers in the city and in the intercity, ticket making forms of different traffic modes in the combined travel mode scheme facing the MaaS system are determined; the travel mode combination scheme is combined with different traffic mode ticketing modes to obtain an integrated ticketing scheme for the MaaS system. The invention fully considers the personalized travel requirements of passengers, realizes the generation of the integrated ticketing scheme based on the MaaS concept, has good practicability, can meet the integrated ticketing scheme requirements of the passengers with different travel characteristics, and has important significance for promoting the development of linked travel, popularizing a better sustainable travel mode and realizing the travel service reform under the MaaS.

Description

Integrated ticketing scheme generation method and device for MaaS system
Technical Field
The invention relates to an integrated ticketing scheme generation method and device for a MaaS system, and belongs to the technical field of travel service.
Background
Along with the gradual and deep application of big data in the field of transportation, MaaS is gradually a hot spot as an advanced technology and key link research for realizing the intellectualization and integration of a travel integration service.
At present, most of research aiming at the MaaS stays at a theoretical level, although a small amount of relevant technologies in the urban traffic field appear, the research mainly focuses on simple combination of certain two traffic modes such as public transport, shared bicycle and subway, and the ticket business combination scheme has fixed content and single selection, and lacks an integrated ticket business generation scheme considering selection preferences of different passengers, and cannot meet personalized travel requirements of passengers. Therefore, an integrated ticketing scheme generation technology facing the MaaS system is urgently needed to be designed, and a scheme is provided for the optimized implementation of the MaaS service.
Disclosure of Invention
The invention aims to provide an integrated ticketing scheme generation technology for a MaaS system. The method comprises the steps that through classification prediction of historical travel data of passengers, selection preference of a passenger travel mode facing a MaaS system is obtained, and a travel mode combination scheme suitable for the selection preference of the passengers is formulated for the passengers; meanwhile, according to the historical travel frequency of passengers in the city and in the intercity, ticket making forms of different traffic modes in the combined travel mode scheme facing the MaaS system are determined; the travel mode combination scheme is combined with different traffic mode ticketing modes to obtain an integrated ticketing scheme for the MaaS system. The invention fully considers the personalized travel requirements of passengers, realizes the generation of the integrated ticketing scheme based on the MaaS concept, has good practicability, can meet the integrated ticketing scheme requirements of the passengers with different travel characteristics, and has important significance for promoting the development of linked travel, popularizing a better sustainable travel mode and realizing the travel service reform under the MaaS.
In order to achieve the purpose, the invention provides the following scheme:
Step1: collecting a passenger traffic demand perception data set facing a MaaS system;
Step2: extracting passenger traffic demand characteristics facing a MaaS system according to the passenger traffic demand perception data set, and determining traffic modes contained in ticket combination schemes aiming at different passenger traffic demand characteristics;
Step3: determining the ticketing form of each traffic mode in the ticketing combination scheme according to the personal travel frequency of passengers;
Step4: and generating an integrated ticketing scheme which considers the personalized requirements of passengers and faces to the MaaS system by combining the traffic modes in the ticketing combination scheme and the ticketing forms of all the traffic modes.
The Step1The method comprises the following steps: historical travel data of n passengers are collected and used for predicting the travel preference of the passengers. The historical travel data of the ith passenger comprises the bus travel frequency f1iFrequency of subway trips f2iFrequency of bicycle travel f3iNet taxi/taxi trip frequency f4iSharing the frequency of use of the vehicle f5iCustomizing the frequency of use f of the bus6iTime consumption t in tripiCost of trip ciDistance of trip siPreference for travel ei(ii) a i 1,2, n, n represents the number of passengers. Wherein f is1i、f2i、f3i、f4i1 means that the frequency of travel is 5 times or less, f1i、f2i、f3i、f4i2 denotes trip frequency 6-10 times, f1i、f2i、f3i、f4i3 represents trip frequency more than 10 times; f. of5i、f6i1 means that the frequency of travel is 3 times or less, f5i、f6i2 denotes trip frequency 4-8 times, f5i、f6i3 represents trip frequency more than 8 times; t is ti1 means that the time consumption of a single average trip is within 1 hour, and ti2 means that the average travel time is 1-2 hours, ti3 represents that the time consumption of a single average trip is more than 2 hours; c. Ci1 means that the single average trip cost is within 10 yuan, ci2 means that the cost of a single average trip is 10-30 yuan, ci3 means that the single average trip cost is more than 30 yuan; si1 means that the single average trip distance is within 5 km, si2 denotes a single average travel distance of 5-10 km, si3 represents that the single average travel distance is more than 10 kilometers; e.g. of the typei1 indicates a preference for travel as green share, ei2 for travel preference business comfort, eiThe travel preference is convenient and fast as represented by 3.
The Step2The method comprises the following steps: clustering passenger trip data by adopting a K-Means clustering method, wherein the historical trip data f of the ith passenger1i、f2i、f3i、f4i、f5i、f6i、ti、ci、siCombined as a vector xi，xi＝(f1i、f2i、f3i、f4i、f5i、f6i、ti、ci、si) The goal of the K-Means algorithm is to divide the n vectors into K (K ≦ n) classes so that the sum of squared errors in the group SSE is minimized. The specific process comprises the following steps:
firstly, randomly selecting central points of K categories, i.e. the jth category AjCentral point a ofj＝(aj1，aj2，aj3，aj4，aj5，aj6，aj7，aj8，aj9) X is to beiRandomly assigned to K classes, calculating the centroid muj of the j class at the moment,
Figure BDA0003058283120000021
and calculate xiAnd ajDistance b (x) therebetweeni，aj)，
Figure BDA0003058283120000022
Figure BDA0003058283120000023
Then x is putiReassigning to the class represented by the center point closest to the center point, and calculating the centroid and x of each class at the momentiAnd ajThe distance between them; then continue to reallocate xiUp to the centroid mujNo longer changing.
And calculating the distance between the vector formed by combining the travel data of any passenger and the central point of each category, finding the category represented by the central point closest to the travel data of the passenger, determining the occurrence times of different travel preferences in the category, and taking the travel preference with the highest time as the traffic demand characteristic of the passenger.
And after the traffic demand characteristics predicted by each passenger are obtained, determining the travel mode contained in the ticket business combination scheme of each demand characteristic passenger. The green shared passenger ticket business combination scheme comprises the following steps: the combined scheme of public transport, subway, shared bicycle, shared automobile and customized bus for the comfortable ticket business of the passenger includes: subway, net appointment/taxi, sharing car, customization bus, convenient and fast passenger ticket business combination scheme includes: subway, net appointment/taxi, sharing bicycle, sharing car, customized bus.
The Step3In the above, the ticket system forms of different transportation modes include: public transport
Figure BDA0003058283120000024
n1＝1，2，3，n1When the value is 1, the half-rate ticket of the bus (half-rate of the bus in the month) is expressed, and n1When the time is 2, the time indicates the bus time ticket (taking the bus for free in the month for 15 times), and n1When the month is 3, the month ticket of the bus is represented (the month is free of bus riding); subway
Figure BDA0003058283120000031
n2＝1，2，3，n2When the value is 1, a subway half-price ticket (subway half-price in the month) is indicated, and n2When 2, it represents subway ticket(take subway for free 15 times in the month), n2When the month is 3, the month ticket of the subway is represented (the month is free for taking the subway); sharing bicycle
Figure BDA0003058283120000032
n3＝1，2，3，n3When the vehicle is 1, the shared-bicycle half-price ticket (shared-bicycle starting half-price in the month) is represented, and n3When the value is 2, the shared bicycle secondary ticket (the monthly free shared bicycle starting price is 15 times), and n3When the month is 3, the shared bicycle monthly ticket is indicated (the shared bicycle free starting price is used in the month); net appointment vehicle/taxi
Figure BDA0003058283120000033
n4＝1，2，3，n4When the ticket business combination scheme is 1, the ticket business combination scheme does not include network appointment cars/taxis, and n4When the taxi is 2, the taxi booking/taxi secondary ticket (the taxi booking/taxi free-starting price is 8 times in the month), and n4When the taxi is No. 3, the taxi is taken for a taxi appointment/taxi secondary ticket (the taxi is taken for 12 times in the month); shared automobile
Figure BDA0003058283120000034
n5＝1，2，3，n5When 1 indicates that no shared cars are included in the ticket pool scheme, n5When the vehicle is equal to 2, the vehicle sharing secondary ticket is represented (the vehicle sharing free starting price is 3 times in the month), and n is5When the vehicle is shared, the vehicle is shared again (the vehicle is shared for 6 times in the month); custom bus
Figure BDA0003058283120000035
n6＝1，2，3，n6When 1 indicates that no custom bus is included in the ticket combination scheme, n6When 2, the custom bus ticket (10 times the custom bus is taken free in the month), n6A custom bus monthly ticket is indicated when 3 (free riding the custom bus in the month);
the ticket system mode of the ticket combination scheme is the historical travel frequency f of each travel mode of the passengers1i、f2i、f3i、f4i、f5i、f6iIs a determination conditionLet us assume that the ticket decision coefficient of the kth transportation mode of the ith passenger is σkiThen σkiThe ratio of the k transportation mode trip frequency of the ith passenger to the total transportation mode trip frequency is represented by the formula
Figure BDA0003058283120000036
Figure BDA0003058283120000037
According to the ticket system decision coefficient, different ticket system forms of each traffic mode are obtained, and the specific corresponding relation is shown in table 1.
TABLE 1 correspondence between transportation means, ticket system decision coefficient and ticket system format
Figure BDA0003058283120000041
The Step4In the method, an integrated ticketing scheme for the MaaS system comprises the following steps: green shared passenger ticket service combination scheme
Figure BDA0003058283120000042
Combined scheme for ticket business comfortable passenger
Figure BDA0003058283120000043
Convenient and fast ticket service combination scheme for passenger
Figure BDA0003058283120000044
An integrated ticketing scheme generation device facing a MaaS system comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the following steps when executing the computer program:
collecting a passenger traffic demand perception data set facing a MaaS system;
extracting passenger traffic demand characteristics facing a MaaS system according to the passenger traffic demand perception data set, and determining traffic modes contained in ticket combination schemes aiming at different passenger traffic demand characteristics;
determining the ticketing form of each traffic mode in the ticketing combination scheme according to the personal travel frequency of passengers;
and generating an integrated ticketing scheme which considers the personalized requirements of passengers and faces to the MaaS system by combining the traffic modes in the ticketing combination scheme and the ticketing forms of all the traffic modes.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
collecting a passenger traffic demand perception data set facing a MaaS system;
extracting passenger traffic demand characteristics facing a MaaS system according to the passenger traffic demand perception data set, and determining traffic modes contained in ticket combination schemes aiming at different passenger traffic demand characteristics;
determining the ticketing form of each traffic mode in the ticketing combination scheme according to the personal travel frequency of passengers;
and generating an integrated ticketing scheme which considers the personalized requirements of passengers and faces to the MaaS system by combining the traffic modes in the ticketing combination scheme and the ticketing forms of all the traffic modes.
The invention adopts the following technical scheme for solving the technical problems:
compared with the prior art, the invention adopting the technical scheme has the following technical effects:
according to the integrated ticketing scheme generation technology for the MaaS system, provided by the invention, the selection preference of the passenger travel mode for the MaaS system is obtained through classification prediction of the historical travel data of the passenger, and a travel mode combination scheme suitable for the selection preference of the passenger is formulated for the passenger; meanwhile, according to the historical travel frequency of passengers in the city and in the intercity, ticket making forms of different traffic modes in the combined travel mode scheme facing the MaaS system are determined; the travel mode combination scheme is combined with different traffic mode ticketing modes to obtain an integrated ticketing scheme for the MaaS system. The invention fully considers the personalized travel requirements of passengers, realizes the generation of the integrated ticketing scheme based on the MaaS concept, has good practicability, can meet the integrated ticketing scheme requirements of the passengers with different travel characteristics, and has important significance for promoting the development of linked travel, popularizing a better sustainable travel mode and realizing the travel service reform under the MaaS.
Drawings
Fig. 1 is a flowchart of an integrated ticketing scheme generation method for a MaaS system according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide an integrated ticketing scheme generation technology for a MaaS system, which fully considers the personalized travel requirements of passengers, realizes the generation of the integrated ticketing scheme based on the MaaS concept, has good practicability, can meet the requirements of the integrated ticketing scheme of the passengers with different travel characteristics, and has important significance for promoting the development of linked travel, popularizing a better sustainable travel mode and realizing the reform of travel service under the MaaS.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
As shown in fig. 1, an integrated ticketing scheme generation method for a MaaS system according to an embodiment of the present invention includes:
step 1: the method comprises the steps of collecting a MaaS system-oriented passenger traffic demand perception data set for predicting passenger trip preference. The multisource data of the ith passenger (i ═ 1, 2.., n) specifically includes the following data acquisition:
step 1A), the urban historical travel data of the ith passenger comprises bus travel frequency f1iFrequency of subway tripsf2iFrequency of bicycle travel f3iNet taxi/taxi trip frequency f4i1,2, n, wherein f1i、f2i、f3i、f4i1 means that the frequency of travel is 5 times or less, f1i、f2i、f3i、f4i2 denotes trip frequency 6-10 times, f1i、f2i、f3i、f4i3 represents trip frequency more than 10 times;
step 2A), the intercity historical travel data of the ith passenger comprises the use frequency f of the shared automobile5iCustomizing the frequency of use f of the bus6i1,2, n, wherein f5i、f6i1 means that the frequency of travel is 3 times or less, f5i、f6i2 denotes trip frequency 4-8 times, f5i、f6i3 represents trip frequency more than 8 times;
step 3A) time consumption t of the ith passenger in travelingi，ti1 means that the time consumption of a single average trip is within 1 hour, and ti2 means that the average travel time is 1-2 hours, ti3 represents that the time consumption of a single average trip is more than 2 hours;
step 4A) travel cost c of the ith passengeri，ci1 means that the single average trip cost is within 10 yuan, ci2 means that the cost of a single average trip is 10-30 yuan, ci3 means that the single average trip cost is more than 30 yuan;
step 5A) travel distance s of the ith passengeri，si1 means that the single average trip distance is within 5 km, si2 denotes a single average travel distance of 5-10 km, si3 represents that the single average travel distance is more than 10 kilometers;
step 6A) travel preference ei，ei1 indicates a preference for travel as green share, ei2 for travel preference business comfort, eiThe travel preference is convenient and fast as represented by 3.
Step 2: the method for extracting the passenger traffic demand characteristics facing the MaaS system comprises the following steps:
step 2A) clustering passenger travel data by adopting a K-Means clustering method, wherein the historical travel data f of the ith passenger1i、f2i、f3i、f4i、f5i、f6i、ti、ci、siCombined as a vector xi，xi＝(f1i、f2i、f3i、f4i、f5i、f6i、ti、ci、si) The goal of the K-Means algorithm is to divide these n variables into K (K ≦ n) sets such that the sum of squared errors in the set SSE is minimized.
Step 2B) randomly selecting the central points of K categories, the jth category AjCentral point a ofj＝(aj1，aj2，aj3，aj4，aj5，aj6，aj7，aj8，aj9) X is to beiRandomly assigned to K classes, and calculating the centroid mu of the j class at the momentj，
Figure BDA0003058283120000071
And calculate xiAnd ajDistance b (x) therebetweeni，aj)，
Figure BDA0003058283120000072
Figure BDA0003058283120000073
Step 2C) of reacting xiReassigning to the class represented by the center point closest to the center point, and calculating the centroid and x of each class at the momentiAnd ajThe distance between them; then continue to reallocate xiUp to the centroid mujNo longer changing.
And 2D) after the circulation is finished, calculating the distance between the vector formed by combining the travel data of any passenger and the central point of each category, finding the category represented by the central point closest to the travel data, determining the occurrence frequency of different travel preferences in the category, and taking the travel preference with the highest frequency as the traffic demand characteristic of the passenger.
And 2E) after the traffic demand characteristics predicted by each passenger are obtained, determining a travel mode contained in the ticket business combination scheme of each demand characteristic passenger. The green shared passenger ticket business combination scheme comprises the following steps: the combined scheme of public transport, subway, shared bicycle, shared automobile and customized bus for the comfortable ticket business of the passenger includes: subway, net appointment/taxi, sharing car, customization bus, convenient and fast passenger ticket business combination scheme includes: subway, net appointment/taxi, sharing bicycle, sharing car, customized bus.
For any passenger L needing to predict traffic demand characteristics, obtaining historical trip data bus trip frequency f thereof1LSubway trip frequency f2LAnd the traveling frequency f of the bicycle3LTaxi trip frequency f4LSharing the frequency f of use of the vehicle5LCustomized bus use frequency f6LCost of trip cLDistance s of travelLThe travel preference e of the passenger L is obtained through Step211, the travel preference is green sharing, and the ticket combination scheme of the passenger L includes: buses, subways, shared bicycles, shared cars, custom buses.
Step 3: according to the personal trip frequency of passengers, determining the ticket system form of the traffic mode in the ticket business combination scheme, which comprises the following specific steps:
the ticket system form in the ticket service combination scheme in the step 3A) comprises the following steps: public transport
Figure BDA0003058283120000074
n1＝1，2，3，n1When the value is 1, the half-rate ticket of the bus (half-rate of the bus in the month) is expressed, and n1When the time is 2, the time indicates the bus time ticket (taking the bus for free in the month for 15 times), and n1When the month is 3, the month ticket of the bus is represented (the month is free of bus riding); subway
Figure BDA0003058283120000075
n2＝1，2，3，n2When the ticket is 1, the ticket is a half-price ticket of subway (riding in the month)Half-value of subway), n2When the number is 2, the subway secondary ticket is represented (the subway is taken for 15 times in free in the month), and n2When the month is 3, the month ticket of the subway is represented (the month is free for taking the subway); sharing bicycle
Figure BDA0003058283120000076
n3＝1，2，3，n3When the vehicle is 1, the shared-bicycle half-price ticket (shared-bicycle starting half-price in the month) is represented, and n3When the value is 2, the shared bicycle secondary ticket (the monthly free shared bicycle starting price is 15 times), and n3When the month is 3, the shared bicycle monthly ticket is indicated (the shared bicycle free starting price is used in the month); net appointment vehicle/taxi
Figure BDA0003058283120000081
n4＝1，2，3，n4When the ticket business combination scheme is 1, the ticket business combination scheme does not include network appointment cars/taxis, and n4When the taxi is 2, the taxi booking/taxi secondary ticket (the taxi booking/taxi free-starting price is 8 times in the month), and n4When the taxi is No. 3, the taxi is taken for a taxi appointment/taxi secondary ticket (the taxi is taken for 12 times in the month); shared automobile
Figure BDA0003058283120000082
n5＝1，2，3，n5When 1 indicates that no shared cars are included in the ticket pool scheme, n5When the vehicle is equal to 2, the vehicle sharing secondary ticket is represented (the vehicle sharing free starting price is 3 times in the month), and n is5When the vehicle is shared, the vehicle is shared again (the vehicle is shared for 6 times in the month); custom bus
Figure BDA0003058283120000083
n6＝1，2，3，n6When 1 indicates that no custom bus is included in the ticket combination scheme, n6When 2, the custom bus ticket (10 times the custom bus is taken free in the month), n6A custom bus monthly ticket is indicated when 3 (the custom bus is taken free in the month).
Step 3B) ticket system mode of the ticket combination scheme is based on historical trip frequency f of each trip mode of passengers1i、f2i、f3i、f4i、f5i、f6iFor the determination condition, let us assume that the ticket decision coefficient of the kth transportation mode of the ith passenger is σkiThen σkiThe ratio of the travel frequency of the ith transportation mode to the travel frequency of all the travel modes is represented, and the calculation formula is
Figure BDA0003058283120000084
Figure BDA0003058283120000085
And obtaining different ticket making modes of the travel modes according to different historical travel frequencies of the travel modes of the passengers.
The historical travel information of the passenger L is f1L＝3、f2L＝3、f3L＝2、f4L＝2、f5L＝2、f6L1, namely, the bus monthly trips are more than 10 times, the subway monthly trips are more than 10 times, the sharing single bus monthly trips are 6-10 times, the net appointment/taxi monthly trips are 6-10 times, the sharing automobile monthly trips are 4-8 times, and the number of the customized bus monthly trips is less than or equal to 3 times; passenger L has a ticket decision coefficient of σ1i＝0.48，σ2i＝0.48，σ3i＝0.32，σ4i＝0.32，σ5i＝0.32，σ6iThe ticket system of the passenger L ticket combination scheme is Bus 0.163、Sub3、Bic2、Taxi2、Car2、Dem1The bus taxi sharing system comprises a bus monthly ticket (free bus taking in the month), a subway monthly ticket (free subway taking in the month), a shared single-car secondary ticket (free shared single-car starting price 15 times in the month), a network taxi appointment/taxi secondary ticket (free shared single-car starting price 5 times in the month), a shared automobile secondary ticket (free shared automobile starting price 3 times in the month) and no custom bus.
Step 4: an integrated ticket business scheme which considers the personalized requirements of passengers and faces to the MaaS system is generated, and the integrated ticket business scheme specifically comprises the following steps:
step2 determines that the ticket combination scheme of the passenger L comprises the following steps: the method comprises the steps of public transport, subway, shared bicycle, shared automobile and customized bus, and the Step3 is used for determining the passenger L ticket business combination schemeIn the form of Bus3、Sub3、Bic2、Taxi2、Car2、Dem1The integrated ticket scheme for the MaaS system combined with the obtained passenger L is { Bus3、Sub3、Bic2、Car2、Dem1The ticket combination scheme includes: the method comprises the following steps of bus monthly tickets (free bus taking in the month), subway monthly tickets (free subway taking in the month), shared single-car secondary tickets (15 times of shared-car starting price in the month), and shared car secondary tickets (3 times of shared-car starting price in the month).
According to the method, the selection preference of the passenger travel mode facing to the MaaS system is obtained through classification prediction of the historical travel data of the passengers, and a travel mode combination scheme suitable for the selection preference of the passengers is formulated for the passengers; meanwhile, according to the historical travel frequency of passengers in the city and in the intercity, ticket making forms of different traffic modes in the combined travel mode scheme facing the MaaS system are determined; the travel mode combination scheme is combined with different traffic mode ticketing modes to obtain an integrated ticketing scheme for the MaaS system. The invention fully considers the personalized travel requirements of passengers, realizes the generation of the integrated ticketing scheme based on the MaaS concept, has good practicability, can meet the integrated ticketing scheme requirements of the passengers with different travel characteristics, and has important significance for promoting the development of linked travel, popularizing a better sustainable travel mode and realizing the travel service reform under the MaaS.
In one embodiment, a computer device is provided, which may be a terminal. The apparatus includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to realize an integrated ticket scheme generation method facing a MaaS system. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
In one embodiment, an integrated ticketing scheme generation apparatus for a MaaS system is provided, and includes a memory and a processor, where the memory stores a computer program, and the processor implements the following steps when executing the computer program:
collecting a passenger traffic demand perception data set facing a MaaS system;
extracting passenger traffic demand characteristics facing a MaaS system according to the passenger traffic demand perception data set, and determining traffic modes contained in ticket combination schemes aiming at different passenger traffic demand characteristics;
determining the ticketing form of each traffic mode in the ticketing combination scheme according to the personal travel frequency of passengers;
and generating an integrated ticketing scheme which considers the personalized requirements of passengers and faces to the MaaS system by combining the traffic modes in the ticketing combination scheme and the ticketing forms of all the traffic modes.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (9)

1. An integrated ticketing scheme generation method facing a MaaS system is characterized by comprising the following steps:
collecting a passenger traffic demand perception data set facing a MaaS system;
extracting passenger traffic demand characteristics facing a MaaS system according to the passenger traffic demand perception data set, and determining traffic modes contained in ticket combination schemes aiming at different passenger traffic demand characteristics;
determining the ticketing form of each traffic mode in the ticketing combination scheme according to the personal travel frequency of passengers;
and generating an integrated ticketing scheme which considers the personalized requirements of passengers and faces to the MaaS system by combining the traffic modes in the ticketing combination scheme and the ticketing forms of all the traffic modes.
2. The method of claim 1, wherein collecting historical travel data for a number of said passengers comprises said traffic demand awareness data set, wherein the ith tripThe historical trip data of the passenger comprises the bus trip frequency f1iFrequency of subway trips f2iFrequency of bicycle travel f3iNet taxi/taxi trip frequency f4iSharing the frequency of use of the vehicle f5iCustomizing the frequency of use f of the bus6iTime consumption t in tripiCost of trip ciDistance of trip siPreference for travel ei(ii) a i 1,2, n, n represents the number of passengers.
3. Method according to claim 2, characterized in that f1i、f2i、f3i、f4i1 means that the frequency of travel is 5 times or less, f1i、f2i、f3i、f4i2 denotes trip frequency 6-10 times, f1i、f2i、f3i、f4i3 represents trip frequency more than 10 times; f. of5i、f6i1 means that the frequency of travel is 3 times or less, f5i、f6i2 denotes trip frequency 4-8 times, f5i、f6i3 represents trip frequency more than 8 times; t is ti1 means that the time consumption of a single average trip is within 1 hour, and ti2 means that the average travel time is 1-2 hours, ti3 represents that the time consumption of a single average trip is more than 2 hours; c. Ci1 means that the single average trip cost is within 10 yuan, ci2 means that the cost of a single average trip is 10-30 yuan, ci3 means that the single average trip cost is more than 30 yuan; si1 means that the single average trip distance is within 5 km, si2 denotes a single average travel distance of 5-10 km, si3 represents that the single average travel distance is more than 10 kilometers; e.g. of the typei1 indicates a preference for travel as green share, ei2 for travel preference business comfort, eiThe travel preference is convenient and fast as represented by 3.
4. The method according to claim 2, wherein the method for extracting the passenger traffic demand characteristics comprises the following steps:
by polymerization of K-MeansThe class method is used for clustering historical travel data of n passengers, and specifically comprises the following steps: historical travel data f of ith passenger1i、f2i、f3i、f4i、f5i、f6i、ti、ci、siCombined as a vector xi，xi＝(f1i、f2i、f3i、f4i、f5i、f6i、ti、ci、si) Firstly, randomly selecting the central points of K categories, the jth category AjCentral point a ofj＝(aj1，aj2，aj3，aj4，aj5，aj6，aj7，aj8，aj9) X is to beiRandomly assigned to K classes, and calculating the centroid mu of the j class at the momentj，
Figure FDA0003058283110000011
And calculate xiAnd ajDistance b (x) therebetweeni,aj)，
Figure FDA0003058283110000012
Figure FDA0003058283110000013
Then x is putiReassigning to the class represented by the center point closest to the center point, and calculating the centroid and x of each class at the momentiAnd ajThe distance between them; then continue to reallocate xiUp to the centroid mujNo longer changing;
and calculating the distance between the vector formed by combining the travel data of any passenger and the central point of each category, finding the category represented by the central point closest to the travel data of the passenger, determining the occurrence times of different travel preferences in the category, and taking the travel preference with the highest time as the traffic demand characteristic of the passenger.
5. The method of claim 4, wherein the transportation mode included in the green shared passenger ticketing composition scheme is: the transportation modes contained in the combined scheme of public transport, subway, shared bicycle, shared automobile and customized bus and ticket business of the comfortable passengers are as follows: the traffic modes contained in the convenient and fast passenger ticket business combination scheme of the subway, the network appointment car/taxi, the shared car and the customized bus are as follows: subway, net appointment/taxi, sharing bicycle, sharing car, customized bus.
6. The method of claim 5, wherein the ticketed versions of different transportation modes include: public transport
Figure FDA0003058283110000022
n1＝1,2,3，n1When 1, it represents the half-price ticket of public transport, n1When 2, n represents a bus order1When the number is 3, the bus monthly ticket is represented; subway
Figure FDA0003058283110000023
n2＝1,2,3，n2When 1, it represents the subway half-price ticket, n2When 2, n represents subway ticket, n2When being 3, the subway platform represents a subway monthly ticket; sharing bicycle
Figure FDA0003058283110000024
n3＝1,2,3，n3When 1, it represents the shared half-value ticket of bicycle, n3When 2, it means sharing a single-train ticket, n3When being 3, the shared bicycle monthly ticket is represented; net appointment vehicle/taxi
Figure FDA0003058283110000025
n4＝1,2,3，n4When the ticket business combination scheme is 1, the ticket business combination scheme does not include network appointment cars/taxis, and n4When 2, it represents network taxi appointment, n4When the taxi is 3, the taxi booking/taxi booking is carried out; shared automobile
Figure FDA0003058283110000026
n5＝1,2,3，n5When 1 indicates that no shared cars are included in the ticket pool scheme, n5When 2, the shared car ticket, n5When the ticket is 3, the ticket is shared by the automobile; custom bus
Figure FDA0003058283110000027
n6＝1,2,3，n6When 1 indicates that no custom bus is included in the ticket combination scheme, n6When 2, the custom bus ticket is denoted, n6When being 3, the bus is customized;
assuming that the ticketing decision coefficient of the kth transportation mode of the ith passenger is the proportion of the travel frequency of the kth transportation mode of the ith passenger to the travel frequency of all the transportation modes, the calculation formula is
Figure FDA0003058283110000021
Obtaining different ticketing forms of each traffic mode according to the ticketing decision coefficient, which specifically comprises the following steps:
σ1ithe ticket system is a Bus in the form of less than or equal to 0.2 hour1，0.2＜σ1iThe ticket system is Bus at 0.42 or less2，σ1i>The 0.4 hour ticket system is in the form of Bus3；
σ2iThe ticket system is subway Sub at the time of less than or equal to 0.21，0.2＜σ2iThe ticket system is subway Sub at not more than 0.422，σ2i>The 0.4 hour ticket system is in the form of subway Sub3；
σ3iThe ticket system mode is a sharing bicycle Bic when the time is less than or equal to 0.21，0.2＜σ3iThe ticket system mode is a sharing bicycle Bic when the time is less than or equal to 0.422，σ3i>The 0.4 hour ticket system is in the form of a shared bicycle Bic3；
σ4iThe ticket system is in the form of net Taxi booking/Taxi not more than 0.21，0.2＜σ4iThe ticket system is in the form of net Taxi booking/Taxi not more than 0.422，σ4i>The 0.4 hour ticket system is in the form of net appointment/Taxi3；
σ5iThe ticket system form is a shared Car Car at less than or equal to 0.2 hour1，0.2＜σ5iThe ticket system form is a shared Car Car at less than or equal to 0.422，σ5i>The 0.4 hour ticket system being in the form of a shared Car Car3；
σ6iThe ticket system is in the form of customized bus Dem at 0.2 or less1，0.2＜σ6iThe ticket system is in the form of customized bus Dem at 0.42 or less2，σ6i>0.4 Times Ticket form for custom bus Dem3。
7. The method according to claim 6, wherein the MaaS system-oriented integrated ticketing scheme comprises: green shared passenger ticket service combination scheme
Figure FDA0003058283110000031
Combined scheme for ticket business comfortable passenger
Figure FDA0003058283110000032
Convenient and fast ticket service combination scheme for passenger
Figure FDA0003058283110000033
8. An integrated ticketing scheme generation device for a MaaS system, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method according to any one of claims 1 to 7 when executing the computer program.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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